The DOI matches its Crossref record; 145 of the 145 references it cites were found in a registry or an index.
Animal Models of Inflammation for Screening of Anti-inflammatory Drugs: Implications for the Discovery and Development of Phytopharmaceuticals
Open accessAbstract
Inflammation is one of the common events in the majority of acute as well as chronic debilitating diseases and represent a chief cause of morbidity in today’s era of modern lifestyle. If unchecked, inflammation leads to development of rheumatoid arthritis, diabetes, cancer, Alzheimer’s disease, and atherosclerosis along with pulmonary, autoimmune and cardiovascular diseases. Inflammation involves a complex network of many mediators, a variety of cells, and execution of multiple pathways. Current therapy for inflammatory diseases is limited to the steroidal and non-steroidal anti-inflammatory agents. The chronic use of these drugs is reported to cause severe adverse effects like gastrointestinal, cardiovascular, and renal abnormalities. There is a massive need to explore new anti-inflammatory agents with selective action and lesser toxicity. Plants and isolated phytoconstituents are promising and interesting sources of new anti-inflammatories. However, drug development from natural sources has been linked with hurdles like the complex nature of extracts, difficulties in isolation of pure phytoconstituents, and the yield of isolated compounds in minute quantities that is insufficient for subsequent lead development. Although various in-vivo and in-vitro models for anti-inflammatory drug development are available, judicious selection of appropriate animal models is a vital step in the early phase of drug development. Systematic evaluation of phytoconstituents can facilitate the identification and development of potential anti-inflammatory leads from natural sources. The present review describes various techniques of anti-inflammatory drug screening with its advantages and limitations, elaboration on biological targets of phytoconstituents in inflammation and biomarkers for the prediction of adverse effects of anti-inflammatory drugs. The systematic approach proposed through present article for anti-inflammatory drug screening can rationalize the identification of novel phytoconstituents at the initial stage of drug screening programs.
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Circulating microRNAs as stable blood-based markers for cancer detection
Mitchell, P. S., Parkin, R. K., Kroh, E. M., Fritz, B. R., Wyman, S. K., Pogosova-Agadjanyan, E. L., Peterson, A., Noteboom, J., O'Briant, K. C., Allen, A., et al. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0804549105 · Cited by 7,969
Epstein, F. H., Steinberg, D., Parthasarathy, S., Carew, T. E., Khoo, J. C., & Witztum, J. L. (1989) · New England Journal of Medicine · doi:10.1056/nejm198904063201407 · Cited by 6,427
Carrageenin-Induced Edema in Hind Paw of the Rat as an Assay for Antiinflammatory Drugs
Winter, C. A., Risley, E. A., & Nuss, G. W. (1962) · Experimental Biology and Medicine · doi:10.3181/00379727-111-27849 · Cited by 5,688
Chronic Inflammation (Inflammaging) and Its Potential Contribution to Age-Associated Diseases
Franceschi, C., & Campisi, J. (2014) · The Journals of Gerontology Series A: Biological Sciences and Medical Sciences · doi:10.1093/gerona/glu057 · Cited by 3,891
The evolving role of natural products in drug discovery
Koehn, F. E., & Carter, G. T. (2005) · Nature Reviews Drug Discovery · doi:10.1038/nrd1657 · Cited by 2,572
Eicosanoid storm in infection and inflammation
Dennis, E. A., & Norris, P. C. (2015) · Nature Reviews Immunology · doi:10.1038/nri3859 · Cited by 1,517
Inflammation and cancer: how hot is the link?
Aggarwal, B. B., Shishodia, S., Sandur, S. K., Pandey, M. K., & Sethi, G. (2006) · Biochemical Pharmacology · doi:10.1016/j.bcp.2006.06.029 · Cited by 1,312
Does the Interdependence between Oxidative Stress and Inflammation Explain the Antioxidant Paradox?
Biswas, S. K. (2016) · Oxidative Medicine and Cellular Longevity · doi:10.1155/2016/5698931 · Cited by 1,166
Prognostic Value of Myeloperoxidase in Patients with Chest Pain
Brennan, M.-L., Penn, M. S., Van Lente, F., Nambi, V., Shishehbor, M. H., Aviles, R. J., Goormastic, M., Pepoy, M. L., McErlean, E. S., Topol, E. J., et al. (2003) · New England Journal of Medicine · doi:10.1056/nejmoa035003 · Cited by 1,070
ROLE OF C5A IN INFLAMMATORY RESPONSES
Guo, R.-F., & Ward, P. A. (2005) · Annual Review of Immunology · doi:10.1146/annurev.immunol.23.021704.115835 · Cited by 1,021
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Ginkgetin: A natural biflavone with versatile pharmacological activities
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Interleukin-10 deficiency exacerbates inflammation-induced tau pathology
Weston, L. L., Jiang, S., Chisholm, D., Jantzie, L. L., & Bhaskar, K. (2021) · Journal of Neuroinflammation · doi:10.1186/s12974-021-02211-1 · Cited by 69
Polydeoxyribonucleotide Regulation of Inflammation
Colangelo, M. T., Galli, C., & Guizzardi, S. (2020) · Advances in Wound Care · doi:10.1089/wound.2019.1031 · Cited by 33
Spampinato, M., Carota, G., Sferrazzo, G., Fuochi, V., Distefano, A., Ronsisvalle, S., Sipala, F., Giuffrida, R., Furneri, P. M., Di Rosa, M., et al. (2022) · Pharmaceutics · doi:10.3390/pharmaceutics14122845 · Cited by 14
“Most of the pathological conditions are based on the chronic inflammation of tissues, which represents one of the most common incipits involved in the onset of debilitating diseases including cancer and cardiovascular and pulmonary diseases [6].”
Background
Metadata
- Authors
- Patil, K. R., Mahajan, U. B., Unger, B. S., Goyal, S. N., Belemkar, S., Surana, S. J., Ojha, S., & Patil, C. R.
- Venue
- International Journal of Molecular Sciences
- Publisher
- MDPI AG
- Published
- 2019-09-05
- Volume
- 20
- Issue
- 18
- Pages
- 4367
- ISSN
- 1422-0067 (ISSN-L)
- OpenAlex
- W2971390047
- Cited by
- 403
- References
- 145
- FWCI
- 22.17
- Type
- journal article
- Language
- en
- Open access
- gold
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- Patil, K. R., Mahajan, U. B., Unger, B. S., Goyal, S. N., Belemkar, S., Surana, S. J., Ojha, S., & Patil, C. R. (2019). Animal Models of Inflammation for Screening of Anti-inflammatory Drugs: Implications for the Discovery and Development of Phytopharmaceuticals. International Journal of Molecular Sciences. https://doi.org/10.3390/ijms20184367
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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