Evidence map›Paper›PMID 42193839›Full record

ArticleAnimals : an open access journal from MDPI2026

Transcriptomic and Proteomic Analysis of the Skeletal Muscle Revealed the Effects and Mechanism of Mulberry Leaf Flavonoids on Alleviating Exercise-Induced Muscle Damage in Mongolian Horses.

Aopan Geng, Xuejiao Wang, Lianhao Li, Sarah Cowie, Dongyi Bai, Manglai Dugarjaviin, Xinzhuang Zhang

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Aopan GengInner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, College of Animal Science and Technology, Inner Mongolia Agricultural University, Hohhot 010018, China.
Xuejiao WangRural Revitalization Research Institute, Inner Mongolia Agricultural University, Hohhot 010018, China.
Lianhao LiInner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, College of Animal Science and Technology, Inner Mongolia Agricultural University, Hohhot 010018, China.
Sarah CowieSchool of Psychology, The University of Auckland City Campus, Private Bag 92019, Auckland 1142, New Zealand.
Dongyi BaiInner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, College of Animal Science and Technology, Inner Mongolia Agricultural University, Hohhot 010018, China.
Manglai DugarjaviinInner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, College of Animal Science and Technology, Inner Mongolia Agricultural University, Hohhot 010018, China.
Xinzhuang ZhangInner Mongolia Key Laboratory of Equine Science Research and Technology Innovation, College of Animal Science and Technology, Inner Mongolia Agricultural University, Hohhot 010018, China.

Funding

Inner Mongolia Agricultural University BR230405Inner Mongolia Agricultural University CG202421Inner Mongolia Department of Science and Technology 2023YFDZ0002Inner Mongolia Education Departmen YLXKZX-NND-007National Natural Science Foundation of China 31902188, U23A20224
6 · The paper itself

Abstract

The scientific evidence regarding the use of plant-derived extracts to alleviate exercise-induced muscle damage in horses remains limited. Mulberry leaf flavonoids (MLFs) are the primary bioactive constituents of a traditional medicinal plant and are potent antioxidants. The aim of this study was to investigate the protective effects of MLFs against exercise-induced muscle damage. In this study, twelve Mongolian horses were used in a 3 × 3 Latin square design to investigate the protective effects of MLFs. Our results showed that high-intensity exercise negatively impacted the immune status, metabolic state, myofibrillar structure, and antioxidant capacity of the horses. Conversely, MLFs significantly reduced blood levels of white blood cells (WBC), monocytes (MON), aspartate aminotransferase (AST), creatine kinase (CK), and malondialdehyde (MDA) across various exercise distances and during recovery. Simultaneously, MLFs increased serum glutathione peroxidase (GPx), superoxide dismutase (SOD), and total antioxidant capacity (T-AOC). Mechanistically, transcriptomic analysis revealed that dietary MLFs upregulated genes associated with myofibrillar structural proteins (

Indexed as

exercise-induced muscle damageMongolian horsesmulberry leaf flavonoidsproteomictranscriptomic

Identifiers

PMID42193839
PMCPMC13203402

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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.