In Vivo Ultrasound Assessment of Gastric Emptying in Newborn Mice
Bibliographic record
Abstract
OBJECTIVES: The aim of the present study was to develop an ultrasonographic approach to comparatively assess gastric emptying in newborn wild-type and guanosine triphosphate cyclohydrolase knockout hph-1 mice, because we previously reported gastroparesis early in life in this strain. METHODS: Stomach transverse, anteroposterior, and longitudinal ultrasonographic measurements were obtained with a 40-MHz transducer in pups immediately after maternal separation and 4 hours later. A conventional equation was used and the predicted values validated by obtaining postmortem gastric content volume measurements. Wild-type and hph-1 mice gastric emptying rates were comparatively evaluated at 1 to 3 and 5 to 8 days of age, respectively. RESULTS: The ultrasound equation closely predicted the newborn stomach content volumes with a correlation coefficient (R) of 0.93 and 0.81 (P < 0.01) for measurements obtained on full stomach and after 4 hours of fasting, respectively. In wild-type mice, gastric emptying was age dependent and associated with a greater residual volume at 1 to 3 days (65% ± 7%), as compared with 5- to 8-day-old pups (33% ± 4%; P < 0.01), after fasting. In contrast, an equal duration of fasting resulted in a significantly greater residual gastric content volume in 5- to 8-day-old hph-1 mice (68% ± 7%; P < 0.01), as compared with same-age wild-type mice. CONCLUSIONS: Ultrasonography offers a sensitive and accurate estimate of gastric content volume in newborn mice. In wild-type newborn mice, gastric emptying rate is age dependent and significantly reduced in the immediate postnatal period. The newborn hph-1 mice have a significantly higher gastric residual volume, as compared with wild-type same-age animals.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".