Streptococcus pneumoniae triggers progression of pulmonary fibrosis through pneumolysin
Bibliographic record
Abstract
RATIONALE: Respiratory tract infections are common in patients suffering from pulmonary fibrosis. The interplay between bacterial infection and fibrosis is characterised poorly. OBJECTIVES: To assess the effect of Gram-positive bacterial infection on fibrosis exacerbation in mice. METHODS: Fibrosis progression in response to Streptococcus pneumoniae was examined in two different mouse models of pulmonary fibrosis. MEASUREMENTS AND MAIN RESULTS: We demonstrate that wild-type mice exposed to adenoviral vector delivery of active transforming growth factor-β1 (TGFß1) or diphteria toxin (DT) treatment of transgenic mice expressing the DT receptor (DTR) under control of the surfactant protein C (SPC) promoter (SPC-DTR) to induce pulmonary fibrosis developed progressive fibrosis following infection with Spn, without exhibiting impaired lung protective immunity against Spn. Antibiotic treatment abolished infection-induced fibrosis progression. The cytotoxin pneumolysin (Ply) of Spn caused this phenomenon in a TLR4-independent manner, as Spn lacking Ply (SpnΔply) failed to trigger progressive fibrogenesis, whereas purified recombinant Ply did. Progressive fibrogenesis was also observed in AdTGFβ1-exposed Ply-challenged TLR4 KO mice. Increased apoptotic cell death of alveolar epithelial cells along with an attenuated intrapulmonary release of antifibrogenic prostaglandin E2 was found to underlie progressive fibrogenesis in Ply-challenged AdTGFβ1-exposed mice. Importantly, vaccination of mice with the non-cytotoxic Ply derivative B (PdB) substantially attenuated Ply-induced progression of lung fibrosis in AdTGFβ1-exposed mice. CONCLUSIONS: Our data unravel a novel mechanism by which infection with Spn through Ply release induces progression of established lung fibrosis, which can be attenuated by protein-based vaccination of mice.
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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".