Efficacy of bioflavonoids of FLAVOBA against severe acute respiratory syndrome-coronavirus 2 in vitro
Bibliographic record
Abstract
Introduction The Severe Acute Respiratory Syndrome-Coronavirus 2 (SARS-CoV-2) is responsible for the global pandemic of Coronavirus disease-2019 (COVID-19). Human-to-human transmission occurs mainly through the aerosolization of respiratory droplets. Improved antisepsis of human and non-human surfaces has been identified as a key feature of transmission reduction. Flavobac, a complex of soluble bioflavonoids and hydroxylated phenolic structures used in oral care products, has demonstrated efficacy to act against microorganisms. This study evaluated nasal and oral antiseptic formulations of FLAVOBAC for the virucidal activity against SARS-CoV-2. Methodology FLAVOBAC nasal antiseptic formulations and FLAVOBAC oral rinse antiseptic formulations from 1-10% concentrations were assayed for virucidal efficacy against the SARS-CoV-2 virus. SARS-CoV-2 was exposed directly to the test compound for 60 seconds or 5 minutes. Compounds were then neutralized, and the surviving virus was quantified. Results All concentrations of nasal antiseptics and oral rinse antiseptics evaluated completely inactivated the SARS-CoV-2 virus. Conclusion Nasal and oral FLAVOBAC solutions are effective at inactivating the SARS-CoV-2 virus at a variety of concentrations after 60-second or 5-minute exposure times. The formulations tested have the potential to reduce the transmission of SARS-CoV-2 if used for nasal/oral decontamination, or surface decontamination in known or suspected cases of COVID-19.
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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) | 0.001 | 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) | 0.002 | 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".