Five batches representative of Ontario-grown American ginseng root produce comparable reductions of postprandial glycemia in healthy individualsThis article is one of a selection of papers published in this special issue (part 1 of 2) on the Safety and Efficacy of Natural Health Products.
Bibliographic record
Abstract
Evidence indicates that the glycemia-lowering effect of American ginseng root may be batch dependent. We therefore evaluated the effect of 5 root batches, representative of Ontario-grown American ginseng, on postprandial glucose and insulin indices. Twelve healthy subjects (5 male, 7 female), mean +/- SE age 26.5 +/- 2 years, body mass index 23.96 +/- 3.41 kg/m2, fasting blood glucose 4.77 +/- 0.04 mmol/L, were assigned to consume 9 g of American ginseng from 5 farms (A-E), administered in randomized sequence on 5 separate visits, and a water-control during the 6th and last visit. Treatments were consumed 40 min before a 2-hour 75-gram oral glucose tolerance test. Plasma glucose and insulin were measured at baseline, before, and during the test. Compared with control, batches A and C reduced glucose incremental area under the curve (IAUC) by 35.2% (156 vs. 240 mmol.min/L) and 32.6% (162 vs. 240 mmol.min/L), respectively. Batches A, C, and E reduced incremental peak glucose by 1.3, 1.2, and 1.1 mmol/L, respectively. Batch C reduced the insulin IAUC by 27.7% (15.8 vs. 21.8 nmol.min/L). Effects on glucose and insulin parameters were not different across ginseng treatments. The mean of the 5 ginseng treatments reduced peak postprandial glucose by 1.0 mmol/L, glucose IAUC by 27.7% (173 vs. 240 mmol.min/L), and insulin IAUC by 23.8% (16.6 vs. 21.8 nmol.min/L) relative to control. (All results statistically significant at p < 0.05.) American ginseng decreased postprandial glycemia and insulinemia; however, 40% of the batches did not reduce glycemia with the anticipated magnitude, irrespective of their saponin composition.
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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 | 0.001 | 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 | 0.001 |
| 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".