Oxygen regulation of arterial smooth muscle cell proliferation and survival
Bibliographic record
Abstract
The purpose of this study was to determine if hypoxia elicits different proliferative and apoptotic responses in systemic arterial smooth muscle cells incubated under conditions that do or do not result in cellular ATP depletion and whether these effects are relevant to vascular remodeling in vivo. Gene expression profiling was used to identify potential regulatory pathways. In human aortic smooth muscle cells (HASMCs) incubated at 3% O(2), proliferation and progression through the G1/S interphase are enhanced. Incubation at 1% O(2) reduced proliferation, delayed G1/S transition, increased apoptotic cell death, and is associated with mitochondrial membrane depolarization and reduced cellular ATP levels. In aorta and mesenteric artery from rats exposed to hypoxia (10% O(2), 48 h), both proliferation and apoptosis are increased, as are medial nuclear density and smooth muscle cell content. Although nuclear levels of hypoxia-inducible factor 1-alpha (HIF-1alpha) are increased to a similar extent in HASMCs incubated at 1 and 3% O(2), expression of tumor protein p53, its transcriptional target p21, as well as their regulatory factors and downstream effectors, are differentially affected under these two conditions, suggesting that the bidirectional effects of hypoxia are mediated by this pathway. We conclude that hypoxia induces a state of enhanced cell turnover through increased rates of both smooth muscle cell proliferation and death. This confers the ability to remodel the vasculature in response to changing tissue metabolic needs while avoiding the accumulation of mutations that may lead to malignant transformation or the formation of abnormal vascular structures.
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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".