Abstract
Ellagic acid (EA) is a polyphenolic compound with antiviral activity against chikungunya, a rapidly spreading new tropical disease transmitted to humans by mosquitoes and now affecting millions worldwide. The most common symptoms of chikungunya virus infection are fever and joint pain. Other manifestations of infection can include encephalitis and an arthritic joint swelling with pain that may persist for months or years after the initial infection. The disease has recently spread to the U.S.A., with locally-transmitted cases of chikungunya virus reported in Florida. There is no approved vaccine to prevent or medicine to treat chikungunya virus infections. In this study, the Estimated Daily Intake (EDI) of EA from the food supply established using the National Health and Nutrition Examination Survey (NHANES) is used to set a maximum dose of an EA formulation for a high priority clinical trial.
Original language | English |
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Title of host publication | Computational Science – ICCS 2018 - 18th International Conference, Proceedings |
Editors | Valeria V. Krzhizhanovskaya, Michael Harold Lees, Peter M. Sloot, Jack Dongarra, Yong Shi, Yingjie Tian, Haohuan Fu |
Pages | 773-782 |
Number of pages | 10 |
DOIs | |
State | Published - 2018 |
Event | 18th International Conference on Computational Science, ICCS 2018 - Wuxi, China Duration: Jun 11 2018 → Jun 13 2018 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 10861 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 18th International Conference on Computational Science, ICCS 2018 |
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Country/Territory | China |
City | Wuxi |
Period | 6/11/18 → 6/13/18 |
Bibliographical note
Funding Information:The project described was supported in part by the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health, through Grant UL1TR001998. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH. This project was also supported by NSF ACI-1053575 allocation number BIO170011.
Publisher Copyright:
© Springer International Publishing AG, part of Springer Nature 2018.
Keywords
- Drug development
- NHANES
- Tropical disease
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science (all)