Heteromultimeric TRPC6-TRPC7 Channels Contribute to Arginine Vasopressin-Induced Cation Current of A7r5 Vascular Smooth Muscle Cells
Bibliographic record
Abstract
The molecular identity of receptor-operated, nonselective cation channels (ROCs) of vascular smooth muscle (VSM) cells is not known for certain. Mammalian homologues of the Drosophila canonical transient receptor potential channels (TRPCs) are possible candidates. This study tested the hypothesis that heteromultimeric TRPC channels contribute to ROC current of A7r5 VSM cells activated by [Arg(8)]-vasopressin. A7r5 cells expressed transcripts encoding TRPC1, TRPC4beta, TRPC6, and TRPC7. TRPC4, TRPC6, and TRPC7 protein expression was confirmed by immunoblotting and association of TRPC6 with TRPC7, but not TRPC4beta, was detected by coimmunoprecipitation. The amplitude of arginine vasopressin (AVP)-induced ROC current was suppressed by dominant-negative mutant TRPC6 (TRPC6(DN)) but not TRPC5 (TRPC5(DN)) mutant subunit expression. These data indicate a role for TRPC6- and/or TRPC7-containing channels and rule a more complex subunit composition including TRPC1 and TRPC4. Increasing extracellular Ca(2+) concentration ([Ca(2+)](o)) from 0.05 to 1 mmol/L suppressed currents owing to native, TRPC7, and heteromultimeric TRPC6-TRPC7 channels, but not TRPC6 current, which was slightly enhanced. The relative changes in native and heteromultimeric TRPC6-TRPC7 current amplitudes for [Ca(2+)](o) between approximately 0.01 and 1 mmol/L were identical, but the changes in homomultimeric TRPC6 and TRPC7 currents were significantly less and greater, respectively, compared with the native channels. Taken together, the data provide biochemical and functional evidence supporting the view that heteromultimeric TRPC6-TRPC7 channels contribute to receptor-activated, nonselective cation channels of A7r5 VSM cells.
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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 | 0.001 |
| 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".