Plasminogen activator inhibitor‐1 is negatively associated with fasting plasma monounsaturated fatty acids but not influenced by postprandial polyunsaturated fatty acid composition in men with high fasting triacylglycerol
Bibliographic record
Abstract
Increased consumption of dietary monounsaturated fatty acids (MUFA) is associated with a favorable risk factor profile associated with the metabolic syndrome (MetS), including lowered plasminogen activator inhibitor (PAI)‐1. In addition, the postprandial response to dietary fat has emerged as a dynamic metabolic period associated with MetS. Plasma fatty acid composition was measured in men with high fasting triacylglycerol (n=8, HTAG>1.69 mmol/L) and low fasting TAG (n=8, LTAG<1.7 mmol/L). Each subject underwent three postprandial oral fat tolerance tests (OFTT) of 1g/kg body weight emulsified lipids consisting of varied PUFA/saturated fatty acid (P/S) ratios of 0.2, 1.0 and 2.0, with blood collected through 8h. Fasting MUFA was negatively correlated with total PAI‐1 antigen (P<0.001, r=−0.98) and PAI‐1 activity (P<0.02, r=−0.8) in HTAG, but not LTAG. Fasting total PUFA concentration was positively correlated with total PAI‐1 antigen (P=0.03, r=0.75) in HTAG, but not LTAG. There was no difference in postprandial PAI‐1 total or activity in response to three OFTTs with similar MUFA but varied PUFA TAG composition. These data suggest that elevated MUFA concentrations may have beneficial effects on PAI‐1 in HTAG subjects and that postprandial PUFA concentrations do not influence postprandial PAI‐1 in this population. Supported by the Ontario Ministry of Agriculture, Food and Rural Affairs (OMAFRA) and NSERC
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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) | 0.002 | 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".