Impact of dairy fat manipulation on endothelial function and lipid regulation in human aortic endothelial cells exposed to human plasma samples: an in vitro investigation from the RESET study
Bibliographic record
Abstract
Abstract Purpose Longer-term intake of fatty acid (FA)-modified dairy products (SFA-reduced, MUFA-enriched) was reported to attenuate postprandial endothelial function in humans, relative to conventional (control) dairy. Thus, we performed an in vitro study in human aortic endothelial cells (HAEC) to investigate mechanisms underlying the effects observed in vivo. Methods This sub-study was conducted within the framework of the RESET study, a 12-week randomised controlled crossover trial with FA-modified and control dairy diets. HAEC were incubated for 24 h with post-intervention plasma samples from eleven adults (age: 57.5 ± 6.0 years; BMI: 25.7 ± 2.7 kg/m2) at moderate cardiovascular disease risk following representative sequential mixed meals. Markers of endothelial function and lipid regulation were assessed. Results Relative to control, HAEC incubation with plasma following the FA-modified treatment increased postprandial NOx production (P-interaction = 0.019), yet up-regulated relative E-selectin mRNA gene expression (P-interaction = 0.011). There was no impact on other genes measured. Conclusion Incubation of HAEC with human plasma collected after longer-term dairy fat manipulation had a beneficial impact on postprandial NOx production. Further ex vivo research is needed to understand the impact of partial replacement of SFA with unsaturated fatty acids in dairy foods on pathways involved in endothelial function.
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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) | 0.000 | 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) | 0.002 | 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".