Effect of intraluminal distension or ischemic strangulation obstruction of the equine jejunum on jejunal motilin receptors and binding of erythromycin lactobionate
Bibliographic record
Abstract
OBJECTIVE: To determine whether inflammation of the jejunum of horses decreases the number of motilin receptors and amounts of motilin receptor mRNA and alters erythromycin lactobionate binding affinity to the motilin receptor in jejunal tissues. SAMPLE POPULATION: Jejunal segments in 6 adult horses. PROCEDURE: Each horse was anesthetized, and a ventral median celiotomy was performed; 2 segments of jejunum underwent a sham operation, 2 segments underwent ischemic strangulation obstruction (ISO), and 2 segments underwent intraluminal distension (ILD). Treatments were maintained for 120 minutes. From each segment, full-thickness biopsy samples were collected and smooth-muscle homogenates were prepared. Affinity and distribution of motilin binding to these preparations were determined by use of iodine 125 (125I)-labeled synthetic porcine motilin. Via displacement experiments, competition between 125I-labeled motilin and erythromycin lactobionate for binding to motilin receptors in the different segments was investigated. A quantitative real-time PCR technique was used to assess motilin receptor mRNA content in the muscle preparations. RESULTS: Compared with the ISO or ILD segments, the number of motilin receptors was significantly higher in the sham-operated segments; ILD segments contained the lowest number of motilin receptors. The expression of motilin receptor mRNA was significantly decreased in ILD segments but not in ISO segments. Erythromycin lactobionate displacement of 125I-labeled motilin from motilin receptors did not differ significantly among the jejunal segments. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggest that downregulation and decreased production of motilin receptors in inflamed jejunal tissue contribute to the altered prokinetic response to erythromycin in horses with gastrointestinal 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 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".