Immunolocalization of Tenascin-C, α9 Integrin Subunit, and αvβ6 Integrin During Wound Healing in Human Oral Mucosa
Bibliographic record
Abstract
Tenascin-C (TN-C) and its isoforms are multidomain extracellular matrix (ECM) proteins that are believed to be involved in the regulation of stromal-epithelial interactions. Some of the interactions between TN-C and cells are mediated by integrins. In this study we analyzed the expression of TN-C and its large molecular weight splice isoform (TN-C(L)) and the putative TN-C-binding alpha9 and alphavbeta6 integrins during human wound repair. In 3-day-old oral mucosal wounds, immunoreactivity for alpha9 integrin localized abundantly at the migrating basal wound epithelial cells. TN-C and TN-C(L) were localized in the matrix between and underneath alpha9-expressing epithelial cells. In parallel with gradual downregulation of alpha9 integrin immunoreactivity in 7-day and older wounds, the expression of alphavbeta6 integrin was temporarily induced. Integrin alphavbeta6 co-localized in the same area as TN-C and TN-C(L) immunoreactivity at the cell-cell contacts of the basal and suprabasal cell layers of the wound epithelium. During granulation tissue formation and reorganization from 7 to 28 days after wounding, TN-C and TN-C(L) were abundantly localized in the granulation tissue. The findings show that TN-C(L) is expressed under the migrating epithelial front and in the granulation tissue during matrix deposition in wound repair. Preferential localization of alpha9 integrin in migrating epithelial cells and of alphavbeta6 integrin in epithelium after wound closure suggests different functions for these integrins in wound repair.
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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".