Evidence map›Paper›PMID 39858803›Full record

ArticleMicroorganisms2024

Characteristics and Differences in the Antler Velvet Microbiota During Regeneration.

Yongxiang Li, Yuhang Zhu, Bo Yang, Shaochen Yu, Songze Li, André-Denis G Wright, Rui Du, Huazhe Si, Zhipeng Li

Abstract read
In one paragraph

Article in Microorganisms, 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. Trial
  2. Article
  3. Article
  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

9 authors.

Yongxiang LiJoint International Research Laboratory of Modern Agricultural Technology, Ministry of Education, Jilin Agricultural University, Changchun 130118, China.
Yuhang ZhuCollege of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China.
Bo YangCollege of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China.
Shaochen YuCollege of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China.
Songze LiCollege of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China.
André-Denis G WrightSchool of Biological Sciences, University of Oklahoma, Norman, OK 73019, USA.ORCID 0000-0003-0315-7786
Rui DuJoint International Research Laboratory of Modern Agricultural Technology, Ministry of Education, Jilin Agricultural University, Changchun 130118, China.
Huazhe SiCollege of Animal Science and Technology, Jilin Agricultural University, Changchun 130118, China.
Zhipeng LiJoint International Research Laboratory of Modern Agricultural Technology, Ministry of Education, Jilin Agricultural University, Changchun 130118, China.ORCID 0000-0001-8474-045X

Funding

Natural Science Foundation of Jilin Province 20240101012JJThe Innovation and Entrepreneurship Talent Program from Jilin Province 2023QN02
6 · The paper itself

Abstract

The skin surface has a complex and dynamic ecosystem inhabited by a diverse microbiota. The wound formed by antler velvet shedding can naturally achieve regenerative restoration, but the changes in microbial composition that occur during antler velvet regeneration are largely unknown. In this study, we analyzed the antler velvet microbiota of sika deer at 15 days (Half) and 30 days (Full) post-pedicle casting using 16S rRNA gene sequencing. A total of 2659 OTUs were identified, which were assigned to 26 phyla, 304 families, and 684 genera. The core microbiota of the two groups were mainly composed of

Indexed as

antler velvetCorynebacteriummicrobiotaStaphylococcuswound healing

Identifiers

PMID39858803
PMCPMC11768019

What OpenQuestion holds

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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.