Advanced and tailored applications of an efficient electrochemical approach assisted by AsLSSRCOW- rPLS and finding ways to cope with challenges arising from the nature of voltamme...

Autores
Jalalvand, Ali R.; Gholivand, Mohammad Bagher; Goicoechea, Hector Casimiro; Rinnan, Asmund; Skov, Thomas
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
The use of chemometric data processing is becoming an important part of modern voltammetry. The most challenges arising from voltammetric data are interactions among analytes and the background interferents which may cause signal changes in comparison with pure analyte profiles, and sample-to-sample potential shifts in the analyte profiles. These disadvantages can be tackled by baseline- and potential shift-correction Regarding the above commented problems, performances of asymmetric least squares spline regression (AsLSSR) algorithm for baseline correction and two well-known chemometric tools including interval correlation optimized shifting (icoshift) and correlation optimized warping (COW) for potential shift correction were examined. Finally, the COW was chosen for potential shift correction before applying recursive weighted partial least squares (rPLS) for simultaneous quantification of dopamine (DP), serotonin (ST), acetaminophen (AC) and noradrenaline (NA). In contrast to many other variable selection methods, the rPLS method has the advantage that only the number of latent factors used in the PLS needs to be estimated. A multivariate calibration (MVC) model was developed as a quaternary calibration model in a blank human serum sample (drug-free) provided by a healthy volunteer to regard the presence of a strong matrix effect which may be caused by the possible interferents present in the serum, and it was validated and tested with two independent sets of analytes mixtures in blank and actual human serum samples, respectively. Fortunately, the AsLSSR–COW–rPLS approach was successful in simultaneous quantification of DP, ST, AC, and NAD in both blank and actual human serum samples.
Fil: Jalalvand, Ali R.. Razi University. Faculty of Chemistry; Irán
Fil: Gholivand, Mohammad Bagher. Razi University. Faculty of Chemistry; Irán
Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Laboratorio de Química Analitica; Argentina
Fil: Rinnan, Asmund. Universidad de Copenhagen; Dinamarca
Fil: Skov, Thomas. Universidad de Copenhagen; Dinamarca
Materia
Cow
Potential-Shift Correction
Icoshift
Rpls
Simultaneous Quantification
Variable Selection
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/17016
Acceder
id CONICETDig_39e58ebb111cf499585f2054ea4fceae
oai_identifier_str oai:ri.conicet.gov.ar:11336/17016
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Advanced and tailored applications of an efficient electrochemical approach assisted by AsLSSRCOW- rPLS and finding ways to cope with challenges arising from the nature of voltammetric dataJalalvand, Ali R.Gholivand, Mohammad BagherGoicoechea, Hector CasimiroRinnan, AsmundSkov, ThomasCowPotential-Shift CorrectionIcoshiftRplsSimultaneous QuantificationVariable Selectionhttps://purl.org/becyt/ford/1.4https://purl.org/becyt/ford/1The use of chemometric data processing is becoming an important part of modern voltammetry. The most challenges arising from voltammetric data are interactions among analytes and the background interferents which may cause signal changes in comparison with pure analyte profiles, and sample-to-sample potential shifts in the analyte profiles. These disadvantages can be tackled by baseline- and potential shift-correction Regarding the above commented problems, performances of asymmetric least squares spline regression (AsLSSR) algorithm for baseline correction and two well-known chemometric tools including interval correlation optimized shifting (icoshift) and correlation optimized warping (COW) for potential shift correction were examined. Finally, the COW was chosen for potential shift correction before applying