Differential Contribution of Bacterial <i>N</i> -Formyl-Methionyl-Leucyl- Phenylalanine and Host-Derived CXC Chemokines to Neutrophil Infiltration into Pulmonary Alveoli during Murine Pneumococcal Pneumonia
Bibliographic record
Abstract
Despite the development of new potent antibiotics, Streptococcus pneumoniae remains the leading cause of death from bacterial pneumonia. Polymorphonuclear neutrophil (PMN) recruitment into the lungs is a primordial step towards host survival. Bacterium-derived N-formyl peptides (N-formyl-methionyl-leucyl-phenylalanine [fMLP]) and host-derived chemokines (KC and macrophage inflammatory protein 2 [MIP-2]) are likely candidates among chemoattractants to coordinate PMN infiltration into alveolar spaces. To investigate the contribution of each in the context of pneumococcal pneumonia, CD1, BALB/c, CBA/ca, C57BL/6, and formyl peptide receptor (FPR)-knockout C57BL/6 mice were infected with 10(6) or 10(7) CFU of penicillin/erythromycin-susceptible or -resistant serotype 3 or 14 S. pneumoniae strains. Antagonists to the FPR, such as cyclosporine H (CsH) and chenodeoxycholic acid, or neutralizing antibodies to KC and MIP-2 were injected either 1 h before or 30 min after infection, and then bronchoalveolar lavage fluids were obtained for quantification of bacteria, leukocytes, and chemokines. CsH was effective over a short period after infection with a high inoculum, while anti-CXC chemokine antibodies were effective after challenge with a low inoculum. CsH prevented PMN infiltration in CD1 mice infected with either serotype 3 or 14, whereas antichemokine antibodies showed better efficacy against the serotype 3 strain. When different mouse strains were challenged with serotype 3 bacteria, CsH prevented PMN migration in the CD1 mice only, whereas the antibodies were effective against CD1 and C57BL/6 mice. Our results suggest that fMLP and chemokines play important roles in pneumococcal pneumonia and that these roles vary according to bacterial and host genetic backgrounds, implying redundancy among chemoattractant molecules.
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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".