Metabolite Signatures of Metabolic Risk Factors and their Longitudinal Changes

Autores
Yin, Xiaoyan; Subramanian, Subha; Willinger, Christine M.; Chen, George; Juhasz, Peter; Courchesne, Paul; Chen, Brian H.; Li, Xiaohang; Hwang, Shih Jen; Fox, Caroline S.; O'Donnell, Christopher J.; Muntendam, Pieter; Fuster, Valentin; Bobeldijk Pastorova, Ivana; Sookoian, Silvia Cristina; Pirola, Carlos José; Gordon, Neal; Adourian, Aram; Larson, Martin G.; Levy, Daniel
Año de publicación
2016
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
CONTEXT: Metabolic dysregulation underlies key metabolic risk factors—obesity, dyslipidemia, and dysglycemia. OBJECTIVE: To uncover mechanistic links between metabolomic dysregulation and metabolic risk by testing metabolite associations with risk factors cross-sectionally and with risk factor changes over time. DESIGN: Cross-sectional—discovery samples (n = 650; age, 36–69 years) from the Framingham Heart Study (FHS) and replication samples (n = 670; age, 61–76 years) from the BioImage Study, both following a factorial design sampled from high vs low strata of body mass index, lipids, and glucose. Longitudinal—FHS participants (n = 554) with 5–7 years of follow-up for risk factor changes. SETTING: Observational studies. PARTICIPANTS: Cross-sectional samples with or without obesity, dysglycemia, and dyslipidemia, excluding prevalent cardiovascular disease and diabetes or dyslipidemia treatment. Age- and sex-matched by group. INTERVENTIONS: None. MAIN OUTCOME MEASURE(S): Gas chromatography-mass spectrometry detected 119 plasma metabolites. Cross-sectional associations with obesity, dyslipidemia, and dysglycemia were tested in discovery, with external replication of 37 metabolites. Single- and multi-metabolite markers were tested for association with longitudinal changes in risk factors. RESULTS: Cross-sectional metabolite associations were identified with obesity (n = 26), dyslipidemia (n = 21), and dysglycemia (n = 11) in discovery. Glutamic acid, lactic acid, and sitosterol associated with all three risk factors in meta-analysis (P < 4.5 × 10−4). Metabolites associated with longitudinal risk factor changes were enriched for bioactive lipids. Multi-metabolite panels explained 2.5–15.3% of longitudinal changes in metabolic traits. CONCLUSIONS: Cross-sectional results implicated dysregulated glutamate cycling and amino acid metabolism in metabolic risk. Certain bioactive lipids were associated with risk factors cross-sectionally and over time, suggesting their upstream role in risk factor progression. Functional studies are needed to validate findings and facilitate translation into treatments or preventive measures.
Fil: Yin, Xiaoyan. Framingham Heart Study; Estados Unidos. Boston University; Estados Unidos
Fil: Subramanian, Subha. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos
Fil: Willinger, Christine M.. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos
Fil: Chen, George. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos
Fil: Juhasz, Peter. BG Medicine; Estados Unidos
Fil: Courchesne, Paul. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos
Fil: Chen, Brian H.. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos
Fil: Li, Xiaohang. BG Medicine; Estados Unidos
Fil: Hwang, Shih Jen. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos
Fil: Fox, Caroline S.. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos. Brigham and Women’s Hospital. Department of Medicine; Estados Unidos. Harvard Medical School; Estados Unidos
Fil: O'Donnell, Christopher J.. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos. Massachusetts General Hospital. Department of Medicine; Estados Unidos. Harvard Medical School; Estados Unidos
Fil: Muntendam, Pieter. BG Medicine; Estados Unidos
Fil: Fuster, Valentin. Mt. Sinai School of Medicine; Estados Unidos. Centro Nacional de Investigaciones Cardiovasculares; España. Cedars Sinai Medical Center; Estados Unidos
