Proteome Analysis and Functional Expression Identify Mortalin as an Antiapoptotic Gene Induced by Elevation of [Na <sup>+</sup> ] <sub>i</sub> /[K <sup>+</sup> ] <sub>i</sub> Ratio in Cultured Vascular Smooth Muscle Cells
Bibliographic record
Abstract
Apoptosis of vascular smooth muscle cells (VSMCs) plays an important role in remodeling of vessel walls, one of the major determinants of long-term blood pressure elevation and an independent risk factor for cardiovascular morbidity and mortality. Recently, we have found that apoptosis in cultured VSMCs can be inhibited by inversion of the intracellular [Na+]/[K+] ratio after the sustained blockage of the Na+,K+-ATPase by ouabain. To understand the mechanism of ouabain action, we analyzed subsets of hydrophilic and hydrophobic VSMC proteins from control and ouabain-treated cells by 2-dimensional electrophoresis. Ouabain treatment led to overexpression of numerous soluble and hydrophobic cellular proteins. Among proteins that showed the highest level of ouabain-induced expression, we identified mortalin (also known as GRP75 or PBP-74), a member of the heat shock protein 70 (HSP70) superfamily and a marker for cellular mortal and immortal phenotypes. Northern and Western blotting and immunocytochemistry all have confirmed that treatment of VSMCs with ouabain results in potent induction of mortalin expression. Transient transfection of cells with mortalin cDNA led to at least a 6-hour delay in the development of apoptosis after serum deprivation. The expression of tumor suppressor gene, p53, in mortalin-transfected cells was delayed to the same extent, and the expressed protein showed abnormal perinuclear distribution, suggesting that p53 is retained and inactivated by mortalin. Our studies therefore define a new [Na+]i/[K+]i-responsive signaling pathway that may play an important role in the regulation of programmed cell death in VSMCs.
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 | 0.000 |
| 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".