Tracheal microbial populations in horses with moderate asthma
Bibliographic record
Abstract
Abstract Background There are limited data on potential dysbiosis of the airway microbiota in horses with asthma. Hypothesis/Objectives We hypothesized that the respiratory microbiota of horses with moderate asthma is altered. Our objectives were (a) to quantify tracheal bacterial populations using culture and qPCR, (2) to compare aerobic culture and qPCR, and (c) to correlate bacterial populations with bronchoalveolar lavage fluid (BALF) cytology. Animals Eighteen horses with moderate asthma from a hospital population and 10 controls. Methods Prospective case-control study. Aerobic culture was performed on tracheal aspirates, and streptococci, Pasteurella multocida, Chlamydophila spp., Mycoplasma spp., as well as 16S (bacterial) and 18S (fungal) rRNA subunits were quantified by qPCR. Results Potential pathogens such as Streptococcus spp., Actinobacillus spp., and Pasteurellaceae were isolated from 8, 5, and 6 horses with asthma and 3, 0, and 2 controls, respectively. There was a positive correlation between Streptococcus spp. DNA and 16S rRNA gene (r ≥ 0.7, P ≤ 0.02 in both groups), but the overall bacterial load (16S) was lower in asthma (1.5 ± 1.3 versus 2.5 ± 0.8 × 104 copy/μL, P < 0.05). There was no association between microbial populations and clinical signs, tracheal mucus or BALF inflammation. Conclusions and Clinical Importance This study does not support that bacterial overgrowth is a common feature of chronic moderate asthma in horses. Lower bacterial load could suggest dysbiosis of the lower airways, either as a consequence of chronic inflammation or previous treatments, or as a perpetuating factor of inflammation.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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".