Broad-spectrum antiviral activity of chebulagic acid and punicalagin against viruses that use glycosaminoglycans for entry
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: We previously identified two hydrolyzable tannins, chebulagic acid (CHLA) and punicalagin (PUG) that blocked herpes simplex virus type 1 (HSV-1) entry and spread. These compounds inhibited viral glycoprotein interactions with cell surface glycosaminoglycans (GAGs). Based on this property, we evaluated their antiviral efficacy against several different viruses known to employ GAGs for host cell entry. RESULTS: Extensive analysis of the tannins' mechanism of action was performed on a panel of viruses during the attachment and entry steps of infection. Virus-specific binding assays and the analysis of viral spread during treatment with these compounds were also conducted. CHLA and PUG were effective in abrogating infection by human cytomegalovirus (HCMV), hepatitis C virus (HCV), dengue virus (DENV), measles virus (MV), and respiratory syncytial virus (RSV), at μM concentrations and in dose-dependent manners without significant cytotoxicity. Moreover, the natural compounds inhibited viral attachment, penetration, and spread, to different degrees for each virus. Specifically, the tannins blocked all these steps of infection for HCMV, HCV, and MV, but had little effect on the post-fusion spread of DENV and RSV, which could suggest intriguing differences in the roles of GAG-interactions for these viruses. CONCLUSIONS: CHLA and PUG may be of value as broad-spectrum antivirals for limiting emerging/recurring viruses known to engage host cell GAGs for entry. Further studies testing the efficacy of these tannins in vivo against certain viruses are justified.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it