Evidence map›Paper›PMID 29691731›Full record

ArticleForensic science, medicine, and pathology2018

Evaluating the potential of housekeeping genes, rRNAs, snRNAs, microRNAs and circRNAs as reference genes for the estimation of PMI.

Chunyan Tu, Tieshuai Du, Chengchen Shao, Zengjia Liu, Liliang Li, Yiwen Shen

Abstract read
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In one paragraph

Article in Forensic science, medicine, and pathology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 2 pooled it
2.4field-weighted citation impact, top 10% of its field
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

30 citing papers in PubMed, 2 syntheses or guidelines pooled it, 74 citations in OpenAlex.

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  16. Review of the current and potential use of biological and molecular methods for the estimation of the postmortem interval in animals and humans.Journal of veterinary diagnostic investigation : official publication of the American Association of Veterinary Laboratory Diagnosticians, Inc · 2023
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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

6 authors at 1 institution in 1 country.

Chunyan TuDepartment of Forensic Medicine, School of Basic Medical Sciences, Fudan University, 138 Yixueyuan Road, Xuhui District, Shanghai, 200032, People's Republic of China.
Tieshuai DuDepartment of Forensic Medicine, School of Basic Medical Sciences, Fudan University, 138 Yixueyuan Road, Xuhui District, Shanghai, 200032, People's Republic of China.
Chengchen ShaoDepartment of Forensic Medicine, School of Basic Medical Sciences, Fudan University, 138 Yixueyuan Road, Xuhui District, Shanghai, 200032, People's Republic of China.
Zengjia LiuDepartment of Forensic Medicine, School of Basic Medical Sciences, Fudan University, 138 Yixueyuan Road, Xuhui District, Shanghai, 200032, People's Republic of China.
Liliang LiDepartment of Forensic Medicine, School of Basic Medical Sciences, Fudan University, 138 Yixueyuan Road, Xuhui District, Shanghai, 200032, People's Republic of China. liliangli11@fudan.edu.cn.
Yiwen ShenDepartment of Forensic Medicine, School of Basic Medical Sciences, Fudan University, 138 Yixueyuan Road, Xuhui District, Shanghai, 200032, People's Republic of China. shenyiwen@fudan.edu.cn.
Shanghai Medical College of Fudan University · CN

Funding

the Opening Foundation of Shanghai Key Laboratory of Crime Scene Evidence XCWZ20
6 · The paper itself

Abstract

The precise estimation of postmortem interval (PMI) is a critical step in death investigation of forensic cases. Detecting the degradation of RNA in tissues by real time quantitative polymerase chain reaction (RT-qPCR) technology provides a new theoretical basis for estimation of PMI. However, most commonly used reference genes degrade over time, while previous studies seldom consider this when selecting suitable reference genes for the estimation of PMI. Studies have shown microRNAs (miRNAs) are very stable and circular RNAs (circRNAs) have recently emerged as a novel class of RNAs with high stability. We aimed to evaluate the stability of the two kinds of RNAs and normal reference genes using geNorm and NormFinder algorithms to identify tissue-specific reference genes for PMI estimation. The content of candidate RNAs from mouse heart, liver and skeletal muscle tissues were dynamically examined in 8 consecutive days after death. Among the 11 candidate genes (β-actin, Gapdh, Rps18, 5S, 18S, U6, miR-133a, miR-122, circ-AFF1, LC-Ogdh and LC-LRP6), the following genes showed prioritized stability: miR-122, miR-133a and 18S in heart tissues; LC-Ogdh, circ-AFF1 and miR-122 in liver tissues; and miR-133a, circ-AFF1 and LC-LRP6 in skeletal muscle tissues. Our results suggested that miRNAs and circRNAs were more stable as reference genes than other kinds of RNAs regarding PMI estimation. The appropriate internal control genes were not completely the same across tissue types.

Indexed as

Genes, EssentialPostmortem ChangesAnimalsLiverMiceMice, Inbred BALB CMicroRNAsMuscle, SkeletalMyocardiumReal-Time Polymerase Chain ReactionRNARNA, CircularRNA, RibosomalRNA, Small NuclearMicroRNAsRNARNA, CircularRNA, RibosomalRNA, Small NuclearcircRNAsmiRNAsPostmortem interval (PMI)Reference genesRT-qPCR

Identifiers

PMID29691731
OpenAlexW2800658546

What OpenQuestion holds

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Read underepoch 390

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.