recursive weighted partial least squares (rPLS) for simultaneous quantification of dopamine (DP), serotonin (ST), acetaminophen (AC) and noradrenaline (NA). In contrast to many other variable selection methods, the rPLS method has the advantage that only the number of latent factors used in the PLS needs to be estimated. A multivariate calibration (MVC) model was developed as a quaternary calibration model in a blank human serum sample (drug-free) provided by a healthy volunteer to regard the presence of a strong matrix effect which may be caused by the possible interferents present in the serum, and it was validated and tested with two independent sets of analytes mixtures in blank and actual human serum samples, respectively. Fortunately, the AsLSSR–COW–rPLS approach was successful in simultaneous quantification of DP, ST, AC, and NAD in both blank and actual human serum samples.Fil: Jalalvand, Ali R.. Razi University. Faculty of Chemistry; IránFil: Gholivand, Mohammad Bagher. Razi University. Faculty of Chemistry; IránFil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Laboratorio de Química Analitica; ArgentinaFil: Rinnan, Asmund. Universidad de Copenhagen; DinamarcaFil: Skov, Thomas. Universidad de Copenhagen; DinamarcaElsevier2015-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/17016Jalalvand, Ali R.; Gholivand, Mohammad Bagher; Goicoechea, Hector Casimiro; Rinnan, Asmund; Skov, Thomas; Advanced and tailored applications of an efficient electrochemical approach assisted by AsLSSRCOW- rPLS and finding ways to cope with challenges arising from the nature of voltammetric data; Elsevier; Chemometrics and Intelligent Laboratory Systems; 146; 7-2015; 437-4460169-7439enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.chemolab.2015.06.017info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0169743915001653info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:52:31Zoai:ri.conicet.gov.ar:11336/17016instacron: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:34982025-09-29 09:52:32.002CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Advanced and tailored applications of an efficient electrochemical approach assisted by AsLSSRCOW- rPLS and finding ways to cope with challenges arising from the nature of voltammetric data
title Advanced and tailored applications of an efficient electrochemical approach assisted by AsLSSRCOW- rPLS and finding ways to cope with challenges arising from the nature of voltammetric data
spellingShingle Advanced and tailored applications of an efficient electrochemical approach assisted by AsLSSRCOW- rPLS and finding ways to cope with challenges arising from the nature of voltammetric data
Jalalvand, Ali R.
Cow
Potential-Shift Correction
Icoshift
Rpls
Simultaneous Quantification
Variable Selection
title_short Advanced and tailored applications of an efficient electrochemical approach assisted by AsLSSRCOW- rPLS and finding ways to cope with challenges arising from the nature of voltammetric data
title_full Advanced and tailored applications of an efficient electrochemical approach assisted by AsLSSRCOW- rPLS and finding ways to cope with challenges arising from the nature of voltammetric data
title_fullStr Advanced and tailored applications of an efficient electrochemical approach assisted by AsLSSRCOW- rPLS and finding ways to cope with challenges arising from the nature of voltammetric data
title_full_unstemmed Advanced and tailored applications of an efficient electrochemical approach assisted by AsLSSRCOW- rPLS and finding ways to cope with challenges arising from the nature of voltammetric data
title_sort Advanced and tailored applications of an efficient electrochemical approach assisted by AsLSSRCOW- rPLS and finding ways to cope with challenges arising from the nature of voltammetric data
dc.creator.none.fl_str_mv Jalalvand, Ali R.
Gholivand, Mohammad Bagher
Goicoechea, Hector Casimiro
Rinnan, Asmund
Skov, Thomas
author Jalalvand, Ali R.
author_facet Jalalvand, Ali R.
