Evidence map›Paper›PMID 34692749›Full record

ArticleFrontiers in nutrition2021

Baicalin-Zinc Complex Alleviates Inflammatory Responses and Hormone Profiles by Microbiome in Deoxynivalenol Induced Piglets.

Andong Zha, Ruiqi Tu, Zhijuan Cui, Ming Qi, Simeng Liao, Jing Wang, Bie Tan, Peng Liao

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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

8 authors.

Andong ZhaChinese Academy of Sciences, Institute of Subtropical Agriculture, Changsha, China.
Ruiqi TuCollege of Veterinary Medicine, Northwest A & F University, Yangling, China.
Zhijuan CuiDepartment of Animal Science and Technology, Hunan Agricultural University, Changsha, China.
Ming QiChinese Academy of Sciences, Institute of Subtropical Agriculture, Changsha, China.
Simeng LiaoChinese Academy of Sciences, Institute of Subtropical Agriculture, Changsha, China.
Jing WangDepartment of Animal Science and Technology, Hunan Agricultural University, Changsha, China.
Bie TanDepartment of Animal Science and Technology, Hunan Agricultural University, Changsha, China.
Peng LiaoChinese Academy of Sciences, Institute of Subtropical Agriculture, Changsha, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to investigate the beneficial effect of baicalin-zinc complex (BZN) on intestinal microorganisms in deoxynivalenol (DON)-challenged piglets and the association between intestinal microorganisms and host immunity and hormone secretion. Forty weaned piglets were randomly divided into four treatments with 10 piglets in each treatment: (1) control (Con) group (pigs fed basal diet); (2) DON group (pigs fed 4 mg DON/kg basal diet); (3) BZN group (pigs fed 0.5% BZN basal diet); and (4) DBZN group (pigs fed 4 mg DON/kg and 0.5% BZN basal diet). The experiment lasted for 14 days. The BZN supplementation in DON-contaminated diets changed the intestinal microbiota composition and increased intestinal microbial richness and diversity of piglets. The BZN supplementation in DON-contaminated diets also alleviated the inflammatory responses of piglets and modulated the secretion of hormones related to the growth axis. Moreover, microbiota composition was associated with inflammatory and hormone secretion. In conclusion, BZN alleviated inflammatory response and hormone secretion in piglets, which is associated with the intestinal microbiome.

Indexed as

baicalin-zinc complexdeoxynivalenolhormone secretioninflammatory responsesintestinal microbiomeweaned piglets

Identifiers

PMID34692749
PMCPMC8534294

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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.