Consumption of a high-fat diet rapidly exacerbates the development of fatty liver disease that occurs with chronically elevated glucocorticoids
Bibliographic record
Abstract
Chronically elevated glucocorticoids (GCs) and a high-fat diet (HFD) independently induce insulin resistance, abdominal obesity, and nonalcoholic fatty liver disease (NAFLD). GCs have been linked to increased food intake, particularly energy-dense "comfort" foods. Thus we examined the synergistic actions of GCs and HFD on hepatic disease development in a new rodent model of chronically elevated GCs. Six-week-old male Sprague-Dawley rats received exogenous GCs, via subcutaneous implantation of four 100-mg corticosterone (Cort) pellets, to elevate basal GC levels for 16 days (n = 8-10 per group). Another subset of animals received wax pellets (placebo) to serve as controls. Animals from each group were randomly assigned to receive a 60% HFD or a standard high-carbohydrate (13% fat and 60% carbohydrate) diet. Cort + HFD resulted in central obesity, despite a relative weight loss, a 4-fold increase in hepatic lipid content, hepatic fibrosis, and a 2.8-fold increase in plasma alanine aminotransferase levels compared with placebo + chow controls. Hepatic injury developed independent of inflammation, as plasma haptoglobin levels were reduced with Cort treatment. Insulin resistance and hepatic steatosis occurred with Cort alone; these outcomes were further exacerbated by the HFD in the presence of elevated Cort. In addition to fatty liver, the Cort + HFD group also developed severe insulin resistance, hyperinsulinemia, hyperglycemia, and hypertriglyceridemia, which were not evident with HFD or Cort alone. Thus a HFD dramatically exacerbates the development of NAFLD and characteristics of the metabolic syndrome in conditions of chronically elevated Cort.
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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) | 0.001 | 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".