Rhinosectan® spray (containing xyloglucan) on the ciliary function of the nasal respiratory epithelium; results of an in vitro study
Bibliographic record
Abstract
To assess the effects of Rhinosectan ® spray, a medical device containing xyloglucan, on nasal ciliary function (in MucilAir™Nasal cells). MucilAir™Nasal, a three-dimensional organotypic airway tissue model (with different cell types), was treated with Rhinosectan ® (30 µl) or with a control (saline solution). The effects of Rhinosectan ® were evaluated at 15 and 60 min post-exposure by: measurement of the cilia beating frequency (Hz), mucin detection (Enzyme-Linked Lectin Assay—ELLA), mucociliary clearance (µm/s) and phagocytosis assay (fluorescence). Exposure of MucilAir™ to Rhinosectan ® did not alter the cilia beating frequency at 15 and 60 min post-exposure (diluted and undiluted). Exposure to Rhinosectan ® (undiluted) during 60 min increased mucociliary clearance (93.3 ± 2.1 µm/s vs. 80.9 ± 1.8 µm/s; p < 0.01) and phagocytic activity (1.89-fold increase) in comparison with saline solution. Moreover, a significant decrease in mucin concentration was observed after 15 min of exposure (171.4 ng/ml vs. 306.5 ng/ml; p < 0.01) and at 60 min post-treatment (242.7 ng/ml vs. 339 ng/ml; p < 0.05). The application of Rhinosectan ® to nasal epithelial cells does not impair ciliary movement, enhances mucociliary clearance and facilitates phagocytosis while reducing mucin secretion, which are optimal properties for the management of rhinitis and associated conditions.
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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 | 0.000 |
| 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".