Gholivand, Mohammad Bagher
Goicoechea, Hector Casimiro
Rinnan, Asmund
Skov, Thomas
author_role author
author2 Gholivand, Mohammad Bagher
Goicoechea, Hector Casimiro
Rinnan, Asmund
Skov, Thomas
author2_role author
author
author
author
dc.subject.none.fl_str_mv Cow
Potential-Shift Correction
Icoshift
Rpls
Simultaneous Quantification
Variable Selection
topic Cow
Potential-Shift Correction
Icoshift
Rpls
Simultaneous Quantification
Variable Selection
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.4
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv The use of chemometric data processing is becoming an important part of modern voltammetry. The most challenges arising from voltammetric data are interactions among analytes and the background interferents which may cause signal changes in comparison with pure analyte profiles, and sample-to-sample potential shifts in the analyte profiles. These disadvantages can be tackled by baseline- and potential shift-correction Regarding the above commented problems, performances of asymmetric least squares spline regression (AsLSSR) algorithm for baseline correction and two well-known chemometric tools including interval correlation optimized shifting (icoshift) and correlation optimized warping (COW) for potential shift correction were examined. Finally, the COW was chosen for potential shift correction before applying recursive weighted partial least squares (rPLS) for simultaneous quantification of dopamine (DP), serotonin (ST), acetaminophen (AC) and noradrenaline (NA). In contrast to many other variable selection methods, the rPLS method has the advantage that only the number of latent factors used in the PLS needs to be estimated. A multivariate calibration (MVC) model was developed as a quaternary calibration model in a blank human serum sample (drug-free) provided by a healthy volunteer to regard the presence of a strong matrix effect which may be caused by the possible interferents present in the serum, and it was validated and tested with two independent sets of analytes mixtures in blank and actual human serum samples, respectively. Fortunately, the AsLSSR–COW–rPLS approach was successful in simultaneous quantification of DP, ST, AC, and NAD in both blank and actual human serum samples.
Fil: Jalalvand, Ali R.. Razi University. Faculty of Chemistry; Irán
Fil: Gholivand, Mohammad Bagher. Razi University. Faculty of Chemistry; Irán
Fil: Goicoechea, Hector Casimiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe; Argentina. Universidad Nacional del Litoral. Facultad de Ingeniería Química. Laboratorio de Química Analitica; Argentina
Fil: Rinnan, Asmund. Universidad de Copenhagen; Dinamarca
Fil: Skov, Thomas. Universidad de Copenhagen; Dinamarca
description The use of chemometric data processing is becoming an important part of modern voltammetry. The most challenges arising from voltammetric data are interactions among analytes and the background interferents which may cause signal changes in comparison with pure analyte profiles, and sample-to-sample potential shifts in the analyte profiles. These disadvantages can be tackled by baseline- and potential shift-correction Regarding the above commented problems, performances of asymmetric least squares spline regression (AsLSSR) algorithm for baseline correction and two well-known chemometric tools including interval correlation optimized shifting (icoshift) and correlation optimized warping (COW) for potential shift correction were examined. Finally, the COW was chosen for potential shift correction before applying recursive weighted partial least squares (rPLS) for simultaneous quantification of dopamine (DP), serotonin (ST), acetaminophen (AC) and noradrenaline (NA). In contrast to many other variable selection methods, the rPLS method has the advantage that only the number of latent factors used in the PLS needs to be estimated. A multivariate calibration (MVC) model was developed as a quaternary calibration model in a blank human serum sample (drug-free) provided by a healthy volunteer to regard the presence of a strong matrix effect which may be caused by the possible interferents present in the serum, and it was validated and tested with two independent sets of analytes mixtures in blank and actual human serum samples, respectively. Fortunately, the AsLSSR–COW–rPLS approach was successful in simultaneous quantification of DP, ST, AC, and NAD in both blank and actual human serum samples.
publishDate 2015
dc.date.none.fl_str_mv 2015-07
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/11336/17016
Jalalvand, Ali R.; Gholivand, Mohammad Bagher; Goicoechea, Hector Casimiro; Rinnan, Asmund; Skov, Thomas; Advanced and tailored applications of an efficient electrochemical approach assisted by AsLSSRCOW- rPLS and finding ways to cope with challenges arising from the nature of voltammetric data; Elsevier; Chemometrics and Intelligent Laboratory Systems; 146; 7-2015; 437-446
0169-7439
url http://hdl.handle.net/11336/17016
identifier_str_mv Jalalvand, Ali R.; Gholivand, Mohammad Bagher; Goicoechea, Hector Casimiro; Rinnan, Asmund; Skov, Thomas; Advanced and tailored applications of an efficient electrochemical approach assisted by AsLSSRCOW- rPLS and finding ways to cope with challenges arising from the nature of voltammetric data; Elsevier; Chemometrics and Intelligent Laboratory Systems; 146; 7-2015; 437-446
0169-7439
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.chemolab.2015.06.017
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0169743915001653
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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 13.070432

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