Effect of a single ultra processed meal on myocardial endothelial function, adenosine mediated effects and cognitive performances
Bibliographic record
Abstract
Consumption of ultra-processed foods has been linked to various adverse health effects; however, the mechanisms underlying these effects remain poorly understood. This study aimed to evaluate the impact of a single ultra-processed meal on myocardial blood flow (MBF), measured using positron emission tomography/computed tomography (PET/CT), and its effects on cognitive performance. Fourteen healthy adult males were enrolled in a randomized crossover trial, receiving either a non-ultra-processed meal (comprising foods from NOVA groups 1 to 3) or an ultra-processed meal (comprising foods from NOVA groups 1 to 4) before crossing over to the alternate meal. After each meal, rubidium-chloride PET/CT scans were conducted at baseline and during intermediate (80 µg/kg/min) and high-dose adenosine (140 µg/kg/min). Neuropsychological testing followed each meal. MBF and MFR at intermediate-dose adenosine was significantly higher after the ultra-processed meal compared to the non-ultra-processed meal (1.62 vs. 1.22 mL/min/g, p = 0.015, and 2.43 vs. 1.88, p = 0.012, respectively), with a mean relative difference of 40.7%. No significant differences were observed between the meals at baseline or high-dose adenosine for both MBF and MFR. When considering carry-over and learning effects, overall performance on neuropsychological testing was worse following the ultra-processed meal during the first period. In healthy adult males, a single ultra-processed meal enhanced adenosine-mediated MBF and MFR at intermediate-dose adenosine and was associated with potentially reduced cognitive performance compared to a non-ultra-processed meal.Trial registration number: NCT06353009 (ClinicalTrials.gov ID). Trial registration Date: 08/04/2024 https://clinicaltrials.gov/study/NCT06353009 .
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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) | 0.001 | 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 | 0.000 | 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".