Evidence map›Paper›PMID 41249520›Full record

ReviewInternational journal of legal medicine2026

Application of RNA markers in forensic body fluid analysis: from specificity and stability to polymorphism.

Zhiyong Liu 刘志勇, Riga Wu, Hanzong Li, Bin Cong, Hongyu Sun

Abstract readReview
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In one paragraph

Review in International journal of legal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Zhiyong Liu 刘志勇 *Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China.ORCID http://orcid.org/0000-0003-2176-6884
Riga Wu *Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China.ORCID http://orcid.org/0000-0002-8594-2843
Hanzong LiChobanian & Avedisian School of Medicine, Boston University, Boston, 02118, USA.
Bin CongCollege of Forensic Medicine, Hebei Key Laboratory of Forensic Medicine, Hebei Medical University, Shijiazhuang, 050017, China. cong6406@hebmu.edu.cn.
Hongyu SunFaculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, 510080, China. sunhy@mail.sysu.edu.cn.ORCID http://orcid.org/0000-0002-5926-4495

Funding

National Natural Science Foundation of China 82293650National Natural Science Foundation of China 82293655
6 · The paper itself

Abstract

Body fluid/tissue identification (BFID) is a fundamental forensic task for determining the origin of biological evidence such as blood, saliva, and semen. While traditional BFID methods rely on enzymatic, immunological, or spectroscopic methods, the emergence of RNA profiling has expanded its capabilities to not only identify body fluid/tissue but also, to some extent, assign them to specific contributors. This review focuses on three fundamental biological characteristics of RNA molecules that underpin their applications: specificity, stability, and polymorphism (length, sequence, and expression variations). Furthermore, research progress in RNA-based fluid/tissue analysis is discussed, highlighting the applications of these properties and addressing the remaining challenges. This article provides a comprehensive overview of the principles and current state of RNA analysis for forensic body fluid/tissue identification and contributor assignment.

Indexed as

Body FluidsForensic GeneticsPolymorphism, GeneticRNAGenetic MarkersHumansRNA StabilitySalivaSemenGenetic MarkersRNABody fluid/tissue identificationContributor assignmentForensic geneticsRNA characteristicsRNA polymorphism

Identifiers

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.