Late-pregnancy uterine artery ligation increases susceptibility to postnatal Western diet-induced fat accumulation in adult female offspring
Bibliographic record
Abstract
Stressors during the fetal and postnatal period affect the growth and developmental trajectories of offspring, causing lasting effects on physiologic regulatory systems. Here, we tested whether reduced uterine artery blood flow in late pregnancy would alter body composition in the offspring, and whether feeding offspring a western diet (WD) would aggravate these programming effects. Pregnant rats underwent bilateral uterine artery ligation (BUAL) or sham surgery on gestational day (GD)18 (term = GD22). At weaning, offspring from each group received either a normal diet (ND) or a WD. BUAL surgery increased fetal loss and caused offspring growth restriction, albeit body weights were no longer different at weaning, suggesting postnatal catch-up growth. BUAL did not affect body weight gain, fat accumulation, or plasma lipid profile in adult male offspring. In contrast, while ND-fed females from BUAL group were smaller and leaner than their sham-littermates, WD consumption resulted in excess weight gain, fat accumulation, and visceral adiposity. Moreover, WD increased plasma triglycerides and cholesterol in the BUAL-treated female offspring without any effect on sham littermates. These results demonstrate that reduced uterine artery blood flow during late pregnancy in rodents can impact body composition in the offspring in a sex-dependent manner, and these effects may be exacerbated by postnatal chronic WD consumption.
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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 | 0.001 |
| 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".