In vivo recruitment by painful stimuli of AMPA receptor subunits to the plasma membrane of spinal cord neurons
Bibliographic record
Abstract
The persistent increase in pain sensitivity observed after injury, known as hyperalgesia, depends on synaptic plasticity in the pain pathway, particularly in the spinal cord. Several potential mechanisms have been proposed, including post-synaptic exocytosis of the AMPA subclass of glutamate receptors (AMPA-R), which is known to play a critical role in synaptic plasticity in the hippocampus. AMPA-R trafficking has been described in spinal neurons in culture but it is unknown if it can also occur in spinal neurons in vivo, or if it can be induced by natural painful stimulation. Here we have induced referred mechanical hyperalgesia in vivo by intracolonic instillation of capsaicin in mice and have observed a recruitment of GluR1 AMPA-R subunits to neuronal plasma membranes in the lumbar spinal cord. Intracolonic capsaicin induced a rapid (10 min) increase in GluR1, but not GluR2/3 in the synaptosomal membrane fraction which lasted at least 3 h and a decrease in GluR1 subunit in the cytosolic fraction. Capsaicin treatment also provoked CaMKII activation and pre-treatment with a specific CaMKII inhibitor prevented the GluR1 trafficking. Brefeldin-A, an antibiotic that inhibits exocytosis of proteins, not only prevented GluR1 trafficking to the membrane but also inhibited referred hyperalgesia in capsaicin-treated mice. Our results show that delivery of GluR1 AMPA receptor subunits to the cell membrane through a CaMKII activity-dependent exocytotic regulated pathway contributes to the development of hyperalgesia after a painful stimulus. We conclude that AMPA-R trafficking contributes to the synaptic strengthening induced in the pain pathway by natural stimulation.
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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 | 0.001 |
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".