Localization of small leucine‐rich proteoglycans and transforming growth factor‐β in human oral mucosal wound healing
Bibliographic record
Abstract
Wound healing in oral mucosa is fast and results in little scar formation as compared with skin. The biological mechanisms underlying this property are poorly understood but may provide valuable information about the factors that promote wound regeneration. Small leucine-rich proteoglycans (SLRPs) decorin, biglycan, fibromodulin and lumican are extracellular matrix molecules that regulate collagen fibrillogenesis, inhibit transforming growth factor-beta (TGF-beta) activity and reduce scarring. In the present study, we analyzed accumulation of SLRPs and TGF-beta during non-scarring human oral mucosal wound healing. Biopsies were collected from healthy volunteers from unwounded tissue and from standardized experimental wounds 3-60 days postwounding. Localization of SLRPs, TGF-beta1 and TGF-beta3 was analyzed by immunohistochemical staining and quantitated by image analysis. Double immunostaining was used to study localization of SLRPs or active TGF-beta in distinct cells. Decorin, biglycan, fibromodulin, and TGF-beta isoforms showed significantly increased accumulation in the wound extracellular matrix and distinct wound cells while the abundance of lumican in the extracellular matrix was strongly reduced during wound healing. Localization and abundance of fibromodulin, lumican, and TGF-beta isoforms was also spatiotemporally regulated in the wound epithelium. The findings suggest that SLRPs regulate wound reepithelialization and connective tissue regeneration during oral mucosal wound healing.
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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".