Evidence map›Paper›PMID 21845441›Full record

ArticleInternational journal of legal medicine2012

Validation of reference genes for estimating wound age in contused rat skeletal muscle by quantitative real-time PCR.

Jun-hong Sun, Liang-huan Nan, Cai-rong Gao, Ying-yuan Wang

Abstract read
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In one paragraph

Article in International journal of legal medicine, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
1.6field-weighted citation impact, top 18% 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

18 citing papers in PubMed, 1 synthesis or guideline pooled it, 44 citations in OpenAlex.

  1. State-of-the-Art on Wound Vitality Evaluation: A Systematic Review.International journal of molecular sciences · 2022
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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

4 authors at 2 institutions in 1 country.

Jun-hong SunDepartment of Forensic Pathology, Shanxi Medical University, Taiyuan 030001, Shanxi, People's Republic of China.
Liang-huan Nan
Cai-rong Gao
Ying-yuan Wang
Shanxi Medical University · CNTaiyuan Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Gene expression profiling by quantitative real-time PCR (RT-qPCR) is a valuable tool in forensic science for estimating the age of a wound. To accurately assess gene expression levels over time in injured tissue, the genes used as internal reference standards must be carefully validated for transcriptional stability. This study examined the transcriptional stability of nine potential reference genes (β-actin, GAPDH, RPL32, PGK1, SDHA, RPL13, HPRT, Tbp, and Ywhaz) in contused rat skeletal muscle by RT-qPCR. The raw Ct values were determined for each candidate gene at different time points following contusion, and the data were analyzed by the NormFinder, geNorm, and BestKeeper validation programs. The reference genes RPL13 and RPL32 were the most stably expressed genes in contused skeletal muscle, whereas PGK1 was the least stable. The commonly used reference genes β-actin and GAPDH appeared to be too unstable for normalization of RT-qPCR expression profiling in contused muscle. The reference genes RPL13 and RPL32 were also the best combination for multianalysis. The use of RPL13 and RPL32 as internal standards may improve the accuracy of gene expression studies aimed at determining the age of early wounds in forensic investigations.

Indexed as

Gene Expression ProfilingReal-Time Polymerase Chain ReactionAnimalsContusionsHindlimbMaleMuscle, SkeletalRatsRats, Sprague-DawleyTime Factors

Identifiers

PMID21845441
OpenAlexW2006839026

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.