Developmental changes in hemodynamics of uterine artery, utero- and umbilicoplacental, and vitelline circulations in mouse throughout gestation
Bibliographic record
Abstract
In human pregnancy, abnormal placental hemodynamics likely contribute to the etiology of early-onset preeclampsia and fetal intrauterine growth restriction. The mouse is increasingly being deployed to study normal and abnormal mammalian placental development, yet the placental hemodynamics in normal pregnancy in mice is currently unknown. We used ultrasound biomicroscopy to noninvasively image and record Doppler blood velocity waveforms from the maternal and embryonic placental circulations in mice throughout gestation. In the uterine artery, peak systolic velocity (PSV) increased significantly from 23 ± 2 (SE) to 59 ± 3 cm/s, and end-diastolic velocity (EDV) increased from 7 ± 1 to 28 ± 2 cm/s in nonpregnant versus full-term females so that the uterine arterial resistance index (RI) decreased from 0.70 ± 0.02 to 0.53 ± 0.02. Velocities in the maternal arterial canal in the placenta were low and nearly steady and increased from 0.9 ± 0.03 cm/s at embryonic day 10.5 (E10.5) to 2.4 ± 0.07 cm/s at E18.5. PSV in the umbilical artery increased steadily from 0.8 ± 0.1 cm/s at E8.5 to 15 ± 0.6 cm/s at E18.5, whereas PSV in the vitelline artery increased from 0.6 ± 0.1 cm/s at E8.5 to 4 ± 0.2 cm/s at E13.5 and then remained stable to term. In the umbilical artery, the EDV detection rate was 0% at ≤E14.5 and 94% at E18.5, and the RI decreased from 1 to 0.82 ± 0.01 during this interval. We conclude that ultrasound biomicroscopy can be used to monitor placental hemodynamics during pregnancy in mice. These results provide novel information concerning the development of the vitelline and placental circulations in mice and reveal strong similarities in placental hemodynamics between mice and humans.
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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 | 0.001 | 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".