Assessing the Effects of Acute and Chronic Whole Apple Consumption on Metabolic Disease Risk Factors in Overweight and Obese Adults: Apple Study Protocol
Bibliographic record
Abstract
Obesity is characterized by an altered gut microbial profile and corresponding underlying inflammatory state in which various gut- and adipose tissue-derived inflammatory signaling molecules (e.g. endotoxins, cytokines) affect metabolic processes central to the development of type 2 diabetes and cardiovascular disease. While this phenomenon is promoted by digestion of a high-fat meal, whole foods with proposed anti-inflammatory actions, such as apples, may be beneficial but have been less well-studied. Thus, this study will assess the effects of acute and chronic consumption of whole, raw, Ontario-grown Gala apples on the gut microbial profile and immunometabolism in overweight and obese adults. 60 overweight or obese participants in otherwise good health will be recruited. With 30 participants, we will conduct a randomized, crossover trial to assess the effects of acute (one time) consumption of 3 apples on the 2, 4 and 6h postprandial response to ingestion of 1 g fat/kg body weight. Plasma markers of metabolism (triglycerides, glucose, insulin) and inflammation (endotoxin, cytokines) will be measured. Fasted and 4h postprandial peripheral blood mononuclear cells (PBMCs) will be isolated from whole blood and stimulated with 10 ng/mL LPS for 24h to measure secreted cytokines. With all 60 participants, we will conduct a parallel-arm, randomized, controlled trial to assess the effects of chronic (6 week) daily consumption of 3 apples on fasted plasma markers of metabolism and inflammation, PBMC-secreted cytokines in response to LPS stimulation, and the gut microbial profile. This study will be the first to comprehensively assess apples as a dietary component for optimizing food-health relationships, especially those integral to the burgeoning obesity-health crisis.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 0.005 |
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".