The Therapeutic Potential of Extracellular Vesicles in Psoriasis Treatment: Mechanisms, Applications, and Prospects
Bibliographic record
Abstract
Psoriasis is a chronic inflammatory skin disease driven by dysregulated immune responses and aberrant keratinocyte (KC) proliferation, with a profound impact on patient quality of life. Emerging evidence highlights extracellular vesicles (EVs) as promising therapeutic candidates in regenerative medicine, offering new avenues for psoriasis management. This review provides a critical overview of psoriasis pathophysiology and evaluates the mechanistic basis of EV-based therapies, emphasizing their immunomodulatory capacity to restore immune homeostasis. We synthesize findings from preclinical studies, demonstrating the therapeutic potential of EVs derived from diverse cellular sources, including their ability to attenuate inflammation, regulate immune responses, enhance wound repair, and modulate KC function. Finally, we explore future directions aimed at optimizing EV therapeutic efficacy and translating these findings into clinical practice. Collectively, this review underscores EVs as a novel, targeted, and cell-free therapeutic strategy with the potential to transform psoriasis treatment.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".