Evidence map›Paper›PMID 40206950›Full record

ArticleFrontiers in nutrition2025

Ethanol extract of propolis relieves exercise-induced fatigue via modulating the metabolites and gut microbiota in mice.

Shan Huang, Xiaofei Yang, Jingxuan Ma, Chen Li, Yajing Wang, Zhaoxia Wu

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Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed, 1 pooled it
–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

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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, 1 synthesis or guideline pooled it.

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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

6 authors.

Shan HuangCollege of Food Science, Shenyang Agricultural University, Shenyang, Liaoning, China.
Xiaofei YangCollege of Grain Science and Technology, Shenyang Normal University, Shenyang, Liaoning, China.
Jingxuan MaCollege of Food Science, Shenyang Agricultural University, Shenyang, Liaoning, China.
Chen LiCollege of Food and Health, Jinzhou Medical University, Jinzhou, Liaoning, China.
Yajing WangCollege of Food Science, Shenyang Agricultural University, Shenyang, Liaoning, China.
Zhaoxia WuCollege of Food Science, Shenyang Agricultural University, Shenyang, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Propolis, a natural mixture rich in bioactive compounds, has shown the potential to relieve exercise-induced fatigue. However, the underlying mechanism remains unclear. This study aimed to explore the anti-fatigue effects of ethanol extract of propolis (EEP) and its potential mechanisms. Methods: Male C57BL/6 mice aged 6-8 weeks were subjected to swim training with or without EEP supplementation (400 mg/kg.bw) for 3 weeks, followed by a exhaustive swimming test to simulate exercise-induced fatigue. The exhaustion time and fatigue-related biochemical indices were measured to assess the anti-fatigue effects. The anti-fatigue mechanism of EEP was further investigated using untargeted serum metabolomics and 16S rRNA gene sequencing of the gut microbiota. Results: The results showed that supplementation with EEP significantly increased the exhaustive swimming time of the mice by 27.64%, with no significant effects on body weight, food intake, or viscera and muscle index among the 3 groups. Biochemical analysis indicated that EEP effectively alleviated fatigue-related biochemical indices caused by excessive exercise, including liver glycogen (LG), muscle glycogen (MG), blood lactate (BLA), blood urea nitrogen (BUN), lactate dehydrogenase (LDH), interleukin-6 (IL-6), interleukin-1β (IL-1β), tumor necrosis factor-alpha (TNF- Conclusion: Our study showed that EEP significantly increased exercise endurance in mice and exerted anti-fatigue effects by modulating key metabolites and the gut microbiota.

Indexed as

ethanol extract of propolisexercise-induced fatiguegut microbiotametabolomicspropolis

Identifiers

PMID40206950
PMCPMC11980171

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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.