Multivariate analysis for animal selection in experimental research

Detalhes bibliográficos
Autor(a) principal: Pinto, Renan Mercuri [UNESP]
Data de Publicação: 2015
Outros Autores: Campos, Dijon Henrique Salomé de [UNESP], Tomasi, Loreta Casquel [UNESP], Cicogna, Antonio Carlos [UNESP], Okoshi, Katashi [UNESP], Padovani, Carlos Roberto [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0066-782X2015000200002&lng=en&nrm=iso&tlng=en
http://hdl.handle.net/11449/127344
Resumo: Background: Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective: To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods: The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results: The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion: The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate.
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spelling Multivariate analysis for animal selection in experimental researchAnálise multivariada na seleção de animais em pesquisas experimentaisMultivariate AnalysisAnimalsEpidemiologyExperimentalAortic valve stenosisAnálise multivariadaAnimaisEpidemiologia ExperimentalEstenose da válvula aórticaBackground: Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective: To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods: The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results: The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion: The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate.Fundamento: Muitos pesquisadores buscam métodos para a seleção de grupos homogêneos de animais em pesquisas experimentais, fato que se justifica por ser a homogeneidade pré-requisito indispensável à casualização de tratamentos. A ausência de métodos robustos, que atendam a princípios estatísticos e biológicos, faz com que os pesquisadores utilizem métodos empíricos ou subjetivos, influenciando seus resultados. Objetivo: Desenvolver modelo estatístico multivariado para a seleção de grupo homogêneo de animais para pesquisas experimentais e elaborar pacote computacional que o operacionalize. Métodos: O conjunto de dados ecocardiográficos de 115 ratos Wistar, machos, com estenose aórtica (EAo) supravalvular foi utilizado para exemplificar o desenvolvimento do modelo. Inicialmente, os dados foram padronizados, tornando-se adimensionais. Em sequência, submeteu-se a matriz de variabilidade do conjunto à análise de componentes principais (ACP) buscando-se reduzir o espaço paramétrico e conservar a variabilidade relevante. Essa técnica estabeleceu um novo sistema cartesiano em que os animais foram alocados e, finalmente, construiu-se a região de confiança (elipsoide) para o perfil de respostas homogêneas dos animais. Os que se situaram no interior do elipsoide foram considerados pertencentes ao grupo homogêneo; caso contrário, espúrios ao grupo. Resultados: A ACP estabeleceu oito eixos descritores que representaram a variabilidade acumulada dos dados em 88,71%. A alocação dos animais no novo sistema e a construção da região de confiança revelou a presença de seis espúrios ao lote homogêneo formado por 109 animais. Conclusão: O critério biométrico proposto mostra-se eficiente, pois considera o animal como um todo, analisando conjuntamente todos os parâmetros mensurados, além de apresentar pequena frequência de descartes.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)Universidade Estadual Paulista Instituto de Ciências Biológicas Departamento de BioestatísticaUniversidade Estadual Paulista Faculdade de Medicina de Botucatu Departamento de Clínica MédicaUniversidade Estadual Paulista Instituto de Ciências Biológicas Departamento de BioestatísticaUniversidade Estadual Paulista Faculdade de Medicina de Botucatu Departamento de Clínica MédicaSociedade Brasileira de Cardiologia - SBCUniversidade Estadual Paulista (Unesp)Pinto, Renan Mercuri [UNESP]Campos, Dijon Henrique Salomé de [UNESP]Tomasi, Loreta Casquel [UNESP]Cicogna, Antonio Carlos [UNESP]Okoshi, Katashi [UNESP]Padovani, Carlos Roberto [UNESP]2015-08-26T19:19:15Z2015-08-26T19:19:15Z2015-02-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article97-103application/pdfhttp://www.scielo.br/scielo.php?script=sci_arttext&pid=S0066-782X2015000200002&lng=en&nrm=iso&tlng=enArquivos Brasileiros de Cardiologia, v. 104, n. 2, p. 97-103, 2015.0066-782Xhttp://hdl.handle.net/11449/12734410.5935/abc.20140219S0066-782X2015000200002S0066-782X2015000200002.pdf941897010356413787278970805222891590971576309420SciELOreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengArquivos Brasileiros de Cardiologia1.318info:eu-repo/semantics/openAccess2024-08-14T17:22:48Zoai:repositorio.unesp.br:11449/127344Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-14T17:22:48Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Multivariate analysis for animal selection in experimental research
Análise multivariada na seleção de animais em pesquisas experimentais
