Spatial association of the Cav1.2 calcium channel with α<sub>5</sub>β<sub>1</sub>-integrin
Bibliographic record
Abstract
Engagement of α(5)β(1)-integrin by fibronectin (FN) acutely enhances Cav1.2 channel (Ca(L)) current in rat arteriolar smooth muscle and human embryonic kidney cells (HEK293-T) expressing Ca(L). Using coimmunoprecipitation strategies, we show that coassociation of Ca(L) with α(5)- or β(1)-integrin in HEK293-T cells is specific and depends on cell adhesion to FN. In rat arteriolar smooth muscle, coassociations between Ca(L) and α(5)β(1)-integrin and between Ca(L) and phosphorylated c-Src are also revealed and enhanced by FN treatment. Using site-directed mutagenesis of Ca(L) heterologously expressed in HEK293-T cells, we identified two regions of Ca(L) required for these interactions: 1) COOH-terminal residues Ser(1901) and Tyr(2122), known to be phosphorylated by protein kinase A (PKA) and c-Src, respectively; and 2) two proline-rich domains (PRDs) near the middle of the COOH terminus. Immunofluorescence confocal imaging revealed a moderate degree of wild-type Ca(L) colocalization with β(1)-integrin on the plasma membrane. Collectively, our results strongly suggest that 1) upon ligation by FN, Ca(L) associates with α(5)β(1)-integrin in a macromolecular complex including PKA, c-Src, and potentially other protein kinases; 2) phosphorylation of Ca(L) at Y(2122) and/or S(1901) is required for association of Ca(L) with α(5)β(1)-integrin; and 3) c-Src, via binding to PRDs that reside in the II-III linker region and/or the COOH terminus of Ca(L), mediates current potentiation following α(5)β(1)-integrin engagement. These findings provide new evidence for how interactions between α(5)β(1)-integrin and FN can modulate Ca(L) entry and consequently alter the physiological function of multiple types of excitable 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 | 0.000 |
| 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".