Characterization of fungal exposure and dectin-1 expression in healthy horses and horses with severe asthma
Bibliographic record
Abstract
OBJECTIVE: To quantify dectin-1 expression in bronchoalveolar lavage fluid (BALF), create polyclonal antibodies against equine dectin-1 and localize it in tissues, and quantify fungal exposure in pastured and stabled asthmatic and nonasthmatic horses. SAMPLES: BALF samples from 6 controls and 6 horses with severe asthma. Stored lung and nasal wash samples. PROCEDURES: Dectin-1 expression was quantified by quantitative PCR (qPCR). Purified peptide from equine dectin-1 was used to generate polyclonal antibodies and was confirmed with immunological testing. Fungal exposure was quantified in BALF samples by counting fungal-like intracellular particles in phagocytic cells, by qPCR quantification of the "universal" 18S rRNA fungal gene, and by quantifying 36 specific fungi in equine and dust samples using qPCR assays. RESULTS: Equine dectin-1 was localized in tissues and cells, and functional isoforms were upregulated significantly in BALF after stabling. Pastured horses from both groups had low levels of fungi in BALF, and there was a significant increase in some specific fungi, most notably for Eurotium amstelodami, Wallemia sebi, and Aspergillus niger after stabling. However, stabled asthmatic horses had fewer phagocytized particles, less 18S rRNA signal, and fewer specific fungi compared to nonasthmatic horses. CLINICAL RELEVANCE: Stabling increases exposure to fungi, but asthmatic horses had fewer fungi reaching their lower airways, presumably resulting from congestion and narrowing of the airways. Exposure to fungi could contribute to airway inflammation by increasing dectin-1 functional isoforms, and exposure to indoor molds should be avoided.
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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".