Evidence map›Paper›PMID 42267670›Full record

ReviewClinical science (London, England : 1979)2026

Muscle fibre denervation in ageing.

Casper Soendenbroe

Abstract readReview
In one paragraph

Review in Clinical science (London, England : 1979), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

1 author.

Casper SoendenbroeThe August Krogh Section for Human Physiology, Department of Nutrition, Exercise and Sports, University of Copenhagen, Copenhagen, Denmark.ORCID 0000-0002-6579-5700

Funding

Lundbeck Foundation (Lundbeckfonden) R402-2022-1387
6 · The paper itself

Abstract

Muscle fibre denervation describes the loss of effective neural input from a motor neuron to one or more muscle fibres. In ageing, denervation is increasingly recognised as an important contributor to progressive declines in muscle strength and functional capacity, yet it remains heterogeneous and difficult to define in humans. This ambiguity reflects both biological complexity and current methodological limitations. The purpose of the present review is to synthesise current human evidence for muscle fibre denervation in ageing, clarify key conceptual distinctions, and evaluate methodological approaches used to assess denervation in humans. Muscle fibre denervation can occur through structural disconnection of the motor neuron from the fibre or through functional impairment of neuromuscular transmission. Evidence for denervation in ageing is derived from histological, molecular, electrophysiological, and circulating biomarker approaches, each capturing distinct and only partially overlapping aspects of neuromuscular integrity. Importantly, no single measure provides a comprehensive assessment of denervation. Experimental models of disuse in humans reveal a functional denervation phenotype, characterised by molecular and electrophysiological changes that partially resemble those observed with ageing. Physical activity appears to mitigate against aspects of muscle fibre denervation; however, the mechanisms underlying these effects remain incompletely understood. Collectively, the available evidence indicates that denervation in ageing is a multifaceted and dynamic process that requires multimodal, longitudinal approaches to define, detect, and ultimately target denervation-related mechanisms to preserve neuromuscular function across the human lifespan.

Indexed as

AgingMuscle DenervationMuscle Fibers, SkeletalAnimalsHumansMotor NeuronsMuscle, Skeletalagingdenervationmotor unitneuromuscular junctionSarcopeniaskeletal muscle

Identifiers

PMID42267670
PMCPMC13266841

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Registered trials

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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.