A respiratory‐gated micro‐<scp>CT</scp> comparison of respiratory patterns in free‐breathing and mechanically ventilated rats
Bibliographic record
Abstract
Abstract In this study, we aim to quantify the differences in lung metrics measured in free‐breathing and mechanically ventilated rodents using respiratory‐gated micro‐computed tomography. Healthy male Sprague‐Dawley rats were anesthetized with ketamine/xylazine and scanned with a retrospective respiratory gating protocol on a GE Locus Ultra micro‐CT scanner. Each animal was scanned while free‐breathing, then intubated and mechanically ventilated (MV) and rescanned with a standard ventilation protocol (56 bpm, 8 mL/kg and PEEP of 5 cm H2O) and again with a ventilation protocol that approximates the free‐breathing parameters (88 bpm, 2.14 mL/kg and PEEP of 2.5 cm H2O). Images were reconstructed representing inspiration and end expiration with 0.15 mm voxel spacing. Image‐based measurements of the lung lengths, airway diameters, lung volume, and air content were compared and used to calculate the functional residual capacity (FRC) and tidal volume. Images acquired during MV appeared darker in the airspaces and the airways appeared larger. Image‐based measurements showed an increase in lung volume and air content during standard MV, for both respiratory phases, compared with matched MV and free‐breathing. Comparisons of the functional metrics showed an increase in FRC for mechanically ventilated rats, but only the standard MV exhibited a significantly higher tidal volume than free‐breathing or matched MV. Although standard mechanical ventilation protocols may be useful in promoting consistent respiratory patterns, the amount of air in the lungs is higher than in free‐breathing animals. Matching the respiratory patterns with the free‐breathing case allowed similar lung morphology and physiology measurements while reducing the variability in the measurements.
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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 | 0.001 | 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".