The endothelial protein C receptor impairs the antibacterial response in murine pneumococcal pneumonia and sepsis
Bibliographic record
Abstract
Pneumococcal pneumonia is a frequent cause of gram-positive sepsis and has a high mortality. The endothelial protein C receptor (EPCR) has been implicated in both the activation of protein C (PC) and the anti-inflammatory actions of activated (A)PC. The aim of this study was to determine the role of the EPCR in murine pneumococcal pneumonia and sepsis. Wild-type (WT), EPCR knockout (KO) and Tie2-EPCR mice, which overexpress EPCR on the endothelium, were infected intranasally (pneumonia) or intravenously (sepsis) with viable Streptococcus pneumoniae and euthanised at 24 or 48 hours after initiation of the infection for analyses. Pneumonia did not alter constitutive EPCR expression on pulmonary endothelium but was associated with an influx of EPCR positive neutrophils into lung tissue. In pneumococcal pneumonia EPCR KO mice demonstrated diminished bacterial growth in the lungs and dissemination to spleen and liver, reduced neutrophil recruitment to the lungs and a mitigated inflammatory response. Moreover, EPCR KO mice displayed enhanced activation of coagulation in the early phase of disease. Correspondingly, in pneumococcal sepsis EPCR KO mice showed reduced bacterial growth in lung and liver and attenuated cytokine release. Conversely, EPCR-overexpressing mice displayed higher bacterial outgrowth in lung, blood, spleen and liver in pneumococcal sepsis. In conclusion, EPCR impairs antibacterial defense in both pneumococcal pneumonia and sepsis, which is associated with an enhanced pro-inflammatory response.
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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 | 0.001 | 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".