Evidence map›Paper›PMID 38467753›Full record

SynthesisInternational journal of legal medicine2024

Advances in body fluid identification: MiRNA markers as powerful tool.

Mohd Hamza, Deeksha Sankhyan, Saurabh Shukla, Preeti Pandey

Abstract readSystematic Review
PubMed Publisher
In one paragraph

Synthesis in International journal of legal medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
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

4 authors.

Mohd HamzaDepartment of Forensic Science, School of Bioengineering and Biosciences, Lovely Professional University, Phagwara, Punjab, 144411, India.
Deeksha SankhyanDepartment of Forensic Science, School of Bioengineering and Biosciences, Lovely Professional University, Phagwara, Punjab, 144411, India. deeksha.sankhyan@gmail.com.ORCID http://orcid.org/0000-0002-1899-9786
Saurabh ShuklaDepartment of Forensic Science, School of Bioengineering and Biosciences, Lovely Professional University, Phagwara, Punjab, 144411, India.
Preeti PandeyDepartment of Forensic Science, School of Bioengineering and Biosciences, Lovely Professional University, Phagwara, Punjab, 144411, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Body fluids are one of the most encountered types of evidence in any crime and are commonly used for identifying a person's identity. In addition to these, they are also useful in ascertaining the nature of crime by determining the ty pe of fluid such as blood, semen, saliva, urine etc. Body fluids collected from crime scenes are mostly found in degraded, trace amounts and/or mixed with other fluids. However, the existing immunological and enzyme-based methods used for differentiating these fluids show limited specificity and sensitivity in such cases. To overcome these challenges, a new method utilizing microRNA expression of the body fluids has been proposed. This method is believed to be non-destructive as well as sensitive in nature and researches have shown promising results for highly degraded samples as well. This systematic review focuses on and explores the use and reliability of miRNAs in body fluid identification. It also summarizes the researches conducted on various aspects of miRNA in terms of body fluid examination in forensic investigations.

Indexed as

Body FluidsMicroRNAsBiomarkersForensic GeneticsGenetic MarkersHumansSalivaSemenBiomarkersGenetic MarkersMicroRNAsBody fluid identificationForensic biologyForensic biomarkersmicroRNASocial and criminal justice

Identifiers

What OpenQuestion holds

Textmetadata
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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.