The heart‐rate‐reducing agent, ivabradine, reduces mechanical allodynia in a rodent model of neuropathic pain
Bibliographic record
Abstract
BACKGROUND: Peripheral nerve injury increases the excitability of primary sensory neurons. This triggers the onset of neuropathic pain and maintains its persistence. Because changes in hyperpolarization-activated cyclic nucleotide-gated cation (HCN) channels are implicated in this process, we examined the action of the heart-rate-reducing agent, ivabradine, a clinically approved HCN blocker, in the rat chronic constriction injury (CCI) model of neuropathic pain. METHODS: The effects of ivabradine on mechanical allodynia were assessed using von Frey filaments, and the effects on cardiovascular parameters were monitored by telemetry. Ivabradine block of HCN channels in dorsal root ganglion neurons was confirmed by whole-cell recording. RESULTS: In rats subject to CCI, ivabradine (6 mg/kg by gavage twice a day) significantly reduced mechanical allodynia. Cumulative effects were seen with twice daily oral administration over a 4-day period. Allodynia returned 4 days after the final drug dose. Mean arterial pressure was maintained and only a 15% pharmacological reduction in heart rate was observed. There was no cumulative effect of ivabradine on cardiovascular parameters. CONCLUSION: Because ivabradine is effective at an oral dose that produces only moderate pharmacological heart rate reduction, and this is known to be well tolerated in a clinical context, these results underline its possible use in neuropathic pain management.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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".