Platelets and neutrophil extracellular traps collaborate to promote intravascular coagulation during sepsis in mice
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Neutrophil extracellular traps (NETs; webs of DNA coated in antimicrobial proteins) are released into the vasculature during sepsis where they contribute to host defense, but also cause tissue damage and organ dysfunction. Various components of NETs have also been implicated as activators of coagulation. Using multicolor confocal intravital microscopy in mouse models of sepsis, we observed profound platelet aggregation, thrombin activation, and fibrin clot formation within (and downstream of) NETs in vivo. NETs were critical for the development of sepsis-induced intravascular coagulation regardless of the inciting bacterial stimulus (gram-negative, gram-positive, or bacterial products). Removal of NETs via DNase infusion, or in peptidylarginine deiminase-4-deficient mice (which have impaired NET production), resulted in significantly lower quantities of intravascular thrombin activity, reduced platelet aggregation, and improved microvascular perfusion. NET-induced intravascular coagulation was dependent on a collaborative interaction between histone H4 in NETs, platelets, and the release of inorganic polyphosphate. Real-time perfusion imaging revealed markedly improved microvascular perfusion in response to the blockade of NET-induced coagulation, which correlated with reduced markers of systemic intravascular coagulation and end-organ damage in septic mice. Together, these data demonstrate, for the first time in an in vivo model of infection, a dynamic NET-platelet-thrombin axis that promotes intravascular coagulation and microvascular dysfunction in sepsis.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it