Toward Long-Acting Psoriasis Therapy with Phloretin-Loaded Microneedle Patches: Insights from <i>In Vitro</i> Patient-Derived Skin Models
Bibliographic record
Abstract
Plaque psoriasis is a chronic inflammatory skin disorder characterized by excessive T lymphocyte infiltration and keratinocyte hyperproliferation, resulting in epidermal thickening. Current treatments often require lifelong administration and carry risks of systemic toxicity, limiting patient adherence. Microneedle patches represent a promising alternative, offering localized, minimally invasive, and controlled drug delivery. This study evaluates the therapeutic potential of a sustained-release microneedle patch delivering phloretin or methotrexate using a tissue-engineered human psoriatic skin model. The model was developed using keratinocytes and fibroblasts isolated from lesional skin of patients with psoriasis, preserving the disease's genetic profile. Human T lymphocytes were incorporated to replicate the inflammatory microenvironment. This study demonstrates a significant reduction in epidermal thickness while no changes were observed in healthy skin substitutes, confirming specificity for hyperproliferative tissue. The therapeutic effect was comparable to systemic methotrexate. To assess molecular diffusion, Cy5-COOH was used as a fluorescent tracer, revealing sustained dermal and longitudinal diffusion for up to 2 weeks. These results suggest that a single application could provide extended therapeutic benefit for at least 2 weeks. This is the first study to demonstrate the efficacy of microneedle patch treatment in a human psoriatic skin model, supporting their potential as a targeted, long-acting therapy for psoriasis.
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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".