Multi-omics integration strategy in the post-mortem interval of forensic science

Li, Jian; Wu, Yan-juan; Liu, Ming-feng; Li, Na; Dang, Li-hong; An, Guo-shuai; Lu, Xiao-jun; Wang, Liang-liang; Du, Qiu-xiang; Cao, Jie; Sun, Jun-hong

doi:10.1016/j.talanta.2023.125249

Cited by 4 publications

(2 citation statements)

References 34 publications

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“…While many studies have utilized a single omics methodology to explore forensic inquiries or have combined one omics approach with other non-omics techniques [355][356][357][358][359], there remains a notable scarcity of research that delves into the use of multiple omics approaches and in their integration to approach the same questions from diverse perspectives. Burcham et al [360] used a murine model that included various organs to investigate the bacterial dynamics during decomposition.…”

Section: Integration Of Omics Approachesmentioning

confidence: 99%

From flesh to bones: Multi‐omics approaches in forensic science

Procopio,

Bonicelli

2024

Proteomics

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Recent advancements in omics techniques have revolutionised the study of biological systems, enabling the generation of high‐throughput biomolecular data. These innovations have found diverse applications, ranging from personalised medicine to forensic sciences. While the investigation of multiple aspects of cells, tissues or entire organisms through the integration of various omics approaches (such as genomics, epigenomics, metagenomics, transcriptomics, proteomics and metabolomics) has already been established in fields like biomedicine and cancer biology, its full potential in forensic sciences remains only partially explored. In this review, we have presented a comprehensive overview of state‐of‐the‐art analytical platforms employed in omics research, with specific emphasis on their application in the forensic field for the identification of the cadaver and the cause of death. Moreover, we have conducted a critical analysis of the computational integration of omics approaches, and highlighted the latest advancements in employing multi‐omics techniques for forensic investigations.

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Section: Integration Of Omics Approachesmentioning

confidence: 99%

From flesh to bones: Multi‐omics approaches in forensic science

Procopio,

Bonicelli

2024

Proteomics

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“…Several applications have been used to perform biomechanical studies on patterns of cranial bone fracture [36]. Furthermore, other papers have focused on the application of AI for the definition of the post-mortem interval (PMI) [37]. Finally, in medico-legal sciences, AI could play a pivotal role in the management of medical liability [38,39].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence and Forensic Genetics: Current Applications and Future Perspectives

Sessa,

Esposito,

Cocimano

et al. 2024

Applied Sciences

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The term artificial intelligence (AI) was coined in the 1950s and it has successfully made its way into different fields of medicine. Forensic sciences and AI are increasingly intersecting fields that hold tremendous potential for solving complex criminal investigations. Considering the great evolution in the technologies applied to forensic genetics, this literature review aims to explore the existing body of research that investigates the application of AI in the field of forensic genetics. Scopus and Web of Science were searched: after an accurate evaluation, 12 articles were included in the present systematic review. The application of AI in the field of forensic genetics has predominantly focused on two aspects. Firstly, several studies have investigated the use of AI in haplogroup analysis to enhance and expedite the classification process of DNA samples. Secondly, other research groups have utilized AI to analyze short tandem repeat (STR) profiles, thereby minimizing the risk of misinterpretation. While AI has proven to be highly useful in forensic genetics, further improvements are needed before using these applications in real cases. The main challenge lies in the communication gap between forensic experts: as AI continues to advance, the collaboration between forensic sciences and AI presents immense potential for transforming investigative practices, enabling quicker and more precise case resolutions.

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The metabolic clock of ketamine abuse in rats by a machine learning model

Wang,

Zheng,

Yang

et al. 2024

Sci Rep

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Ketamine has recently become an anesthetic drug used in human and veterinary clinical medicine for illicit abuse worldwide, but the detection of illicit abuse and inference of time intervals following ketamine abuse are challenging issues in forensic toxicological investigations. Here, we developed methods to estimate time intervals since ketamine use is based on significant metabolite changes in rat serum over time after a single intraperitoneal injection of ketamine, and global metabolomics was quantified by ultra-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (UPLC-Q-TOF–MS). Thirty-five rats were treated with saline (control) or ketamine at 3 doses (30, 60, and 90 mg/kg), and the serum was collected at 21 time points (0 h to 29 d). Time-dependent rather than dose-dependent features were observed. Thirty-nine potential biomarkers were identified, including ketamine and its metabolites, lipids, serotonin and other molecules, which were used for building a random forest model to estimate time intervals up to 29 days after ketamine treatment. The accuracy of the model was 85.37% in the cross-validation set and 58.33% in the validation set. This study provides further understanding of the time-dependent changes in metabolites induced by ketamine abuse.

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Multi-omics integration strategy in the post-mortem interval of forensic science

Cited by 4 publications

References 34 publications

From flesh to bones: Multi‐omics approaches in forensic science

From flesh to bones: Multi‐omics approaches in forensic science

Artificial Intelligence and Forensic Genetics: Current Applications and Future Perspectives

The metabolic clock of ketamine abuse in rats by a machine learning model

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