The Effects of Neutrophil Extracellular Traps (NETs) on Endothelial Health and Function
Bibliographic record
Abstract
Background: Neutrophil extracellular traps (NETs) are intricate webs of extracellular DNA, citrullinated histones and granular protein that play an essential role in innate immunity. Dysregulation of NET formation has been implicated in acute kidney injury, lupus nephritis, and diabetic kidney disease. However, the mechanisms by which NETs contribute to kidney injury have yet to be fully elucidated. As the vasculature may represent a common pathogenic target, we examined the effect of NETs on endothelial cells in vitro and on ex vivo mesenteric artery function. Methods: The human promyelocytic cell line, HL-60, was used to generate neutrophil-like cells in vitro. Differentiation was induced by incubation with 1.25% dimethyl sulfoxide (DMSO) for 5 days. Differentiated cells were then stimulated with 500 nM phorbol 12-myristate 13-acetate (PMA) for 4 hours to induce NET formation. NETs were isolated from the cell culture medium by differential centrifugation. Cultured Human Umbilical Vein Endothelial Cells (HUVECs) were treated with the isolated NETs at 0.5-500 ng/ml for 24 hours. Cell viability and proliferative capacity were measured in the treated HUVECs using an XTT and BrdU assay, respectively. Second-order mouse mesenteric arteries were harvested and mounted to a wire myograph. Vessels were treated with the isolated NETs at 15 ng/mL for 30 minutes, after which we measured vascular relaxation during chemical stimulation with acetylcholine, to assess their effect on endothelium-dependent vasorelaxation. Results: NETs decreased HUVEC viability ˜2-fold at 5 ng/ml (P=<0.0001) and dose dependently decreased proliferative capacity from 0.5-500 ng/ml, with proliferation being decreased by ˜80% at 500 ng/ml. NETs also significantly impaired endothelium-dependent vasorelaxation, with relaxation being 43% lower in treated vessels at 10-6 M acetylcholine. This was reflected in smaller pD2 values in NET-treated vessels (5.55 vs 6.72 in control vessels) (p=0.0284). Conclusions: These results show that NETs induce endothelial cell injury in vitro and impair endothelial function in intact vessels. Identifying the underlying mechanisms of NET-induced endothelial injury may help further understand their contribution to kidney and cardiovascular injury.
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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".