Evidence map›Paper›PMID 37701714›Full record

ArticleData in brief2023

Meta-analysis data of skeletal muscle slow fiber content across mammalian species.

Samantha R Queeno, Kirstin N Sterner, Matthew C O'Neill

Open access · goldAbstract read
In one paragraph

Article in Data in brief, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 20% of its field
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

5 citing papers in PubMed, 8 citations in OpenAlex.

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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 at 2 institutions in 1 country.

Samantha R QueenoDepartment of Anthropology, University of Oregon, 1218 University of Oregon, Eugene, OR 97403 USA.
Kirstin N SternerDepartment of Anthropology, University of Oregon, 1218 University of Oregon, Eugene, OR 97403 USA.
Matthew C O'NeillDepartment of Anatomy, Midwestern University, Glendale, AZ 85309 USA.
University of Oregon · USMidwestern University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Herein, the dataset generated for Queeno et al. [1] is presented and described. Mammalian skeletal muscle slow (MyHC-I) fiber composition data was collated from 269 eligible studies identified via a systematic literature search and meta-analysis, following a structure similar to PRISMA [2]. Academic search systems were queried with terms relating to mammalian skeletal muscle fiber content and reference lists of selected articles were thoroughly investigated for additional studies. Eligible studies were those that provided skeletal muscle fiber composition data from mammalian species that were not subjected to experimental manipulations. Taxonomic information, sex, age, number of individuals sampled, average body mass (kg), average slow fiber content (%) of each skeletal muscle under investigation and fiber-typing methodology were collated from eligible studies when available. Muscle fiber composition data was collected from more than 200 skeletal muscles across 174 mammalian species, which will be of value to those interested in muscle physiology, interspecific muscle comparisons, and connections between muscle physiology, taxonomy, body mass, ecomorphology and locomotor strategy (among others).

Indexed as

Fiber typingInterspecific muscle physiology comparisonMuscle fiber compositionMyHC IMyosin heavy chain ISlow-twitch

Identifiers

PMID37701714
PMCPMC10493253
OpenAlexW4386192359

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.