Weight classification does not influence the short-term endocrine or metabolic effects of high-fructose corn syrup-sweetened beverages
Bibliographic record
Abstract
Obesity and high-fructose corn syrup (HFCS)-sweetened beverages are associated with an increased risk of chronic disease, but it is not clear whether obese (Ob) individuals are more susceptible to the detrimental effects of HFCS-sweetened beverages. The purpose of this study was to examine the endocrine and metabolic effects of consuming HFCS-sweetened beverages, and whether weight classification (normal weight (NW) vs. Ob) influences these effects. Ten NW and 10 Ob men and women who habitually consumed ≤355 mL per day of sugar-sweetened beverages were included in this study. Initially, the participants underwent a 4-h mixed-meal test after a 12-h overnight fast to assess insulin sensitivity, pancreatic and gut endocrine responses, insulin secretion and clearance, and glucose, triacylglycerol, and cholesterol responses. Next, the participants consumed their normal diet ad libitum, with 1065 mL per day (117 g·day(-1)) of HFCS-sweetened beverages added for 2 weeks. After the intervention, the participants repeated the mixed-meal test. HFCS-sweetened beverages did not significantly alter body weight, insulin sensitivity, insulin secretion or clearance, or endocrine, glucose, lipid, or cholesterol responses in either NW or Ob individuals. Regardless of previous diet, Ob individuals, compared with NW individuals, had ∼28% lower physical activity levels, 6%-9% lower insulin sensitivity, 12%-16% lower fasting high-density-lipoprotein cholesterol concentrations, 84%-144% greater postprandial triacylglycerol concentrations, and 46%-79% greater postprandial insulin concentrations. Greater insulin responses were associated with reduced insulin clearance, and there were no differences in insulin secretion. These findings suggest that weight classification does not influence the short-term endocrine and metabolic effects of HFCS-sweetened beverages.
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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 | 0.001 |
| 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".