Leukotriene B<sub>4</sub>mediates macrophage influx and pulmonary hypertension in bleomycin-induced chronic neonatal lung injury
Bibliographic record
Abstract
Systemically-administered bleomycin causes inflammation, arrested lung growth, and pulmonary hypertension (PHT) in the neonatal rat, similar to human infants with severe bronchopulmonary dysplasia (BPD). Leukotrienes (LTs) are inflammatory lipid mediators produced by multiple cell types in the lung. The major LTs, LTB4 and cysteinyl LTs, are suggested to contribute to BPD, but their specific roles remain largely unexplored in experimental models. We hypothesized that LTs are increased in bleomycin-induced BPD-like injury, and that inhibition of LT production would prevent inflammatory cell influx and thereby ameliorate lung injury. Rat pups were exposed to bleomycin (1 mg·kg(-1)·day(-1) ip) or vehicle (control) from postnatal days 1-14 and were treated with either zileuton (5-lipoxygenase inhibitor), montelukast (cysteinyl LT1 receptor antagonist), or SC57461A (LTA4 hydrolase inhibitor) 10 mg·kg(-1)·day(-1) ip. Bleomycin led to increased lung content of LTB4, but not cysteinyl LTs. Bleomycin-induced increases in tissue neutrophils and macrophages and lung contents of LTB4 and tumor necrosis factor-α were all prevented by treatment with zileuton. Treatment with zileuton or SC57461A also prevented the hemodynamic and structural markers of chronic PHT, including raised pulmonary vascular resistance, increased Fulton index, and arterial wall remodeling. However, neither treatment prevented impaired alveolarization or vascular hypoplasia secondary to bleomycin. Treatment with montelukast had no effect on macrophage influx, PHT, or on abnormal lung structure. We conclude that LTB4 plays a crucial role in lung inflammation and PHT in experimental BPD. Agents targeting LTB4 or LTB4-mediated signaling may have utility in infants at risk of developing BPD-associated PHT.
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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) | 0.001 | 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 | 0.001 |
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".