The Emerging Field of Regenerative Aesthetics—Where We Are Now
Bibliographic record
Abstract
BACKGROUND: Regenerative aesthetics is an emerging branch of regenerative medicine with therapies aimed at recapturing youthful structure and function using the body's own systems. OBJECTIVE: To introduce the field of regenerative aesthetics, and to explore themes and evidence surrounding current and emerging therapies in the field. MATERIALS AND METHODS: A review of the literature was performed for each of the 3 pillars of regeneration; namely, stem cells, biochemical cues, and scaffolds. RESULTS: Herein, we provide an overview of the field of regenerative aesthetics, a discussion surrounding the 3 pillars of regeneration, and an overview of the evidence supporting current and emerging therapeutic modalities that could play a pivotal role in the future of aesthetic treatments. CONCLUSION: An enhanced understanding of this field can serve to further enhance our awareness about the regenerative effects of therapies we already offer, in addition to providing inspiration for future innovation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".