Evidence map›Paper›PMID 36873600›Full record

ArticleAnimal nutrition (Zhongguo xu mu shou yi xue hui)2023

Low rumen degradable starch promotes the growth performance of goats by increasing protein synthesis in skeletal muscle via the AMPK-mTOR pathway.

Ziqi Liang, Chunjia Jin, Hanxun Bai, Gaofeng Liang, Xiaodong Su, Dangdang Wang, Junhu Yao

Open access · goldAbstract read
In one paragraph

Article in Animal nutrition (Zhongguo xu mu shou yi xue hui), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.3field-weighted citation impact, top 20% 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

9 citing papers in PubMed, 15 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Impact of KalanchoeBiology · 2025
    Article
  5. Article
  6. Article
  7. Article
  8. Article
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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

7 authors at 1 institution in 1 country.

Ziqi LiangCollege of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China.
Chunjia JinCollege of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China.
Hanxun BaiCollege of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China.
Gaofeng LiangCollege of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China.
Xiaodong SuCollege of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China.
Dangdang WangCollege of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China.
Junhu YaoCollege of Animal Science and Technology, Northwest A&F University, Yangling 712100, Shaanxi, China.
Northwest A&F University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since starch digestion in the small intestine provides more energy than digestion in the rumen of ruminants, reducing dietary rumen degradable starch (RDS) content is beneficial for improving energy utilization of starch in ruminants. The present study tested whether the reduction of rumen degradable starch by restricting dietary corn processing for growing goats could improve growth performance, and further investigated the possible underlying mechanism. In this study, twenty-four 12-wk-old goats were selected and randomly allocated to receive either a high RDS diet (HRDS, crushed corn-based concentrate, the mean of particle sizes of corn grain = 1.64 mm,

Indexed as

Amino acidAMPK-mTOR pathwayGlucoseProtein synthesisRumen degradable starch

Identifiers

PMID36873600
PMCPMC9981809
OpenAlexW4309634739

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.