Role of NF-κB in Flow-Induced Vascular Remodeling
Bibliographic record
Abstract
Vascular remodeling associated with increased blood flow involves reactive oxygen species (ROS)-dependent activation of matrix metalloproteinases (MMPs). To investigate the potential role of NF-kappaB in this process, human umbilical vein endothelial cells were subjected to different flow conditions during a 24-h period. Normal (15 dynes/cm(2)) and high (30 dynes/cm(2)) shear stress induced IkappaBalpha degradation and NF-kappaB p65 phosphorylation, and activated MMP-2 and MMP-9. These effects were blunted in cells incubated with the NF-kappaB inhibitor pyrrolidine dithio-carbamate (PDTC). In mice, creation of a carotid artery-jugular vein arteriovenous fistula (AVF) increased carotid blood flow sixfold, triggering the increase in carotid diameter from 459 +/- 8 microm (before AVF) to 531 +/- 13 and 669 +/- 21 microm (7 and 21 days after AVF). ROS production and NF-kappaB activity were enhanced in fistulated carotids, but only the latter was blocked by PDTC, although PDTC blocked ROS production in vitro. In PDTC-treated mice, changes in carotid caliber and shear stress matched controls at 7 days, but carotids enlarged only marginally thereafter, reaching only 578 +/- 8 microm at 21 days (p < 0.01 vs. untreated). Similarly, both MMP-9 expression and activity were abrogated by PDTC at 3 weeks. Hence, induction of NF-kappaB by shear stress contributes to MMP induction and allows long-term flow-induced vascular enlargement.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".