Evidence map›Paper›PMID 37571349›Full record

ReviewNutrients2023

Resveratrol, a Multitasking Molecule That Improves Skeletal Muscle Health.

Luana Toniolo, Monica Concato, Emiliana Giacomello

Abstract readReview
In one paragraph

Review in Nutrients, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 1 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

21 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

3 authors.

Luana TonioloLaboratory of Muscle Biophysics, Department of Biomedical Sciences, University of Padova, 35131 Padova, Italy.ORCID 0000-0001-7160-5638
Monica ConcatoDepartment of Medicine, Surgery and Health Sciences, University of Trieste, 34149 Trieste, Italy.ORCID 0000-0003-1026-3106
Emiliana GiacomelloDepartment of Medicine, Surgery and Health Sciences, University of Trieste, 34149 Trieste, Italy.ORCID 0000-0003-3329-6269

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Resveratrol is a natural polyphenol utilized in Chinese traditional medicine and thought to be one of the determinants of the "French Paradox". More recently, some groups evidenced its properties as a calorie-restriction mimetic, suggesting that its action passes through the modulation of skeletal muscle metabolism. Accordingly, the number of studies reporting the beneficial effects of resveratrol on skeletal muscle form and function, in both experimental models and humans, is steadily increasing. Although studies on animal models confer to resveratrol a good potential to ameliorate skeletal muscle structure, function and performance, clinical trials still do not provide clear-cut information. Here, we first summarize the effects of resveratrol on the distinct components of the skeletal muscle, such as myofibers, the neuromuscular junction, tendons, connective sheaths and the capillary bed. Second, we review clinical trials focused on the analysis of skeletal muscle parameters. We suggest that the heterogeneity in the response to resveratrol in humans could depend on sample characteristics, treatment modalities and parameters analyzed; as well, this heterogeneity could possibly reside in the complexity of skeletal muscle physiology. A systematic programming of treatment protocols and analyses could be helpful to obtain consistent results in clinical trials involving resveratrol administration.

Indexed as

Muscle, SkeletalStilbenesAnimalsCaloric RestrictionHumansPolyphenolsResveratrolPolyphenolsResveratrolStilbenesclinical trialsresveratrolskeletal muscle

Identifiers

PMID37571349
PMCPMC10421121

What OpenQuestion holds

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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.