Enhanced Neurokinin‐1 Receptor Expression Is Associated with Human Dental Pulp Inflammation and Pain Severity
Bibliographic record
Abstract
Substance P (SP) is a peptide involved in many biological processes, including nociception and inflammation. SP has a high affinity for its receptor neurokinin‐1 (NK‐1R). SP/NK‐1R complex plays a major role in the interactions going on during the onset of dental pain and inflammation. Objective . To identify the expression of NK‐1R in healthy and inflamed human dental pulp, as well as to identify any association with severity of dental pain. Methods . This case‐control study included ten irreversibly inflamed samples of dental pulp, which were extirpated from patients presenting with chief complaint of dental pain due to caries. Ten healthy pulps, extirpated from those teeth which were indicated for extraction due to orthodontic reasons, were used as the control group. Visual analog scale (VAS) and modified McGill Pain Questionnaire were used to assess the characteristic and severity of pain. Immunohistochemical study was performed using monoclonal antibodies against NK‐1R. Results . The results showed that the NK‐1R was expressed intensely in patients with higher pain score. The mean pain score in cases was 7.0 ± 2.0. The healthy dental pulps had negative or mild NK‐1R staining of +1 intensity. The NK‐1R score in cases was 2.4 ± 0.516 and 0.2 ± 0.4216 in controls. There was significant difference in NK‐1R score between both groups ( p value <0.05). There was a strong positive correlation between the pain score and NK‐1R expression score. As the pain increased, the NK‐1R expression score was also increased (0.95 ∗∗ , p value 0.000). Conclusions . NK‐1R is overexpressed in inflamed dental pulp. SP/NK‐1R modulation may provide a novel approach for the treatment of pulpal inflammation and pain.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 teacher head, 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".