Pharmacokinetics and antiangiogenic studies of potassium koetjapate in rats
Bibliographic record
Abstract
PURPOSE: Koetjapic acid is an active compound of a traditional medicinal plant, Sandoricum koetjape. Although koetjapic acid has a promising anticancer potential, yet it is highly insoluble in aqueous solutions. To increase aqueous solubility of koetjapic acid, we have previously reported a chemical modification of koetjapic acid to potassium koetjapate (KKA). However, pharmacokinetics of KKA has not been studied. In this study, pharmacokinetics and antiangiogenic efficacy of KKA are investigated. METHODS: Pharmacokinetics of KKA was studied after intravenous and oral administration in SD rats using HPLC. Anti-angiogenic efficacy of KKA was investigated in rat aorta, human endothelial cells (EA.hy926) and nude mice implanted with matrigel. RESULTS: 18.4 ± 4.2 μM and demonstrated remarkable inhibition of major endothelial functions such as migration, differentiation and VEGF expression in endothelial cells. Further, KKA significantly inhibited vascularization in matrigel plugs implanted in nude mice. CONCLUSIONS: The results indicate that bioabsorption of KKA from oral route was considerably efficient with longer retention in body than compared to that of the intravenous route. Further, improved antiangiogenic activity of KKA was recorded which could probably be due to its increased solubility and bioavailability. The results revealed that KKA inhibits angiogenesis by suppressing endothelial functions and expression of VEGF.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".