Influence of habitual high dietary fat intake on endothelium-dependent vasodilation
Bibliographic record
Abstract
High-fat diets are associated with an increased risk of cardiovascular disease. A potential underlying mechanism for the increased cardiovascular risk is endothelial dysfunction. Nitric oxide (NO)-mediated endothelium-dependent vasodilation is critical in the regulation of vascular tone and overall vascular health. The aim of this study was to determine the influence of dietary fat intake on endothelium-dependent vasodilation. Forty-four middle-aged and older sedentary, healthy adults were studied: 24 consumed a lower fat diet (LFD; 29% ± 1% calories from fat) and 20 consumed a high-fat diet (HFD; 41% ± 1% calories from fat). Four-day diet records were used to assess fat intake, and classifications were based on American Heart Association guidelines (<35% of total calories from fat). Forearm blood flow (FBF) responses to acetylcholine, in the absence and presence of the endothelial NO synthase inhibitor N(G)-monomethyl-l-arginine (L-NMMA), as well as responses to sodium nitroprusside were determined by plethysmography. The FBF response to acetylcholine was lower (∼15%; P < 0.05) in the HFD group (4.5 ± 0.2 to 12.1 ± 0.8 mL/100 mL tissue/min) than in the LFD group (4.6 ± 0.2 to 14.4 ± 0.6 mL/100 mL tissue/min). L-NMMA significantly reduced the FBF response to acetylcholine in the LFD group (∼25%) but not in the HFD group. There were no differences between groups in the vasodilator response to sodium nitroprusside. These data indicate that a high-fat diet is associated with endothelium-dependent vasodilator dysfunction due, in part, to diminished NO bioavailability. Impaired NO-mediated endothelium-dependent vasodilation may contribute to the increased cardiovascular risk with high dietary fat intake.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| 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".