Optimized mass fatalities victim identification: an airplane crash as a test case

Autores
Corach, Daniel; Sala, Adriana Andrea; Bobillo, Maria Cecilia; Caputo, Mariela; Alechine, Evguenia; Irisarri, Maximiliano; Marino, M.; Canonaco, Enzo; Rodriguez, C.
Año de publicación
2013
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Efficient corpse tissue preservation, automated DNA extraction, sensitive DNA quantification and expert analysis software makes possible to design highly efficient workflows that speed up the mass disaster victim identification process from highly fragmented human bodies. Herein we describe the workflow employed in the reconstruction of the identity of 22 victims fragmented in 418 remains that emerged from the airplane crash occurred on May 18th 2011 in the province of Rio Negro, Argentina. Fatal victims identification was performed by comparison with first degree relatives by autosomal and Y STRs analysis. A SAAB plane carrying 19 passengers and three crew members (3 females and 19 males) exploded at high altitude over the ground level (approx. 2000 m). All bodies were severely fragmented and a high number of isolated cranial bones were found. Remains were collected at the disaster area and sent to Buenos Aires where samples were selected and preserved in 50 mL polypropylene tubes containing solid sodium chloride (table salt). DNA extractions from muscle and bone were performed using a semi-automated DNA purification system, quantification was carried out by Real Time PCR, STRs amplification using commercial kits and STR profile analysis with the help of an expert software. The implementation of this strategy allowed us to identify all the victims in one week. However, the complete task of identifying all remains recovered within the disaster area took over ten months due to the wide dispersion of fragments and the court's decision to identify each morphologically recognizable human tissue found within the disaster area.
Fil: Corach, Daniel. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Sala, Adriana Andrea. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Bobillo, Maria Cecilia. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Caputo, Mariela. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Alechine, Evguenia. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Irisarri, Maximiliano. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Marino, M.. Provincia de Mendoza. Poder Judicial de la Provincia de Mendoza. Laboratorio de ADN; Argentina
Fil: Canonaco, Enzo. Corte Suprema de Justicia de la Nación. Cuerpo Medico Forense; Argentina
Fil: Rodriguez, C.. Corte Suprema de Justicia de la Nación. Cuerpo Medico Forense; Argentina
Materia
Mass Fatalities Victim Identification
Autosomal Strs
Y-Strs
Expert Software
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:11336/15890
Acceder
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network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Optimized mass fatalities victim identification: an airplane crash as a test caseCorach, DanielSala, Adriana AndreaBobillo, Maria CeciliaCaputo, MarielaAlechine, EvgueniaIrisarri, MaximilianoMarino, M.Canonaco, EnzoRodriguez, C.Mass Fatalities Victim IdentificationAutosomal StrsY-StrsExpert Softwarehttps://purl.org/becyt/ford/3.5https://purl.org/becyt/ford/3Efficient corpse tissue preservation, automated DNA extraction, sensitive DNA quantification and expert analysis software makes possible to design highly efficient workflows that speed up the mass disaster victim identification process from highly fragmented human bodies. Herein we describe the workflow employed in the reconstruction of the identity of 22 victims fragmented in 418 remains that emerged from the airplane crash occurred on May 18th 2011 in the province of Rio Negro, Argentina. Fatal victims identification was performed by comparison with first degree relatives by autosomal and Y STRs analysis. A SAAB plane carrying 19 passengers and three crew members (3 females and 19 males) exploded at high altitude over the ground level (approx. 2000 m). All bodies were severely fragmented and a high number of isolated cranial bones were found. Remains were collected at the disaster area and sent to Buenos Aires where samples were selected and preserved in 50 mL polypropylene tubes containing solid sodium chloride (table salt). DNA extractions from muscle and bone were performed using a semi-automated DNA purification system, quantification was carried out by Real Time PCR, STRs amplification using commercial kits and STR profile analysis with the help of an expert software. The implementation of this strategy allowed us to identify all the victims in one week. However, the complete task of identifying all remains recovered within the disaster area took over ten months due to the wide dispersion of fragments and the court's decision to identify each morphologically recognizable human tissue found within the disaster area.Fil: Corach, Daniel. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Sala, Adriana Andrea. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Bobillo, Maria Cecilia. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Caputo, Mariela. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Alechine, Evguenia. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Irisarri, Maximiliano. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Marino, M.. Provincia de Mendoza. Poder Judicial de la Provincia de Mendoza. Laboratorio de ADN; ArgentinaFil: Canonaco, Enzo. Corte Suprema de Justicia de la Nación. Cuerpo Medico Forense; ArgentinaFil: Rodriguez, C.. Corte Suprema de Justicia de la Nación. Cuerpo Medico Forense; ArgentinaElsevier Ireland2013-11info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/15890Corach, Daniel; Sala, Adriana Andrea; Bobillo, Maria Cecilia; Caputo, Mariela; Alechine, Evguenia; et al.; Optimized mass fatalities victim identification: an airplane crash as a test case; Elsevier Ireland; Forensic Science International: Genetics Supplement Series; 4; 1; 11-2013; e222-e2231875-1741enginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S1875176813001157info:eu-repo/semantics/altIdentifier/doi/10.1016/j.fsigss.2013.10.114info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-15T14:53:39Zoai:ri.conicet.gov.ar:11336/15890instacron: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 14:53:39.402CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Optimized mass fatalities victim identification: an airplane crash as a test case
title Optimized mass fatalities victim identification: an airplane crash as a test case
spellingShingle Optimized mass fatalities victim identification: an airplane crash as a test case
Corach, Daniel
Mass Fatalities Victim Identification
Autosomal Strs
Y-Strs
Expert Software
title_short Optimized mass fatalities victim identification: an airplane crash as a test case
title_full Optimized mass fatalities victim identification: an airplane crash as a test case
title_fullStr Optimized mass fatalities victim identification: an airplane crash as a test case
title_full_unstemmed Optimized mass fatalities victim identification: an airplane crash as a test case
title_sort Optimized mass fatalities victim identification: an airplane crash as a test case
dc.creator.none.fl_str_mv Corach, Daniel
Sala, Adriana Andrea
Bobillo, Maria Cecilia
Caputo, Mariela
Alechine, Evguenia
Irisarri, Maximiliano
Marino, M.
