Evidence map›Paper›PMID 38882314›Full record

ArticleHeliyon2024

Estimating postmortem interval based on oral microbial community succession in rat cadavers.

Xiaoxue Wang, Cuiyun Le, Xiaoye Jin, Yuhang Feng, Li Chen, Xiaolan Huang, Shunyi Tian, Qiyan Wang, Jingyan Ji, Yubo Liu and 3 more

Abstract read
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 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

7 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

13 authors.

Xiaoxue WangDepartment of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China.
Cuiyun LeDepartment of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China.
Xiaoye JinDepartment of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China.
Yuhang FengDepartment of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China.
Li ChenDepartment of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China.
Xiaolan HuangDepartment of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China.
Shunyi TianDepartment of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China.
Qiyan WangDepartment of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China.
Jingyan JiDepartment of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China.
Yubo LiuDepartment of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China.
Hongling ZhangDepartment of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China.
Jiang HuangDepartment of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China.
Zheng RenDepartment of Forensic Medicine, Guizhou Medical University, Guiyang, 550004, Guizhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The accurate estimation of the postmortem interval has been one of the crucial issues to be solved in forensic research, and it is influenced by various factors in the process of decay. With the development of high-throughput sequencing technology, forensic microbiology has become the major hot topic in forensic science, which provides new research options for postmortem interval estimation. The oral microbial community is one of the most diverse of microbiomes, ranking as the second most abundant microbiota following the gastrointestinal tract. It is remarkable that oral microorganisms have a significant function in the decay process of cadavers. Therefore, we collected outdoor soil to simulate the death environment and focused on the relationship between oral microbial community succession and PMI in rats above the soil. In addition, linear regression models and random forest regression models were developed for the relationship between the relative abundance of oral microbes and PMI. We also identified a number of microorganisms that may be important to estimate PMI, including:

Indexed as

16S rRNAForensic microbiologyOral microbial communityPostmortem interval

Identifiers

PMID38882314
PMCPMC11177140

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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.