Ultrastructure of Human Tracheal Smooth Muscle from Subjects with Asthma and Nonasthmatic Subjects. Standardized Methods for Comparison
Bibliographic record
Abstract
A characteristic feature of asthma is exaggerated airway narrowing, termed airway hyper-responsiveness (AHR) due to contraction of airway smooth muscle (ASM). Although smooth muscle (SM)-specific asthma susceptibility genes have been identified, it is not known whether asthmatic ASM is phenotypically different from nonasthmatic ASM in terms of subcellular structure or mechanical function. The present study is the first to systematically quantify, using electron microscopy, the ultrastructure of tracheal SM from subjects with asthma and nonasthmatic subjects. Methodological details concerning tissue sample preparation, ultrastructural quantification, and normalization of isometric force by appropriate morphometric parameters are described. We reasoned that genetic and/or acquired differences in the ultrastructure of asthmatic ASM could be associated with functional changes. We recently reported that asthmatic ASM is better able to maintain and recover active force generation after length oscillations simulating deep inspirations. The present study was designed to seek structural evidence to account for this observation. Contrary to our hypotheses, no significant qualitative or quantitative differences were found in the subcellular structure of asthmatic versus nonasthmatic tracheal SM. Specifically, there were no differences in average SM cell cross-sectional area; fraction of the cell area occupied by nonfilamentous area; amounts of mitochondria, dense bodies, and dense plaques; myosin and actin filament densities; basal lamina thickness; and the number of microtubules. These results indicate that functional differences in ASM do not necessarily translate into observable structural changes.
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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".