Natural anticoagulants limit lipopolysaccharide-induced pulmonary coagulation but not inflammation
Bibliographic record
Abstract
Pulmonary coagulopathy and hyperinflammation may contribute to an adverse outcome in sepsis. The present study determines the effects of natural inhibitors of coagulation on bronchoalveolar haemostasis and inflammation in a rat model of endotoxaemia. Male Sprague-Dawley rats were randomised to treatment with normal saline, recombinant human activated protein C (APC), plasma-derived antithrombin (AT), recombinant human tissue factor pathway inhibitor (TFPI), heparin or recombinant tissue plasminogen activator (tPA). Rats were intravenously injected with lipopolysaccharide (LPS), which induced a systemic inflammatory response and pulmonary inflammation. Blood and bronchoalveolar lavage were obtained at 4 and 16 h after LPS injection, and markers of coagulation and inflammation were measured. LPS injection caused an increase in the levels of thrombin-AT complexes, whereas plasminogen activator activity was attenuated, both systemically and within the bronchoalveolar compartment. Administration of APC, AT and TFPI significantly limited LPS-induced generation of thrombin-AT complexes in the lungs, and tPA stimulated pulmonary fibrinolytic activity. However, none of the agents had significant effects on the production of pulmonary cytokines, chemokines, neutrophil influx and myeloperoxidase activity. Natural inhibitors of coagulation prevent bronchoalveolar activation of coagulation, but do not induce major alterations of the pulmonary inflammatory response in rat endotoxaemia.
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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) | 0.001 | 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".