American Ginseng From Five Different Sources Has Differential Effects On Postprandial Blood Glucose
Bibliographic record
Abstract
We have previously demonstrated that, among 8 popular ginseng species, cultivated American ginseng (Panax quinquefolius) is one of the most efficacious in lowering postprandial blood glucose. It is not known, however, whether any other batch of cultivated American ginseng would replicate this finding. The present study aimed to assess the glycemia lowering effect of American ginseng from five Ontario farms with varying growing conditions in a controlled multiple cross‐over intervention. 12 healthy individuals (5M:7F, age: 27± 2y, BMI: 24 ± 1 kg/m2) were tested on 6 separate occasions, after a 12h overnight fast. Each subject received 9g of American ginseng root from different farms, in random order, or a water control 40 min prior to a 75g oral glucose tolerance test. Venous blood samples were drawn prior to treatment intake and the 75 g glucose load and 15, 30, 45, 60, 90, 120 min after the glucose intake. Comparisons with control showed that ginseng from three farms significantly lowered blood glucose and area under the curve, farm A being the source of the most potent ginseng identified in this study. Overall, American ginseng reduces postprandial glycemia. However different batches do not consistently reproduce the identified glycemia lowering effect. Even among efficacious batches, differential glucose‐lowering amplitudes are observed. These variable biologic responses might be explained through compositional differences due to various growing conditions of ginseng. This calls for further identification of the active glycemia‐lowering components and subsequent ingredient‐based standardization of ginseng.
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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) | 0.000 | 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) | 0.000 | 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".