Topical photodynamic therapy with 5‐aminolaevulinic acid does not induce hair regrowth in patients with extensive alopecia areata
Bibliographic record
Abstract
BACKGROUND: Photodynamic therapy (PDT) is a new modality involving the administration of a photosensitizer, or photosensitizer precursor, followed by its activation with light to generate a therapeutic effect. 5-Aminolaevulinic acid (ALA) is a photosensitizer precursor that is transformed by cells into protoporphyrin IX (PpIX), which can in turn be activated by red light. OBJECTIVES: To investigate the effect of PDT in alopecia areata (AA). METHODS: In six patients with extensive AA, topical ALA lotion at 5%, 10% and 20% as well as the vehicle lotion alone were applied separately to different scalp areas, followed 3 h later by exposure to red light at each treatment session. RESULTS: No significant hair growth was observed after 20 twice-weekly treatment sessions. A significant increase in erythema and pigmentation was observed for the three concentrations of ALA lotion vs. the vehicle, implying that a phototoxic PDT effect was achieved in the skin. In vivo fluorescence spectroscopy in one patient showed an increase in red PpIX fluorescence 3 h after ALA application followed by a decrease after light exposure. On fluorescence microscopy, bright red fluorescence was present in the epidermis and sebaceous glands, but not in the inflammatory infiltrate surrounding the hair follicle following ALA application. CONCLUSIONS: PDT was ineffective in the treatment of AA.
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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 | 0.001 |
| 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".