Inhibition of hypoxia‐induced angiogenesis by cigarette smoke exposure: impairment of the HIF‐lalpha/VEGF pathway
Bibliographic record
Abstract
Smoking is a major risk factor for atherosclerotic diseases. However, the impact of cigarette smoke exposure on neovascularization that develops in response to tissue ischemia is unknown. Here we demonstrate that cigarette smoke extracts inhibit hypoxia-induced in vitro angiogenesis (matrigel assay) in human umbilical vascular endothelial cells. In vivo, mice exposed to cigarette smoke (MES) were shown to have a significant impairment of angiogenesis following surgically induced hindlimb ischemia. The reduced angiogenic response in MES was documented by Laser Doppler flow perfusion studies and capillary density analyses in ischemic hindlimbs. Inhibition of angiogenesis by cigarette smoke in vitro and in vivo was associated with a reduced expression of hypoxia-inducible factor-1alpha (HIF-1alpha) and vascular endothelial growth factor (VEGF) in hypoxic conditions. Administration of an adenoviral vector encoding for HIF-1alpha/VP16, a hybrid transcription factor that is stable in hypoxic and normoxic conditions, restored VEGF expression and completely reversed the cigarette smoke inhibition of angiogenesis in hypoxic conditions. Taken together, these results suggest that cigarette smoke exposure impairs angiogenesis by inhibiting VEGF through decreased expression of HIF-1alpha in hypoxic 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) | 0.000 | 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".