Novel ethosomal gel formulation for enhanced transdermal delivery of curcumin and cyclosporine: a preclinical approach to rheumatoid arthritis management
Bibliographic record
Abstract
Vesicular systems have demonstrated efficacy in the management of Rheumatoid Arthritis (RA). This study explores the synergistic effect of edge-activated ethosomal gel to enhance the transdermal delivery of Curcumin (CUR) and Cyclosporine (CYC). Ethosomal vesicles prepared via the ethanol injection method were incorporated into a gel, with the optimized formulation exhibiting an average particle size of 93.3 ± 1.17 nm and a zeta potential of −29.2 ± 0.17 mV. Ex vivo diffusion studies on porcine ear skin demonstrated 97.115 ± 0.40% CUR and 98.331 ± 1.08% CYC release over 18 hours, exhibiting Hixson-Crowell diffusion mechanisms. The steady-state flux and permeability coefficients were 0.095 µg/cm2/hr and 0.0095 cm/hr for CUR, and 0.0804 µg/cm2/hr and 0.01608 cm/hr for CYC respectively. In anti-inflammatory tests on lipopolysaccharide (LPS)-induced RAW 264.7 cells, the gel significantly increased IL-10 levels (p < 0.001), inhibited prostaglandin-E2, and reduced IL-6 and TNF-α levels (p < 0.001). Moreover, the ethosomal gel demonstrated nonirritating properties and exhibited significant reduction in arthritic symptoms in the Complete Freund’s Adjuvant induced 28-day rat model, surpassing the effects of marketed and conventional gel. These findings highlight the synergistic benefits of combining CUR and CYC in an ethosomal gel, offering a promising alternative for RA management. Future clinical investigations are warranted to validate its safety and efficacy in humans and facilitate potential therapeutic integration.
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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 | 0.000 |
| 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".