Antiviral Effects of Persimmon Extract on Human Norovirus and Its Surrogate, Bacteriophage MS2
Bibliographic record
Abstract
UNLABELLED: Human noroviruses (NoVs) are the leading cause of gastroenteritis and foodborne illnesses worldwide. In this study, we investigated the effects of persimmon extract (PE) on NoV GII.4 and bacteriophage MS2. We also examined the relationship between the tannin content of PE and its antiviral effects to identify the active ingredient in PE. Different persimmon tannin (PT) solutions were prepared by mixing PE with different concentrations of bovine serum albumin. The antiviral efficacy of these solutions against NoV was evaluated by quantifying the amount of residual noroviral genome using a quantitative reverse transcription PCR (qRT-PCR) assay. The antiviral efficacy of PE against MS2 was examined with an infectivity assay (plaque assay). Solutions containing ≥ 0.11 mg/mL PT reduced the noroviral genome by more than 70.0% and the infectivity of MS2 by more than 2.5 log PFU/mL. However, the effects of PT on both viruses decreased markedly at a concentration of 0.08 mg/mL and solutions containing negligible PT had no antiviral activity. These results suggest that the PT component of PE inactivates NoV and MS2. Our results indicate that PE is a nontoxic antiviral agent effective against enteric viruses. PRACTICAL APPLICATION: Persimmon extract showed antiviral effects against NoV and bacteriophage MS2. Persimmon extract is suitable for use as an antiviral agent.
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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".