Part 1. Evaluation of Epigallocatechin Gallate or Tannic Acid Formulations of Hydrophobic Drugs for Enhanced Dermal and Bladder Uptake or for Local Anesthesia Effects
Bibliographic record
Abstract
Epigallocatechin gallate (EGCG) and tannic acid (TA) are known to increase the aqueous solubility and cellular uptake of the hydrophobic drugs docetaxel, paclitaxel, amphotericin B, and curcumin. In this study the practical application of gallate-based solubilization phenomena for the uptake of these drugs into dermal and bladder tissue and of lidocaine for wound healing application was studied. The penetration of all these drugs into pig skin or docetaxel into pig bladder using EGCG or TA formulations was measured. Overall, EGCG and TA particulate or propylene glycol paste formulations of drugs allowed for greatly increased levels of drug uptake into skin as compared to control formulations. EGCG/propylene glycol pastes allowed for rapid lidocaine uptake into skin. EGCG and TA formulations of docetaxel allowed for approximately 10 fold increases in bladder tissue uptake of docetaxel over tween based solutions. Morphologically, both EGCG and TA caused a mild, dose dependent exfoliation of the bladder wall. Both EGCG and TA formed injectable viscous pastes with propylene glycol which solidified in water and degraded and released lidocaine over 2-35 days. These data support the use of EGCG and TA based formulations of certain drugs for improved dermal, bladder and wound applications.
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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) | 0.000 | 0.001 |
| 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) | 0.004 | 0.001 |
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".