Adverse In utero and Postnatal Environments Promote Hepatic Microvesicular Steatosis in conjunction with Differential Alterations in Fatty Acid and Amino Acid Metabolism in Early Adulthood
Bibliographic record
Abstract
We questioned whether an adverse in utero environment, resulting in low birth weight (LBW), and postnatal Western diet (WD) feeding interact in hepatic steatosis pathogenesis in young males, with particular attention focused upon differential alterations in lipid and amino acid metabolism. LBW guinea pigs, generated via uterine artery ablation, and normal birth weight (NBW) controls were fed either a WD or control diet (CD) after weaning. At 150 days of age, livers were harvested for histologic, molecular and biochemical assessments, gas chromatography and mass spectrometry. In LBW/CD animals, steatosis was absent. NBW/WD animals however, displayed a macrovesicular steatosis whereas LBW/WD animals exhibited a microvesicular steatosis. Hepatic carnitine palmitoyltransferase I and uncoupling protein 2 mRNA, long‐chain acylcarnitines (C16, C18 and C18:1) and amino acids (Asp, Phe, Tyr and Trp) were lower in LBW/WD vs. NBW/WD. Independent of birth weight, WD resulted in increased hepatic triglycerides, fatty acid translocase (CD36) mRNA, expression of lipogenic genes and proteins (FAS, ACC, and HK2), and metabolite‐based lipogenic parameters (C16:1/C16:0, C18:1/C18:0 and C16:0/C18:2n‐6). Hepatic medium chain acylcarnitine (C12), long‐chain acylcarnitines (C14, C14:1, C14‐OH, C16:1, C16‐OH, C18‐OH, C18:1‐OH and C18:3) and amino acid concentrations (Arg, Cys, Thr and Leu) were increased in WD animals. In conclusion, WD and LBW/WD induce hepatic steatosis accompanied with environment specific lipid and amino acid profile alterations. These data imply a less favorable liver health prognosis for adversely in utero grown offspring fed a WD postnatally.
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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 | 0.000 |
| 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".