Delayed Tooth Development and the Impaired Differentiation of Stem/Progenitor Cells in Incisors from Type 2 Diabetes Mice
Bibliographic record
Abstract
Patients with diabetes mellitus (DM) have an increased risk of tooth decay caused by alterations in their tooth development and their oral environment, as well as a tendency to present with pulp infection due to compromised immune response. The present study analyzed the characteristic alterations in tooth development under DM conditions using incisors from db/db type 2 diabetic mouse model (T2DM mice). In micro-CT analyses, T2DM mice showed delayed dentin and enamel formation. Through transcriptomic analyses, pre-ameloblast- and pre-odontoblast-specific genes were found to be significantly decreased in the incisors of T2DM mice, whereas major ameloblast- and mature odontoblast-specific genes were not changed. Stem cell markers were decreased in T2DM mice compared to those from the control mice, suggesting that the stemness of dental pulp cells (DPCs) is attenuated in T2DM mice. In vitro analyses demonstrated that DPCs from T2DM mice have lower colony-forming units (CFU), slower propagation, and diminished differentiation characteristics compared to the control. These data suggest that T2DM conditions could impair the differentiation property of multiple progenitor/stem cells in the tooth, resulting in delayed tooth development in T2DM mice.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".