The DOI matches its Crossref record; 10 of the 10 references it cites were found in a registry or an index.
Nur77 Regulates Lipolysis in Skeletal Muscle Cells
Open accessAbstract
Skeletal muscle is a major mass peripheral tissue that accounts for approximately 40% of total body weight and 50% of energy expenditure and is a primary site of glucose disposal and fatty acid oxidation. Consequently, muscle has a significant role in insulin sensitivity, obesity, and the blood-lipid profile. Excessive caloric intake is sensed by the brain and induces beta-adrenergic receptor (beta-AR)-mediated adaptive thermogenesis. Beta-AR null mice develop severe obesity on a high fat diet. However, the target gene(s), target tissues(s), and molecular mechanism involved remain obscure. We observed that 30-60 min of beta-AR agonist (isoprenaline) treatment of C2C12 skeletal muscle cells strikingly activated (>100-fold) the expression of the mRNA encoding the nuclear hormone receptor, Nur77. In contrast, the expression of other nuclear receptors that regulate lipid and carbohydrate metabolism was not induced. Stable transfection of Nur77-specific small interfering RNAs (siNur77) into skeletal muscle cells repressed endogenous Nur77 mRNA expression. Moreover, we observed attenuation of gene and protein expression associated with the regulation of energy expenditure and lipid homeostasis, for example AMP-activated protein kinase gamma3, UCP3, CD36, adiponectin receptor 2, GLUT4, and caveolin-3. Attenuation of Nur77 expression resulted in decreased lipolysis. Finally, in concordance with the cell culture model, injection and electrotransfer of siNur77 into mouse tibialis cranialis muscle resulted in the repression of UCP3 mRNA expression. This study demonstrates regulatory cross-talk between the nuclear hormone receptor and beta-AR signaling pathways. Moreover, it suggests Nur77 modulates the expression of genes that are key regulators of skeletal muscle lipid and energy homeostasis. In conclusion, we speculate that Nur77 agonists would stimulate lipolysis and increase energy expenditure in skeletal muscle and suggest selective activators of Nur77 may have therapeutic utility in the treatment of obesity.
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
Cloning of adiponectin receptors that mediate antidiabetic metabolic effects
Yamauchi, T., Kamon, J., Ito, Y., Tsuchida, A., Yokomizo, T., Kita, S., Sugiyama, T., Miyagishi, M., Hara, K., Tsunoda, M., et al. (2003) · Nature · doi:10.1038/nature01705 · Cited by 3,176
Leptin stimulates fatty-acid oxidation by activating AMP-activated protein kinase
Minokoshi, Y., Kim, Y.-B., Peroni, O. D., Fryer, L. G. D., Müller, C., Carling, D., & Kahn, B. B. (2002) · Nature · doi:10.1038/415339a · Cited by 2,053
Mice lacking mitochondrial uncoupling protein are cold-sensitive but not obese
Enerbäck, S., Jacobsson, A., Simpson, E. M., Guerra, C., Yamashita, H., Harper, M.-E., & Kozak, L. P. (1997) · Nature · doi:10.1038/387090a0 · Cited by 1,379
Peroxisome-Proliferator-Activated Receptor δ Activates Fat Metabolism to Prevent Obesity
Wang, Y.-X., Lee, C.-H., Tiep, S., Yu, R. T., Ham, J., Kang, H., & Evans, R. M. (2003) · Cell · doi:10.1016/s0092-8674(03)00269-1 · Cited by 1,296
Tanaka, T., Yamamoto, J., Iwasaki, S., Asaba, H., Hamura, H., Ikeda, Y., Watanabe, M., Magoori, K., Ioka, R. X., Tachibana, K., et al. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0306981100 · Cited by 832
