00000caa a22000003i 4500 UP-1685594773862388477 Buklod 20210316094106.0 m | | ta 210316s2018 xx r |||| u|eng d (iLib)UPBAG-00039513667 STII-DOST BAG rda eng ARTICLE-2672 Calacal, Gayvelline C. author. Pathology and DNA analysis of exhumed human remains three-years post-mortem by Gayvelline C. Calacal, Jazelyn M. Salvador, Minerva S. Sagum, Raquel D. Fortun, and Maria Corazon A. De Ungria. 2018. pages 9-16 illustrations (some color) 26 cm text rdacontent unmediated rdamedia volume rdacarrier Includes bibliographical references (pages 14-16) In the past three decades after the discovery of DNA fingerprinting, there has been a remarkable growth in the use of DNA evidence worldwide. This paper highlights the value of using a scientific approach in assisting courts of law in resolving disputed parentage or kinship issues. This report describes the use of pathology in verifying the identity of a cadaver via examination and comparison with ante-mortem information of the deceased. Subsequent DNA testing of the skeletal remains â?? exhumed three years post-mortem â?? was used to confirm the identity of the woman using a living sibling as reference, and to evaluate the relationship of the deceased with a person claiming to be her offspring. Genetic comparisons at 15 autosomal Short Tandem Repeat (aSTR) regions and the mitochondrial hypervariable regions I and II (mtDNA HVR I and HVR II) of the deceased and her brother confirmed that they were siblings. Conversely, the DNA test negated the statements of the person claiming to be the child of the deceased. Autosomal short tandem repeats (astr). Exhumed human remains. Forensic genetics. Maternity analysis. Mitochondrial dna (mtdna) Sibship analysis. Genetics. Salvador, Jazelyn M. author. Sagum, Minerva S. author. Fortun, Raquel D. author. De Ungria, Maria Corazon A. author. The Philippine Journal of Science Vol. 147, no. 1, March 2018. Request full-text access via UPB University Library through https://forms.gle/KZjBv7aRtY6jiL5E9 (viewed 16 March 2021) FI UPBAG UPBAG-MAIN ARTICLE-2672 Analytics