Ral-GTPase interacts with the β1 subunit of Na<sup>+</sup>/K<sup>+</sup>-ATPase and is activated upon inhibition of the Na<sup>+</sup>/K<sup>+</sup>pumpThis paper is one of a selection of papers published in this Special Issue, entitled The Cellular and Molecular Basis of Cardiovascular Dysfunction, Dhalla 70th Birthday Tribute.
Bibliographic record
Abstract
Na+/K+-ATPase functions as both an ion pump and a signal transducer. Cardiac glycosides partially inhibit Na+/K+-ATPase, causing activation of multiple interrelated growth pathways via the Na+/K+-ATPase/c-Src/epidermal growth factor receptor complex. Such pathways include Ras/MEK/ERK and Ral/RalGDS cascades, which can lead to cardiac hypertrophy. In search of novel Ral-GTPase binding proteins, we used RalB as the bait to screen a human testes cDNA expression library using the yeast 2-hybrid system. The results demonstrated that 1 of the RalB interacting clones represented the C-terminal region of the beta1 subunit of Na+/K+-ATPase. Further analysis using the yeast 2-hybrid system and full-length beta1 subunit of Na+/K+-ATPase confirmed the interaction with RalA and RalB. In vitro binding and pull-down assays demonstrated that the beta1 subunit of Na+/K+-ATPase interacts directly with RalA and RalB. Ral-GTP pull-down assays demonstrated that short-term ouabain treatment of A7r5 cells, a rat aorta smooth muscle cell line, caused activation of Ral GTPase. Maximal activation was observed 10 min after ouabain treatment. Ouabain-mediated Ral activation was inhibited upon the stimulation of Na+/K+-ATPase activity by Ang II. We propose that Ral GTPase is involved in the signal transducing function of Na+/K+-ATPase and provides a possible molecular mechanism connecting Ral to cardiac hypertrophy during diseased conditions.
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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) | 0.001 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".