Molecular Markers of Early Orthodontic Tooth Movement
Bibliographic record
Abstract
OBJECTIVE: To understand the molecular basis of early orthodontic tooth movement by looking at the expression of KI-67, runt-related transcription factor 2 (Runx2), and tumor necrosis factor ligand superfamily member 11 (RANKL) proteins. MATERIALS AND METHODS: We employed a rat model of early orthodontic tooth movement using a split-mouth design (where contralateral side serves as a control) and performed immunohistochemical staining to map the spatial expression patterns of three proteins at 3 and 24 hours after appliance insertion. RESULTS: We observed increased expression of KI-67, a proliferation marker, and RANKL, a molecule associated with osteoclastic differentiation, in the compression sites of the periodontal ligament subjected to 3 hours of force. In contrast, there was increased expression of KI-67 and Runx2, a marker of osteoblast precursors, in tension areas after 24 hours of force. Decreased KI-67 expression in the mesial and distal regions of the periodontal ligament was observed at the midpoint of the tooth root. CONCLUSIONS: The early RANKL expression indicates that at this early stage cells are involved in osteoclast precursor signaling. Also, decreased KI-67 expression found near the midpoint of the tooth root is believed to represent the center of rotation, providing a molecular means of visualizing mechanical loading patterns.
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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 | 0.002 | 0.001 |
| 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) | 0.004 | 0.001 |
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".