The inhibition of Kir2.1 potassium channels depolarizes spinal microglial cells, reduces their proliferation, and attenuates neuropathic pain
Bibliographic record
Abstract
Spinal microglia change their phenotype and proliferate after nerve injury, contributing to neuropathic pain. For the first time, we have characterized the electrophysiological properties of microglia and the potential role of microglial potassium channels in the spared nerve injury (SNI) model of neuropathic pain. We observed a strong increase of inward currents restricted at 2 days after injury associated with hyperpolarization of the resting membrane potential (RMP) in microglial cells compared to later time-points and naive animals. We identified pharmacologically and genetically the current as being mediated by Kir2.1 ion channels whose expression at the cell membrane is increased 2 days after SNI. The inhibition of Kir2.1 with ML133 and siRNA reversed the RMP hyperpolarization and strongly reduced the currents of microglial cells 2 days after SNI. These electrophysiological changes occurred coincidentally to the peak of microglial proliferation following nerve injury. In vitro, ML133 drastically reduced the proliferation of BV2 microglial cell line after both 2 and 4 days in culture. In vivo, the intrathecal injection of ML133 significantly attenuated the proliferation of microglia and neuropathic pain behaviors after nerve injury. In summary, our data implicate Kir2.1-mediated microglial proliferation as an important therapeutic target in neuropathic pain.
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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 | 0.000 | 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 | 0.000 |
| 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".