Anti-Influenza Virus Activities of Commercial Oregano oils and their Carriers
Bibliographic record
Abstract
Commercial Oregano oils with high concentrations of carvacrol have been vigorously promoted as antiviral agents effective against colds and 'flu, including the pandemic H1N1 virus. However there seems to be no evidence to support these claims. Furthermore, since carvacrol itself is known to be toxic, so-called "carrier oils", such as olive oil, have been included in formulations to ameliorate the potential toxic effects. We compared the antiinfluenza virus activity of several preparations, with and without "carriers", and pure olive oil and carvacrol, by means of quantitative assays for H1N1 influenza virus, and for cytotoxicity in human lung epithelial cells. A range of concentrations was evaluated, including those relevant to consumer applications. All five Oregano oils showed significant antiviral activity, as did olive oil by itself, although their potencies were not comparable to a standardized preparation of Echinacea purpurea. Carvacrol was also very active, but it was also strongly cytotoxic. In addition all the Oregano oils were more cytotoxic than Echinacea purpurea. Thus certain commercial Oregano oils do possess anti-influenza virus activities, although these are less than a potent standardized Echinacea preparation, and furthermore the toxicity of the oils to lung epithelial cells, at doses relevant to consumer applications, is a limiting factor in their usefulness for oral applications.
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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".