ATF3 is activated in ventilator induced lung injury
Bibliographic record
Abstract
Introduction Mechanical ventilation (MV) has been shown to cause ventilator‐induced lung injury (VILI). We wanted to identify novel molecular targets involved in reducing the harmful effects of MV (VILI). Methods To identify potential novel genes and proteins involved in VILI we i) performed microarray analysis on previously published VILI animal model data, ii) exposed human bronchial epithelial cells (Beas‐2b) in vitro to mechanical cyclic stretch (30 cycles/min for 4 hours), iii) performed western blot analysis on these stretched and non‐stretched cells, and iv) validated the regulation of the newly discovered gene(s) in vivo using wild type (WT) and ATF3 (Activator transcription factor 3) knock‐out mice (ATF3 KO). These two groups of mice were exposed to either injurious or non‐injurious ventilation strategies in combination with LPS or saline. Results ATF3 was identified by microarray analysis as one of the main genes involved in VILI. The presence of this factor was validated in vitro in the mechanically cyclic‐stretched Beas‐2b cells. Western blot assays confirmed expression of ATF3 in the stretched cells and their absence in the static cells. We further confirmed the regulation of ATF3 using WT and ATF3 KO mice in a model of VILI in vivo . ATF3 KO mice exposed to LPS in combination with injurious MV had more inflammation than WT mice of similar treatment or mice treated with saline. Conclusion Expression of ATF3 is stretch dependent and this gene seems to confer protection in combination with MV. Specific targeting of this factor in clinical settings could reduce VILI in patients receiving MV.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".