Evidence map›Paper›PMID 42500602›Full record

ArticleFrontiers in physiology2026

Task specific effects of fatigue on lower limb muscle synergies during single and double leg drop jumps in female athletes.

Jiawei Zheng, Junfeng Teng, Kunpeng Wang, Xikai Lin

Abstract read
In one paragraph

Article in Frontiers in physiology, 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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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

4 authors.

Jiawei Zheng *School of Sports Medicine, Wuhan Sports University, Wuhan, China.
Junfeng Teng *School of Sports Medicine, Wuhan Sports University, Wuhan, China.
Kunpeng WangSchool of Sports Medicine, Wuhan Sports University, Wuhan, China.
Xikai LinPain management and Tuina Department, Beijing University of Chinese Medicine Shenzhen Hospital (Longgang), Shenzhen, Longgang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Drop jump (DJ) tasks are widely used to assess lower-limb neuromuscular function and injury risk. Fatigue is a key factor elevating injury risk, yet its effects on neuromuscular control during single-leg drop jumps (SLDJ) and double-leg drop jumps (DLDJ), and whether these effects differ by task type, remain poorly understood. Methods: Fifteen female athletes performed SLDJ and DLDJ before and after a standardized fatigue protocol. Surface electromyography signals from nine lower-limb muscles were collected. Muscle synergies were extracted via non-negative matrix factorization, and synergy similarity was assessed using scalar product and Pearson correlation coefficients. Linear mixed-effects models examined differences in muscle contributions and temporal activation features. Results: Three muscle synergy modules were consistently identified across both tasks and fatigue conditions, with high inter-module similarity (scalar product and Pearson r > 0.80). Synergy structure remained stable regardless of task or fatigue, while task type and fatigue selectively modulated specific muscle contributions. Notably, vastus lateralis contribution showed opposing fatigue-related trends between tasks, and lateral gastrocnemius contribution decreased significantly after fatigue in SLDJ only. Conclusions: The central nervous system maintains a stable modular control strategy across DJ tasks and fatigue conditions. Adaptations to fatigue manifest primarily through task-specific modulation of intra-module muscle weights rather than restructuring of synergy organization. SLDJ demonstrated greater neuromuscular sensitivity to fatigue than DLDJ, indicating that single-leg landing tasks may be more susceptible to fatigue-induced alterations in neuromuscular control. These findings inform neuromuscular screening and targeted training strategies for female athletes.

Indexed as

drop jumpelectromyographyfatiguemuscle synergynon-negative matrix factorization

Identifiers

PMID42500602
PMCPMC13395738

What Socratic holds

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LicenceCC BY
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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 Socratic graph.