Preclinical Pharmacokinetics and Pharmacodynamics and Content Analysis of Gnetol in Foodstuffs
Bibliographic record
Abstract
Studies were undertaken to evaluate the bioavailability in rats and content analysis of gnetol in Gnetum gnemon products reported to contain gnetol and to examine the pharmacological properties of gnetol in in vitro models including anti-inflammatory/analgesic, antidiabetic, anti-adipogenesis, and anticancer activity. Male Sprague-Dawley rats were cannulated and dosed either intravenously with gnetol (10 mg/kg) or orally (100 mg/kg). Various methanolic extractions of G. gnemon products were quantified. Gnetol's effect on cell viability in selected cell lines with or without inflammatory stimulus was assessed. α-Amylase and α-glucosidase inhibition was evaluated. Cyclooxygenase (COX)-1, COX-2, and histone deacetylase inhibition and adipogenesis inhibition were examined. After oral and intravenous administration, gnetol was detected in both serum and urine as the parent compound and as a glucuronidated metabolite. The bioavailability of gnetol was determined to be 6%. Gnetol is rapidly glucuronidated and is excreted in urine and via nonrenal routes. Gnetol was found to exist as an aglycone and as a glycoside in G. gnemon products. Gnetol showed concentration-dependent reductions in cell viability in cancer cell lines with greatest activity in colorectal cancer and potent COX-1, histone deacetylase, and weak COX-2 activities along with limited reduction in inflammation. Gnetol also possessed concentration-dependent alpha-amylase, alpha-glucosidase, and adipogenesis activities. Pretreatment of mice with gnetol was able to increase the latency period to response in analgesia models.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".