Transcriptomic Changes Triggered by Hypoxia: Evidence for HIF-1α -Independent, [Na+]i/[K+]i-Mediated, Excitation-Transcription Coupling
Bibliographic record
Abstract
This study examines the relative impact of canonical hypoxia-inducible factor-1alpha- (HIF-1α and Na+i/K+i-mediated signaling on transcriptomic changes evoked by hypoxia and glucose deprivation. Incubation of RASMC in ischemic conditions resulted in ∼3-fold elevation of [Na+]i and 2-fold reduction of [K+]i. Using global gene expression profiling we found that Na+,K+-ATPase inhibition by ouabain or K+-free medium in rat aortic vascular smooth muscle cells (RASMC) led to the differential expression of dozens of genes whose altered expression was previously detected in cells subjected to hypoxia and ischemia/reperfusion. For further investigations, we selected Cyp1a1, Fos, Atf3, Klf10, Ptgs2, Nr4a1, Per2 and Hes1, i.e. genes possessing the highest increments of expression under sustained Na+,K+-ATPase inhibition and whose implication in the pathogenesis of hypoxia was proved in previous studies. In ouabain-treated RASMC, low-Na+, high-K+ medium abolished amplification of the [Na+]i/[K+]i ratio as well as the increased expression of all tested genes. In cells subjected to hypoxia and glucose deprivation, dissipation of the transmembrane gradient of Na+ and K+ completely eliminated increment of Fos, Atf3, Ptgs2 and Per2 mRNAs and sharply diminished augmentation expression of Klf10, Edn1, Nr4a1 and Hes1. In contrast to low-Na+, high-K+ medium, RASMC transfection with Hif-1a siRNA attenuated increments of Vegfa, Edn1, Klf10 and Nr4a1 mRNAs triggered by hypoxia but did not impact Fos, Atf3, Ptgs2 and Per2 expression. Thus, our investigation demonstrates, for the first time, that Na+i/K+i-mediated, Hif-1α- -independent excitation-transcription coupling contributes to transcriptomic changes evoked in RASMC by hypoxia and glucose deprivation.
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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".