Wnt/β-Catenin Signaling Regulates Postnatal Development and Regeneration of the Salivary Gland
Bibliographic record
Abstract
Regenerative therapy of the salivary gland (SG) is a promising therapeutic approach for irreversible hyposalivation in patients with head and neck cancer treated by radiotherapy. However, little is known about the molecular regulators of stem/progenitor cell activity and regenerative processes in the SG. Wnt/β-catenin signaling regulates the function of many adult stem cell populations, but its role in SG development and regeneration is unknown. Using BAT-gal Wnt reporter transgenic mice, we demonstrate that in the submandibular glands (SMGs) of newborn mice Wnt/β-catenin signaling is active in a few cells at the basal layer of intercalated ducts, the putative location of salivary gland stem/progenitor cells (SGPCs). Wnt activity decreases as mice age, but is markedly enhanced in SG ducts during regeneration of adult SMG after ligation of the main secretory duct. The Hedgehog (Hh) pathway is also activated after duct ligation. Inhibition of epithelial β-catenin signaling in young Keratin5-rtTA/tetO-Dkk1 mice impairs the postnatal development of SMG, particularly affecting maturation of granular convoluted tubules. Conversely, forced activation of epithelial β-catenin signaling in adult Keratin5-rtTA/tetO-Cre/Ctnnb1((Ex3)fl) mice promotes proliferation of ductal cells, expansion of the SGPC compartment, and ectopic activation of Hh signaling. Taken together, these results indicate that Wnt/β-catenin signaling regulates the activity of SGPCs during postnatal development and regeneration upstream of the Hh pathway, and suggest the potential of modulating Wnt/β-catenin and/or Hh pathways for functional restoration of SGs after irradiation.
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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".