Use of multichannel electrointestinography for noninvasive assessment of myoelectrical activity in the cecum and large colon of horses
Bibliographic record
Abstract
OBJECTIVE: To evaluate whether changes in myoelectrical activity in the cecum and large colon of horses can be detected via multichannel electrointestinography (EIG). ANIMALS: 6 healthy mature horses. PROCEDURES: Each horse underwent 3 EIG procedures. Intestinal myoelectrical activity (cecum and large colon) was recorded during a 20-minute period following i.v. administration of physiologic saline (0.9% NaCl) solution (20 mL; baseline), erythromycin lactobionate (0.5 mg/kg), or detomidine (0.015 mg/kg); intestinal contractions were concurrently viewed via B-mode ultrasonography. By use of computer software, 8-channel EIG recordings were analyzed and the mean of the dominant frequency (a measure of the rhythmicity of gastric electrical activity) expressed in cycles per minute (cpm) was obtained. Total power (muV(2)) was calculated, and treatment effect was expressed as the power ratio (ie, treatment-associated power divided by the baseline power). RESULTS: The dominant frequency cpm values were not stable, and no significant differences between treatments were detected. Compared with the effects of saline solution treatment, detomidine significantly reduced the mean cecal and colonic power ratios. Erythromycin significantly reduced the cecal power ratio and increased the colonic power ratio, although the increase was significant in only 1 channel. Ultrasonographic findings and total power (predominantly from the long-distance electrode pairs) were significantly correlated. CONCLUSIONS AND CLINICAL RELEVANCE: In horses, EIG was useful for assessment of changes in myoelectrical activity in the cecum and large colon. Multiple electrodes should be used to cover a larger area of the intestine, and agreement between multiple channels is needed to make the analysis meaningful.
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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) | 0.000 | 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 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".