Short‐Term Ingestion of Virgin Coconut Oil Improves Endothelial‐Dependent Dilation but not Exercise‐Mediated Hyperemia in Healthy Young Adults
Bibliographic record
Abstract
Virgin coconut oil (VCO) is high in antioxidants (e.g., polyphenols) that may reduce reactive oxygen species‐induced conversion of vascular endothelial‐derived nitric oxide (NO) to toxic peroxynitrite. As such, flow‐mediated dilation (FMD, a surrogate marker of NO bioavailability) and exercise‐mediated hyperemia may be enhanced following short‐term VCO supplementation. However, these potential beneficial effects have never been assessed in humans. We tested the hypotheses that a 4 week VCO supplement (30 ml·day −1 ) would improve resting popliteal artery (PA) FMD and the hyperemic response to aerobic exercise. Thirty‐four young, healthy participants were divided into VCO (n=19, 10♂, 22±2 years, 24±3 kg·m −2 ), and Control (n=15, 10♂, 24±2 years, 24±3 kg·m −2 ) groups. PA‐FMD and PA blood flow were assessed via high‐resolution duplex ultrasonography (Vivid i, GE Healthcare) and analyzed using commercial software (Cardiovascular Suite, Quipu). After resting measurements, a 10‐minute bout of moderate‐intensity (60% heart rate reserve) cycling exercise was completed. PA blood flow was measured for 5‐minutes post‐exercise and total PA blood volume was calculated from the area under the curve. After 4 weeks, PA‐FMD increased (p < 0.05) following VCO supplementation (4.9±0.9% to 5.5±1.2%) with no change (p > 0.9) in the Control group (5.7±2.1% to 5.8±1.9%). There were no differences (both, p > 0.28) in post‐exercise total PA blood volumes in either group (VCO: 495±355 ml to 598±384 ml; Control: 562±362 ml to 488±229 ml). The increased FMD response observed in our young healthy adults suggests that short‐term VCO supplementation has potential as a dietary treatment for populations with elevated ROS levels and reduced vascular endothelial (e.g., older adults, smokers, etc.). However, additional research is required to test this hypothesis. Support or Funding Information Support provided by: Canadian Foundation for Innovation: Leaders Opportunity Fund, and a Faculty of Health Professions Research Development grant. SAR and MWO were recipients of a NS Graduate Scholarship. MWO was awarded a NSHRF Scotia Scholar Award and a Heart & Stroke BrightRed Award. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0.000 |
| 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".