Adaptation of an amphibian mucociliary clearance model to evaluate early effects of tobacco smoke exposure
Bibliographic record
Abstract
RATIONALE: Inhaled side-stream tobacco smoke brings in all of its harmful components impairing mechanisms that protect the airways and lungs. Chronic respiratory health consequences are a complex multi-step silent process. By the time clinical manifestations require medical attention, several structural and functional changes have already occurred. The respiratory system has to undergo an iterative process of injury, healing and remodeling with every exposure. METHODS: To have a better understanding of the initial changes that take place when first exposed to environmental tobacco smoke, we have developed an exposure model, using the frog palate that closely represents the features of obstructive airways where ciliary dysfunction and mucus hypersecretion occur. RESULTS: Mucus transport was significantly reduced, even after exposure to the smoke of one cigarette (p < 0.05) and even further with 4-cigarettes exposure (p < 0.001). Morphometric and ultrastructural studies by SEM show extensive areas of tissue disruption. Gelatinase zymography shows activation of MMP9 in mucus from palates exposed to tobacco smoke. CONCLUSIONS: The clearance of mucus on the frog palate is significantly reduced after exposure to environmental tobacco smoke. Cilia and the extracellular matrix are anatomically disrupted. Tobacco smoke triggers an increased activity of matrix metalloproteinases associated with a substantial defoliation of ciliated epithelium. These studies enhance the knowledge of the changes in the mucociliary apparatus that occur initially after exposure to environmental tobacco smoke, with the goal of understanding how these changes relate to the genesis of chronic airway pathologies 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".