The DOI matches its Crossref record.
Anti‐glycative and anti‐inflammatory effects of caffeic acid and ellagic acid in kidney of diabetic mice
Abstract
Protective effects of caffeic acid (CA) and ellagic acid (EA) in kidney of diabetic mice were examined. CA or EA at 2.5 and 5% was mixed in diet and supplied to diabetic mice for 12 wk. Results showed that the intake of CA or EA increased renal content of these compounds, alleviated body weight loss, decreased urine output, increased plasma insulin and decreased blood glucose levels at weeks 6 and 12 (p<0.05). The intake of these compounds dose dependently reduced plasma blood urea nitrogen and elevated creatinine clearance (p<0.05). CA or EA at 5% significantly decreased the levels of plasma HbA1c, urinary glycated albumin, renal carboxymethyllysine, pentosidine, sorbitol and fructose (p<0.05), and significantly diminished renal activity of aldose reductase and sorbitol dehydrogenase, as well as suppressed renal aldose reductase mRNA expression (p<0.05). CA or EA dose dependently lowered renal levels of IL‐6, IL‐1β, tumor necrosis factor (TNF)‐α and monocyte chemoattractant protein 1 (MCP‐1) (p<0.05). Furthermore, CA or EA dose dependently down‐regulated tumor necrosis factor‐α and monocyte chemoattractant protein‐1 mRNA expression in kidney (p<0.05). Based on the observed anti‐glycative and anti‐inflammatory effects, the supplement of CA or EA might be helpful for the prevention or attenuation of diabetic kidney diseases.
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
Cited by
Bioactivities of Phenolics by Focusing on Suppression of Chronic Diseases: A Review
Shahidi, F., & Yeo, J. (2018) · International Journal of Molecular Sciences · doi:10.3390/ijms19061573 · Cited by 474
Alam, M. A., Subhan, N., Hossain, H., Hossain, M., Reza, H. M., Rahman, M. M., & Ullah, M. O. (2016) · Nutrition & Metabolism · doi:10.1186/s12986-016-0080-3 · Cited by 359
Polyphenols with antiglycation activity and mechanisms of action: A review of recent findings
Yeh, W.-J., Hsia, S.-M., Lee, W.-H., & Wu, C.-H. (2017) · Journal of Food and Drug Analysis · doi:10.1016/j.jfda.2016.10.017 · Cited by 353
Dietary polyphenols as antidiabetic agents: Advances and opportunities
Sun, C., Zhao, C., Guven, E. C., Paoli, P., Simal‐Gandara, J., Ramkumar, K. M., Wang, S., Buleu, F., Pah, A., Turi, V., et al. (2020) · Food Frontiers · doi:10.1002/fft2.15 · Cited by 305
Pharmacological effects and mechanisms of tannic acid
Jing, W., Xiaolan, C., Yu, C., Feng, Q., & Haifeng, Y. (2022) · Biomedicine & Pharmacotherapy · doi:10.1016/j.biopha.2022.113561 · Cited by 299
Metadata
- Authors
- Chao, C., Mong, M., Chan, K., & Yin, M.
- Venue
- Molecular Nutrition & Food Research
- Publisher
- Wiley
- Published
- 2010-03
- Volume
- 54
- Issue
- 3
- Pages
- 388-395
- ISSN
- 1613-4125 (ISSN-L)
- 1613-4133
- OpenAlex
- W2162368537
- Cited by
- 226
- References
- 0
- FWCI
- 3.66
- Type
- journal article
- Language
- en
- Open access
- closed
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: Anti‐glycative and anti‐inflammatory effects of caffeic acid and ellagic acid in kidney of diabetic mice. https://app.cochat.ai/papers/10.1002/mnfr.200900087
- The paper
- Chao, C., Mong, M., Chan, K., & Yin, M. (2010). Anti‐glycative and anti‐inflammatory effects of caffeic acid and ellagic acid in kidney of diabetic mice. Molecular Nutrition & Food Research. https://doi.org/10.1002/mnfr.200900087
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.