Identification of potential biomarkers of disease progression in bovine tuberculosis
- Autores
- Blanco, Federico Carlos; Bigi, Fabiana; Soria, Marcelo Abel
- Año de publicación
- 2014
- Idioma
- inglés
- Tipo de recurso
- artículo
- Estado
- versión publicada
- Descripción
- Bovine tuberculosis (bTB) remains an important animal and zoonotic disease in many countries. The diagnosis of bTB is based on tuberculin skin test and IFN-γ release assays (IGRA). Positive animals are separated from the herd and sacrificed. The cost of this procedure is difficult to afford for developing countries with high prevalence of bTB; therefore, the improvement of diagnostic methods and the identification of animals in different stages of the disease will be helpful to control the infection. To identify biomarkers that can discriminate between tuberculin positive cattle with and without tuberculosis lesions (ML+ and ML-, respectively), we assessed a group of immunological parameters with three different classification methods: lineal discriminant analysis (LDA), quadratic discriminant analysis (QDA) and K nearest neighbors (k-nn). For this purpose, we used data from 30 experimentally infected cattle. All the classifiers (LDA, QDA and k-nn) selected IL-2 and IL-17 as the most discriminatory variables. The best classification method was LDA using IL-17 and IL-2 as predictors. The addition of IL-10 to LDA improves the performance of the classifier to discriminate ML-individuals (93.3% vs. 86.7%). Thus, the expression of IL-17, IL-2 and, in some cases, IL-10 would serve as an additional tool to study disease progression in herds with a history of bTB.
Fil: Blanco, Federico Carlos. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina
Fil: Bigi, Fabiana. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina
Fil: Soria, Marcelo Abel. Universidad de Buenos Aires. Facultad de Agronomía; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Biología Aplicada y Alimentos. Cátedra de Microbiología Agrícola; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales; Argentina - Materia
-
Bovine Tuberculosis
Il-17
Discriminant Analysis
Biomarker - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/33659
Ver los metadatos del registro completo
id |
CONICETDig_158e59c70859751b55b1b3cae50888b0 |
---|---|
oai_identifier_str |
oai:ri.conicet.gov.ar:11336/33659 |
network_acronym_str |
CONICETDig |
repository_id_str |
3498 |
network_name_str |
CONICET Digital (CONICET) |
spelling |
Identification of potential biomarkers of disease progression in bovine tuberculosisBlanco, Federico CarlosBigi, FabianaSoria, Marcelo AbelBovine TuberculosisIl-17Discriminant AnalysisBiomarkerhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Bovine tuberculosis (bTB) remains an important animal and zoonotic disease in many countries. The diagnosis of bTB is based on tuberculin skin test and IFN-γ release assays (IGRA). Positive animals are separated from the herd and sacrificed. The cost of this procedure is difficult to afford for developing countries with high prevalence of bTB; therefore, the improvement of diagnostic methods and the identification of animals in different stages of the disease will be helpful to control the infection. To identify biomarkers that can discriminate between tuberculin positive cattle with and without tuberculosis lesions (ML+ and ML-, respectively), we assessed a group of immunological parameters with three different classification methods: lineal discriminant analysis (LDA), quadratic discriminant analysis (QDA) and K nearest neighbors (k-nn). For this purpose, we used data from 30 experimentally infected cattle. All the classifiers (LDA, QDA and k-nn) selected IL-2 and IL-17 as the most discriminatory variables. The best classification method was LDA using IL-17 and IL-2 as predictors. The addition of IL-10 to LDA improves the performance of the classifier to discriminate ML-individuals (93.3% vs. 86.7%). Thus, the expression of IL-17, IL-2 and, in some cases, IL-10 would serve as an additional tool to study disease progression in herds with a history of bTB.Fil: Blanco, Federico Carlos. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; ArgentinaFil: Bigi, Fabiana. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; ArgentinaFil: Soria, Marcelo Abel. Universidad de Buenos Aires. Facultad de Agronomía; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Biología Aplicada y Alimentos. Cátedra de Microbiología Agrícola; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales; ArgentinaElsevier2014-05info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/33659Soria, Marcelo Abel; Bigi, Fabiana; Blanco, Federico Carlos; Identification of potential biomarkers of disease progression in bovine tuberculosis; Elsevier; Veterinary Immunology And Immunopathology; 160; 3-4; 5-2014; 177-1830165-2427CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.vetimm.2014.04.008info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0165242714001111info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-10T13:05:32Zoai:ri.conicet.gov.ar:11336/33659instacron: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:34982025-09-10 13:05:32.302CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse |
dc.title.none.fl_str_mv |
Identification of potential biomarkers of disease progression in bovine tuberculosis |
title |
Identification of potential biomarkers of disease progression in bovine tuberculosis |
spellingShingle |
