Cellular Senescence in Human Skin Aging: Leveraging Senotherapeutics
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: As the largest organ in the human body, the skin is continuously exposed to intrinsic and extrinsic stimuli that impact its functionality and morphology with aging. Skin aging entails dysregulation of skin cells and loss, fragmentation, or fragility of extracellular matrix fibers that are manifested macroscopically by wrinkling, laxity, and pigmentary abnormalities. Age-related skin changes are the focus of many surgical and nonsurgical treatments aimed at improving overall skin appearance and health. SUMMARY: As a hallmark of aging, cellular senescence, an essentially irreversible cell cycle arrest with apoptosis resistance and a secretory phenotype, manifests across skin layers by affecting epidermal and dermal cells. Knowledge of skin-specific senescent cells, such as melanocytes (epidermal aging) and fibroblasts (dermal aging), will promote our understanding of age-related skin changes and how to optimize patient outcomes in esthetic procedures. KEY MESSAGES: This review provides an overview of skin aging in the context of cellular senescence and discusses senolytic intervention strategies to selectively target skin senescent cells that contribute to premature skin aging.
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.
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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 it