Evidence map›Paper›PMID 31662290›Full record

ReviewEBioMedicine2019

Skeletal muscle as potential central link between sarcopenia and immune senescence.

Christopher Nelke, Rainer Dziewas, Jens Minnerup, Sven G Meuth, Tobias Ruck

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in EBioMedicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 260 papers, 9 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
260citing papers in PubMed, 9 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

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

260 citing papers in PubMed, 9 syntheses or guidelines pooled it.

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200 more citing papers are in PubMed but not listed here.

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

5 authors.

Christopher NelkeClinic of Neurology with Institute of Translational Neurology, University of Münster, Münster, Germany.
Rainer DziewasClinic of Neurology with Institute of Translational Neurology, University of Münster, Münster, Germany.
Jens MinnerupClinic of Neurology with Institute of Translational Neurology, University of Münster, Münster, Germany.
Sven G MeuthClinic of Neurology with Institute of Translational Neurology, University of Münster, Münster, Germany.
Tobias RuckClinic of Neurology with Institute of Translational Neurology, University of Münster, Münster, Germany. Electronic address: tobias.ruck@ukmuenster.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As our population grows older, age-related pathologies are becoming more prevalent. Deterioration of skeletal muscle and the immune system manifests as sarcopenia and immune senescence respectively. The disease burden of these pathologies emphasizes the need for a better understanding of the underlying mechanisms. Skeletal muscle has emerged as a potent regulator of immune system function. As such, skeletal muscle might be the central integrator between sarcopenia and immune senescence in an aging biological system. Therapeutic approaches targeting skeletal muscle might be able to restore both muscle and immune system function. In this review, we therefore outline the current - however still fragmentary - knowledge about the potential communication pathways of muscle and immune system, how they are affected by aging of skeletal muscle and discuss possible treatment strategies. The review intends to be hypothesis-generating and should thereby stimulate further research in this important scientific field.

Indexed as

AgingCell CommunicationHumansImmune SystemMuscle, SkeletalRisk FactorsSarcopeniaIL-15IL-6, IL-7Immune senescenceMyokinesSarcopeniaSkeletal muscle

Identifiers

PMID31662290
PMCPMC6945275

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.