Acute Lung Injury Induces Cardiovascular Dysfunction
Bibliographic record
Abstract
Acute lung injury (ALI) is associated with systemic inflammation and cardiovascular dysfunction. IL-6 is a biomarker of this systemic response and a predictor of cardiovascular events, but its possible causal role is uncertain. Inhaled corticosteroids and long-acting β2 agonists (ICS/LABA) down-regulate the systemic expression of IL-6, but whether they can ameliorate the cardiovascular dysfunction related to ALI is uncertain. We sought to determine whether IL-6 contributes to the cardiovascular dysfunction related to ALI, and whether budesonide/formoterol ameliorates this process. Wild-type mice were pretreated for 3 hours with intratracheal budesonide, formoterol, or both, before LPS was sprayed into their tracheas. IL-6-deficient mice were similarly exposed to LPS. Four hours later, bronchoalveolar lavage fluid (BALF) and serum were collected, and endothelial and cardiac functions were measured, using wire myography of the aortic tissue and echocardiography, respectively. LPS significantly impaired vasodilatory responses to acetylcholine (P < 0.001) and cardiac output (P = 0.002) in wild-type but not IL-6-deficient mice. Intratracheal instillations of exogenous IL-6 into IL-6-deficient mice restored these impairments (vasodilatory responses to acetylcholine, P = 0.005; cardiac output, P = 0.025). Pretreatment with the combination of budesonide and formoterol, but not either alone, ameliorated the vasodilatory responses to acetylcholine (P = 0.018) and cardiac output (P < 0.001). These drugs also attenuated the rise in the systemic expression of IL-6 (P < 0.05) related to LPS. IL-6 contributes to the cardiovascular dysfunction related to LPS, and pretreatment with budesonide/formoterol reduces the systemic expression of IL-6 and improves cardiovascular dysfunction. ICS/LABA may reduce acute cardiovascular events related to ALI.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".