Bead study: a novel method to measure gastrointestinal transit in mice
Bibliographic record
Abstract
BACKGROUND: Intestinal transit assessment in mice using existing methods requires long recording periods or euthanization of animals to localize a tracer. We have developed a novel in vivo method to assess gastrointestinal (GI) transit in mice based on a clinically used 'shapes study'. METHODS: Mice (n = 70) were gavaged with 5 steel beads and barium 3 h before, with another dose of barium gavaged 10 min before imaging. Mice were fluoroscoped for 20-60 s, and then most of them were euthanized and the GI tract removed to confirm the localization of the beads fluoroscopically. The in vivo and postmortem recordings were analyzed and each bead was scored depending on its location; a total score was calculated by adding individual bead scores. Total scores obtained from the two methods were compared. A group of mice (n = 10) were examined on three occasions, before and after treatment with loperamide or prucalopride. KEY RESULTS: The stomach and cecum were consistently outlined by barium, serving as reference landmarks. There was an excellent overall correlation between in vivo and postmortem transit scores (r = 0.93). Analysis of scores for individual gut segments revealed high agreement for stomach, cecum, and expelled beads, and moderate agreement for the small bowel and colon. Gastrointestinal transit scores were decreased by loperamide and increased by prucalopride compared with baseline. CONCLUSIONS & INFERENCES: Metallic beads are reliably localized by videofluoroscopy in vivo within the GI tract. This novel imaging method enables repetitive measurements of GI transit in vivo and detects changes induced by motility-modifying agents.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".