The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Skeletal muscle fiber type: using insights from muscle developmental biology to dissect targets for susceptibility and resistance to muscle disease
Open accessAbstract
Skeletal muscle fibers are classified into fiber types, in particular, slow twitch versus fast twitch. Muscle fiber types are generally defined by the particular myosin heavy chain isoforms that they express, but many other components contribute to a fiber's physiological characteristics. Skeletal muscle fiber type can have a profound impact on muscle diseases, including certain muscular dystrophies and sarcopenia, the aging‐induced loss of muscle mass and strength. These findings suggest that some muscle diseases may be treated by shifting fiber type characteristics either from slow to fast, or fast to slow phenotypes, depending on the disease. Recent studies have begun to address which components of muscle fiber types mediate their susceptibility or resistance to muscle disease. However, for many diseases it remains largely unclear why certain fiber types are affected. A substantial body of work has revealed molecular pathways that regulate muscle fiber type plasticity and early developmental muscle fiber identity. For instance, recent studies have revealed many factors that regulate muscle fiber type through modulating the activity of the muscle regulatory transcription factor MYOD1. Future studies of muscle fiber type development in animal models will continue to enhance our understanding of factors and pathways that may provide therapeutic targets to treat muscle diseases. WIREs Dev Biol 2016, 5:518–534. doi: 10.1002/wdev.230 This article is categorized under: Gene Expression and Transcriptional Hierarchies > Regulatory Mechanisms Vertebrate Organogenesis > Musculoskeletal and Vascular Birth Defects > Organ Anomalies
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Mootha, V. K., Lindgren, C. M., Eriksson, K.-F., Subramanian, A., Sihag, S., Lehar, J., Puigserver, P., Carlsson, E., Ridderstråle, M., Laurila, E., et al. (2003) · Nature Genetics · doi:10.1038/ng1180 · Cited by 10,197
Fiber Types in Mammalian Skeletal Muscles
Schiaffino, S., & Reggiani, C. (2011) · Physiological Reviews · doi:10.1152/physrev.00031.2010 · Cited by 3,022
Sandri, M., Sandri, C., Gilbert, A., Skurk, C., Calabria, E., Picard, A., Walsh, K., Schiaffino, S., Lecker, S. H., & Goldberg, A. L. (2004) · Cell · doi:10.1016/s0092-8674(04)00400-3 · Cited by 3,012
Bodine, S. C., Stitt, T. N., Gonzalez, M., Kline, W. O., Stover, G. L., Bauerlein, R., Zlotchenko, E., Scrimgeour, A., Lawrence, J. C., Glass, D. J., et al. (2001) · Nature Cell Biology · doi:10.1038/ncb1101-1014 · Cited by 2,752
Transcriptional co-activator PGC-1α drives the formation of slow-twitch muscle fibres
Lin, J., Wu, H., Tarr, P. T., Zhang, C.-Y., Wu, Z., Boss, O., Michael, L. F., Puigserver, P., Isotani, E., Olson, E. N., et al. (2002) · Nature · doi:10.1038/nature00904 · Cited by 2,546
AMP-activated protein kinase (AMPK) action in skeletal muscle via direct phosphorylation of PGC-1α
Jäger, S., Handschin, C., St.-Pierre, J., & Spiegelman, B. M. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0705070104 · Cited by 2,491
Data on the distribution of fibre types in thirty-six human muscles
Johnson, M. A., Polgar, J., Weightman, D., & Appleton, D. (1973) · Journal of the Neurological Sciences · doi:10.1016/0022-510x(73)90023-3 · Cited by 2,200
Rommel, C., Bodine, S. C., Clarke, B. A., Rossman, R., Nunez, L., Stitt, T. N., Yancopoulos, G. D., & Glass, D. J. (2001) · Nature Cell Biology · doi:10.1038/ncb1101-1009 · Cited by 1,583
Human aging, muscle mass, and fiber type composition.
Evans, W. J., & Lexell, J. (1995) · The Journals of Gerontology Series A: Biological Sciences and Medical Sciences · doi:10.1093/gerona/50a.special_issue.11 · Cited by 1,308
Sandri, M., Lin, J., Handschin, C., Yang, W., Arany, Z. P., Lecker, S. H., Goldberg, A. L., & Spiegelman, B. M. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0607795103 · Cited by 974
Cited by
Role of Age-Related Mitochondrial Dysfunction in Sarcopenia
Ferri, E., Marzetti, E., Calvani, R., Picca, A., Cesari, M., & Arosio, B. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21155236 · Cited by 224
Muscle metabolism and atrophy: let’s talk about sex
Rosa-Caldwell, M. E., & Greene, N. P. (2019) · Biology of Sex Differences · doi:10.1186/s13293-019-0257-3 · Cited by 202
BDNF is a mediator of glycolytic fiber-type specification in mouse skeletal muscle
Delezie, J., Weihrauch, M., Maier, G., Tejero, R., Ham, D. J., Gill, J. F., Karrer-Cardel, B., Rüegg, M. A., Tabares, L., & Handschin, C. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1900544116 · Cited by 141
Transcriptomic analyses reveal rhythmic and CLOCK-driven pathways in human skeletal muscle
Perrin, L., Loizides-Mangold, U., Chanon, S., Gobet, C., Hulo, N., Isenegger, L., Weger, B. D., Migliavacca, E., Charpagne, A., Betts, J. A., et al. (2018) · eLife · doi:10.7554/elife.34114 · Cited by 139
Protective Effects of Ghrelin on Fasting-Induced Muscle Atrophy in Aging Mice
Wu, C.-S., Wei, Q., Wang, H., Kim, D. M., Balderas, M., Wu, G., Lawler, J., Safe, S., Guo, S., Devaraj, S., et al. (2020) · The Journals of Gerontology: Series A · doi:10.1093/gerona/gly256 · Cited by 81
Metadata
- Authors
- Talbot, J., & Maves, L.
- Venue
- WIREs Developmental Biology
- Publisher
- Wiley
- Published
- 2016-05-19
- Volume
- 5
- Issue
- 4
- Pages
- 518-534
- ISSN
- 1759-7684 (ISSN-L)
- 1759-7692
- OpenAlex
- W2403881977
- Cited by
- 437
- References
- 21
- FWCI
- 1.19
- Type
- journal article
- Language
- en
- Open access
- green
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Skeletal muscle fiber type: using insights from muscle developmental biology to dissect targets for susceptibility and resistance to muscle disease. https://app.cochat.ai/papers/10.1002/wdev.230
- The paper
- Talbot, J., & Maves, L. (2016). Skeletal muscle fiber type: using insights from muscle developmental biology to dissect targets for susceptibility and resistance to muscle disease. WIREs Developmental Biology. https://doi.org/10.1002/wdev.230
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
