6-OR: PAR2 Downregulates Adipose LPL through MIF—A Novel Adipose Mechanism Contributing to the Development of Hypertriglyceridemia
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Bibliographic record
Abstract
Lipoprotein lipase (LPL) is a key enzyme that hydrolyzes circulating triglycerides to release fatty acid (FA). In adipose tissue, LPL is required for lipid storage. However, it is currently unknown whether alteration of LPL in white adipose tissue (WAT) contributes to the development of hypertriglyceridemia. Our present study indicated that WAT isolated from human obese patients have increased expression of PAR2 which is negatively associated with LPL gene. The reduced LPL expression is also negatively correlated with increased plasma TG levels, suggesting that adipose PAR2 may modulate hyperlipidemia through downregulating LPL. In mice, aging and high palmitic oil diet significantly increased PAR2 expression in adipose tissue which was associated with high plasma MIF levels. PAR2 deficiency attenuates the rise of MIF, suggesting a key role of PAR2 in regulating adipose MIF release. MIF reduced LPL expression and activity in adipocytes. In a MIF overexpressed animal model (Mif lung Tg), high circulating MIF levels inhibited adipose LPL which was associated with increased plasma triglyceride but not fatty acid. Following high palmitic oil diet feeding, adipose LPL expression and activity were also reduced, and this reduction was reversed in PAR2 knockout mice. Interestingly, PAR2 mediated LPL in adipose tissue regulates hypertriglyceridemia through controlling adipocyte lipid storage. In Par2-/- mice, recombinant MIF perfusion recovered high plasma MIF levels, which decreased LPL and attenuated adipocyte lipid storage leading to hypertriglyceridemia. These data together suggest that the downregulation of adipose LPL by PAR2/MIF is an important mechanism for the development of hypertriglyceridemia. Disclosure Y.Huang: None. L.Li: None. L.Chen: None. X.Chen: None. P.Gao: None. Y.Qi: None. D.Qi: None. Funding Canadian Institutes of Health Research (PJT156116)
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
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 it