Nebulized antithrombin limits bacterial outgrowth and lung injury in Streptococcus pneumoniae pneumonia in rats
Bibliographic record
Abstract
INTRODUCTION: Disturbed alveolar fibrin turnover is a cardinal feature of severe pneumonia. Clinical studies suggest that natural inhibitors of coagulation exert lung-protective effects via anticoagulant and possibly also anti-inflammatory pathways. Intravenous infusion of the natural anticoagulants increases the risk of bleeding. Local administration may allow for higher treatment dosages and increased local efficacy while at the same time reducing the risk of bleeding. We evaluated the effect of nebulized anticoagulants on pulmonary coagulopathy and inflammation in a rat model of Streptococcus pneumoniae pneumonia. METHODS: In this randomized controlled in vivo laboratory study rats were challenged intratracheally with S. pneumoniae, inducing pneumonia, and randomized to treatment with normal saline (placebo), recombinant human activated protein C (rh-APC), plasma-derived antithrombin (AT), heparin or danaparoid, by means of nebulization. RESULTS: S. pneumoniae infection increased pulmonary levels of thrombin-antithrombin complexes and fibrin degradation products. All nebulized anticoagulants significantly limited pulmonary coagulopathy. None of the agents except danaparoid resulted in changes in systemic coagulopathy. Treatment with plasma-derived AT reduced outgrowth of S. pneumoniae and histopathologic damage in lungs. In vitro experiments confirmed outgrowth was reduced in bronchoalveolar lavage fluid (BALF) from rats treated with plasma-derived AT compared with placebo. Neutralizing of cationic components in BALF diminished the inhibitory effects on bacterial outgrowth of BALF, suggesting a role for cationic antimicrobial proteins. CONCLUSIONS: Nebulization of anticoagulants attenuates pulmonary coagulopathy during S. pneumoniae pneumonia in rats while only danaparoid affects systemic coagulation. Nebulized plasma-derived AT reduces bacterial outgrowth and exerts significant lung-protective effects.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".