Priming for Enhanced Alveolar Fibrin Deposition after Hemorrhagic Shock: Role of Tumor Necrosis Factor
Bibliographic record
Abstract
Hemorrhagic shock due to major trauma predisposes to the development of acute respiratory distress syndrome. Because lung fibrin deposition is one of the hallmarks of this syndrome, we hypothesized that resuscitated shock might predispose to the development of a net procoagulant state in the lung. A rodent model of shock/resuscitation followed by low-dose intratracheal lipopolysaccharide (LPS), a clinically relevant "two-hit" model, was used to test this hypothesis. Resuscitated shock primed the lungs for an increased tissue factor and plasminogen activator (PA) inhibitor-1 gene expression in response to LPS, while the fibrinolytic PA was reduced. These alterations were recapitulated in isolated alveolar macrophages, suggesting their role in the process. LPS-induced tumor necrosis factor (TNF) was also augmented in animals after antecedent shock/resuscitation, and studies using anti-TNF antibodies revealed that TNF expression was critical to the induction of the procoagulant molecules and the reduction in PA. By contrast, TNF did not appear to play an important role in neutrophil sequestration in this model, inasmuch as anti-TNF had no effect on lung neutrophil accumulation or chemokine expression. However, treatment prevented albumin leak by preventing alveolar neutrophil activation. The inclusion of the antioxidant N-acetyl-cysteine in the resuscitation fluid resulted in prevention of both the development of the net procoagulant state and lung neutrophil sequestration, suggesting a role for upstream oxidant effects in the priming process. These studies provide a cellular and molecular basis for lung fibrin deposition after resuscitated shock and demonstrate a divergence of pathways responsible for fibrin generation and neutrophil accumulation.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".