Long-term upregulation of cortical glutamatergic AMPA receptors in a mouse model of chronic visceral pain
Bibliographic record
Abstract
BACKGROUND: Irritable bowel syndrome (IBS) is one of the most common functional gastrointestinal disorders and it causes long-lasting visceral pain and discomfort. AMPA receptor mediated long-term potentiation (LTP) has been shown to play a critical role in animal models of neuropathic and inflammatory pain. No report is available for central changes in the ACC of mice with chronic visceral pain. RESULTS: In this study, we used integrative methods to investigate potential central plastic changes in the anterior cingulate cortex (ACC) of a visceral pain mouse model induced by intracolonic injection of zymosan. We found that visceral pain induced an increased expression of AMPA receptors (at the post synapses) in the ACC via an enhanced trafficking of the AMPA receptors to the membrane. Both GluA1 and GluA2/3 subunits were significantly increased. Supporting biochemical changes, excitatory synaptic transmission in the ACC were also significantly enhanced. Microinjection of AMPA receptor inhibitor IEM1460 into the ACC inhibited visceral and spontaneous pain behaviors. Furthermore, we found that the phosphorylation of GluA1 at the Ser845 site was increased, suggesting that GluA1 phosphorylation may contribute to AMPA receptor trafficking. Using genetically knockout mice lacking calcium-calmodulin stimulated adenylyl cyclase subtype 1 (AC1), we found that AMPA receptor phosphorylation and its membrane trafficking induced by zymosan injection were completely blocked. CONCLUSIONS: Our results provide direct evidence for cortical AMPA receptors to contribute to zymosan-induced visceral and spontaneous pain and inhibition of AC1 activity may help to reduce chronic visceral pain.
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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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".