Acute glycemic and blood lipid response to the ingestion of a candy bar–like protein supplement compared with its candy bar counterpart
Bibliographic record
Abstract
Candy bar-like protein supplements are sometimes consumed for their sugar alcohol content, which lowers the glycemic response. The purpose of this study was to determine the acute glycemic and blood lipid response to the ingestion of a candy bar-like protein supplement compared with its candy bar counterpart. In a crossover design, 5 males and 5 females (N = 10; age, 24 ± 5.5 years; height, 174 ± 8.3 cm; weight, 80 ± 21.9 kg) consumed a candy bar (CBR) or a similar protein bar (PBR) after a 10-h fast. Blood draws occurred at baseline and at 15, 30, 45, and 60 min after consumption and were analyzed for blood glucose, insulin, and lipid profiles. A 2×5 ANOVA was used, with Student's t tests for significant interactions. A significant (p < 0.05) blood glucose time effect occurred in both groups, with a more profound glucose response from the CBR at 15 min (CBR: 6.2 ± 0.8 mmol·L(-1); PBR: 4.9 ± 0.5 mmol·L(-1)). Triglycerides increased significantly (p < 0.05), independent of group, peaking at 60 min (Δ CBR: 0.8 ± 0.3 mmol·L(-1); Δ PBR: 1.3 ± 0.3 mmol·L(-1)). Insulin increased significantly (p < 0.05), independent of group, peaking at 15 min (Δ CBR: 42 ± 27 μIU·mL(-1); Δ PBR: 25 ± 11 μIU·mL(-1)). No significant change (p > 0.05) was observed in total cholesterol. Blood glucose, triglycerides, and insulin all increased significantly in response to both CBR and PBR consumption. The CBR elicited a greater effect on blood glucose; however, the PBR had a strong impact on serum triglycerides and insulin.
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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) | 0.001 | 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 | 0.001 | 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".