Evidence map›Paper›PMID 37024992›Full record

ArticleJournal of animal science and biotechnology2023

Profiling of N6-methyladenosine methylation in porcine longissimus dorsi muscle and unravelling the hub gene ADIPOQ promotes adipogenesis in an m

Huanfa Gong, Tao Gong, Youhua Liu, Yizhen Wang, Xinxia Wang

Open access · goldAbstract read
In one paragraph

Article in Journal of animal science and biotechnology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.5field-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

8 citing papers in PubMed, 10 citations in OpenAlex.

  1. The role of mNaunyn-Schmiedeberg's archives of pharmacology · 2026
    Review
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  3. Review
  4. Review
  5. Article
  6. Article
  7. Review
  8. mAging and disease · 2024
    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

5 authors at 2 institutions in 1 country.

Huanfa Gong *Key Laboratory of Molecular Animal Nutrition, Ministry of Education, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, People's Republic of China.
Tao Gong *Key Laboratory of Molecular Animal Nutrition, Ministry of Education, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, People's Republic of China.
Youhua LiuKey Laboratory of Molecular Animal Nutrition, Ministry of Education, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, People's Republic of China.
Yizhen WangKey Laboratory of Molecular Animal Nutrition, Ministry of Education, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, People's Republic of China.
Xinxia WangKey Laboratory of Molecular Animal Nutrition, Ministry of Education, College of Animal Sciences, Zhejiang University, Hangzhou, 310058, People's Republic of China. xinxiawang@zju.edu.cn.
Zhejiang University · CNMinistry of Agriculture and Rural Affairs · CN

Funding

Innovative Research Group Project of the National Natural Science Foundation of China No. U21A20249Postdoctoral Research Foundation of China 2022M712794
6 · The paper itself

Abstract

backgroundIntramuscular fat (IMF) content is a critical indicator of pork quality, and abnormal IMF is also relevant to human disease as well as aging. Although N6-methyladenosine (m

resultsIn this work, we collected 20 longissimus dorsi muscle samples with high (average 3.95%) or low IMF content (average 1.22%) from a unique heterogenous swine population for m

conclusionsOur study provided a comprehensive profiling of m

Indexed as

ADIPOQIntramuscular fatN6-methyladenosinePigYTHDF1

Identifiers

PMID37024992
PMCPMC10077699
OpenAlexW4362668183

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.