Sox2 marks epithelial competence to generate teeth in mammals and reptiles
Bibliographic record
Abstract
Tooth renewal is initiated from epithelium associated with existing teeth. The development of new teeth requires dental epithelial cells that have competence for tooth formation, but specific marker genes for these cells have not been identified. Here, we analyzed expression patterns of the transcription factor Sox2 in two different modes of successional tooth formation: tooth replacement and serial addition of primary teeth. We observed specific Sox2 expression in the dental lamina that gives rise to successional teeth in mammals with one round of tooth replacement as well as in reptiles with continuous tooth replacement. Sox2 was also expressed in the dental lamina during serial addition of mammalian molars, and genetic lineage tracing indicated that Sox2(+) cells of the first molar give rise to the epithelial cell lineages of the second and third molars. Moreover, conditional deletion of Sox2 resulted in hyperplastic epithelium in the forming posterior molars. Our results indicate that the Sox2(+) dental epithelium has competence for successional tooth formation and that Sox2 regulates the progenitor state of dental epithelial cells. The findings imply that the function of Sox2 has been conserved during evolution and that tooth replacement and serial addition of primary teeth represent variations of the same developmental process. The expression patterns of Sox2 support the hypothesis that dormant capacity for continuous tooth renewal exists in mammals.
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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 | 0.001 | 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".