The Junctional Epithelium Attachment Is Regulated by Wnt Signaling
Bibliographic record
Abstract
The molecular mechanisms mediating barrier functions of the junctional epithelium (JE) are incompletely understood. The aim of this study was to gain mechanistic insights into how reduced Wnt/β-catenin signaling affects the metabolism, turnover, and attachment of JE cells to the tooth surface. A membrane-permeable selective inhibitor of the Wntless protein, C59, was topically delivered to the JE. Wnt pathway suppression was verified by using Axin2 LacZ/+ and Axin2Cre ERT2/+ ; R26R mTmG/+ strains of mice. Quantitative analyses were carried out at multiple time points to assess mitotic activity, apoptosis, expression of hemidesmosomal attachment proteins, distribution of immune cells, collagen remodeling, and alveolar bone resorption. To complement these studies, Wntless was genetically deleted in osteocalcin-expressing cells, including those in the JE, after which the same quantitative analyses were performed. C59 caused a dose-dependent inhibition in Wnt signaling, which led to reduced mitotic activity and increased apoptosis in the JE. Continued dosing of C59 was accompanied by downregulation of the hemidesmosome attachment proteins laminin 5, plectin, and integrin β4 and a disruption in collagen orientation. A genetic approach in which Wntless function was inhibited in osteocalcin-expressing JE cells yielded similar inhibitory effects on Wnt signaling, mitotic activity, the JE’s attachment to the tooth surface, and an increase in immune cells within the connective tissue. Wnt/β-catenin signaling is required for JE homeostasis, and disruptions to the pathway are sufficient to cause JE breakdown and attachment loss. Methods to modulate Wnt/β-catenin signaling may prove beneficial in restoring JE homeostasis after injury or disease.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".