Identification of potential biomarkers of disease progression in bovine tuberculosis Blanco, Federico Carlos Bovine Tuberculosis Il-17 Discriminant Analysis Biomarker |
title_short |
Identification of potential biomarkers of disease progression in bovine tuberculosis |
title_full |
Identification of potential biomarkers of disease progression in bovine tuberculosis |
title_fullStr |
Identification of potential biomarkers of disease progression in bovine tuberculosis |
title_full_unstemmed |
Identification of potential biomarkers of disease progression in bovine tuberculosis |
title_sort |
Identification of potential biomarkers of disease progression in bovine tuberculosis |
dc.creator.none.fl_str_mv |
Blanco, Federico Carlos Bigi, Fabiana Soria, Marcelo Abel |
author |
Blanco, Federico Carlos |
author_facet |
Blanco, Federico Carlos Bigi, Fabiana Soria, Marcelo Abel |
author_role |
author |
author2 |
Bigi, Fabiana Soria, Marcelo Abel |
author2_role |
author author |
dc.subject.none.fl_str_mv |
Bovine Tuberculosis Il-17 Discriminant Analysis Biomarker |
topic |
Bovine Tuberculosis Il-17 Discriminant Analysis Biomarker |
purl_subject.fl_str_mv |
https://purl.org/becyt/ford/1.6 https://purl.org/becyt/ford/1 |
dc.description.none.fl_txt_mv |
Bovine tuberculosis (bTB) remains an important animal and zoonotic disease in many countries. The diagnosis of bTB is based on tuberculin skin test and IFN-γ release assays (IGRA). Positive animals are separated from the herd and sacrificed. The cost of this procedure is difficult to afford for developing countries with high prevalence of bTB; therefore, the improvement of diagnostic methods and the identification of animals in different stages of the disease will be helpful to control the infection. To identify biomarkers that can discriminate between tuberculin positive cattle with and without tuberculosis lesions (ML+ and ML-, respectively), we assessed a group of immunological parameters with three different classification methods: lineal discriminant analysis (LDA), quadratic discriminant analysis (QDA) and K nearest neighbors (k-nn). For this purpose, we used data from 30 experimentally infected cattle. All the classifiers (LDA, QDA and k-nn) selected IL-2 and IL-17 as the most discriminatory variables. The best classification method was LDA using IL-17 and IL-2 as predictors. The addition of IL-10 to LDA improves the performance of the classifier to discriminate ML-individuals (93.3% vs. 86.7%). Thus, the expression of IL-17, IL-2 and, in some cases, IL-10 would serve as an additional tool to study disease progression in herds with a history of bTB. Fil: Blanco, Federico Carlos. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina Fil: Bigi, Fabiana. Instituto Nacional de Tecnología Agropecuaria. Centro de Investigación en Ciencias Veterinarias y Agronómicas. Instituto de Biotecnología; Argentina Fil: Soria, Marcelo Abel. Universidad de Buenos Aires. Facultad de Agronomía; Argentina. Universidad de Buenos Aires. Facultad de Agronomía. Departamento de Biología Aplicada y Alimentos. Cátedra de Microbiología Agrícola; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones en Biociencias Agrícolas y Ambientales; Argentina |
description |
Bovine tuberculosis (bTB) remains an important animal and zoonotic disease in many countries. The diagnosis of bTB is based on tuberculin skin test and IFN-γ release assays (IGRA). Positive animals are separated from the herd and sacrificed. The cost of this procedure is difficult to afford for developing countries with high prevalence of bTB; therefore, the improvement of diagnostic methods and the identification of animals in different stages of the disease will be helpful to control the infection. To identify biomarkers that can discriminate between tuberculin positive cattle with and without tuberculosis lesions (ML+ and ML-, respectively), we assessed a group of immunological parameters with three different classification methods: lineal discriminant analysis (LDA), quadratic discriminant analysis (QDA) and K nearest neighbors (k-nn). For this purpose, we used data from 30 experimentally infected cattle. All the classifiers (LDA, QDA and k-nn) selected IL-2 and IL-17 as the most discriminatory variables. The best classification method was LDA using IL-17 and IL-2 as predictors. The addition of IL-10 to LDA improves the performance of the classifier to discriminate ML-individuals (93.3% vs. 86.7%). Thus, the expression of IL-17, IL-2 and, in some cases, IL-10 would serve as an additional tool to study disease progression in herds with a history of bTB. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-05 |
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/11336/33659 Soria, Marcelo Abel; Bigi, Fabiana; Blanco, Federico Carlos; Identification of potential biomarkers of disease progression in bovine tuberculosis; Elsevier; Veterinary Immunology And Immunopathology; 160; 3-4; 5-2014; 177-183 0165-2427 CONICET Digital CONICET |
url |
http://hdl.handle.net/11336/33659 |
identifier_str_mv |
Soria, Marcelo Abel; Bigi, Fabiana; Blanco, Federico Carlos; Identification of potential biomarkers of disease progression in bovine tuberculosis; Elsevier; Veterinary Immunology And Immunopathology; 160; 3-4; 5-2014; 177-183 0165-2427 CONICET Digital CONICET |
dc.language.none.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.vetimm.2014.04.008 info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S0165242714001111 |
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 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 |
_version_ |
1842980206646657024 |
score |
12.993085 |