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J Forensic Sci ; 65(4): 1049-1055, 2020 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31999362

RESUMO

One of the many difficulties associated with identifying undocumented border crossers stems from an inability to narrow down the search area for the region of origin and family members to obtain family reference samples for DNA comparison. While the geography of regions of origins is wide, the biological profiles of the undocumented border crossers often show strong similarities, young and male. The isotopic composition of human bones, teeth, and hair has been demonstrated to be useful biomarkers for tracing locations and movements of individuals and for aiding in the identification of human remains. Data obtained from human remains can be compared to and aligned with various reference sources, such as soils and bedrock, archaeological remains, or cultural data. Here, the spatial deficiency in isotopic reference data for Mexico, specifically for oxygen (δ18 O) isotopes in tap water, is being addressed through the collection and analysis of over 150 water samples and explored with tooth enamel isotopic values from recently identified Mexican nationals. The isoscape was developed using a Spine with Barriers interpolation method and shows sufficient detail to narrow down the regions where specific isotopic values are represented. The individuals were plotted on the developed isoscape using conditional correlations. The methodology was successful in assigning the correct regions of origin for the two individuals, which shows the tremendous potential of the developed isoscape. Nonetheless, there is more research needed to further improve upon this geolocation method, including analysis of multiple isotopes in different tissues, and the development of new isotopic methods.


Assuntos
Esmalte Dentário/química , Emigrantes e Imigrantes , Geografia , Isótopos de Oxigênio/análise , Abastecimento de Água , Água/química , Dente Pré-Molar/química , Restos Mortais , Antropologia Forense/métodos , Odontologia Legal/métodos , Humanos , México , Modelos Estatísticos , Estados Unidos
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