Enhancing KCC2 function counteracts morphine-induced hyperalgesia
Bibliographic record
Abstract
Abstract Morphine-induced hyperalgesia (MIH) is a severe adverse effect accompanying repeated morphine treatment, causing a paradoxical decrease in nociceptive threshold. Previous reports associated MIH with a decreased expression of the Cl− extruder KCC2 in the superficial dorsal horn (SDH) of the spinal cord, weakening spinal GABAA/glycine-mediated postsynaptic inhibition. Here, we tested whether the administration of small molecules enhancing KCC2, CLP257 and its pro-drug CLP290, may counteract MIH. MIH was typically expressed within 6–8 days of morphine treatment. Morphine-treated rats exhibited decreased withdrawal threshold to mechanical stimulation and increased vocalizing behavior to subcutaneous injections. Chloride extrusion was impaired in SDH neurons measured as a depolarizing shift in EGABA under Cl− load. Delivering CLP257 to spinal cord slices obtained from morphine-treated rats was sufficient to restore Cl− extrusion capacity in SDH neurons. In vivo co-treatment with morphine and oral CLP290 prevented membrane KCC2 downregulation in SDH neurons. Concurrently, co-treatment with CLP290 significantly mitigated MIH and acute administration of CLP257 in established MIH restored normal nociceptive behavior. Our data indicate that enhancing KCC2 activity is a viable therapeutic approach for counteracting MIH. Chloride extrusion enhancers may represent an effective co-adjuvant therapy to improve morphine analgesia by preventing and reversing MIH.
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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) | 0.001 | 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".