Tooth Removal in the Leopard Gecko and the de Novo Formation of Replacement Teeth
Bibliographic record
Abstract
Introduction and Objectives: The ability to replace teeth throughout life is a trait found in most vertebrates and was present in ancient mammals. Modern mammals including humans can only replace their teeth once and much effort is currently being devoted to uncovering stem cells to be used in tooth regeneration. Work from our lab and others has identified some of the differences in the reptilian dentition that could underlie the basis of polyphyodonty. In lizards, the dental lamina, a source of putative dental epithelial progenitor cells, persists until adulthood. In contrast, in humans there are very few remnants of the dental lamina remaining once the permanent dentition is complete. In this project we use the leopard gecko ( Eublepharis macularius ) and surgical treatments to trace the contribution of label‐retaining cells to the next generation of teeth. We hypothesized that premature removal of unerupted second generation teeth will stimulate populations of quiescent label‐retaining cells to proliferate. Then by following the labeled cells for several months we will identify progeny of the epithelial progenitor cells in newly formed teeth. Materials and Methods: Second generation, unerupted teeth were removed from geckos under sedation. A pulse of BrdU was administered over 3 sequential days. Animals were euthanized at 1 week post surgery (immediately after the BrdU pulse or time 0) and 1 or 2 months post surgery (N = 3 animals per timepoint). Animals were processed for immunofluorescence staining with BrdU antibodies. We counted the proportion of nuclei in the dental lamina that stained positive for BrdU. Results: One week after the surgery, we identified statistically significant higher uptake of BrdU in the dental epithelium of treated as compared to the control, non‐manipulated regions (P < 0.01). One month after the surgery, there was a significant decrease in BrdU label in the dental lamina (P< 0.001), decreasing to the same level as controls at time zero The newly formed tooth buds regenerating in the sites of tooth removal contained BrdU labeled cells in all parts of the enamel organ. The original label‐retaining cells divided several times since the original pulse, based on the fragmented appearance of the BrdU in the nuclei. Conclusion: In our previous work, it was difficult to label the quiescent cells of the dental lamina. Here the removal of the successional teeth stimulates proliferation of the dental lamina. With a larger population of label‐retaining cells that could be tracked we were able to find transit amplifying cells that divide and contribute to the enamel organ. Significance: We have developed an injury model that will allow us to test the ability of different signals to regulate the activity of stem cells. Moreover label‐retaining cells are multipotent and can self‐renew, thereby possessing some of the properties of progenitor cells.
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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".