Evidence map›Paper›PMID 40727271›Full record

SynthesisFrontiers in veterinary science2025

Multi-omics insights into Chinese herbal medicine additives for mutton flavor enhancement: epigenetic and microbial mechanisms.

Kai Quan, Huibin Shi, Haoyuan Han, Kun Liu, Qiufang Cui, Huihua Wang, Meilin Jin, Wei Sun, Caihong Wei, Yibao Jiang and 1 more

Abstract readSystematic Review
PubMed Full text at PMC Publisher
In one paragraph

Synthesis in Frontiers in veterinary science, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

11 authors.

Kai QuanCollege of Animal Science and Technology, Henan University of Animal Husbandry and Economy, Zhengzhou, China.
Huibin ShiCollege of Animal Science and Technology, Henan University of Animal Husbandry and Economy, Zhengzhou, China.
Haoyuan HanCollege of Animal Science and Technology, Henan University of Animal Husbandry and Economy, Zhengzhou, China.
Kun LiuCollege of Animal Science and Technology, Henan University of Animal Husbandry and Economy, Zhengzhou, China.
Qiufang CuiCollege of Animal Science and Technology, Henan University of Animal Husbandry and Economy, Zhengzhou, China.
Huihua WangInstitute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Meilin JinInstitute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Wei SunCollege of Animal Science and Technology, Yangzhou University, Yangzhou, China.
Caihong WeiInstitute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
Yibao JiangCollege of Animal Science and Technology, Henan Agricultural University, Zhengzhou, China.
Jun LiCollege of Animal Science and Technology, Henan University of Animal Husbandry and Economy, Zhengzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Chinese herbal medicine additives (CHMAs) have become increasingly popular as sustainable alternatives to synthetic compounds for improving the quality of mutton. However, the precise molecular mechanisms underlying their effects are not well understood. By integrating transcriptomic profiling, metabolomic pathways, and microbial community dynamics, this review deciphers the synergistic mechanisms of CHMAs in enhancing mutton flavor, supported by empirical evidence from 2014 to 2024. Our key findings highlight three synergistic pathways: (1) Epigenetic suppression of

Indexed as

Chinese herbal medicine additiveslipid metabolismmulti-omicsmutton flavorrumen microbiota

Identifiers

PMID40727271
PMCPMC12302508

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.