Autologous Cell Therapy for Aged Human Skin: A Randomized, Placebo-Controlled, Phase-I Study
Bibliographic record
Abstract
INTRODUCTION: Skin ageing involves senescent fibroblast accumulation, disturbance in extracellular matrix (ECM) homeostasis, and decreased collagen synthesis. OBJECTIVE: to assess a cell therapy product for aged skin (RCS-01; verum) consisting of ~25 × 106 cultured, autologous cells derived from anagen hair follicle non-bulbar dermal sheath (NBDS). METHODS: For each subject in the verum group, 4 areas of buttock skin were injected intradermally 1 or 3 times at monthly intervals with RCS-01, cryomedium, or needle penetration without injection; in the placebo group RCS-01 was replaced by cryomedium. The primary endpoint was assessment of local adverse event profiles. As secondary endpoints, expression of genes related to ECM homeostasis was assessed in biopsies from randomly selected volunteers in the RCS-01 group taken 4 weeks after the last injection. -Results: Injections were well tolerated with no severe adverse events reported 1 year after the first injection. When compared with placebo-treated skin, a single treatment with RCS-01 resulted in a significant upregulation of TGFβ1, CTGF, COL1A1, COL1A2, COL3A1, and lumican mRNA expression. LIMITATIONS: The cohort size was insufficient for dose -ranging evaluation and subgroup analyses of efficacy. CONCLUSIONS: RCS-01 therapy is well tolerated and associated with a gene expression response consistent with an improvement of ECM homeostasis.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".