A Pilot Randomized Controlled Trial (RCT) Evaluating the Efficacy of an Exosome-Containing Plant Extract Formulation for Treating Male Alopecia
Bibliographic record
Abstract
Background/Objectives: Hair loss affects self-esteem, confidence, and psychological well-being. Exosomes, as molecular carriers of growth factors and active compounds, offer a promising treatment. This study evaluates the efficacy of an exosome formulation containing extracts from two known hair-regenerating plants, Ecklonia cava and Thuja orientalis (ECPE), for male pattern alopecia. Methods: A randomized controlled trial included 20 male participants with Norwood grade 2–3 androgenetic alopecia who were randomly assigned into two groups, placebo (0.9% sodium chloride) and ECPE, administered bi-weekly across four sessions. Evaluations included hair density measurements, adverse effect tracking, and self-assessments. Results: Most participants (55%) were aged 18 to 35, with 75% reporting hair loss for over a year and 80% noting scalp thinning. The hair counts showed no significant change in the placebo group from baseline to week 16 (Wilcoxon signed-rank test: V = 13.5, p = 0.163), while a significant increase was observed in the ECPE group (V = 0, p = 0.002). Between-group analysis revealed a significant difference in the hair count changes (Wilcoxon rank-sum test: W = 86.5, p = 0.006) with a large effect size (Cliff’s Delta: & = 0.73, 95% CI: 0.41–0.89), with the ECPE group showing higher median hair growth (9.5, IQR = 16.88) compared to the placebo group (1.5, IQR = 3.00). A Bayesian ANCOVA, adjusted for covariates (the father’s scalp hair condition, baseline hair count, and Norwood classification), showed no significant effect of these factors on the outcomes. Conclusions: These findings suggest that ECPE significantly improves hair regrowth compared to the placebo, with no notable adverse effects.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".