Identification of the phytobioactive Polygonum cuspidatum as an antiviral source for restricting dengue virus entry
Bibliographic record
Abstract
Dengue virus (DENV) is a mosquito-borne pathogen that is becoming a serious global threat, owing to its rising incidence in inter-tropical regions that yield over 50 million annual infections. There are currently no approved antiviral agents for the management of dengue, and recent shortcomings in its immunization called for immediate action to develop effective drugs with prophylactic ability to better manage its infection. In an attempt to discover novel antiviral sources, we identified the medicinal herb Polygonum cuspidatum (PC) as a bioactive botanical material against DENV infectivity. Specifically, the methanolic extract from PC rhizomes (PCME) potently inhibited DENV infection without causing significant cytotoxicity. Further examination on the viral life cycle demonstrated that PCME particularly targeted the initial stages of DENV infection, while pre- and post-infection treatments had no effect. More importantly, the PCME could efficiently inactivate DENV free virus particles and block the viral attachment and entry/fusion events without apparently influencing viral replication, egress, and cell-to-cell spread. The antiviral effect of PCME was also recapitulated in infection analysis using DENV pseudoparticles displaying viral structural proteins that mediate DENV particle entry. Besides, PCME treatment also inhibited direct DENV entry into several cell types relevant to its infection and reduced viral infectivity of other members of the Flaviviridae family, including the hepatitis C virus (HCV) and Zika virus (ZIKV). Due to its potency against DENV entry, we suggest that the phytobioactive extract from PC is an excellent starting point as an antiviral source material for further development of therapeutic strategies in the prophylactic management of DENV infection.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".