Excitatory amino acid concentrations increase in the spinal cord dorsal horn after repeated intramuscular injection of acidic saline
Bibliographic record
Abstract
Chronic muscle pain is common and often difficult to treat. In this study, we further characterize a model of chronic muscle pain induced by repeated intramuscular injection of acidic saline. Two injections of acid into muscle separated by 5 days result in secondary mechanical hyperalgesia that lasts for up to 4 weeks. Blockade of spinal NMDA receptors prior to the second injection intramuscular acid injection delays the onset of hyperalgesia, where as the maintenance phase of hyperalgesia, evaluated 1 week after the second intramuscular injection, is dependent on activation of spinal AMPA/kainate and NMDA receptors. In order to determine if behavioral hyperalgesia and glutamate receptor involvement are associated with increased concentrations of excitatory amino acids (EAA), we utilized microdialysis to evaluate extracellular glutamate and aspartate concentrations in the spinal dorsal horn during the first and second intramuscular acid injections, and 1 week after the development of mechanical hyperalgesia. The second intramuscular injection evoked a calcium-dependent increase in both spinal glutamate and aspartate concentrations. Glutamate concentrations within the dorsal horn were also increased 1 week after the second acid injection. Our data suggest increased release of spinal EAAs in the dorsal horn contributes to the development and maintenance of hyperalgesia.
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 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) | 0.001 | 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 | 0.001 | 0.001 |
| 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 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".