Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method

Autores
Lozano, Valeria Antonella; Ibañez, Gabriela Alejandra; Olivieri, Alejandro Cesar
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Analyte quantitation can be achieved from second-order data in the presence of uncalibrated components using multivariate calibration methods such as partial leastsquares with residual bilinearization. However, the latter fails under conditions of identical profiles for interfering agents and calibrated components in one of the data dimensions. To overcome this problem, a new residual bilinearization procedure for linear dependency is here introduced. Simulated data show that the new model can conveniently handle the studied analytical problem, with a success comparable to multivariate curve resolutionalternating least-squares and also comparable to a version of parallel factor analysis adapted to cope with linear dependencies. The new approach has also been applied to two experimental examples involving the determination of the antibiotic ciprofloxacin in (1) urine samples from lanthanide-sensitized excitation-time decay matrixes and (2) serum samples from a novel second-order signal based on the time evolution of chemiluminescence emission. The results indicate good analytical performance of the new procedure toward the analyte in comparison with the classical approaches.
Fil: Lozano, Valeria Antonella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Ibañez, Gabriela Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Materia
SECOND-ORDER ADVANTAGE
PARTIAL LEAST-SQUARES
RESIDUAL BILINEARIZATION FOR LINEAR DEPENDENCY
IDENTICAL PROFILES IN ONE DIMENSION
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/127801
Acceder
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repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization methodLozano, Valeria AntonellaIbañez, Gabriela AlejandraOlivieri, Alejandro CesarSECOND-ORDER ADVANTAGEPARTIAL LEAST-SQUARESRESIDUAL BILINEARIZATION FOR LINEAR DEPENDENCYIDENTICAL PROFILES IN ONE DIMENSIONhttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1Analyte quantitation can be achieved from second-order data in the presence of uncalibrated components using multivariate calibration methods such as partial leastsquares with residual bilinearization. However, the latter fails under conditions of identical profiles for interfering agents and calibrated components in one of the data dimensions. To overcome this problem, a new residual bilinearization procedure for linear dependency is here introduced. Simulated data show that the new model can conveniently handle the studied analytical problem, with a success comparable to multivariate curve resolutionalternating least-squares and also comparable to a version of parallel factor analysis adapted to cope with linear dependencies. The new approach has also been applied to two experimental examples involving the determination of the antibiotic ciprofloxacin in (1) urine samples from lanthanide-sensitized excitation-time decay matrixes and (2) serum samples from a novel second-order signal based on the time evolution of chemiluminescence emission. The results indicate good analytical performance of the new procedure toward the analyte in comparison with the classical approaches.Fil: Lozano, Valeria Antonella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; ArgentinaFil: Ibañez, Gabriela Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; ArgentinaFil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; ArgentinaAmerican Chemical Society2010-06info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/127801Lozano, Valeria Antonella; Ibañez, Gabriela Alejandra; Olivieri, Alejandro Cesar; Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method; American Chemical Society; Analytical Chemistry; 82; 11; 6-2010; 4510-45190003-2700CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://pubs.acs.org/doi/abs/10.1021/ac100424dinfo:eu-repo/semantics/altIdentifier/doi/10.1021/ac100424dinfo:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:29:17Zoai:ri.conicet.gov.ar:11336/127801instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-15 15:29:18.161CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method
title Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method
spellingShingle Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method
Lozano, Valeria Antonella
SECOND-ORDER ADVANTAGE
PARTIAL LEAST-SQUARES
RESIDUAL BILINEARIZATION FOR LINEAR DEPENDENCY
IDENTICAL PROFILES IN ONE DIMENSION
title_short Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method
title_full Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method
title_fullStr Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method
