A Pilot Crossover Study of Berberine and its Short-Term Effects on Blood Glucose Levels in Healthy Volunteers
Bibliographic record
Abstract
Abstract INTRODUCTION: Different berberine preparations were evaluated for their effectiveness on lowering blood glucose in a pilot, open-label, crossover study conducted in healthy adults. METHODS: Fourteen healthy volunteers of both sexes were recruited, and seven completed all treatments in the study. Study participants ingested one of three berberine preparations containing 500mg of berberine, respectively. A one week wash out period was included between treatments. A control group was included to measure the participants’ baseline response to a 75g glucose solution without any treatment, and the following interventions were administered: berberine powder in hard gelatin capsules, berberine in an oil matrix encapsulated in soft-gelatin capsules, and berberine in LipoMicel® matrix encapsulated in soft-gelatin capsules. Blood glucose concentrations in each participant were monitored from pre-dose baseline, before the capsules were ingested, until up to 3 hours after the capsules were ingested. RESULTS: LipoMicel Berberine treatment led to reduced blood glucose concentrations Area Under Curve (AUC, mean difference: 1.57; 95% CI: 0.021 - 3.12; P = 0.046; Cohen’s d = 1.53) and reduced maximum glucose concentration (Gmax, mean difference: 1.07; 95% CI 0.004 - 2.14; P = 0.049; Cohen’s d = 1.52) compared to the control group when no-treatment was given. No adverse events related to berberine treatments were reported by participants throughout the study period. CONCLUSIONS: LipoMicel Berberine was effective in lowering blood glucose AUC by 12% after two 500mg doses in 7 participants. Berberine in other formulations may require a longer dosing regimen before blood glucose lowering effects can be demonstrated.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| 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".