Consumption of vegetable oils with different unsaturated fatty acid profiles increases cholesterol efflux from THP‐1 macrophages (269.4)
Bibliographic record
Abstract
Cholesterol efflux (CEx) from peripheral tissues is thought to be cardioprotective. Vegetable oils with different unsaturated fatty acid (UFA) profiles and low in saturated fatty acids (SFA) (<10g /100g) may enhance CEx from lipid laden macrophages. The Canola Oil Multicentre Intervention Trial was a double‐blind, randomized, 5‐period crossover, controlled feeding (weight maintenance) study designed to evaluate the efficacy of five vegetable oil treatments on CEx in individuals at risk for Mets with central obesity. These treatment oils were canola oil (62.8% MUFA, 29.3% PUFA: 19.5% LA, 10% ALA), high oleic canola oil (72% MUFA, 17% PUFA: 15% LA, 2% ALA), high oleic canola oil with DHA (63.8% MUFA, 13% LA, 6% DHA), corn/safflower oil (69.3% LA, 17.6% MUFA), and flax/safflower oil (69.4% PUFA: 37.5% LA, 32% ALA, 17.9% MUFA). Subjects (n=100: 51 women, 49 men) were fed isocaloric, heart healthy diet (50% CHO, 15% PRO, 35% FAT, SFA < 7%) containing one of the five treatment oils incorporated in a smoothie for 4 weeks followed by a 2‐4 week break between diets. CEx was measured via a high‐throughput assay using THP‐1 macrophages incubated with human sera from baseline or post diet treatment. At the end of each treatment, canola oil, high oleic canola oil with DHA, corn/safflower oil and flax/safflower oil increased CEx by 28.5%, 31.6%, 20.7%, 20.1% respectively, compared to baseline values (p<0.05). The increase in CEx following high oleic canola oil consumption was 8% (NS). Predictors of CEx capacity in subjects at risk for MetS with central obesity include gender, weight status and baseline CEx. In summary, vegetable oils high in UFA and low in SFA increase CEx from macrophages. Grant Funding Source : Supported by: Canola Council of Canada
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 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".