Endothelial Cells Negatively Modulate Reactive Oxygen Species Generation in Vascular Smooth Muscle Cells
Bibliographic record
Abstract
In intact vessels, endothelial cells (ECs) and vascular smooth muscle cells (VSMCs) act as an integrated system, possibly through reactive oxygen species (ROS). Using a coculture system we tested whether ECs modulate VSMC redox status by regulating activity of NAD(P)H oxidase and antioxidants. VSMC production of O(2)(*-), H(2)O(2), and NO was assessed using fluoroprobes and amplex-red. NAD(P)H oxidase subunit expression and oxidase activity were determined by Western blotting and chemiluminescence, respectively. Expression of thioredoxin, SOD, growth signaling pathways (PCNA, p21cip1, CDK4, ERK1/2, p38MAPK) was evaluated by immunoblotting. Thioredoxin activity was assessed by the insulin disulfide reduction assay. In cocultured conditions, VSMC ROS production was reduced by approximately 50% without changes in NAD(P)H oxidase expression/activity versus monoculture (P<0.05). This was associated with decreased cell growth (P<0.05). Expression of Cu/Zn SOD and thioredoxin was increased in coculture versus monoculture VSMCs (P<0.01). Pretreatment of ECs with L-NAME (NOS inhibitor), NS-398 (Cox2 inhibitor), and HET0016 (20-HETE inhibitor) did not influence VSMC ROS formation, whereas CDNB, thioredoxin reductase inhibitor, abolished ROS modulating effects of ECs. These findings indicate that in a coculture system recapitulating intact vessels, ECs negatively regulate ROS production in VSMCs through thioredoxin upregulation. Functionally this is associated with growth inhibition. The modulatory actions of ECs are independent of NOS/NO, Cox2, and HETE and do not involve NAD(P)H oxidase. Our data identify novel mechanisms whereby ECs protect against VSMC oxidative stress, a process that may be important in maintaining vascular integrity.
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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 | 0.001 |
| 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".