Maternal Undernourishment in Guinea Pigs Leads to Fetal Growth Restriction with Increased Hypoxic Cells and Oxidative Stress in the Brain
Bibliographic record
Abstract
BACKGROUND: We determined whether maternal nutrient restriction (MNR) in guinea pigs leading to fetal growth restriction (FGR) impacts markers for brain hypoxia and oxidative stress. METHODS: Guinea pigs were fed ad libitum (control) or 70% of the control diet before pregnancy, switching to 90% at mid-pregnancy (MNR). Near term, hypoxyprobe-1 (HP-1) was injected into pregnant sows. Fetuses were then necropsied and brain tissues were processed for HP-1 (hypoxia marker) and 4HNE, 8-OHdG, and 3-nitrotyrosine (oxidative stress markers) immunoreactivity (IR). RESULTS: FGR-MNR fetal and brain weights were decreased 38 and 12%, respectively, with brain/fetal weights thereby increased 45% as a measure of brain sparing, and more so in males than females. FGR-MNR HP-1 IR was increased in most of the brain regions studied, and more so in males than females, while 4HNE and 8-OHdG IR were increased in select brain regions, but with no sex differences. CONCLUSIONS: Chronic hypoxia is likely to be an important signaling mechanism in the FGR brain, but with males showing more hypoxia than females. This may involve sex differences in adaptive decreases in growth and normalizing of oxygen, with implications for sex-specific alterations in brain development and risk for later neuropsychiatric disorder.
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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 | 0.001 |
| 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".