Fil: Bobeldijk Pastorova, Ivana. TNO Triskelion BV; Países Bajos
Fil: Sookoian, Silvia Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Médicas. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; Argentina
Fil: Pirola, Carlos José. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Médicas. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; Argentina
Fil: Gordon, Neal. BG Medicine; Estados Unidos
Fil: Adourian, Aram. BG Medicine; Estados Unidos
Fil: Larson, Martin G.. Framingham Heart Study; Estados Unidos. Boston University; Estados Unidos
Fil: Levy, Daniel. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos. Boston University; Estados Unidos
Materia
Metabolomics
Metabolic Syndrome
Diabetes
Biomarkers
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:11336/44356
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/44356
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Metabolite Signatures of Metabolic Risk Factors and their Longitudinal ChangesYin, XiaoyanSubramanian, SubhaWillinger, Christine M.Chen, GeorgeJuhasz, PeterCourchesne, PaulChen, Brian H.Li, XiaohangHwang, Shih JenFox, Caroline S.O'Donnell, Christopher J.Muntendam, PieterFuster, ValentinBobeldijk Pastorova, IvanaSookoian, Silvia CristinaPirola, Carlos JoséGordon, NealAdourian, AramLarson, Martin G.Levy, DanielMetabolomicsMetabolic SyndromeDiabetesBiomarkershttps://purl.org/becyt/ford/3.2https://purl.org/becyt/ford/3CONTEXT: Metabolic dysregulation underlies key metabolic risk factors—obesity, dyslipidemia, and dysglycemia. OBJECTIVE: To uncover mechanistic links between metabolomic dysregulation and metabolic risk by testing metabolite associations with risk factors cross-sectionally and with risk factor changes over time. DESIGN: Cross-sectional—discovery samples (n = 650; age, 36–69 years) from the Framingham Heart Study (FHS) and replication samples (n = 670; age, 61–76 years) from the BioImage Study, both following a factorial design sampled from high vs low strata of body mass index, lipids, and glucose. Longitudinal—FHS participants (n = 554) with 5–7 years of follow-up for risk factor changes. SETTING: Observational studies. PARTICIPANTS: Cross-sectional samples with or without obesity, dysglycemia, and dyslipidemia, excluding prevalent cardiovascular disease and diabetes or dyslipidemia treatment. Age- and sex-matched by group. INTERVENTIONS: None. MAIN OUTCOME MEASURE(S): Gas chromatography-mass spectrometry detected 119 plasma metabolites. Cross-sectional associations with obesity, dyslipidemia, and dysglycemia were tested in discovery, with external replication of 37 metabolites. Single- and multi-metabolite markers were tested for association with longitudinal changes in risk factors. RESULTS: Cross-sectional metabolite associations were identified with obesity (n = 26), dyslipidemia (n = 21), and dysglycemia (n = 11) in discovery. Glutamic acid, lactic acid, and sitosterol associated with all three risk factors in meta-analysis (P < 4.5 × 10−4). Metabolites associated with longitudinal risk factor changes were enriched for bioactive lipids. Multi-metabolite panels explained 2.5–15.3% of longitudinal changes in metabolic traits. CONCLUSIONS: Cross-sectional results implicated dysregulated glutamate cycling and amino acid metabolism in metabolic risk. Certain bioactive lipids were associated with risk factors cross-sectionally and over time, suggesting their upstream role in risk factor progression. Functional studies are needed to validate findings and facilitate translation into treatments or preventive measures.Fil: Yin, Xiaoyan. Framingham Heart Study; Estados Unidos. Boston University; Estados UnidosFil: Subramanian, Subha. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados UnidosFil: Willinger, Christine M.. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados UnidosFil: Chen, George. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados UnidosFil: Juhasz, Peter. BG Medicine; Estados UnidosFil: Courchesne, Paul. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados UnidosFil: Chen, Brian H.. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados UnidosFil: Li, Xiaohang. BG Medicine; Estados UnidosFil: Hwang, Shih Jen. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados UnidosFil: Fox, Caroline S.. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos. Brigham and Women’s Hospital. Department of Medicine; Estados Unidos. Harvard Medical School; Estados UnidosFil: O'Donnell, Christopher J.. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos. Massachusetts General Hospital. Department of Medicine; Estados Unidos. Harvard Medical School; Estados UnidosFil: Muntendam, Pieter. BG Medicine; Estados UnidosFil: Fuster, Valentin. Mt. Sinai School of Medicine; Estados Unidos. Centro Nacional de Investigaciones Cardiovasculares; España. Cedars Sinai Medical Center; Estados UnidosFil: Bobeldijk Pastorova, Ivana. TNO Triskelion BV; Países BajosFil: Sookoian, Silvia Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Médicas. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Pirola, Carlos José. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Médicas. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; ArgentinaFil: Gordon, Neal. BG Medicine; Estados UnidosFil: Adourian, Aram. BG Medicine; Estados UnidosFil: Larson, Martin G.. Framingham Heart Study; Estados Unidos. Boston University; Estados UnidosFil: Levy, Daniel. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos. Boston University; Estados UnidosEndocrine Society2016-04info: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/11336/44356Yin, Xiaoyan; Subramanian, Subha; Willinger, Christine M.; Chen, George; Juhasz, Peter; et al.; Metabolite Signatures of Metabolic Risk Factors and their Longitudinal Changes; Endocrine Society; Journal of Clinical Endocrinology and Metabolism; 101; 4; 4-2016; 1779-17890021-972X1945-7197CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/doi/10.1210/jc.2015-2555info:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/jcem/article/101/4/1779/2804590info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T15:38:22Zoai:ri.conicet.gov.ar:11336/44356instacron: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 15:38:22.706CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Metabolite Signatures of Metabolic Risk Factors and their Longitudinal Changes
title Metabolite Signatures of Metabolic Risk Factors and their Longitudinal Changes
spellingShingle Metabolite Signatures of Metabolic Risk Factors and their Longitudinal Changes
Yin, Xiaoyan
Metabolomics
Metabolic Syndrome
Diabetes
Biomarkers
title_short Metabolite Signatures of Metabolic Risk Factors and their Longitudinal Changes
title_full Metabolite Signatures of Metabolic Risk Factors and their Longitudinal Changes
title_fullStr Metabolite Signatures of Metabolic Risk Factors and their Longitudinal Changes
title_full_unstemmed Metabolite Signatures of Metabolic Risk Factors and their Longitudinal Changes
title_sort Metabolite Signatures of Metabolic Risk Factors and their Longitudinal Changes
dc.creator.none.fl_str_mv Yin, Xiaoyan
Subramanian, Subha
Willinger, Christine M.
Chen, George
Juhasz, Peter
Courchesne, Paul
Chen, Brian H.
Li, Xiaohang
Hwang, Shih Jen
Fox, Caroline S.
O'Donnell, Christopher J.
Muntendam, Pieter
Fuster, Valentin
Bobeldijk Pastorova, Ivana
Sookoian, Silvia Cristina
Pirola, Carlos José
Gordon, Neal
Adourian, Aram
Larson, Martin G.
Levy, Daniel
author Yin, Xiaoyan
author_facet Yin, Xiaoyan
Subramanian, Subha
Willinger, Christine M.
Chen, George
Juhasz, Peter
Courchesne, Paul
Chen, Brian H.
Li, Xiaohang
Hwang, Shih Jen
Fox, Caroline S.
O'Donnell, Christopher J.
Muntendam, Pieter
Fuster, Valentin
Bobeldijk Pastorova, Ivana
Sookoian, Silvia Cristina
Pirola, Carlos José
Gordon, Neal
Adourian, Aram
Larson, Martin G.
Levy, Daniel
author_role author
author2 Subramanian, Subha
Willinger, Christine M.