title Multivariate analysis for animal selection in experimental research
spellingShingle Multivariate analysis for animal selection in experimental research
Pinto, Renan Mercuri [UNESP]
Multivariate Analysis
Animals
Epidemiology
Experimental
Aortic valve stenosis
Análise multivariada
Animais
Epidemiologia Experimental
Estenose da válvula aórtica
title_short Multivariate analysis for animal selection in experimental research
title_full Multivariate analysis for animal selection in experimental research
title_fullStr Multivariate analysis for animal selection in experimental research
title_full_unstemmed Multivariate analysis for animal selection in experimental research
title_sort Multivariate analysis for animal selection in experimental research
author Pinto, Renan Mercuri [UNESP]
author_facet Pinto, Renan Mercuri [UNESP]
Campos, Dijon Henrique Salomé de [UNESP]
Tomasi, Loreta Casquel [UNESP]
Cicogna, Antonio Carlos [UNESP]
Okoshi, Katashi [UNESP]
Padovani, Carlos Roberto [UNESP]
author_role author
author2 Campos, Dijon Henrique Salomé de [UNESP]
Tomasi, Loreta Casquel [UNESP]
Cicogna, Antonio Carlos [UNESP]
Okoshi, Katashi [UNESP]
Padovani, Carlos Roberto [UNESP]
author2_role author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Pinto, Renan Mercuri [UNESP]
Campos, Dijon Henrique Salomé de [UNESP]
Tomasi, Loreta Casquel [UNESP]
Cicogna, Antonio Carlos [UNESP]
Okoshi, Katashi [UNESP]
Padovani, Carlos Roberto [UNESP]
dc.subject.por.fl_str_mv Multivariate Analysis
Animals
Epidemiology
Experimental
Aortic valve stenosis
Análise multivariada
Animais
Epidemiologia Experimental
Estenose da válvula aórtica
topic Multivariate Analysis
Animals
Epidemiology
Experimental
Aortic valve stenosis
Análise multivariada
Animais
Epidemiologia Experimental
Estenose da válvula aórtica
description Background: Several researchers seek methods for the selection of homogeneous groups of animals in experimental studies, a fact justified because homogeneity is an indispensable prerequisite for casualization of treatments. The lack of robust methods that comply with statistical and biological principles is the reason why researchers use empirical or subjective methods, influencing their results. Objective: To develop a multivariate statistical model for the selection of a homogeneous group of animals for experimental research and to elaborate a computational package to use it. Methods: The set of echocardiographic data of 115 male Wistar rats with supravalvular aortic stenosis (AoS) was used as an example of model development. Initially, the data were standardized, and became dimensionless. Then, the variance matrix of the set was submitted to principal components analysis (PCA), aiming at reducing the parametric space and at retaining the relevant variability. That technique established a new Cartesian system into which the animals were allocated, and finally the confidence region (ellipsoid) was built for the profile of the animals’ homogeneous responses. The animals located inside the ellipsoid were considered as belonging to the homogeneous batch; those outside the ellipsoid were considered spurious. Results: The PCA established eight descriptive axes that represented the accumulated variance of the data set in 88.71%. The allocation of the animals in the new system and the construction of the confidence region revealed six spurious animals as compared to the homogeneous batch of 109 animals. Conclusion: The biometric criterion presented proved to be effective, because it considers the animal as a whole, analyzing jointly all parameters measured, in addition to having a small discard rate.
publishDate 2015
dc.date.none.fl_str_mv 2015-08-26T19:19:15Z
2015-08-26T19:19:15Z
2015-02-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0066-782X2015000200002&lng=en&nrm=iso&tlng=en
Arquivos Brasileiros de Cardiologia, v. 104, n. 2, p. 97-103, 2015.
0066-782X
http://hdl.handle.net/11449/127344
10.5935/abc.20140219
S0066-782X2015000200002
S0066-782X2015000200002.pdf
9418970103564137
8727897080522289
1590971576309420
url http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0066-782X2015000200002&lng=en&nrm=iso&tlng=en
http://hdl.handle.net/11449/127344
identifier_str_mv Arquivos Brasileiros de Cardiologia, v. 104, n. 2, p. 97-103, 2015.
0066-782X
10.5935/abc.20140219
S0066-782X2015000200002
S0066-782X2015000200002.pdf
9418970103564137
8727897080522289
1590971576309420
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Arquivos Brasileiros de Cardiologia
1.318
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 97-103
application/pdf
dc.publisher.none.fl_str_mv Sociedade Brasileira de Cardiologia - SBC
publisher.none.fl_str_mv Sociedade Brasileira de Cardiologia - SBC
dc.source.none.fl_str_mv SciELO
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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