Effects of airway tree asymmetry on the emergence and spatial persistence of ventilation defects
Bibliographic record
Abstract
Asymmetry and heterogeneity in the branching of the human bronchial tree are well documented, but their effects on bronchoconstriction and ventilation distribution in asthma are unclear. In a series of seminal studies, Venegas et al. have shown that bronchoconstriction may lead to self-organized patterns of patchy ventilation in a computational model that could explain areas of poor ventilation [ventilation defects (VDefs)] observed in positron emission tomography images during induced bronchoconstriction. To investigate effects of anatomic asymmetry on the emergence of VDefs we used the symmetric tree computational model that Venegas and Winkler developed using different trees, including an anatomic human airway tree provided by M. Tawhai (University of Auckland), a symmetric tree, and three trees with intermediate asymmetry (Venegas JG, Winkler T, Musch G, Vidal Melo MF, Layfield D, Tgavalekos N, Fischman AJ, Callahan RJ, Bellani G, Harris RS. Nature 434: 777-782, 2005 and Winkler T, Venegas JG. J Appl Physiol 103: 655-663, 2007). Ventilation patterns, lung resistance (RL), lung elastance (EL), and the entropy of the ventilation distribution were compared at different levels of airway smooth muscle activation. We found VDefs emerging in both symmetric and asymmetric trees, but VDef locations were largely persistent in asymmetric trees, and bronchoconstriction reached steady state sooner than in a symmetric tree. Interestingly, bronchoconstriction in the asymmetric tree resulted in lower RL (∼%50) and greater EL (∼%25). We found that VDefs were universally caused by airway instability, but asymmetry in airway branching led to local triggers for the self-organized patchiness in ventilation and resulted in persistent locations of VDefs. These findings help to explain the emergence and the persistence in location of VDefs found in imaging studies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".