title_full_unstemmed Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method
title_sort Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method
dc.creator.none.fl_str_mv Lozano, Valeria Antonella
Ibañez, Gabriela Alejandra
Olivieri, Alejandro Cesar
author Lozano, Valeria Antonella
author_facet Lozano, Valeria Antonella
Ibañez, Gabriela Alejandra
Olivieri, Alejandro Cesar
author_role author
author2 Ibañez, Gabriela Alejandra
Olivieri, Alejandro Cesar
author2_role author
author
dc.subject.none.fl_str_mv SECOND-ORDER ADVANTAGE
PARTIAL LEAST-SQUARES
RESIDUAL BILINEARIZATION FOR LINEAR DEPENDENCY
IDENTICAL PROFILES IN ONE DIMENSION
topic SECOND-ORDER ADVANTAGE
PARTIAL LEAST-SQUARES
RESIDUAL BILINEARIZATION FOR LINEAR DEPENDENCY
IDENTICAL PROFILES IN ONE DIMENSION
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Analyte quantitation can be achieved from second-order data in the presence of uncalibrated components using multivariate calibration methods such as partial leastsquares with residual bilinearization. However, the latter fails under conditions of identical profiles for interfering agents and calibrated components in one of the data dimensions. To overcome this problem, a new residual bilinearization procedure for linear dependency is here introduced. Simulated data show that the new model can conveniently handle the studied analytical problem, with a success comparable to multivariate curve resolutionalternating least-squares and also comparable to a version of parallel factor analysis adapted to cope with linear dependencies. The new approach has also been applied to two experimental examples involving the determination of the antibiotic ciprofloxacin in (1) urine samples from lanthanide-sensitized excitation-time decay matrixes and (2) serum samples from a novel second-order signal based on the time evolution of chemiluminescence emission. The results indicate good analytical performance of the new procedure toward the analyte in comparison with the classical approaches.
Fil: Lozano, Valeria Antonella. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Ibañez, Gabriela Alejandra. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
Fil: Olivieri, Alejandro Cesar. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Rosario. Instituto de Química Rosario. Universidad Nacional de Rosario. Facultad de Ciencias Bioquímicas y Farmacéuticas. Instituto de Química Rosario; Argentina
description Analyte quantitation can be achieved from second-order data in the presence of uncalibrated components using multivariate calibration methods such as partial leastsquares with residual bilinearization. However, the latter fails under conditions of identical profiles for interfering agents and calibrated components in one of the data dimensions. To overcome this problem, a new residual bilinearization procedure for linear dependency is here introduced. Simulated data show that the new model can conveniently handle the studied analytical problem, with a success comparable to multivariate curve resolutionalternating least-squares and also comparable to a version of parallel factor analysis adapted to cope with linear dependencies. The new approach has also been applied to two experimental examples involving the determination of the antibiotic ciprofloxacin in (1) urine samples from lanthanide-sensitized excitation-time decay matrixes and (2) serum samples from a novel second-order signal based on the time evolution of chemiluminescence emission. The results indicate good analytical performance of the new procedure toward the analyte in comparison with the classical approaches.
publishDate 2010
dc.date.none.fl_str_mv 2010-06
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/127801
Lozano, Valeria Antonella; Ibañez, Gabriela Alejandra; Olivieri, Alejandro Cesar; Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method; American Chemical Society; Analytical Chemistry; 82; 11; 6-2010; 4510-4519
0003-2700
CONICET Digital
CONICET
url http://hdl.handle.net/11336/127801
identifier_str_mv Lozano, Valeria Antonella; Ibañez, Gabriela Alejandra; Olivieri, Alejandro Cesar; Second-order analyte quantitation under Identical profiles in one data dimension. A dependency-adapted partial least-squares/residual bilinearization method; American Chemical Society; Analytical Chemistry; 82; 11; 6-2010; 4510-4519
0003-2700
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://pubs.acs.org/doi/abs/10.1021/ac100424d
info:eu-repo/semantics/altIdentifier/doi/10.1021/ac100424d
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv American Chemical Society
publisher.none.fl_str_mv American Chemical Society
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.22299

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