Collagen Fragments Inhibit Hyaluronan Synthesis in Skin Fibroblasts in Response to Ultraviolet B (UVB)
Bibliographic record
Abstract
UVB irradiation causes characteristic features of skin aging including remodeling of the dermal extracellular matrix. A key feature during this process is the up-regulation of matrix metalloproteinases and cleavage of collagen. Hyaluronic acid (HA), a major component of the dermal matrix, decreases after chronic UVB exposure. However, the factors that govern the decline of HA synthesis during the course of actinic aging are largely unknown. The aim of the present study was to explore whether collagen degradation causes inhibition of HA synthesis in human skin fibroblasts. After treatment of fibroblasts with collagen fragments (CF) in vitro, resolution of the actin cytoskeleton and inhibition of HA secretion occurred because of specific down-regulation of hyaluronan synthase 2 (HAS2) expression. The α(v)β(3)-agonist, RGDS, latrunculin A, and an inhibitor of Rho-activated kinase inhibited HAS2 expression. Conversely, blocking antibodies to α(v)β(3) abolished the down-regulation of HAS2 and the cytoskeletal effects. Furthermore, inhibition of cofilin phosphorylation in response to CF was prevented by α(v)β(3)-blocking antibodies. The key role of ERK signaling was shown by reduced nuclear accumulation of phosphoERK and of ELK-1 phosphorylation in response to CF. In addition, the ERK inhibitor PD98059 reduced HAS2 expression. Also, UVB irradiation of fibroblasts caused down-regulation of HAS2, which was sensitive to matrix metalloproteinase inhibitors and to α(v)β(3)-blocking antibodies. In conclusion, these data suggest that CF activate α(v)β(3)-integrins and in turn inhibit Rho kinase (ROCK) signaling and nuclear translocation of phosphoERK, resulting in reduced HAS2 expression. Therefore, a novel mechanism is presented how proteolytic collagen cleavage may inhibit HA synthesis in dermal fibroblasts during extrinsic skin aging.
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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 | 0.000 |
| 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) | 0.001 | 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".