The effect of sugars in solution on subjective appetite and short‐term food intake in normal weight boys
Bibliographic record
Abstract
The role of sugars in solution in regulating appetite and food intake (FI) has received little investigation in children. Therefore, we examined the effect of sugars solutions (200 kcal) containing glucose, high‐fructose corn syrup‐55 (HFCS‐55), and sucrose on appetite and FI compared to a sucralose control in 9–14 y old normal weight (NW) boys. NW boys (n=15) received in random order four equally sweetened solutions containing sucralose (0 kcal), glucose, HFCS‐55 or sucrose made up to 250 mL with water 2 h after a standardized breakfast. FI (mean kcal ± SEM) at an ad libitum pizza meal was measured 60 min later. Subjective appetite was measured at baseline and at 15, 30, 45, 60 and 90 min. Compared to sucralose (1127 ± 56), glucose reduced FI by 18% (975 ± 58; P < 0.01), however, HFCS‐55 (1075 ± 65) and sucrose (1074 ± 81) failed to result in a statistically significant decrease in FI. Caloric compensation scores for glucose, HFCS‐55 and sucrose were 76%, 26% and 26% respectively. Fat‐mass correlated positively with FI (r = 0.75, P < 0.01). Change from baseline average appetite was higher after sucrose compared to all other treatments (P < 0.01). We conclude that glucose, when compared to the other sugars solutions, produces greater physiological effects on FI in NW boys. Grant Funding Source: MSVU New Investigator Award. Grant Funding Source : MSVU New Investigator Award
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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 | 0.001 |
| 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".