Enhancing K–Cl co-transport restores normal spinothalamic sensory coding in a neuropathic pain model
Bibliographic record
Abstract
Neuropathic pain is a widespread and highly debilitating condition commonly resulting from injury to the nervous system, one main sequela of which is tactile allodynia, a pain induced by innocuous mechanical stimulation of the skin. Yet, the cellular mechanisms and neuronal substrates underlying this pathology have remained elusive. We studied this by quantifying and manipulating behavioural and neuronal nociceptive thresholds in normal and pathological pain conditions. We found that, in both control rats and those with pain hypersensitivity induced by nerve injury, the nociceptive paw withdrawal threshold matches the response threshold of nociceptive-specific deep spinothalamic tract neurons. In contrast, wide dynamic range or multimodal spinothalamic tract neurons showed no such correlation nor any change in properties after nerve injury. Disrupting Cl(-) homeostasis by blocking K(+)-Cl(-) co-transporter 2 replicated the decrease in threshold of nociceptive-specific spinothalamic tract neurons without affecting wide dynamic range spinothalamic tract cells. Accordingly, only combined blockade of both GABAA- and glycine-gated Cl(-) channels replicated the effects of nerve injury or K(+)-Cl(-) co-transporter 2 blockade to their full extent. Conversely, rescuing K(+)-Cl(-) co-transporter 2 function restored the threshold of nociceptive-specific spinothalamic tract neurons to normal values in animals with nerve injury. Thus, we unveil a tight association between tactile allodynia and abnormal sensory coding within the normally nociceptive-specific spinothalamic tract. Thus allodynia appears to result from a switch in modality specificity within normally nociceptive-specific spinal relay neurons rather than a change in gain within a multimodal ascending tract. Our findings identify a neuronal substrate and a novel cellular mechanism as targets for the treatment of pathological 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 | 0.001 | 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".