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Record W2150999391 · doi:10.1002/nbm.962

MRS assessment of glutamate clearance in a novel masticatory muscle pain model

2005· article· en· W2150999391 on OpenAlexaff
Giulio Gambarota, M.E.P. Philippens, Brian E. Cairns, Xiaoqing Dong, W.K.J. Renema, Arend Heerschap

Bibliographic record

VenueNMR in Biomedicine · 2005
Typearticle
Languageen
FieldMedicine
TopicAdvanced MRI Techniques and Applications
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Dental and Craniofacial Research
KeywordsGlutamate receptorMasseter muscleMasticatory forceNerve fiberSensitizationAnesthesiaElectrophysiologyChemistryMedicineAnatomyInternal medicineNeuroscienceBiologyDentistryReceptor

Abstract

fetched live from OpenAlex

The injection of 1.0 M glutamate into the masseter (jaw-closer) muscle results in a short period of muscle pain (5-10 min) and a prolonged period of mechanical sensitization (> 30 min). It is unclear, however, whether there is a temporal relationship between intramuscular glutamate concentration and either muscle pain or mechanical sensitization. In the present study, (1)H MRS and electrophysiological recording of masticatory muscle nerve fibers were performed in order to monitor glutamate clearance and nerve fiber activity, respectively, after injection of glutamate into rat masticatory muscles. Glutamate signal amplitude was found to decay rapidly (half-life t 1/2 = 108 +/- 42 s), and became indistinguishable from the baseline 10 min after the injection. Glutamate-evoked nerve fiber activity was also found to decay rapidly (t 1/2 = 76 +/- 28 s). These results suggest that glutamate clearance correlates well with the time course of glutamate-evoked muscle pain fiber discharge.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.809
Threshold uncertainty score0.419

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 head0.025
GPT teacher head0.364
Teacher spread0.339 · 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 designSimulation or modeling
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

Citations11
Published2005
Admission routes1
Has abstractyes

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