Evaluating Receptor Activator of Nuclear Factor Kappa B Ligand (RANKL) and Osteoprotegerin (OPG) expression during canine retraction: A comparison between periodontal distraction versus conventional retraction
Bibliographic record
Abstract
OBJECTIVE: To evaluate and compare the expression levels of Receptor Activator of Nuclear Factor Kappa B Ligand (RANKL) and Osteoprotegerin (OPG) in canine periodontal tissues subjected to periodontal distraction versus conventional retraction at different treatment time points. MATERIALS AND METHODS: The study involved 40 cuspids from 20 patients (9 males, 11 females) randomly allocated to either the periodontal distraction (PD) group or the conventional retraction group. Appliances were applied by a single practitioner in a split-mouth design. In Group 1 (PD), a trans-palatal arch and Hyrax expanders were used following premolar extraction with osteotomies performed to facilitate distraction. Group 2 (conventional retraction) used MBT brackets with sectional archwires and elastic chains. Gingival crevicular fluid samples were collected on the first day (D0), after 1 week (W1), and 6 weeks (W6) and OPG and RANKL levels were analyzed using ELISA test. RESULTS: There was a significant difference in canine retraction duration between methods ( P < 0.001), with periodontal distraction taking 24.1 ± 2.08 days versus 110.5 ± 4.84 days for conventional retraction. RANKL levels showed no baseline difference, but were significantly higher in the periodontal distraction group at weeks 1 and 6 ( P = 0.010 and P = 0.001, respectively). OPG levels were initially similar, but by weeks 1 and 6, they were significantly lower in the periodontal distraction group ( P = 0.001). CONCLUSION: The periodontal distraction method significantly reduces the duration of canine retraction and enhances osteoclastic activity, as evidenced by increased RANKL and decreased OPG levels, facilitating accelerated tooth movement through efficient bone resorption and remodeling.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".