Acute effects of a reformulated plant-based meat alternative compared to beef within a high-fat meal on inflammatory and metabolic factors: a randomized crossover trial
Bibliographic record
Abstract
Plant-based meat alternative (PBMA) consumption has increased amid significant reformulation efforts. Although reformulated PBMAs have characteristics that could provide cardiometabolic benefits over animal proteins (e.g., higher fiber, certain phytochemicals/micronutrients), their acute health effects remain unclear. Moreover, whether baseline adiposity (i.e., normal weight or overweight/obesity) affects the response to PBMA intake is unknown. We conducted a randomized crossover study where healthy participants (N = 30) with a normal body mass index (BMI; 18.5–24.9 kg/m2; n = 15) or overweight/obese BMI (>25.0 kg/m2; n = 15) consumed two high-fat meals on separate occasions containing a reformulated PBMA (Beyond Meat Cookout ClassicTM) or similar beef product (80% lean ground beef). Meals were matched for energy (950 kcal) and macronutrient matched (71 g fat/31–35 g carbohydrate/41–42 g protein). At each trial, an intravenous catheter was inserted and biomarkers of inflammation (i.e., interleukin (IL)-6, tumor necrosis factor (TNF)-α), intestinal permeability (i.e., lipopolysaccharide binding protein (LBP), soluble CD14 (sCD14), LBP:sCD14 ratio), and metabolic factors (triglycerides, HDL-C, glucose) were measured at baseline and hourly for 4 hours post-meal. Paired t tests and two-way mixed model ANOVAs were used to examine within-meal-condition changes and differences in incremental area under the curve (iAUC) across meal and BMI conditions, respectively. Regardless of protein source, high-fat meals increased IL-6, TNF-α, LBP, sCD14, LBP:sCD14, and triglycerides and decreased HDL-C ( p ≤ 0.01). In BMI subgroup analyses, an interaction effect for IL-6 iAUC was observed ( pMealxBMI < 0.05), but post hoc analyses were not significant ( p ≥ 0.07). Overall, inclusion of a reformulated PBMA within a high-fat meal resulted in a similar cardiometabolic response to a nearly identical meal containing animal protein (ClinicalTrials.gov:NCT06445296).
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".