Consumption of sucrose and high-fructose corn syrup does not increase liver fat or ectopic fat deposition in muscles
Bibliographic record
Abstract
It has been postulated that fructose-induced triglyceride synthesis is augmented when accompanied by glucose. Chronic elevations could lead to excess fat accumulation in the liver and ectopic fat deposition in muscles, which in turn could contribute to the induction of abnormalities in glucose homeostasis, insulin resistance, and the subsequent development of type 2 diabetes. Our objective was to evaluate the effect of the addition of commonly consumed fructose- and (or) glucose-containing sugars in the usual diet on liver fat content and intramuscular adipose tissue. For 10 weeks, 64 individuals (mean age, 42.16 ± 11.66 years) consumed low-fat milk sweetened with either high-fructose corn syrup (HFCS) or sucrose; the added sugar matched consumption levels of fructose in the 25th, 50th, and 90th percentiles of the population. The fat content of the liver was measured with unenhanced computed tomography imaging, and the fat content of muscle was assessed with magnetic resonance imaging. When the 6 HFCS and sucrose groups were averaged, there was no change over the course of 10 weeks in the fat content of the liver (13.32% ± 10.49% vs. 13.21% ± 10.75%; p > 0.05), vastus lateralis muscle (3.07 ± 0.74 g per 100 mL vs. 3.15 ± 0.84 g per 100 mL; p > 0.05), or gluteus maximus muscle (4.08 ± 1.50 g per 100 mL vs. 4.24 ± 1.42 g per 100 mL; p > 0.05). Group assignment did not affect the result (interaction > 0.05). These data suggest that when fructose is consumed as part of a typical diet in normally consumed sweeteners, such as sucrose or HFCS, ectopic fat storage in the liver or muscles is not promoted.
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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".