The Association of Lipoprotein Lipase and Phosphatidylinositol 3‐Kinase with Macrophage Lipid Accumulation
Bibliographic record
Abstract
Lipoprotein lipase (LPL) is an extracellular enzyme that hydrolyzes triglycerides and phospholipids within lipoproteins. LPL is expressed in several tissues, including macrophages within atherosclerotic lesions, where it has been shown to promote foam cell formation. Our laboratory previously showed that the hydrolysis products generated by LPL from total lipoproteins, and specifically the free fatty acids (FFA), increased the phosphorylation of the signaling molecule protein kinase B (or Akt). Thus, we hypothesized that the FFA liberated from total lipoproteins by LPL promote lipid accumulation in macrophages in part through a mechanism associated with the phosphatidylinositol 3-kinase (PI3K) signaling pathway. To test this hypothesis, THP-1 macrophages were incubated with a mixture of purified FFA (which matched the concentrations of the FFA species liberated by LPL lipoprotein hydrolysis) for 18 hours in the absence or presence of the PI3K inhibitor LY294002. As expected, Oil Red O staining showed an increased cellular accumulation of lipids following the FFA mixture treatment. THP-1 macrophages in the presence of both the FFA mixture and LY294002 exhibited a 20% decrease of Oil Red O staining (n=9, p<0.0001). However, no differences in Oil Red O staining were observed between THP-1 macrophages incubated with individual species of FFA in the absence or presence of LY294002, thus suggesting that multiple FFA species together are necessary to modulate the PI3K signaling pathway. Overall, our data show that the FFA mixture indeed promotes macrophage lipid accumulation partially through a PI3K pathway. Funded by the Natural Sciences and Engineering Research Council of Canada (grant #402185/2011).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 | 0.000 | 0.001 |
| 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 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".