The Role of Exosomes in Medical Dermatology: Literature Review and Update
Bibliographic record
Abstract
BACKGROUND: Exosomes are extracellular vesicles, composed of a phospholipid bilayer, that are primarily derived from stem cells. The contents of exosomes can be incorporated into the tissue in which they are introduced, which presents a unique therapeutic option. AIMS: Exosomes have been investigated as a treatment for a number of medical ailments, but the literature supporting these indications is inconclusive. In addition, much of the study on exosomes and their uses has been recently completed. Thus, this review summarizes the efficacy and implications of exosomes in the treatment of different dermatologic conditions. METHODS: A literature review surrounding the use of exosomes for multiple medical dermatological conditions was conducted. Additionally, we present numerous practical cases in which patients had been treated with exosomes. RESULTS: Overall, the success of exosomes in treating medical dermatologic conditions demonstrated varying efficacy in the literature, but the preliminary evidence is generally positive. The patient cases also showed satisfactory clinical outcomes but further studies and cases will be necessary to fully characterize the efficacy of exosomes and the ideal modalities for their application, including formulation, mode of distribution, and frequency of treatment. CONCLUSIONS: Exosomes may serve as an effective treatment option for wound healing, reconstruction of skin flaps, radiation dermatitis, acne vulgaris, psoriasis, atopic dermatitis, allergic contact dermatitis, lichen simplex chronicus, vulvar lichen sclerosis, systemic sclerosis, systemic lupus erythematosus, and vitiligo although additional studies are needed to confirm their efficacy and safety.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".