The combination of trailer transport and exercise increases gastrointestinal permeability and markers of systemic inflammation in horses
Bibliographic record
Abstract
BACKGROUND: Leaky gut syndrome (LGS) is an idiopathic disorder characterised by alterations in intestinal permeability and low-grade systemic inflammation. Factors contributing to development of LGS are not well-understood but physiological stressors such as exercise and transport may play a role which may be of pathophysiological relevance in horses. OBJECTIVES: To characterise the combined effect of transport stress and exercise on gastrointestinal permeability, and to determine whether these effects are associated with increased inflammatory biomarkers in plasma. STUDY DESIGN: Controlled, randomised and cross-over study. METHODS: Horses (n = 8 per group) were given a gastrointestinal permeability tracer (iohexol; 5.6% solution; 1 ml/kg bwt) via nasogastric entubation prior to being assigned to a stressed (EX; 1 h of trailer transport immediately followed by 30 min moderate intensity exercise; n = 4) or sedentary control (CON; n = 4) group. Plasma samples were obtained prior to iohexol administration (P1), after transport (P2), at exercise cessation (P3), and at 1 (P4), 2 (P5), 4 (P6) and 8 (P7) hours after cessation of exercise and were analysed for iohexol, inflammatory biomarkers (SAA, LPS, IFABP and LBP) and tight junction proteins (zonulin). Faecal samples were collected at times corresponding to before and after stress from both groups and analysed for zonulin. Data were analysed using a 2-way RM ANOVA. RESULTS: In EX horses, a significant increase in iohexol was observed at P2 (1.5 ± 0.24 μg/ml; p = 0.03), P3 (2.1 ± 0.29 μg/ml; p < 0.001), P4 (2.1 ± 0.17 μg/ml; p < 0.001) compared with P1 (0.7 ± 0.21 μg/ml); iohexol was significantly higher in EX than CON horses at P3 (p < 0.001), P4 (p < 0.001) and P5 (p = 0.003). LPS and SAA were significantly higher in EX than CON at P4 (p < 0.001) and P6 (p = 0.04), respectively. MAIN LIMITATIONS: Data from our small sample size may not be generalisable to the larger equine population. CONCLUSIONS: Combined transport and exercise increases gastrointestinal permeability and systemic SAA and LPS. The model described herein may be useful in further studies on the role of alterations in gastrointestinal permeability in equine disease.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".