Binding of radiolabeled porcine motilin and erythromycin lactobionate to smooth muscle membranes in various segments of the equine gastrointestinal tract
Bibliographic record
Abstract
OBJECTIVE: To identify and characterize motilin receptors in equine duodenum, jejunum, cecum, and large colon and to determine whether erythromycin lactobionate competes with porcine motilin for binding to these receptors. SAMPLE POPULATION: Specimens of various segments of the intestinal tracts of 4 adult horses euthanatized for reasons unrelated to gastrointestinal tract disease. PROCEDURE: Cellular membranes were prepared from smooth muscle tissues of the duodenum, jejunum, pelvic flexure, and cecum. Affinity and distribution of motilin binding on membrane preparations were determined by use of 125I-labeled synthetic porcine motilin. Displacement studies were used to investigate competition between 125I-labeled synthetic porcine motilin and erythromycin lactobionate for binding to motilin receptors in various segments of bowel. RESULTS: Affinity of 125I-labeled synthetic porcine motilin for the equine motilin receptor was estimated to be 6.1nM. A significantly higher number of motilin receptors was found in the duodenum than in the pelvic flexure and cecum. The jejunum had a significantly higher number of motilin receptors than the cecum. Erythromycin lactobionate displacement of 125I-labeled porcine motilin from the equine motilin receptor did not differ significantly among various segments of bowel. CONCLUSIONS AND CLINICAL RELEVANCE: Motilin receptors were found in the duodenum, jejunum, pelvic flexure, and cecum of horses. The highest number of motilin receptors was in the duodenum, and it decreased in more distal segments of bowel. Erythromycin lactobionate competed with motilin binding in the equine gastrointestinal tract. This suggests that 1 of the prokinetic actions of erythromycin in horses is likely to be secondary to binding on motilin receptors.
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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) | 0.002 | 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".