Innovative strategies for estimating the postmortem interval in forensic practice: multiomics, artificial intelligence, and hybrid models (a review)

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Abstract

Determination of the postmortem interval remains one of the key tasks in forensic practice, as the accuracy of this assessment directly affects the objectivity of expert conclusions and the effectiveness of investigative procedures. Traditional postmortem interval estimation methods based on morphological indicators and thermometry have limited reliability, especially in the late postmortem period. Current research focuses on developing innovative approaches employing molecular technologies, microbiome analysis, multiomic strategies, and the integration of artificial intelligence for large-scale data processing.

This review summarizes modern methods for estimating the postmortem interval, including nucleic acid (DNA and RNA) analysis, proteomic and metabolomic approaches, and the study of microbiome changes. Particular attention is given to immunohistochemical markers, mass spectrometry, and nuclear magnetic resonance for quantification of biochemical processes in tissues and biological fluids. The prospects of applying molecular and chemical methods in forensic entomology during the late postmortem period are highlighted. A separate section discusses the use of machine and deep learning algorithms to construct predictive models based on multimodal data, including microbiome profiles, imaging features, and environmental parameters. Examples of combined approaches integrating biomolecular markers and computational technologies are presented, enabling more accurate estimation of the postmortem interval during both early and late postmortem periods.

About the authors

Gulgena R. Mustafina

Bashkir State Medical University

Email: gulgenarm@mail.ru
ORCID iD: 0000-0003-2534-6385
SPIN-code: 8904-2046

MD, Cand. Sci. (Medicine), Assistant Professor

Russian Federation, Ufa

Kirill O. Kuznetsov

Ufa University of Science and Technology; Bureau of Forensic Medical Examination

Author for correspondence.
Email: kuznetsovarticles@mail.ru
ORCID iD: 0000-0002-2405-1801
SPIN-code: 3053-3773

MD

Russian Federation, Ufa; Ufa

Svetlana A. Kosobutskaya

Sechenov First Moscow State Medical University (Sechenov University)

Email: fotinia78@mail.ru
ORCID iD: 0000-0002-5484-9574
SPIN-code: 2589-3752

MD, Cand. Sci. (Medicine)

Russian Federation, Moscow

Maksim A. Sokolovskiy

The Russian National Research Medical University named after N.I. Pirogov

Email: maks_sokolovskiy@internet.ru
ORCID iD: 0009-0005-4998-3532
SPIN-code: 8809-6895
Russian Federation, Moscow

Alvina I. Semenova

The Russian National Research Medical University named after N.I. Pirogov

Email: semyonowaalvina@yandex.ru
ORCID iD: 0009-0009-7823-9322
Russian Federation, Moscow

Valeriy N. Korotun

Bashkir State Medical University

Email: korotun_vn@mail.ru
ORCID iD: 0000-0001-9654-3269
SPIN-code: 5855-3161

MD, Cand. Sci. (Medicine), Assistant Professor

Russian Federation, Ufa

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