Pulmonary and Systemic Host Response to<i>Streptococcus pneumoniae</i>and<i>Klebsiella pneumoniae</i>Bacteremia in Normal and Immunosuppressed Mice
Bibliographic record
Abstract
Mortality related to bacteremic pneumonia remains high, and the role of sepsis in inflammation, pulmonary injury, and death remains unclear, mostly in leukopenic states. In the present study, the microbiology, histopathology, and host response to Streptococcus pneumoniae and Klebsiella pneumoniae infection were determined in an experimental model of bacteremia in immunocompetent and leukopenic mice. Leukocyte depletion by cyclophosphamide did not impair the early clearance of pneumococci from blood but facilitated growth in lungs. By contrast, klebsiellae rapidly grew in blood of leukopenic mice. These observations suggest that tissue-based phagocytes and circulating leukocytes, respectively, play prominent roles in S. pneumoniae and K. pneumoniae eradication. The kinetics of leukocyte recruitment in lungs during S. pneumoniae bacteremia suggested early strong inflammation in immunocompetent mice that is associated with tumor necrosis factor alpha release and histological disorders, including cell debris and surfactant in alveolar spaces. Leukocyte depletion further stimulated pulmonary capillary leakage both in S. pneumoniae and K. pneumoniae bacteremia, which seemed attributable to bacterial virulence factors. Nitric oxide production did not differ significantly among groups. Leukopenia and low platelet counts characterized the late stage of bacteremia for both strains, but only K. pneumoniae altered renal function. Understanding the pathogenesis of bacteremia will help establish beneficial therapies for both sepsis and pneumonia.
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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".