Double-chamber plethysmography <i>versus</i> oscillometry to detect baseline airflow obstruction in a model of asthma in two mouse strains
Bibliographic record
Abstract
Aim of the study The current gold standard to assess respiratory mechanics in mice is oscillometry, a technique from which several readouts of the respiratory system can be deduced, such as resistance and elastance. However, these readouts are often not altered in mouse models of asthma. This is in stark contrast with humans, where asthma is generally associated with alterations when assessed by either oscillometry or other techniques. In the present study, we have used double-chamber plethysmography (DCP) to evaluate the breathing pattern and the degree of airflow obstruction in a mouse model of asthma.Materials and Methods Female C57BL/6 and BALB/c mice were studied at day 1 using DCP, as well as at day 11 using both DCP and oscillometry following a once-daily exposure to either house-dust mite (HDM) or saline for 10 consecutive days.Results All DCP readouts used to describe either the breathing pattern (e.g., tidal volume and breathing frequency) or the degree of airflow obstruction (e.g., specific airway resistance) were different between mouse strains at day 1. Most of these strain differences persisted at day 11. Most oscillometric readouts (e.g., respiratory system resistance and elastance) were also different between strains. Changes caused by HDM were obvious with DCP, including decreases in tidal volume, minute ventilation, inspiratory time and mid-tidal expiratory flow and an increase in specific airway resistance. HDM also caused some strain specific alterations in breathing pattern, including increases in expiratory time and end inspiratory pause, which were only observed in C57BL/6 mice. Oscillometry also detected a small but significant increase in tissue elastance in HDM versus saline-exposed mice.Conclusions DCP successfully identified differences between C57BL/6 and BALB/c mice, as well as alterations in mice from both strains exposed to HDM. We conclude that, depending on the study purpose, DCP may sometimes outweigh oscillometry.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| 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".