The Tao of IGF-1: Insulin-Like Growth Factor Receptor Activation Increases Pain by Enhancing T-Type Calcium Channel Activity
Bibliographic record
Abstract
T-type calcium channels are important players in the transmission of pain signals in the primary afferent pathway. Indeed, inhibiting or depleting T-type calcium channels in dorsal root ganglion (DRG) neurons mediates analgesia. Conversely, nerve injury or peripheral inflammation have been shown to induce T-type calcium channel activity in DRG neurons, and this in turn has been linked to the development of chronic pain states. The mechanisms that underlie this enhancement of T-type channels remain incompletely understood and may include changes in channel stability in the plasma membrane or alterations in channel function. In this issue of Science Signaling, Zhang and colleagues identify a cell signaling pathway that potently regulates T-type calcium channel activity in afferent neurons and link this process to pain hypersensitivity. Specifically, they show that insulin-like growth factor-1 receptors in DRG neurons mediate a protein kinase C α (PKCα)-dependent enhancement of T-type calcium currents and that interfering with this pathway reduces both mechanical and thermal pain hypersensitivity in rodents. Targeting this process offers a new avenue for developing pain therapeutics.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".