Human neutrophil peptides induce endothelial-monocyte interactions and accelerate foam cell formation
Bibliographic record
Abstract
Introduction. Atherosclerosis involves the coupling of inflammatory responses and dyslipidemia, but the underlying mechanisms by which inflammation contributes to atherosclerosis remains unclear. Human neutrophil peptides (HNP) released from activated neutrophils have demonstrated immune modulating effects. Hypothesis. HNP induce endothelial-monocyte interactions and accelerate foam cell formation. Methods. Human pulmonary artery endothelial cells were stimulated with HNP to assess adhesion and migration of monocytes in co-culture. THP-1 derived macrophages were stained for intracellular lipids after exposure to HNP and native low density lipoprotein. Results. HNP increased expression of inflammatory cytokines and adhesion molecules in all cell types studied. These were associated with an increase in adhesion, migration, and foam cell formation, which was abrogated using the reactive oxygen species scavenger super oxide dismutase. Conclusions. HNP can activate endothelial cells that leads to endothelial-monocyte interactions, and HNP induce foam cell formation through oxidative stress.
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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) | 0.003 | 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".