Sensitive physiological readouts to evaluate countermeasures for lipopolysaccharide-induced lung alterations in mice
Bibliographic record
Abstract
Despite decades of research, studies investigating the physiological alterations caused by an acute bout of inflammation induced by exposing the lung to lipopolysaccharide have yielded inconsistent results. This can be attributed to small effects and/or a lack of fitted physiological testing. Herein, a comprehensive investigation of lung mechanics was conducted on 270 male C57BL/6 mice at 24, 48, or 96 h after an intranasal exposure to saline or lipopolysaccharide at either 1 or 3 mg/kg (30 mice per group). Traditional techniques that probe the lung using small-amplitude perturbations (i.e., oscillometry) were used, together with less conventional and new techniques that probe the lung using maneuvers of large amplitudes. The latter include a partial and a full-range pressure-volume maneuvers to measure quasi-static elastance, compliance, total lung volume, vital capacity, and residual volume. The results demonstrate that lung mechanics assessed by oscillometry was only slightly affected by lipopolysaccharide, confirming previous findings. In contradistinction, lipopolysaccharide markedly altered mechanics when the lung was probed with maneuvers of large amplitudes. With the dose of 3 mg/kg at the peak of inflammation (48 h postexposure), lipopolysaccharide increased quasi-static elastance by 26.7% ( P < 0.0001) and decreased compliance by 34.5% ( P < 0.0001). It also decreased lung volumes, including total lung capacity, vital capacity, and residual volume by 33.3%, 30.5%, and 43.3%, respectively (all P < 0.0001). These newly reported physiological alterations represent sensitive outcomes to efficiently evaluate countermeasures (e.g., drugs) in the context of several lung diseases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".