Cell-specific expression of the transcriptional regulator RHAMM provides a timing mechanism that controls appropriate wound re-epithelialization
Bibliographic record
Abstract
Prevention of aberrant cutaneous wound repair and appropriate regeneration of an intact and functional integument require the coordinated timing of fibroblast and keratinocyte migration. Here, we identified a mechanism whereby opposing cell-specific motogenic functions of a multifunctional intracellular and extracellular protein, the receptor for hyaluronan-mediated motility (RHAMM), coordinates fibroblast and keratinocyte migration speed and ensures appropriate timing of excisional wound closure. We found that, unlike in WT mice, in Rhamm -null mice, keratinocyte migration initiates prematurely in the excisional wounds, resulting in wounds that have re-surfaced before the formation of normal granulation tissue, leading to a defective epidermal architecture. We also noted aberrant keratinocyte and fibroblast migration in the Rhamm -null mice, indicating that RHAMM suppresses keratinocyte motility but increases fibroblast motility. This cell context–dependent effect resulted from cell-specific regulation of extracellular signal-regulated kinase 1/2 (ERK1/2) activation and expression of a RHAMM target gene encoding matrix metalloprotease 9 (MMP-9). In fibroblasts, RHAMM promoted ERK1/2 activation and MMP-9 expression, whereas in keratinocytes, RHAMM suppressed these activities. In keratinocytes, loss of RHAMM function or expression promoted epidermal growth factor receptor–regulated MMP-9 expression via ERK1/2, which resulted in cleavage of the ectodomain of the RHAMM partner protein CD44 and thereby increased keratinocyte motility. These results identify RHAMM as a key factor that integrates the timing of wound repair by controlling cell migration.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".