Assessing the Effects of Acute and Chronic Whole Apple Consumption on Biomarkers of Inflammation in Overweight and Obese Adults (P21-011-19)
Bibliographic record
Abstract
Systemic low-grade inflammation mechanistically links obesity to impairments in the metabolic processes central to the development of type 2 diabetes and cardiovascular disease. This phenomenon is promoted by digestion of a high-fat meal, whereas whole foods with proposed anti-inflammatory actions, such as apples, may be beneficial. Thus, the current studies aimed to assess the effects of acute and chronic consumption of whole apples on biomarkers of inflammation in overweight and obese adults. Overweight or obese adults in otherwise good health were recruited. With n = 26 (17 female/9 male; mean age 45.5 ± 3.1 y; mean BMI 34.1 ± 0.2 kg/m2), a randomized, crossover trial was conducted to assess the effects of acute (one time) consumption of 3 whole Gala apples (∼200 g) on the 6 h postprandial inflammatory response (e.g., plasma gut-derived lipopolysaccharide (LPS), cytokines) to an oral fat tolerance test (1 g fat/kg body weight). Fasting and 4 h postprandial peripheral blood mononuclear cells (PBMCs) were also isolated from whole blood and stimulated with 10 ng/mL LPS for 24 h to measure secreted cytokines. With n = 46 (32 female/14 male; mean age, 46.2 ± 2.2 y; mean BMI 33.5 ± 0.8 kg/m2), a parallel-arm, randomized, controlled trial was conducted to assess the effects of chronic (6 week) consumption of 3 whole Gala apples per day (∼200 g) on fasting inflammatory markers. Acute apple consumption decreased 4 h postprandial unstimulated (IL-1β, granulocyte-macrophage colony-stimulating factor (GM-CSF), macrophage inflammatory protein (MIP)-1β, TNF-α) and LPS-stimulated (IL-6, TNF-α) PBMC-secreted inflammatory cytokines (P < 0.05, n = 18). Similarly, chronic apple consumption decreased fasting unstimulated (IL-6) and LPS-stimulated (IL-6, INF-γ, TNF-α) PBMC-secreted inflammatory cytokines (P < 0.05; n = 16–18/group), as well as plasma IL-6 (P < 0.05, n = 22/group). Both acute and chronic whole apple consumption may be an effective dietary strategy to mitigate the obesity-associated inflammation that precedes and exacerbates metabolic disease risk. Ontario Ministry of Agriculture, Food & Rural Affairs; Ontario Apple Growers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".