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Record W2143894546 · doi:10.1177/0022034512462397

ERK is Involved in Tooth-pressure-induced Fos Expression in Vc Neurons

2012· article· en· W2143894546 on OpenAlexafffund
Megumi Hasegawa, Masahiro Kondo, Issei Suzuki, Nobutaka Shimizu, Barry J. Sessle, Koichi Iwata

Bibliographic record

VenueJournal of Dental Research · 2012
Typearticle
Languageen
FieldMedicine
TopicPain Mechanisms and Treatments
Canadian institutionsCanada Research ChairsUniversity of TorontoUniversity of New Brunswick
FundersCanadian Institutes of Health ResearchCanada Research ChairsNihon University
KeywordsMAPK/ERK pathwaySpinal trigeminal nucleusNociceptionChemistrySpinal cordNucleusNoxious stimulusc-FosMicrogliaMedicineNeuroscienceKinaseCell biologyInternal medicineInflammationBiologyGene expressionReceptor

Abstract

fetched live from OpenAlex

Discomfort and pain encountered during orthodontic treatment are major problems for patients, but the details of the underlying neural processes and molecular mechanisms are not well-understood. Here we show that noxious tooth mechanical pressure induced by orthodontic elastics resulted in a rapid and transient activation of extracellular signal-regulated protein kinase (ERK) in the trigeminal spinal subnucleus interpolaris and caudalis transition zone (Vi/Vc), trigeminal spinal subnucleus caudalis (Vc), and upper cervical spinal cord (Vc/C2). The phosphorylated ERK (pERK) was observed in neurons but not in astroglia and microglia. Single-plane scanning analysis indicated that the pERK was localized to the nucleus of Vc neurons. In addition, the tooth mechanical pressure led to Fos expression in the pERK-positive Vc neurons that would be suppressed by intrathecal administration of an MEK1/2 inhibitor (PD98059). Taken together, these findings suggest that activation of the ERK signaling cascade following noxious mechanical pressure on the teeth regulates Fos expression in Vc neurons and may thereby contribute to pain associated with orthodontic treatment.

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)0.002
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 score0.159
Threshold uncertainty score0.377

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.151
GPT teacher head0.441
Teacher spread0.290 · 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

Citations20
Published2012
Admission routes2
Has abstractyes

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