Angiopoietin 1 release from human neutrophils is independent from neutrophil extracellular traps (NETs)
Bibliographic record
Abstract
BACKGROUND: Neutrophils induce the synthesis and release of angiopoietin 1 (Ang1), a cytosolic growth factor involved in angiogenesis and capable of inducing several pro-inflammatory activities in neutrophils. Neutrophils also synthesize and release neutrophil extracellular traps (NETs), comprised from decondensed nuclear DNA filaments carrying proteins such as neutrophil elastase (NE), myeloperoxidase (MPO), proteinase 3 (PR3) and calprotectin (S100A8/S100A9), which together, contribute to the innate immune response against pathogens (e.g., bacteria). NETs are involved in various pathological conditions through pro-inflammatory, pro-thrombotic and endothelial dysfunction effects and have recently been found in heart failure (HF) and type 2 diabetes (T2DM) patients. The aim of the present study was to investigate the role of NETs on the synthesis and release of Ang1 by the neutrophils in patients with T2DM and HF with preserved ejection fraction (HFpEF) (stable or acute decompensated; ADHFpEF) with or without T2DM. RESULTS: Our data show that at basal level (PBS) and upon treatment with LPS, levels of NETs are slightly increased in patients suffering from T2DM, HFpEF ± T2DM and ADHF without (w/o) T2DM, whereas this increase was significant in ADHFpEF + T2DM patients compared to healthy control (HC) volunteers and ADHFpEF w/o T2DM. We also observed that treatments with PMA or A23187 increase the synthesis of Ang1 (from 150 to 250%) in HC and this effect is amplified in T2DM and in all cohorts of HF patients. Ang1 is completely released (100%) by neutrophils of all groups and does not bind to NETs as opposed to calprotectin. CONCLUSIONS: Our study suggests that severely ill patients with HFpEF and diabetes synthesize and release a greater abundance of NETs while Ang1 exocytosis is independent of NETs synthesis.
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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".