The Effect of Tidal Volume on Systemic Inflammation in Acid-Induced Lung Injury
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Overwhelming systemic inflammation has been implicated in the progression of acute lung injury (ALI) leading to multiple organ failure (MOF) and death. Previous studies suggest that mechanical ventilation (MV) may be a key mediator of MOF through an upregulation of the systemic inflammatory response. OBJECTIVES: It was the aim of this study to investigate mechanisms whereby mechanical stress induced by different tidal volumes may contribute to the development of systemic inflammation and maladaptive peripheral organ responses in the setting of ALI. METHODS: An acid aspiration model of ALI was employed in 129X1/SVJ mice through an intratracheal administration of hydrochloric acid followed by MV employing either a low (5 ml/kg) or high (12.5 ml/kg) tidal volume ventilation for 120 min. The isolated perfused mouse lung setup was used to assess the specific contribution of the lung to systemic inflammation during MV. Furthermore, lung perfusate collected over the course of MV was used to assess the effects of lung-derived mediators on activation (expression of a proadhesive phenotype) of liver endothelial cells. RESULTS: High tidal volume MV of acid-injured lungs resulted in greater physiologic and histological indices of lung injury compared to control groups. Additionally, there was an immediate and significant release of multiple inflammatory mediators from the lung into the systemic circulation which resulted in greater levels of mRNA adhesion molecule expression in liver endothelial cells in vitro. CONCLUSIONS: This study suggests that MV, specifically tidal volume strategy, influences the development of MOF through an upregulation of lung-derived systemic inflammation resulting in maladaptive cellular changes in peripheral organs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it