Keratinocyte-releasable Stratifin Regulates Matrix Metalloproteinases Gene Expression in Dermal Fibroblasts
Bibliographic record
Abstract
Communication between keratinocytes and fibroblasts is critical in wound healing as well as maintaining the integrity of skin. Previously, we have demonstrated that keratinocyte releasable stratifin, also known as 14–3-3ς protein, stimulates collagenase expression in dermal fibroblasts. The effect of stratifin on other extracellular matrix (ECM) factors produced by fibroblasts is not yet known. As delays in re-epithelialization lead to development of hypertrophic scar (HSc) in burn patients, we hypothesized that stratifin can regulate the production of anti-fibrogenic factors in dermal fibroblasts. Fibroblasts were either co-cultured with keratinocytes or treated with recombinant stratifin protein for 24 h. Following isolation of total RNA from fibroblasts, large scale gene expression analysis was carried out by ECM specific microarray. Gene expression and protein level of selected ECM factors were then examined by reverse-transcribed PCR (RT-PCR), Northern, and Western blot. Stratifin significantly increased the expression of collagenase-1, stromelysin-1 and -2, neutrophil collagenase, and membrane type 5 MMP in dermal fibroblasts. Similar gene expression patterns were observed in RT-PCR, further confirming the array results. Stromelysin-1 (MMP-3) mRNA and protein analysis in fibroblasts revealed a dose and time dependence in response to stratifin. In a lasting effect study, MMP-3 protein level remained significantly high in fibroblast conditioned medium for 48 h after removal of stratifin.
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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".