Expression of Nitric Oxide Synthases in Orthodontic Tooth Movement
Bibliographic record
Abstract
OBJECTIVE: To investigate differential expression of NOS isoforms in periodontal ligament (PDL) and bone in tension and pressure sides using a rat model of orthodontic tooth movement (OTM). MATERIALS AND METHODS: Immunohistochemistry with NOS isoform (iNOS, eNOS, and nNOS) antibodies was performed on horizontal sections of the first maxillary molars subjected to 3 and 24 hours of OTM. The PDL and adjacent osteocytes of the distopalatal root at pressure and tension areas were analyzed for expression of these proteins. The contralateral molar served as a control. Results were analyzed with one-way ANOVA and with two-way ANOVA. RESULTS: Expression of all isoforms was increased in the tension side. iNOS and nNOS expression in the pressure side with cell-free zone was decreased but in the pressure side without cell-free zone was increased. The number of eNOS-positive cells did not change, but the intensity of the staining was visibly increased in the tension side. Duration of OTM changed only the pattern of nNOS expression. Osteocyte NOS expression did not change significantly in response to OTM. CONCLUSIONS: All NOS isoforms are involved in OTM with different expression patterns between tension and pressure sides, with nNOS being more involved in early OTM events. NOS expression did not change in osteocytes, suggesting that PDL cells rather than osteocytes are the mechanosensors in early OTM events with regard to NO signaling.
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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 | 0.000 | 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".