Nociceptor clock genes control excitability and pain perception in a sex and time-dependent manner
Bibliographic record
Abstract
ABSTRACT Nociception is critical for pain perception and survival and begins with the activation of nociceptors, specialized sensory neurons located in the dorsal root ganglia (DRGs). Both sex and circadian rhythms, governed by clock genes, seem to play a significant role in modulating pain perception. However, the potential interaction between circadian rhythms and sex differences in nociception at the peripheral level has been largely overlooked. Here, we first report that DRGs from mice express clock genes in a time- and sex-dependent manner. Using whole-cell recordings in whole-mounted DRGs and optogenetic stimulation of Nav1.8-expressing neurons, we demonstrate that male nociceptors exhibit reduced excitability during the night, while female nociceptor excitability remains stable across time points. Disruption of the core clock gene Bmal1 in Nav1.8-expressing neurons not only diminished nociceptor activity but also abolished the nighttime reduction in heat sensitivity, highlighting a pivotal role for the molecular clock in regulating nociception. Transcriptomic analyses, voltage-clamp recordings, and pharmacological experiments identified the voltage-gated chloride channel ClC-2, controlled by Bmal1 , as a key mediator for the observed fluctuations in male nociceptor excitability. This work opens new avenues for chronobiology-inspired strategies in pain management tailored to sex-specific mechanisms.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".