Lung Volumes in a Mouse Model of Pulmonary Allergic Inflammation
Bibliographic record
Abstract
PURPOSE: Air trapping, often attested in humans by elevated residual volume (RV) and ratio of RV on total lung capacity (RV/TLC), is frequently observed in asthma. Confirming these alterations in experimental asthma would be important for translational purposes. Herein, lung volumes were investigated in a mouse model of pulmonary allergic inflammation. METHODS: Eight- to 10-week-old male C57BL/6 and BALB/c mice were exposed once daily to intranasal house dust mite (HDM) for 10 consecutive days. All readouts were measured 24 h after the last exposure. Lung volumes were assessed with the flexiVent using a new automated method consisting of degassing the lungs followed by a full-range pressure-volume maneuver. The weight and the volume of the lungs were also measured ex vivo and a lobe was further processed for histological analyses. RESULTS: HDM exposure led to tissue infiltration with inflammatory cells, goblet cell hyperplasia, thickening of the airway epithelium, and elevated ex vivo lung weight and volume. It also decreased TLC and vital capacity but without affecting RV and RV/TLC. These observations were similar between the two mouse strains. CONCLUSION: Alterations of lung volumes in a murine model of pulmonary allergic inflammation are inconsistent with observations made in human asthma. These discrepancies reflect the different means whereby lung volumes are measured between species. The invasive method used herein enables RV to be measured more precisely and without the confounding effect of air trapping, suggesting that changes in RV and RV/TLC using this method in mice should be interpreted differently than in humans.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".