The presence of acylated homoserine lactones and diffusible signal factor in bronchoalveolar lavage fluid from horses with clinical exacerbation of severe equine asthma
Bibliographic record
Abstract
Several bacteria associated with chronic lung pathology use quorum sensing (QS) signaling molecules to regulate their virulence in pure cultures and poly-microbial communities. Their excessive growth and biofilm formation in the respiratory tract increase the morbidity and mortality of inflammatory airway diseases in humans, such as chronic obstructive pulmonary disease (COPD), asthma and cystic fibrosis (CF). In horses, severe equine asthma (SEA) has many parallels to these human diseases. We hypothesized that QS molecules associated with the most common biofilm-forming lung pathogens in humans (Pseudomonas aeruginosa, Stenotrophomonas maltophilia) may also be present in the lungs of horses with SEA. Samples of bronchoalveolar lavage fluid (BALf) were taken from twenty horses with exacerbated SEA. Microbiological cultures of the BALf samples were performed. Liquid chromatography coupled with tandem mass spectrometry was used to identify C4-HSL, C6-HSL, 3-oxo-C12-HSL and 11-methyl-2-dodecenoic acid, which are associated with the QS mechanisms of Pseudomonas aeruginosa and Stenotrophomonas maltophilia. Stenotrophomonas maltophilia was identified in three horses. Pseudomonas aeruginosa was not identified in any sample. The quorum sensing molecules C4-HSL, C6-HSL, 3-oxo-C12-HSL associated with biofilm formation by P. aeruginosa and 11-methyl-2-dodecenoic acid associated with biofilm formation by S. maltophila were not detected. It is unlikely that biofilm-forming bacterial strains associated with chronic lung disease in humans express similar virulence in SEA.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".