Comparative Human Skin Permeation Study on Nanocarriers for Potential Transdermal Delivery of Progesterone
Bibliographic record
Abstract
This study is the first attempt to directly compare the ability of several nanocarrier formulations to deliver progesterone into the skin.Four progesterone-loaded nanocarriers; cubosomes [1], nanoliposomes [2], nanoemulsions [3] and polymeric nanomicelles [4] were formulated and characterized regarding particle size, zeta potential, % drug encapsulation, loading capacity and in-vitro release.The aim of the current investigation is to explore the feasibility of various nanocarriers to enhance the penetration of progesterone via the full thickness of human abdominal skin.Structural elucidation of each nanoplatform was performed using the Transmission electron microscope.Each nanocarrier was fabricated with a negative surface, nanometric size (≤ 270 nm), narrow size distribution and reasonable encapsulation capacity.The in-vitro progesterone release showed a sustained release pattern for 24 h following a non-fickian transport diffusion mechanism.Ex-vivo skin permeation, deposition ability and histopathological examination were evaluated using Franz diffusion cells.All nanocarriers exhibited higher transdermal flux value relative to free progesterone.Cubosomes revealed a higher skin penetration with transdermal steady flux of 48.57.10-2 µg/cm2 h.Nanoliposomes offered a significant increase in the % skin deposition compared to other carriers.Based on the histopathological examination, cubosomes and nanoliposomes were found to be biocompatible for skin application.Confocal laser scanning microscopy confirmed the ability of fluorolabeled cubosomes to penetrate deeply through the whole skin layers.The novel elaborated cubosomes were proved to be a promising non-invasive nanocarrier for transdermal hormonal delivery without causing any sign of irritation.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".