Evidence map›Paper›PMID 39980289›Full record

ArticleCurrent pharmaceutical biotechnology2026

Study on the Anti-fatigue Effects of Polysaccharides from Erjing Formula.

Zicheng Lin, Mingshuo Yang, Jinsui Liu, Can Yang, Lixuan Liang, Jiaqi Pan, Quan Yang, Liming Pan

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Article in Current pharmaceutical biotechnology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Zicheng LinSchool of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China.
Mingshuo YangSchool of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China.
Jinsui LiuSchool of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China.
Can YangSchool of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China.
Lixuan LiangSchool of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China.
Jiaqi PanSchool of Pharmacy, Guangdong Pharmaceutical University, Guangzhou, 510006, China.
Quan YangSchool of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China.
Liming PanSchool of Traditional Chinese Medicine, Guangdong Pharmaceutical University, Guangzhou, 510006, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe traditional Chinese recipe "Erjing Formula", composed of HuangJing and GouQi, is recognized for its tonifying and revitalizing properties, but the active components responsible for these effects are poorly explored. This study investigated the antifatigue effects of Erjing Formula polysaccharides (EJFP).

objectiveThe present study aimed to investigate the anti-fatigue effects of EJFP through weight-loaded swimming tests in mice.

methodsSPF-grade healthy male mice species KM mice were gavaged with EJFP and then subjected to a weight-loaded swimming test. Later, the levels of various biochemical indicators, including blood lactate (BLA), blood urea nitrogen (BUN), superoxide dismutase (SOD), malondialdehyde (MDA), muscle glycogen (MG), and hepatic glycogen (HG), were measured. The muscle tissue slices were analyzed using hematoxylin and eosin H&E) staining. Additionally, the expression levels of Kelch-like ECH-associated Protein 1 (Keap-1) and nuclear factor erythroid 2-related factor 2 (Nrf2) in the muscle tissue of each group were detected using Western Blotting.

resultsEJFP (Erjing Formula Polysaccharides) significantly increased swimming time (p ≤ 0.01), reduced oxidative stress markers and detrimental metabolites (BLA, BUN, and MDA), and elevated SOD, MG, and HG levels. Histologically, it improved muscle integrity. Nrf2 expression increased, indicating a relationship between antioxidant effects and antifatigue activity.

conclusionEJFP demonstrated anti-fatigue effects, mainly at moderate doses, by modulating the Nrf2/Keap1 pathway and improving glycogen and antioxidant levels. This is the first study to document the anti-fatigue effects of Erjing Formula polysaccharides, establishing a theoretical basis for practical applications in the development of anti-fatigue products.

Indexed as

Drugs, Chinese HerbalFatiguePolysaccharidesAnimalsGlycogenKelch-Like ECH-Associated Protein 1LiverMaleMiceMuscle, SkeletalNF-E2-Related Factor 2Superoxide DismutaseSwimmingDrugs, Chinese HerbalGlycogenKeap1 protein, mouseKelch-Like ECH-Associated Protein 1Nfe2l2 protein, mouseNF-E2-Related Factor 2PolysaccharidesSuperoxide DismutaseantioxidantKeap1- Nrf2 pathwayLycium barbarum LOxidative stress modulationPolygonatum kingianum Coll.et Hemslpolysaccharidesresist fatigue

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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.