Efficacy of Hovenia dulcis Fruit Extract in Hangover Mitigation: Double-Blind Randomized Clinical Evaluation
Bibliographic record
Abstract
The fruit of Hovenia dulcis Thunb. (HD) is renowned for its medicinal properties and is rich in bioactive compounds, traditionally used in East Asian medicine as a natural antidote for alcohol intoxication. A randomized, double-blind, crossover, placebo (PLA)-controlled clinical trial was conducted to compare the effects of beverages containing 0.475% HD (HDB), HD combined with 0.1% Pueraria lobata extract (HDPB), and HD combined with 0.02% glutathione yeast extract (HDGB) with the PLA on the symptoms of a hangover. Subjects (n = 30) were randomized into six test groups consuming three beverages, including the PLA. After ingestion, blood alcohol and blood acetaldehyde concentrations were measured at 0, 0.25, 0.5, 1, 2, 4, 6, and 15 h post-alcohol consumption. No significant differences in hematology tests and vital signs were observed amongst the treatment groups; however, at 0.5 and 6 h, the blood alcohol concentrations of the HDB and HDPB groups were significantly lower compared to the PLA group (p < 0.05). Additionally, the blood acetaldehyde concentrations in the HDPB group showed significantly lower values than the PLA after 6 h (p < 0.05). These findings suggest that HD may aid in alcohol detoxification and limit acetaldehyde accumulation. This indicates the potential for HD as a functional food ingredient for alleviating hangover symptoms.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".