Hypoxia-Induced Intrauterine Growth Restriction Increases the Susceptibility of Rats to High-Fat Diet–Induced Metabolic Syndrome
Bibliographic record
Abstract
OBJECTIVE: It is recognized that there is a remarkable variability in the systemic response to high-fat (HF) diets that cannot be completely explained by genetic factors. In addition, pregnancy complications leading to intrauterine growth restriction (IUGR) have been associated with an increased risk of developing metabolic syndrome (MetS) later in life. Thus, we hypothesized that offspring born with IUGR exhibit permanent metabolic changes that make them more susceptible to HF diet-induced MetS. RESEARCH DESIGN AND METHODS: SD rats born normal (control) or with hypoxia-induced IUGR were randomized to low-fat (10% fat) or HF (45% fat) diets. After 9 weeks of feeding, physiological and molecular pathways involved in the MetS were evaluated. RESULTS: IUGR offspring exhibited decreased energy intake and physical activity relative to controls. In offspring fed a HF diet, IUGR was associated with decreased total body fat content, a relative increase in intra-abdominal fat deposition and adipocyte size, an increase in fasting plasma concentrations of leptin, triglyceride and free fatty acids, and an increased concentration of triglycerides and ceramides in both liver and skeletal muscle. These changes in lipid homeostasis were accompanied by in vivo insulin resistance and impaired glucose tolerance and associated with increased phosphorylation of protein kinase C , inhibition of insulin receptor substrate 1, and a decreased activation of protein kinase B (PKB; also known as Akt) in liver and skeletal muscle in response to insulin. CONCLUSIONS: IUGR enhances specific deleterious metabolic responses to a HF diet. Our results suggest that offspring born with IUGR may require special attention and follow-up to prevent the early onset of MetS.
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) | 0.001 | 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 | 0.000 |
| 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".