Assessment of taphonomic effects on biomolecule degradation for the estimation of post-mortem interval of human remains

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Understanding the decomposition process and its correlation with Post-Mortem Interval (PMI) estimation is crucial in forensic science. This thesis explores various aspects of decomposition research, focusing on visual assessment, nuclear DNA (nDNA) and mitochondrial DNA (mtDNA) degradation and the assessment of proteins as biomarkers for correlation with PMI. The study, conducted in an Australian context, provides insights into the complex interplay of intrinsic and extrinsic factors affecting decomposition for future application in Australian case work. Visual assessment, utilising a Total Body Score (TBS) method, revealed trends in decomposition progression influenced by seasons. The study suggests adapting TBS methods to regional compilatory values to reduce subjectivity, however, the legal admissibility of visual assessments in Australian contexts presents challenges, indicating a need for a more objective understanding of the decomposition process and its correlation with PMI. nDNA degradation showed a linear relationship with time, impacted by thermal energy and body mass. Contrary to previous research, body mass significantly influenced degradation rates, suggesting its incorporation into PMI estimations. Issues with mtDNA assessment hindered conclusive results necessitating further validation and highlighting the need for improved mtDNA analysis techniques. Proteomic biomarkers for PMI estimation, identified through LC-MS/MS techniques, show promise due to their stability against intrinsic factors like body mass, sex, and age. Thirteen proteins were proposed as potential biomarkers, showing a consistent correlation with PMI across samples. Future research should consider intrinsic factors such as cause of death, pre-mortem conditions, and microbiomes. Collaborative efforts, machine learning, and consistent experimental designs is proposed for robust dataset creation, and the validation and review of any PMI prediction models is crucial before forensic application. This thesis contributes valuable insights into decomposition processes and their implications for PMI estimation. Of the included analytic techniques, proteomic biomarkers show greater promise for more reliable PMI estimations, though further research and validation are necessary. Overall, this research lays a foundation for improved PMI estimation techniques in forensic science.
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