Toll-Like Receptor 4 in the Rat Caudal Medulla Mediates Tooth Pulp Inflammatory Pain
Bibliographic record
Abstract
The aims of this study were to investigate if Toll-like receptor 4 (TLR4) is expressed in the medullary dorsal horn (MDH) and if medullary application of a TLR4 antagonist (lipopolysaccharides from Rhodobacter sphaeroides, LPS-RS) can attenuate changes in nociceptive sensorimotor responses or TLR4 expression that might be evoked by mustard oil (MO) application to the right maxillary first molar tooth pulp. Of 41 adult male Sprague-Dawley rats used in the study, 23 received intrathecal application of the TLR4 antagonist LPS-RS (25 μg/10 μl; LPS-RS group) or isotonic saline (10 μl; vehicle control group) 10 min before pulpal application of MO (95%; 0.2µl). Bilateral electromyographic (EMG) activities of the anterior digastric and masseter muscles were recorded continuously before and until 15 min after the MO application to the pulp. In 6 of these 23 rats and an additional 18 rats, the caudal medulla containing the ipsilateral and contralateral MDH was removed after euthanasia for subsequent Western Blot analysis of TLR4 expression in LPS-RS (n= 8) and vehicle (n=8) groups and a naïve group (n=8). The % change from baseline in the MO-evoked EMG activities within the anterior digastric muscles were significantly smaller in the LPS-RS group than the control group (two -way ANOVA, post-hoc Bonferroni, P ˂ 0.0001). Western Blot analysis revealed similar levels of TLR4 expression in the caudal medulla of the naïve, vehicle and LPS-RS groups. These novel findings suggest that TLR4 signaling in the caudal medulla may mediate MO-induced acute dental inflammatory pain in rats.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".