Bibliographic record
Abstract
BACKGROUND: Gastrointestinal microbiota can be influenced by several factors, including diet and systemic inflammation, and in turn could act as a modulator of the allergic response. Fecal microbiota of horses with asthma has not been described. HYPOTHESIS/OBJECTIVES: Analyze the bacterial fecal microbiota of horses with and without asthma under different environment and diet conditions, during both remission and exacerbation. METHODS: Prospective observational study. Feces from 6 asthmatic and 6 healthy horses were collected under 3 different conditions: on pasture, housed indoors receiving good quality hay ("good hay"), and housed indoors receiving poor quality hay ("dusty hay"). Sequencing was performed using an Illumina MiSeq platform and data were processed using the software mothur v.1.41.3 and LEfSe. RESULTS: In horses with asthma, low-abundance bacteria were more affected by changes in environment and diet (ie, when horses were experiencing an exacerbation), as shown by changes in membership and results from the LEfSe analysis. There was a significant increase in the relative abundance of Fibrobacter in healthy horses eating hay, a change that was not observed in horses with asthma. CONCLUSIONS AND CLINICAL IMPORTANCE: The intestinal microbiota of horses with asthma does not adapt in the same way to changes in diet and environment compared to the microbiota of healthy horses. Mechanisms explaining how airway obstruction and inflammation could influence the intestinal microbiota and how in turn this microbiota could modulate systemic inflammation in asthmatic horses deserves further investigation.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".