Endobronchial Ultrasound Reliably Quantifies Airway Smooth Muscle Remodeling in an Equine Asthma Model
Bibliographic record
Abstract
Endobronchial ultrasonography (EBUS) revealed differences in the thickness of the layer representing subepithelial tissues (L2) between human asthmatics and controls, but whether this measurement correlates with airway smooth muscle (ASM) remodeling in asthma is unknown. In this study, we sought to determine the ability of EBUS to predict histological ASM remodeling in normal and equine asthmatic airways. We studied 109 isolated bronchi from the lungs of 13 horses. They underwent EBUS examination using a 30 MHz radial probe before being processed for histology. ASM remodeling parameters were evaluated in EBUS images (L2 thickness, L2 area, L2 area/internal perimeter [Pi] and L2 area/Pi2) and histological cuts (ASM area/Pi2), and compared. EBUS was then performed ex vivo on the lungs of 4 horses with heaves, an asthma-like condition of horses, and 7 controls to determine whether central bronchial remodeling could be detected with this technique. An optimized approach was developed based on data variability within airways, subjects, and groups, and then validated in 7 horses (3 controls, 4 with heaves) that underwent EBUS in vivo. L2 area was significantly associated to ASM area in isolated lungs (p<0.0001), in the absence of significant bias related to the airway size. Bronchial size significantly affected EBUS ASM-related parameters, except for L2 area/Pi2. L2 area/Pi2 was increased in the airways of asthmatic horses compared to controls, both ex vivo and in vivo (p<0.05). Bronchial histology confirmed our findings (AASM/Pi2 was increased in asthmatic horses compared to controls, p<0.05). In both horses with heaves and controls, L2 was composed of ASM for the outer 75% of its thickness and by ECM for the remaining inner 25%. In conclusion, EBUS reliably allows assessment of asthma-associated ASM remodeling of central airways in a non-invasive way.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".