Betamethasone prevents human rhinovirus- and cigarette smoke- induced loss of respiratory epithelial barrier function
Bibliographic record
Abstract
The respiratory epithelium is a barrier against pathogens and allergens and a target for therapy in respiratory allergy, asthma and chronic obstructive pulmonary disease (COPD). We investigated barrier-damaging factors and protective factors by real-time measurement of respiratory cell barrier integrity. Barrier integrity to cigarette smoke extract (CSE), house dust mite (HDM) extract, interferon-γ (IFN-γ) or human rhinovirus (HRV) infection alone or in combination was assessed. Corticosteroids, lipopolysaccharide (LPS), and nasal mucus proteins were tested for their ability to prevent loss of barrier integrity. Real-time impedance-based measurement revealed different patterns of CSE-, HDM-, IFN-γ- and HRV-induced damage. When per se non-damaging concentrations of harmful factors were combined, a synergetic effect was observed only for CSE and HDM. Betamethasone prevented the damaging effect of HRV and CSE, but not damage caused by HDM or IFN-γ. Real-time impedance-based measurement of respiratory epithelial barrier function is useful to study factors, which are harmful or protective. The identification of a synergetic damaging effect of CSE and HDM as well as the finding that Betamethasone protects against HRV- and CSE-induced damage may be important for asthma and COPD.
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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".