Evidence map›Paper›PMID 26363634›Full record

ArticleForensic science, medicine, and pathology2015

Exploration of the R code-based mathematical model for PMI estimation using profiling of RNA degradation in rat brain tissue at different temperatures.

Jianlong Ma, Hui Pan, Yan Zeng, Yehui Lv, Heng Zhang, Aimin Xue, Jieqing Jiang, Kaijun Ma, Long Chen

Abstract read
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In one paragraph

Article in Forensic science, medicine, and pathology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 3 pooled it
–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

27 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
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  14. 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
    Review
  15. Article
  16. Article
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  19. Article
  20. MicroRNAs: An Update of Applications in Forensic Science.Diagnostics (Basel, Switzerland) · 2020
    Review
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

9 authors.

Jianlong MaDepartment of Forensic Medicine, Shanghai Medical School of Fudan University, 131 Dongan Road, Shanghai, 200032, People's Republic of China.
Hui PanDepartment of Forensic Medicine, Shanghai Medical School of Fudan University, 131 Dongan Road, Shanghai, 200032, People's Republic of China.
Yan ZengDepartment of Forensic Medicine, Shanghai Medical School of Fudan University, 131 Dongan Road, Shanghai, 200032, People's Republic of China.
Yehui LvDepartment of Forensic Medicine, Shanghai Medical School of Fudan University, 131 Dongan Road, Shanghai, 200032, People's Republic of China.
Heng ZhangDepartment of Forensic Medicine, Shanghai Medical School of Fudan University, 131 Dongan Road, Shanghai, 200032, People's Republic of China.
Aimin XueDepartment of Forensic Medicine, Shanghai Medical School of Fudan University, 131 Dongan Road, Shanghai, 200032, People's Republic of China.
Jieqing JiangDepartment of Forensic Medicine, Shanghai Medical School of Fudan University, 131 Dongan Road, Shanghai, 200032, People's Republic of China.
Kaijun MaForensic Lab, Criminal Science and Technology Institute, Shanghai Public Security Bureau, 803 North Zhongshan Road, Shanghai, 200082, People's Republic of China. makaijun@sina.cn.
Long ChenDepartment of Forensic Medicine, Shanghai Medical School of Fudan University, 131 Dongan Road, Shanghai, 200032, People's Republic of China. chenlong@shmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Precise estimation of postmortem interval (PMI) is crucial in some criminal cases. This study aims to find some optimal markers for PMI estimation and build a mathematical model that could be used in various temperature conditions. Different mRNA and microRNA markers in rat brain samples were detected using real-time fluorescent quantitative PCR at 12 time points within 144 h postmortem and at temperatures of 4, 15, 25, and 35 °C. Samples from 36 other rats were used to verify the animal mathematical model. Brain-specific mir-9 and mir-125b are effective endogenous control markers that are not affected by PMI up to 144 h postmortem under these temperatures, whereas the commonly used U6 is not a suitable endogenous control in this study. Among all the candidate markers, ΔCt (β-actin) has the best correlation coefficient with PMI and was used to build a new model using R software which can simultaneously manage both PMI and temperature parameters. This animal mathematical model is verified using samples from 36 other rats and shows increased accuracy for higher temperatures and longer PMI. In this study, β-actin was found to be an optimal marker to estimate PMI and some other markers were found to be suitable to act as endogenous controls. Additionally, we have used R code software to build a model of PMI estimation that could be used in various temperature conditions.

Indexed as

Models, TheoreticalPostmortem ChangesRNA StabilityTemperatureActinsAnimalsBrainGenetic MarkersMicroRNAsModels, AnimalRats, Sprague-DawleyReal-Time Polymerase Chain ReactionSoftwareSpecimen HandlingActinsGenetic MarkersMicroRNAsMIRN125 microRNA, ratMIRN9 microRNA, ratPostmortem interval (PMI)R codeReverse transcription quantitative real-time PCRRNA

Identifiers

PMID26363634

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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.