The DOI matches its Crossref record; 8 of the 8 references it cites were found in a registry or an index.
Rodent Models for Metabolic Syndrome Research
Open accessAbstract
Rodents are widely used to mimic human diseases to improve understanding of the causes and progression of disease symptoms and to test potential therapeutic interventions. Chronic diseases such as obesity, diabetes and hypertension, together known as the metabolic syndrome, are causing increasing morbidity and mortality. To control these diseases, research in rodent models that closely mimic the changes in humans is essential. This review will examine the adequacy of the many rodent models of metabolic syndrome to mimic the causes and progression of the disease in humans. The primary criterion will be whether a rodent model initiates all of the signs, especially obesity, diabetes, hypertension and dysfunction of the heart, blood vessels, liver and kidney, primarily by diet since these are the diet‐induced signs in humans with metabolic syndrome. We conclude that the model that comes closest to fulfilling this criterion is the high carbohydrate, high fat‐fed male rodent.
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
Positional cloning of the mouse obese gene and its human homologue
Zhang, Y., Proenca, R., Maffei, M., Barone, M., Leopold, L., & Friedman, J. M. (1994) · Nature · doi:10.1038/372425a0 · Cited by 13,419
Cardiovascular Morbidity and Mortality Associated With the Metabolic Syndrome
Isomaa, B., Almgren, P., Tuomi, T., Forsén, B., Lahti, K., Nissén, M., Taskinen, M.-R., & Groop, L. (2001) · Diabetes Care · doi:10.2337/diacare.24.4.683 · Cited by 4,760
Huang, W., Metlakunta, A., Dedousis, N., Zhang, P., Sipula, I., Dube, J. J., Scott, D. K., & O'Doherty, R. M. (2010) · Diabetes · doi:10.2337/db09-0016 · Cited by 520
Nakagawa, T., Tuttle, K. R., Short, R. A., & Johnson, R. J. (2005) · Nature Clinical Practice Nephrology · doi:10.1038/ncpneph0019 · Cited by 382
“Control” laboratory rodents are metabolically morbid: Why it matters
Martin, B., Ji, S., Maudsley, S., & Mattson, M. P. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0912955107 · Cited by 354
Sahai, A., Malladi, P., Pan, X., Paul, R., Melin-Aldana, H., Green, R. M., & Whitington, P. F. (2004) · American Journal of Physiology-Gastrointestinal and Liver Physiology · doi:10.1152/ajpgi.00199.2004 · Cited by 290
Wada, T., Kenmochi, H., Miyashita, Y., Sasaki, M., Ojima, M., Sasahara, M., Koya, D., Tsuneki, H., & Sasaoka, T. (2010) · Endocrinology · doi:10.1210/en.2009-0869 · Cited by 189
Sutherland, L. N., Capozzi, L. C., Turchinsky, N. J., Bell, R. C., & Wright, D. C. (2008) · American Journal of Physiology-Endocrinology and Metabolism · doi:10.1152/ajpendo.90408.2008 · Cited by 147
Cited by
High-Fat Diet Induced Anxiety and Anhedonia: Impact on Brain Homeostasis and Inflammation
Dutheil, S., Ota, K. T., Wohleb, E. S., Rasmussen, K., & Duman, R. S. (2016) · Neuropsychopharmacology · doi:10.1038/npp.2015.357 · Cited by 355
Lindholm, C. R., Ertel, R. L., Bauwens, J. D., Schmuck, E. G., Mulligan, J. D., & Saupe, K. W. (2013) · Journal of Physiology and Biochemistry · doi:10.1007/s13105-012-0199-2 · Cited by 136
Hypogonadism and metabolic syndrome.
(2011) · PubMed · doi:10.3275/7806 · Cited by 125
Cordero, P., Milagro, F. I., Campion, J., & Martinez, J. A. (2014) · Journal of Developmental Origins of Health and Disease · doi:10.1017/s204017441400035x · Cited by 45
Buniam, J., Chukijrungroat, N., Rattanavichit, Y., Surapongchai, J., Weerachayaphorn, J., Bupha-Intr, T., & Saengsirisuwan, V. (2020) · BMC Complementary Medicine and Therapies · doi:10.1186/s12906-020-02936-1 · Cited by 35
Metadata
- Authors
- Panchal, S. K., & Brown, L.
- Venue
- BioMed Research International
- Publisher
- Wiley
- Published
- 2010-12-30
- Volume
- 2011
- Issue
- 1
- Pages
- 351982-351982
- ISSN
- 1110-7243 (ISSN-L)
- 2314-6133
- 2314-6141
- OpenAlex
- W2060294481
- Cited by
- 408
- References
- 8
- FWCI
- 14.31
- 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: Rodent Models for Metabolic Syndrome Research. https://app.cochat.ai/papers/10.1155/2011/351982
- The paper
- Panchal, S. K., & Brown, L. (2011). Rodent Models for Metabolic Syndrome Research. BioMed Research International. https://doi.org/10.1155/2011/351982
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.
