Recombinant activated protein C attenuates coagulopathy and inflammation when administered early in murine pneumococcal pneumonia
Bibliographic record
Abstract
Recombinant human activated protein C (APC), which has both anticoagulant and anti-inflammatory properties, improves survival of patients with severe sepsis. This beneficial effect is especially apparent in patients with pneumococcal pneumonia. Earlier treatment with APC in sepsis has been associated with a better therapeutic response as compared to later treatment. In a mouse model it was recently confirmed that recombinant murine (rm-)APC decreases coagulation activation and improves survival in pneumococcal pneumonia; however, APC did not impact on the inflammatory response. The aim of this study was to determine the effect of APC treatment instigated early in infection on activation of coagulation and inflammation after induction of pneumococcal pneumonia. Mice were infected intranasally with viable S. pneumoniae . Mice were treated with rm-APC (125 μg) or vehicle intraperitoneally 12 hours after infection and were sacrificed after 20 hours, after which blood and organs were harvested for determination of bacterial outgrowth, coagulation activation and inflammatory markers. In this early treatment model, rm-APC treatment inhibited pulmonary and systemic activation of coagulation as reflected by lower levels of thrombin-antithrombin complexes and D-dimer. Moreover, rm-APC reduced the levels of a large number of cytokines and chemokines in the lung. When administered early in pneumococcal pneumonia, rm-APC inhibits systemic and pulmonary activation of coagulation and moreover exerts various anti-inflammatory effects in the lung.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".