Local Delivery of GM-CSF Protects Mice from Lethal Pneumococcal Pneumonia
Bibliographic record
Abstract
The growth factor GM-CSF has an important role in pulmonary surfactant metabolism and the regulation of antibacterial activities of lung sentinel cells. However, the potential of intra-alveolar GM-CSF to augment lung protective immunity against inhaled bacterial pathogens has not been defined in preclinical infection models. We hypothesized that transient overexpression of GM-CSF in the lungs of mice by adenoviral gene transfer (Ad-GM-CSF) would protect mice from subsequent lethal pneumococcal pneumonia. Our data show that intra-alveolar delivery of Ad-GM-CSF led to sustained increased pSTAT5 expression and PU.1 protein expression in alveolar macrophages during a 28-d observation period. Pulmonary Ad-GM-CSF delivery 2-4 wk prior to infection of mice with Streptococcus pneumoniae significantly reduced mortality rates relative to control vector-treated mice. This increased survival was accompanied by increased inducible NO synthase expression, antibacterial activity, and a significant reduction in caspase-3-dependent apoptosis and secondary necrosis of lung sentinel cells. Importantly, therapeutic treatment of mice with rGM-CSF improved lung protective immunity and accelerated bacterial clearance after pneumococcal challenge. We conclude that prophylactic delivery of GM-CSF triggers long-lasting immunostimulatory effects in the lung in vivo and rescues mice from lethal pneumococcal pneumonia by improving antibacterial immunity. These data support use of novel antibiotic-independent immunostimulatory therapies to protect patients against bacterial pneumonias.
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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".