Molecular Profiling of Odontoclasts during Physiological Tooth Replacement
Bibliographic record
Abstract
The odontoclast is a rarely studied cell type that is overly active in many dental pathologies, leading to tooth loss. It is difficult to find diphyodont mammals in which either physiological or pathological root resorption can be studied. Here we use the adult leopard gecko, which has repeated cycles of physiological tooth resorption and shedding. RNA-seq was carried out to compare gene expression profiles of functional teeth to developing teeth. Genes more highly expressed in bell-stage developing teeth were related to morphogenesis ( PTHLH , SFRP2 , SHH , EDAR ). Some genes expressed in osteoclasts ( ACP5 , CTSK , CSF1R ) were relatively more abundant in functional teeth compared with developing teeth. There was, however, no differential expression of RANKL ( TNFSF11 ) in the 2 tooth types. In addition, functional teeth expressed proteolysis genes not found in osteoclasts ( ADAMTS2 , 3 , 4 , 14; CTSA , CTSH , CTSS ). We used tartrate acid resistant phosphatase and cathepsin K (CTSK) staining to identify odontoclasts in and around the gecko dentition. There were 3 populations of CTSK cells: (1) large, functional multinucleated odontoclasts in the crown of the tooth with a ruffled border inside resorption pits; (2) smaller, precursor cells in the pulp with fewer nuclei; and (3) flattened external precursor cells next to the root and bone of attachment. We found a positive relationship between developing teeth and the population of CTSK+ cells on the root surface. We tested a candidate signal that may be involved in CTSK+ cell presence. An antagonist of CSF1R was delivered to developing teeth in vivo, which resulted in a significant decrease in CTSK and CSF1R compared with DMSO controls. Thus, the CSF1 signaling pathway is upstream of CTSK in teeth. This is the first work to detail the molecular characteristics of odontoclasts during physiological tooth shedding and to demonstrate that in vivo, local drug delivery is possible in the gecko model.
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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 | 0.001 | 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".