Loss of STEP61 couples disinhibition to N-methyl-d-aspartate receptor potentiation in rodent and human spinal pain processing
Bibliographic record
Abstract
Dysregulated excitability within the spinal dorsal horn is a critical mediator of chronic pain. In the rodent nerve injury model of neuropathic pain, BDNF-mediated loss of inhibition (disinhibition) gates the potentiation of excitatory GluN2B N-methyl-d-aspartate receptor (NMDAR) responses at lamina I dorsal horn synapses. However, the centrality of this mechanism across pain states and species, as well as the molecular linker involved, remain unknown. Here, we show that KCC2-dependent disinhibition is coupled to increased GluN2B-mediated synaptic NMDAR responses in a rodent model of inflammatory pain, with an associated downregulation of the tyrosine phosphatase STEP61. The decreased activity of STEP61 is both necessary and sufficient to prime subsequent phosphorylation and potentiation of GluN2B NMDAR by BDNF at lamina I synapses. Blocking disinhibition reversed the downregulation of STEP61 as well as inflammation-mediated behavioural hypersensitivity. For the first time, we characterize GluN2B-mediated NMDAR responses at human lamina I synapses and show that a human ex vivo BDNF model of pathological pain processing downregulates KCC2 and STEP61 and upregulates phosphorylated GluN2B at dorsal horn synapses. Our results demonstrate that STEP61 is the molecular brake that is lost following KCC2-dependent disinhibition and that the decrease in STEP61 activity drives the potentiation of excitatory GluN2B NMDAR responses in rodent and human models of pathological pain. The ex vivo human BDNF model may thus form a translational bridge between rodents and humans for identification and validation of novel molecular pain targets.
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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 | 0.000 |
| 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 | 0.000 |
| 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".