Proteomic‐based identification of upstream intermediates of Na+i,K+i‐independent death signaling triggered by interaction of cardiotonic steroids with alpha‐subunit of Na,K‐ATPase
Bibliographic record
Abstract
During the last decade, it was shown that side‐by‐side with a major role in regulation of Na + i /K + i ratio, interaction of the Na,K‐ATPase with ouabain and other cardiotonic steroids (CTS) triggers diverse Na + i ,K + i ‐ independent signaling involved in cell proliferation and death. Thus, we demonstrated that chronic exposure to CTS results in massive death of renal epithelial, vascular endothelial and colon epithelial (Caco‐2) cells via their interaction with Na,K‐ATPase α‐subunit but independently of elevation of [Na + ] i /[K + ] i ratio. We designed this study to identify upstream intermediates of this novel CTS‐induce Na + i ,K + i ‐ independent signaling pathway using proteomic‐based approaches. We used cell lysates from control and ouabain‐treated Caco‐2 cells for co‐immunoprecipitation with anti‐α1 Na,K‐ATPase antibodies following by separation with 2D‐PAGE. From comparative analyse we detected more than 20 proteins sports whose interaction with Na,K‐ATPase was triggered by ouabain. 18 proteins were identified by mass spectrometry, including 8 signaling proteins from superfamilies of glucocorticoid receptors, Ser/Thr protein kinases and 2C phosphatases, Src and Rho GTPases. The role of these proteins in ouabain‐induced Na + i , K + i ‐ independent cell death signaling is currently under investigation. Supported by grants from the Canadian Institute of Health Research and the Kidney Foundation of Canada .
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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".