Energy metabolism in uncoupling protein 3 gene knockout mice
Vidal-Puig, A. J., Grujic, D., Zhang, C.-Y., Hagen, T., Boss, O., Ido, Y., Szczepanik, A., Wade, J., Mootha, V., Cortright, R., et al. (2000) · Journal of Biological Chemistry · doi:10.1074/jbc.m910179199 · Cited by 677
Peroxisome proliferator‐activated receptor δ controls muscle development and oxydative capability
Luquet, S., Lopez‐Soriano, J., Holst, D., Fredenrich, A., Melki, J., Rassoulzadegan, M., & Grimaldi, P. A. (2003) · The FASEB Journal · doi:10.1096/fj.03-0269fje · Cited by 509
Barnes, B. R., Marklund, S., Steiler, T. L., Walter, M., Hjälm, Amarger, V., Mahlapuu, M., Leng, Y., Johansson, C., Galuska, D., et al. (2004) · Journal of Biological Chemistry · doi:10.1074/jbc.m405533200 · Cited by 317
Minireview: Malonyl CoA, AMP-Activated Protein Kinase, and Adiposity
Ruderman, N. B., Saha, A. K., & Kraegen, E. W. (2003) · Endocrinology · doi:10.1210/en.2003-0849 · Cited by 266
Cloning and characterization of mouse 5′-AMP-activated protein kinase γ3 subunit
Yu, H., Fujii, N., Hirshman, M. F., Pomerleau, J. M., & Goodyear, L. J. (2004) · American Journal of Physiology-Cell Physiology · doi:10.1152/ajpcell.00319.2003 · Cited by 67
Cited by
The NR4A Subgroup: Immediate Early Response Genes with Pleiotropic Physiological Roles
Maxwell, M. A., & Muscat, G. E. O. (2006) · Nuclear Receptor Signaling · doi:10.1621/nrs.04002 · Cited by 448
Self-citationMetabolic signatures of exercise in human plasma
Lewis, G. D., Farrell, L., Wood, M. J., Martinovic, M., Arany, Z., Rowe, G. C., Souza, A., Cheng, S., McCabe, E. L., Yang, E., et al. (2010) · Science Translational Medicine · doi:10.1126/scitranslmed.3001006 · Cited by 432
Role of β-Adrenoceptor Signaling in Skeletal Muscle: Implications for Muscle Wasting and Disease
Lynch, G. S., & Ryall, J. G. (2008) · Physiological Reviews · doi:10.1152/physrev.00028.2007 · Cited by 410
Orphan nuclear receptor NR4A1 regulates transforming growth factor-β signaling and fibrosis
Palumbo-Zerr, K., Zerr, P., Distler, A., Fliehr, J., Mancuso, R., Huang, J., Mielenz, D., Tomcik, M., Fürnrohr, B. G., Scholtysek, C., et al. (2015) · Nature Medicine · doi:10.1038/nm.3777 · Cited by 342
The biological applications of DNA nanomaterials: current challenges and future directions
Ma, W., Zhan, Y., Zhang, Y., Mao, C., Xie, X., & Lin, Y. (2021) · Signal Transduction and Targeted Therapy · doi:10.1038/s41392-021-00727-9 · Cited by 331
Metadata
- Authors
- Maxwell, M. A., Cleasby, M. E., Harding, A., Stark, A., Cooney, G. J., & Muscat, G. E. O.
- Venue
- Journal of Biological Chemistry
- Publisher
- Elsevier BV
- Published
- 2005-04
- Volume
- 280
- Issue
- 13
- Pages
- 12573-12584
- ISSN
- 0021-9258 (ISSN-L)
- OpenAlex
- W2143567463
- Cited by
- 158
- References
- 10
- FWCI
- 3.62
- Type
- journal article
- Language
- en
- Open access
- hybrid
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: Nur77 Regulates Lipolysis in Skeletal Muscle Cells. https://app.cochat.ai/papers/10.1074/jbc.m409580200
- The paper
- Maxwell, M. A., Cleasby, M. E., Harding, A., Stark, A., Cooney, G. J., & Muscat, G. E. O. (2005). Nur77 Regulates Lipolysis in Skeletal Muscle Cells. Journal of Biological Chemistry. https://doi.org/10.1074/jbc.m409580200
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.