The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Grapes (Vitis vinifera) as a Potential Candidate for the Therapy of the Metabolic Syndrome
Abstract
Metabolic syndrome is associated with several disorders, including hypertension, diabetes, hyperlipidemia as well as cardiovascular diseases and stroke. Plant‐derived polyphenols, compounds found in numerous plant species, play an important role as potential treatments for components of metabolic syndrome. Studies have provided evidence for protective effects of various polyphenol‐rich foods against metabolic syndrome. Fruits, vegetables, cereals, nuts, and berries are rich in polyphenolic compounds. Grapes (Vitis vinifera), especially grape seeds, stand out as rich sources of polyphenol potent antioxidants and have been reported helpful for inhibiting the risk factors involved in the metabolic syndrome such as hyperlipidemia, hyperglycemia, and hypertension. There are also many studies about gastroprotective, hepatoprotective, and anti‐obesity effects of grape polyphenolic compounds especially proanthocyanidins in the literature. The present study investigates the protective effects of grape seeds in metabolic syndrome. The results of this study show that grape polyphenols have significant effects on the level of blood glucose, lipid profile, blood pressure, as well as beneficial activities in liver and heart with various mechanisms. In addition, the pharmacokinetics of grape polyphenols is discussed. More detailed mechanistic investigations and phytochemical studies for finding the exact bioactive component(s) and molecular signaling pathways are suggested. Copyright © 2016 John Wiley & Sons, Ltd.
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Lagouge, M., Argmann, C., Gerhart-Hines, Z., Meziane, H., Lerin, C., Daussin, F., Messadeq, N., Milne, J., Lambert, P., Elliott, P., et al. (2006) · Cell · doi:10.1016/j.cell.2006.11.013 · Cited by 4,057
MicroRNAs in metabolism and metabolic disorders
Rottiers, V., & Näär, A. M. (2012) · Nature Reviews Molecular Cell Biology · doi:10.1038/nrm3313 · Cited by 1,156
Interaction between flavonoids and the blood–brain barrier: in vitro studies
Youdim, K. A., Dobbie, M. S., Kuhnle, G., Proteggente, A. R., Abbott, N. J., & Rice‐Evans, C. (2003) · Journal of Neurochemistry · doi:10.1046/j.1471-4159.2003.01652.x · Cited by 578
Resveratrol: Anti-Obesity Mechanisms of Action
Aguirre, L., Fernández-Quintela, A., Arias, N., & Portillo, M. (2014) · Molecules · doi:10.3390/molecules191118632 · Cited by 205
The relationship between obesity and hypoferraemia in adults: A systematic review
Cheng, H. L., Bryant, C., Cook, R., O'Connor, H., Rooney, K., & Steinbeck, K. (2012) · Obesity Reviews · doi:10.1111/j.1467-789x.2011.00938.x · Cited by 159 · cited 2×
“For instance, an association between iron deficiency and obesity has long been recognized (Cheng et al., 2012), as well as between plasma copper levels and inflammatory status-induced metabolic disorders (de Luis et al., 2011).”
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Potential Adverse Effects of Resveratrol: A Literature Review
Shaito, A., Posadino, A. M., Younes, N., Hasan, H., Halabi, S., Alhababi, D., Al-Mohannadi, A., Abdel-Rahman, W. M., Eid, A. H., Nasrallah, G. K., et al. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21062084 · Cited by 716
Proanthocyanidins and hydrolysable tannins: occurrence, dietary intake and pharmacological effects
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Self-citationCurrent evidence on the effect of dietary polyphenols intake on chronic diseases
Costa, C., Tsatsakis, A., Mamoulakis, C., Teodoro, M., Briguglio, G., Caruso, E., Tsoukalas, D., Margina, D., Dardiotis, E., Kouretas, D., et al. (2017) · Food and Chemical Toxicology · doi:10.1016/j.fct.2017.10.023 · Cited by 258
Ashraf, M. V., Khan, S., Misri, S., Gaira, K. S., Rawat, S., Rawat, B., Khan, M. A. H., Shah, A. A., Asgher, M., & Ahmad, S. (2024) · Pharmaceuticals · doi:10.3390/ph17080975 · Cited by 102
Shi, Y., Jia, M., Xu, L., Fang, Z., Wu, W., Zhang, Q., Chung, P., Lin, Y., Wang, S., & Zhang, Y. (2019) · Phytotherapy Research · doi:10.1002/ptr.6318 · Cited by 30
Metadata
- Authors
- Akaberi, M., & Hosseinzadeh, H.
- Venue
- Phytotherapy Research
- Publisher
- Wiley
- Published
- 2016-01-22
- Volume
- 30
- Issue
- 4
- Pages
- 540-556
- ISSN
- 0951-418X (ISSN-L)
- 1099-1573
- OpenAlex
- W2309170544
- Cited by
- 164
- References
- 5
- FWCI
- 11.08
- Type
- journal article
- Language
- en
- Open access
- closed
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