Involvement of Peripheral Ionotropic Glutamate Receptors in Orofacial Thermal Hyperalgesia in Rats
Bibliographic record
Abstract
BACKGROUND: The purpose of the present study was to elucidate the mechanisms that may underlie the sensitization of trigeminal spinal subnucleus caudalis (Vc) and upper cervical spinal cord (C1-C2) neurons to heat or cold stimulation of the orofacial region following glutamate (Glu) injection. RESULTS: Glu application to the tongue or whisker pad skin caused an enhancement of head-withdrawal reflex and extracellular signal-regulated kinase (ERK) phosphorylation in Vc-C2 neurons. Head-withdrawal reflex and ERK phosphorylation were also enhanced following cold stimulation of the tongue but not whisker pad skin in Glu-injected rats, and the head-withdrawal reflex and ERK phosphorylation were enhanced following heat stimulation of the tongue or whisker pad skin. The enhanced head-withdrawal reflex and ERK phosphorylation after heat stimulation of the tongue or whisker pad skin, and those following cold stimulation of the tongue but not whisker pad skin were suppressed following ionotropic glutamate receptor antagonists administration into the tongue or whisker pad skin. Furthermore, intrathecal administration of MEK1/2 inhibitor PD98059 caused significant suppression of enhanced head-withdrawal reflex in Glu-injected rats, heat head-withdrawal reflex in the rats with Glu injection into the tongue or whisker pad skin and cold head-withdrawal reflex in the rats with Glu injection into the tongue. CONCLUSIONS: The present findings suggest that peripheral Glu receptor mechanisms may contribute to cold hyperalgesia in the tongue but not in the facial skin, and also contribute to heat hyperalgesia in the tongue and facial skin, and that the mitogen-activated protein kinase cascade in Vc-C2 neurons may be involved in these Glu-evoked hyperalgesic effects.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".