Identification of interleukin-1 beta as a key mediator in the upregulation of Cav3.2–USP5 interactions in the pain pathway
Bibliographic record
Abstract
Abstract: We recently reported that nerve injury or peripheral inflammation triggers an upregulation of the deubiquitinase, USP5 in mouse dorsal root ganglion and spinal dorsal horn. This leads to dysregulated ubiquitination of Cav3.2 T-type calcium channels, thus increasing Cav3.2 channel plasma membrane expression and nociceptive signaling in the primary afferent pain pathway. This phenomenon could be recapitulated by noninvasive, optogenetic activation of transient receptor potential vanilloid-1–expressing nociceptors, indicating that neuronal activity is a key player in this process. Given the relevance of the pro-inflammatory cytokine interleukin-1 beta in many forms of pathological pain, we hypothesized that interleukin-1 beta may be a critical cofactor required to drive upregulation of interactions between USP5 and Cav3.2 channels. Here, we report that gene expression, as well as protein levels for interleukin-1 beta and the endogenous interleukin-1 receptor-I antagonist, IL-1Ra are unaltered following conditioning stimulation of optogenetically targeted cutaneous nociceptors, indicating that neuronal activity is not a driver of interleukin-1 beta signaling. In contrast, co-immunoprecipitation experiments revealed that intrathecal administration of interleukin-1 beta in wild-type mice led to an increase in the interaction between USP5 and Cav3.2 in the spinal dorsal horn. Moreover, disruption of the interaction between USP5 and Cav3.2 with TAT peptides suppressed acute nocifensive responses produced by interleukin-1 beta, which was similar to that achieved by elimination of T-type channel activity with the channel blockers, mibefradil, or TTA-A2. Finally, this upregulation could be maintained in dorsal root ganglion neuron cultures exposed overnight to interleukin-1 beta, while the copresence of interleukin-1 receptor antagonist or the dampening of neuronal cell activity with tetrodotoxin attenuated this response. Altogether, our findings identify interleukin-1 beta as an upstream trigger for the upregulation of interactions between USP5 and Cav3.2 channels in the pain pathway, presumably by triggering increased firing activity in afferent fibers.
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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) | 0.001 | 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".