Natural Killer Cells Induce the Formation of Neutrophil Extracellular Traps (NETs) in Venous Thrombosis
Bibliographic record
Abstract
Abstract Thrombosis is considered to be a pathological deviation of physiologic hemostasis involving similar mechanisms. Interestingly, recent work demonstrates that innate immune cells promote venous thrombosis. Innate immune cells were shown to collaborate to induce the activation of the coagulation cascade and platelets. In particular, neutrophils contribute to venous thrombosis through the release of neutrophil extracellular traps (NETs). However, the mechanism triggering the formation of NETs during venous thrombosis remain unknown. Of interest, a study showed that IFNγ induced the formation of NETs. Thus, we investigated the role of IFNγ-producing cells in the development of thrombosis. We used mice lacking IFNγ, Tbet (the transcription factor regulating the expression of IFNγ) or wild type mice. Venous thrombosis was induced using the flow restriction model in the inferior vena cava , as has been previously published. In Tbet-/-, IFNγ-/- and WT mice, we show that the absence of Tbet or IFNγ decreases the formation of thrombi after venous thrombosis induction, suggesting that the Tbet+/IFNγ producing cells are required for the early development of venous thrombosis. Comparing the composition of the thrombi from Tbet-/-, IFNγ-/- and WT mice, we show that, in all mice, neutrophils are the main cellular component of thrombi followed by monocytes; however, the number of neutrophil extracellular traps (NETs) formed during thrombosis is significantly lower in Tbet-/- and IFNγ-/- mice. Furthermore, NET formation is also decreased in WT mice specifically depleted of IFNγ and increases in Tbet-/- and IFNγ-/- mice injected with recombinant IFNγ. In vitro, we show that stimulation of WT murine neutrophils with recombinant IFNγ triggers the formation of NETs demonstrating that Tbet and IFNγ are crucial for NET formation by neutrophils. Natural killer (NK) cells are the main producers of IFNγ . Thus, we investigated the role of NK cells in venous thrombosis induced by flow restriction. NK cells were specifically depleted with an antibody during the development of venous thrombosis. The absence of NK cells results in smaller thrombi suggesting that NK cells are required for early thrombus development. Additionally, depletion in NK cells results in decreased in-situ IFNγ production and decreased NET formation. To directly link NK cells to the formation of NETs, WT neutrophils were co-cultured with Tbet-/- and IFNγ-/- NK cells. We show that WT neutrophils release less NETs when cultured with Tbet-/- and IFNγ-/- NK cells as compared to WT NK cells. These data suggest that NK cells trigger the formation of NETs by neutrophils through the production of IFNγ. Hence, we demonstrate that, in a partial flow restriction model of venous thrombosis, Tbet and IFNγ are crucial for thrombus development by promoting the formation of NETs by neutrophils and that NK cells are key effector cells in this process. Disclosures Blostein: boehringer-ingelheim: Research Funding.
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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) | 0.002 | 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".