Neuroimmune Regulation of Ventilator-induced Lung Injury
Bibliographic record
Abstract
RATIONALE: Ventilator-induced lung injury (VILI) contributes to the mortality in patients with acute lung injury by increasing inflammation. Recent evidence suggests that stimulation of the cholinergic antiinflammatory pathway may be an attractive way to attenuate inflammatory injury. OBJECTIVES: To determine the role of vagus nerve signaling in VILI and establish whether stimulation of the vagus reflex can mitigate VILI. METHODS: We performed bilateral vagotomy in a mouse model of high-tidal volume-induced lung injury. We performed pharmacological and electrical vagus nerve stimulation in a rat model of VILI following ischemia/reperfusion injury. To determine the contribution of the alpha 7 acetylcholine nicotinic receptor to pulmonary cell injury, we exposed human bronchial epithelial cells to cyclic stretch in the presence of specific agonist or antagonist of the alpha 7 receptor. MEASUREMENTS AND MAIN RESULTS: Vagotomy exacerbates lung injury from VILI in mice as demonstrated by increased wet-to-dry ratio, infiltration of neutrophils, and increased IL-6. Vagal stimulation attenuates lung injury in rats after ischemia/reperfusion injury ventilated with high-volume strategies. Treatment of both mice and rats with the vagus mimetic drug semapimod resulted in decreased lung injury. Vagotomy also increased pulmonary apoptosis, whereas vagus stimulation (electrical and pharmacological) attenuated VILI-induced apoptosis. In vitro studies suggest that vagus-dependent effects on inflammation and apoptosis are mediated via the α7 nicotinc acetylcholine receptor-dependent effects on cyclic stretch-dependent signaling pathways c-jun N-terminal kinase and tumor necrosis factor receptor superfamily, member 6. CONCLUSIONS: Stimulation of the cholinergic antiinflammatory reflex may represent a promising alternative for the treatment of VILI.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".