Moderate doses of commercial preparations of Ginkgo biloba do not alter markers of liver function but moderate alcohol intake does: A new approach to identify and quantify biomarkers of ‘adverse effects’ of dietary supplements
Bibliographic record
Abstract
It is difficult to determine if certain dietary supplements are safe for human consumption. Extracts of leaves of Ginkgo biloba trees are dietary supplements used for various purported therapeutic benefits. However, recent studies reported they increased risk of liver cancer in rodents. Therefore, this study assessed the association between ginkgo consumption and liver function using NHANES 2001-2012 data (N = 29,684). Since alcohol is known to adversely affect liver function, association of its consumption with liver function was also assessed. Alcohol and ginkgo extract intake of adult consumers and clinical markers of liver function (alkaline phosphatase, alanine aminotransferase, aspartate aminotransferase, gamma glutamyl transferase, lactate dehydrogenase, bilirubin) were examined. Moderate consumers of alcohol (0.80 ± 0.02 drinks/day) had higher levels of aspartate aminotransferase and gamma glutamyl transferase than non-consumers (P < 0.001). There was no difference (P > 0.01) in levels of markers of liver function in 616 ginkgo consumers (65.1 ± 4.4 mg/day intake) compared to non-consumers. While moderate alcohol consumption was associated with changes in markers of liver function, ginkgo intake as typically consumed by U.S. adults was not associated with these markers. Biomarkers measured by NHANES may be useful to examine potential adverse effects of dietary supplements for which insufficient human adverse event and toxicity data are available. TRIAL REGISTRATION NUMBER: Not applicable, as this is secondary analysis of publicly released observational data (NHANES 2001-2012).
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".