CCR2 Receptor Ligands Inhibit Cav3.2 T-Type Calcium Channels
Bibliographic record
Abstract
Monocyte chemoattractant protein-1 (MCP-1) is a cytokine known to be involved in the recruitment of monocytes to sites of injury. MCP-1 activates the chemokine (C-C motif) receptor 2 (CCR2), a seven-transmembrane helix G protein-coupled receptor that has been implicated in inflammatory pain responses. Here we show that MCP-1 mediates activation of the CCR2 receptor and inhibits coexpressed N-type calcium channels in tsA-201 cells via a voltage-dependent pathway. Moreover, MCP-1 inhibits Ca(v)3.2 calcium channels, but not other members of the Cav3 calcium channel family, with nanomolar affinity. Unlike in N-type channels, this modulation does not require CCR2 receptor activation and seems to involve a direct action of the ligand on the channel. Whole-cell T-type calcium currents in acutely dissociated dorsal root ganglia neurons are effectively inhibited by MCP-1, consistent with the notion that these cells express Ca(v)3.2. The effects of MCP-1 were eliminated by heat denaturation. Furthermore, they were sensitive to the application of the divalent metal ion chelator diethylenetriaminepentaacetic acid, suggesting the possibility that metal ions may act as a cofactor. Finally, small organic CCR2 receptor antagonists inhibit Ca(v)3.2 and other members of the T-type channel family with micromolar affinity. Our findings provide novel avenues for the design of small organic inhibitors of T-type calcium channels for the treatment of pain and other T-type channel linked disorders.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".