Central and Metabolic Effects of High Fructose Consumption: Evidence from Animal and Human Studies
Bibliographic record
Abstract
Fructose consumption has increased dramatically in the last 40 years, and its role in the pathogenesis of the metabolic syndrome has been implicated by many studies. It is most often encountered in the diet as sucrose (glucose and fructose) or high-fructose corn syrup (55% fructose). At high levels, dietary exposure to fructose triggers a series of metabolic changes originating in the liver, leading to hepatic steatosis, hypertriglyceridemia, insulin resistance, and decreased leptin sensitivity. Fructose has been identified to alter biological pathways in other tissues including the central nervous system (CNS), adipose tissue, and the gastrointestinal system. Unlike glucose, consumption of fructose produces smaller increases in the circulating satiety hormone glucagon-like peptide 1 (GLP-1), and does not attenuate levels of the appetite suppressing hormone ghrelin. In the brain, fructose contributes to increased food consumption by activating appetite and reward pathways, and stimulating hypothalamic AMPK activity, a nutrient-sensitive regulator of food intake. Recent studies investigating the neurophysiological factors linking fructose consumption and weight gain in humans have demonstrated differential activation of brain regions that govern appetite, motivation and reward processing. Compared to fructose, glucose ingestion produces a greater reduction of hypothalamic neuronal activity, and increases functional connectivity between the hypothalamus and other reward regions of the brain, indicating that these two sugars regulate feeding behavior through distinct neural circuits. This review article outlines the current findings in fructose-feeding studies in both human and animal models, and discusses the central effects on the CNS that may lead to increased appetite and food intake. Keywords: Fructose, Metabolic syndrome, Appetite, Central nervous system
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".