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Record W2044247178 · doi:10.2319/050808-252.1

Expression of Nitric Oxide Synthases in Orthodontic Tooth Movement

2008· article· en· W2044247178 on OpenAlexafffund
Dorrin Nilforoushan, Morris F. Manolson

Bibliographic record

VenueThe Angle Orthodontist · 2008
Typearticle
Languageen
FieldMedicine
TopicNitric Oxide and Endothelin Effects
Canadian institutionsUniversity of Toronto
FundersUniversity of TorontoOntario Innovation Trust
KeywordsNitric oxideOrthodonticsNitric oxide synthaseDentistryMedicineChemistryInternal medicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.032
GPT teacher head0.272
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations32
Published2008
Admission routes2
Has abstractyes

Explore more

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