Chen, George
Juhasz, Peter
Courchesne, Paul
Chen, Brian H.
Li, Xiaohang
Hwang, Shih Jen
Fox, Caroline S.
O'Donnell, Christopher J.
Muntendam, Pieter
Fuster, Valentin
Bobeldijk Pastorova, Ivana
Sookoian, Silvia Cristina
Pirola, Carlos José
Gordon, Neal
Adourian, Aram
Larson, Martin G.
Levy, Daniel
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Metabolomics
Metabolic Syndrome
Diabetes
Biomarkers
topic Metabolomics
Metabolic Syndrome
Diabetes
Biomarkers
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.2
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv CONTEXT: Metabolic dysregulation underlies key metabolic risk factors—obesity, dyslipidemia, and dysglycemia. OBJECTIVE: To uncover mechanistic links between metabolomic dysregulation and metabolic risk by testing metabolite associations with risk factors cross-sectionally and with risk factor changes over time. DESIGN: Cross-sectional—discovery samples (n = 650; age, 36–69 years) from the Framingham Heart Study (FHS) and replication samples (n = 670; age, 61–76 years) from the BioImage Study, both following a factorial design sampled from high vs low strata of body mass index, lipids, and glucose. Longitudinal—FHS participants (n = 554) with 5–7 years of follow-up for risk factor changes. SETTING: Observational studies. PARTICIPANTS: Cross-sectional samples with or without obesity, dysglycemia, and dyslipidemia, excluding prevalent cardiovascular disease and diabetes or dyslipidemia treatment. Age- and sex-matched by group. INTERVENTIONS: None. MAIN OUTCOME MEASURE(S): Gas chromatography-mass spectrometry detected 119 plasma metabolites. Cross-sectional associations with obesity, dyslipidemia, and dysglycemia were tested in discovery, with external replication of 37 metabolites. Single- and multi-metabolite markers were tested for association with longitudinal changes in risk factors. RESULTS: Cross-sectional metabolite associations were identified with obesity (n = 26), dyslipidemia (n = 21), and dysglycemia (n = 11) in discovery. Glutamic acid, lactic acid, and sitosterol associated with all three risk factors in meta-analysis (P < 4.5 × 10−4). Metabolites associated with longitudinal risk factor changes were enriched for bioactive lipids. Multi-metabolite panels explained 2.5–15.3% of longitudinal changes in metabolic traits. CONCLUSIONS: Cross-sectional results implicated dysregulated glutamate cycling and amino acid metabolism in metabolic risk. Certain bioactive lipids were associated with risk factors cross-sectionally and over time, suggesting their upstream role in risk factor progression. Functional studies are needed to validate findings and facilitate translation into treatments or preventive measures.
Fil: Yin, Xiaoyan. Framingham Heart Study; Estados Unidos. Boston University; Estados Unidos
Fil: Subramanian, Subha. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos
Fil: Willinger, Christine M.. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos
Fil: Chen, George. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos
Fil: Juhasz, Peter. BG Medicine; Estados Unidos
Fil: Courchesne, Paul. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos
Fil: Chen, Brian H.. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos
Fil: Li, Xiaohang. BG Medicine; Estados Unidos
Fil: Hwang, Shih Jen. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos
Fil: Fox, Caroline S.. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos. Brigham and Women’s Hospital. Department of Medicine; Estados Unidos. Harvard Medical School; Estados Unidos
Fil: O'Donnell, Christopher J.. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos. Massachusetts General Hospital. Department of Medicine; Estados Unidos. Harvard Medical School; Estados Unidos
Fil: Muntendam, Pieter. BG Medicine; Estados Unidos
Fil: Fuster, Valentin. Mt. Sinai School of Medicine; Estados Unidos. Centro Nacional de Investigaciones Cardiovasculares; España. Cedars Sinai Medical Center; Estados Unidos
Fil: Bobeldijk Pastorova, Ivana. TNO Triskelion BV; Países Bajos