Canonaco, Enzo
Rodriguez, C.
author Corach, Daniel
author_facet Corach, Daniel
Sala, Adriana Andrea
Bobillo, Maria Cecilia
Caputo, Mariela
Alechine, Evguenia
Irisarri, Maximiliano
Marino, M.
Canonaco, Enzo
Rodriguez, C.
author_role author
author2 Sala, Adriana Andrea
Bobillo, Maria Cecilia
Caputo, Mariela
Alechine, Evguenia
Irisarri, Maximiliano
Marino, M.
Canonaco, Enzo
Rodriguez, C.
author2_role author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Mass Fatalities Victim Identification
Autosomal Strs
Y-Strs
Expert Software
topic Mass Fatalities Victim Identification
Autosomal Strs
Y-Strs
Expert Software
purl_subject.fl_str_mv https://purl.org/becyt/ford/3.5
https://purl.org/becyt/ford/3
dc.description.none.fl_txt_mv Efficient corpse tissue preservation, automated DNA extraction, sensitive DNA quantification and expert analysis software makes possible to design highly efficient workflows that speed up the mass disaster victim identification process from highly fragmented human bodies. Herein we describe the workflow employed in the reconstruction of the identity of 22 victims fragmented in 418 remains that emerged from the airplane crash occurred on May 18th 2011 in the province of Rio Negro, Argentina. Fatal victims identification was performed by comparison with first degree relatives by autosomal and Y STRs analysis. A SAAB plane carrying 19 passengers and three crew members (3 females and 19 males) exploded at high altitude over the ground level (approx. 2000 m). All bodies were severely fragmented and a high number of isolated cranial bones were found. Remains were collected at the disaster area and sent to Buenos Aires where samples were selected and preserved in 50 mL polypropylene tubes containing solid sodium chloride (table salt). DNA extractions from muscle and bone were performed using a semi-automated DNA purification system, quantification was carried out by Real Time PCR, STRs amplification using commercial kits and STR profile analysis with the help of an expert software. The implementation of this strategy allowed us to identify all the victims in one week. However, the complete task of identifying all remains recovered within the disaster area took over ten months due to the wide dispersion of fragments and the court's decision to identify each morphologically recognizable human tissue found within the disaster area.
Fil: Corach, Daniel. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Sala, Adriana Andrea. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Bobillo, Maria Cecilia. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Caputo, Mariela. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Alechine, Evguenia. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Irisarri, Maximiliano. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Servicio de Huellas Digitales Genéticas; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Marino, M.. Provincia de Mendoza. Poder Judicial de la Provincia de Mendoza. Laboratorio de ADN; Argentina
Fil: Canonaco, Enzo. Corte Suprema de Justicia de la Nación. Cuerpo Medico Forense; Argentina
Fil: Rodriguez, C.. Corte Suprema de Justicia de la Nación. Cuerpo Medico Forense; Argentina
description Efficient corpse tissue preservation, automated DNA extraction, sensitive DNA quantification and expert analysis software makes possible to design highly efficient workflows that speed up the mass disaster victim identification process from highly fragmented human bodies. Herein we describe the workflow employed in the reconstruction of the identity of 22 victims fragmented in 418 remains that emerged from the airplane crash occurred on May 18th 2011 in the province of Rio Negro, Argentina. Fatal victims identification was performed by comparison with first degree relatives by autosomal and Y STRs analysis. A SAAB plane carrying 19 passengers and three crew members (3 females and 19 males) exploded at high altitude over the ground level (approx. 2000 m). All bodies were severely fragmented and a high number of isolated cranial bones were found. Remains were collected at the disaster area and sent to Buenos Aires where samples were selected and preserved in 50 mL polypropylene tubes containing solid sodium chloride (table salt). DNA extractions from muscle and bone were performed using a semi-automated DNA purification system, quantification was carried out by Real Time PCR, STRs amplification using commercial kits and STR profile analysis with the help of an expert software. The implementation of this strategy allowed us to identify all the victims in one week. However, the complete task of identifying all remains recovered within the disaster area took over ten months due to the wide dispersion of fragments and the court's decision to identify each morphologically recognizable human tissue found within the disaster area.
publishDate 2013
dc.date.none.fl_str_mv 2013-11
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/11336/15890
Corach, Daniel; Sala, Adriana Andrea; Bobillo, Maria Cecilia; Caputo, Mariela; Alechine, Evguenia; et al.; Optimized mass fatalities victim identification: an airplane crash as a test case; Elsevier Ireland; Forensic Science International: Genetics Supplement Series; 4; 1; 11-2013; e222-e223
1875-1741
url http://hdl.handle.net/11336/15890
identifier_str_mv Corach, Daniel; Sala, Adriana Andrea; Bobillo, Maria Cecilia; Caputo, Mariela; Alechine, Evguenia; et al.; Optimized mass fatalities victim identification: an airplane crash as a test case; Elsevier Ireland; Forensic Science International: Genetics Supplement Series; 4; 1; 11-2013; e222-e223
1875-1741
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S1875176813001157
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.fsigss.2013.10.114
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
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Ireland
publisher.none.fl_str_mv Elsevier Ireland
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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