Glutamate attenuates nitric oxide release from isolated trigeminal ganglion satellite glial cells
Bibliographic record
Abstract
Abstract Background/aims Elevated concentrations of nitric oxide (NO) and glutamate (Glu) in the trigeminal ganglion (TG) may contribute to the development and maintenance of migraine headache. The role of satellite glial cells (SGC) and their pattern of substance release in relation to the pathophysiology of migraine are currently under investigation. In the present study, we investigated the release of NO from isolated trigeminal SGCs and its modulation by Glu. Methods SGCs from the TG of adult male Sprague-Dawley rats ( n = 8) were isolated and maintained in culture until used. SGCs were treated with graded concentrations of Glu (0, 10, 100, 1000 μM) and samples were withdrawn after 48 h of incubation. In subsequent experiments, SGCs were treated with vehicle medium, 10 μM forskolin (FSK) alone, or 10 μM FSK in conjunction with 100 μM Glu and incubated for 48 h. The NO concentration was determined using the Griess Reagent System and data was subjected to a one-way repeated measures ANOVA analysis, where p <0.05 was considered statistically significant. All experimental procedures were performed at minimum in triplicate. Results The concentration of NO was 3.59 ± 0.04 M under baseline conditions. Application of 10 or 100 μM Glu resulted in a significant drop in NO concentration (2.92 ± 0.017 μM and 2.83 ± 0.012 M, respectively) compared to baseline, whereas treatment with 1000 μM Glu did not significantly alter NO release. Treatment of SGCs with 10 μM FSK significantly increased NO release (to 125.94 ± 3.90% of baseline) compared to baseline. Coapplication of 10 M FSK with 100 M Glu significantly decreased FSK-induced NO release (83.73 ± 2.29% of baseline), compared to both FSK-mediated NO release and baseline levels. Conclusion These findings suggest that one mechanism by which SGCs protect the TG from elevated Glu concentrations that may occur in response to prolonged noxious stimulation is to reduce the release of NO.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".