Fil: Sookoian, Silvia Cristina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Médicas. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; Argentina
Fil: Pirola, Carlos José. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Houssay. Instituto de Investigaciones Médicas. Universidad de Buenos Aires. Facultad de Medicina. Instituto de Investigaciones Médicas; Argentina
Fil: Gordon, Neal. BG Medicine; Estados Unidos
Fil: Adourian, Aram. BG Medicine; Estados Unidos
Fil: Larson, Martin G.. Framingham Heart Study; Estados Unidos. Boston University; Estados Unidos
Fil: Levy, Daniel. Framingham Heart Study; Estados Unidos. National Institutes of Health; Estados Unidos. Boston University; Estados Unidos
description CONTEXT: Metabolic dysregulation underlies key metabolic risk factors—obesity, dyslipidemia, and dysglycemia. OBJECTIVE: To uncover mechanistic links between metabolomic dysregulation and metabolic risk by testing metabolite associations with risk factors cross-sectionally and with risk factor changes over time. DESIGN: Cross-sectional—discovery samples (n = 650; age, 36–69 years) from the Framingham Heart Study (FHS) and replication samples (n = 670; age, 61–76 years) from the BioImage Study, both following a factorial design sampled from high vs low strata of body mass index, lipids, and glucose. Longitudinal—FHS participants (n = 554) with 5–7 years of follow-up for risk factor changes. SETTING: Observational studies. PARTICIPANTS: Cross-sectional samples with or without obesity, dysglycemia, and dyslipidemia, excluding prevalent cardiovascular disease and diabetes or dyslipidemia treatment. Age- and sex-matched by group. INTERVENTIONS: None. MAIN OUTCOME MEASURE(S): Gas chromatography-mass spectrometry detected 119 plasma metabolites. Cross-sectional associations with obesity, dyslipidemia, and dysglycemia were tested in discovery, with external replication of 37 metabolites. Single- and multi-metabolite markers were tested for association with longitudinal changes in risk factors. RESULTS: Cross-sectional metabolite associations were identified with obesity (n = 26), dyslipidemia (n = 21), and dysglycemia (n = 11) in discovery. Glutamic acid, lactic acid, and sitosterol associated with all three risk factors in meta-analysis (P < 4.5 × 10−4). Metabolites associated with longitudinal risk factor changes were enriched for bioactive lipids. Multi-metabolite panels explained 2.5–15.3% of longitudinal changes in metabolic traits. CONCLUSIONS: Cross-sectional results implicated dysregulated glutamate cycling and amino acid metabolism in metabolic risk. Certain bioactive lipids were associated with risk factors cross-sectionally and over time, suggesting their upstream role in risk factor progression. Functional studies are needed to validate findings and facilitate translation into treatments or preventive measures.
publishDate 2016
dc.date.none.fl_str_mv 2016-04
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/11336/44356
Yin, Xiaoyan; Subramanian, Subha; Willinger, Christine M.; Chen, George; Juhasz, Peter; et al.; Metabolite Signatures of Metabolic Risk Factors and their Longitudinal Changes; Endocrine Society; Journal of Clinical Endocrinology and Metabolism; 101; 4; 4-2016; 1779-1789
0021-972X
1945-7197
CONICET Digital
CONICET
url http://hdl.handle.net/11336/44356
identifier_str_mv Yin, Xiaoyan; Subramanian, Subha; Willinger, Christine M.; Chen, George; Juhasz, Peter; et al.; Metabolite Signatures of Metabolic Risk Factors and their Longitudinal Changes; Endocrine Society; Journal of Clinical Endocrinology and Metabolism; 101; 4; 4-2016; 1779-1789
0021-972X
1945-7197
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1210/jc.2015-2555
info:eu-repo/semantics/altIdentifier/url/https://academic.oup.com/jcem/article/101/4/1779/2804590
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 Endocrine Society
publisher.none.fl_str_mv Endocrine 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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