Effect of aging on pulmonary cellular responses during mechanical ventilation
Bibliographic record
Abstract
Acute respiratory distress syndrome (ARDS) results in substantial morbidity and mortality, especially in elderly people. Mechanical ventilation, a common supportive treatment for ARDS, is necessary for maintaining gas exchange but can also propagate injury. We hypothesized that aging leads to alterations in surfactant function, inflammatory signaling, and microvascular permeability within the lung during mechanical ventilation. Young and aged male mice were mechanically ventilated, and surfactant function, inflammation, and vascular permeability were assessed. Additionally, single-cell RNA-Seq was used to delineate cell-specific transcriptional changes. The results showed that, in aged mice, surfactant dysfunction and vascular permeability were significantly augmented, while inflammation was less pronounced. Differential gene expression and pathway analyses revealed that alveolar macrophages in aged mice showed a blunted inflammatory response, while aged endothelial cells exhibited altered cell-cell junction formation. In vitro functional analysis revealed that aged endothelial cells had an impaired ability to form a barrier. These results highlight the complex interplay between aging and mechanical ventilation, including an age-related predisposition to endothelial barrier dysfunction, due to altered cell-cell junction formation, and decreased inflammation, potentially due to immune exhaustion. It is concluded that age-related vascular changes may underlie the increased susceptibility to injury during mechanical ventilation in elderly patients.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".