Untargeted metabolomics reveals sex-specific differences in lipid metabolism of adult rats exposed to dexamethasone in utero
Bibliographic record
Abstract
Prenatal stress through glucocorticoid (GC) exposure leads to an increased risk of developing diseases such as cardiovascular disease, metabolic syndrome and hypertension in adulthood. We have previously shown that administration of the synthetic glucocorticoid, dexamethasone (Dex), to pregnant Wistar-Kyoto dams produces offspring with elevated blood pressures and disrupted circadian rhythm signaling. Given the link between stress, circadian rhythms and metabolism, we performed an untargeted metabolomic screen on the livers of offspring to assess potential changes induced by prenatal Dex exposure. This metabolomic analysis highlighted 18 significantly dysregulated metabolites in females and 12 in males. Pathway analysis using MetaboAnalyst 4.0 highlighted key pathway-level metabolic differences: glycerophospholipid metabolism, purine metabolism and glutathione metabolism. Gene expression analysis revealed significant upregulation of several lipid metabolism genes in females while males showed no dysregulation. Triglyceride concentrations were also found to be significantly elevated in female offspring exposed to Dex in utero, which may contribute to lipid metabolism activation. This study is the first to conduct an untargeted metabolic profile of liver from GC exposed offspring. Corroborating metabolic, gene expression and lipid profiling results demonstrates significant sex-specific lipid metabolic differences underlying the programming of hepatic metabolism.
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) | 0.000 | 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) | 0.001 | 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".