Transcriptomic Analysis of THP‐1 Macrophages Exposed to Lipoprotein Hydrolysis Products Generated by Lipoprotein Lipase
Bibliographic record
Abstract
Macrophage lipoprotein lipase (LPL) induces lipid accumulation and promotes atherosclerosis. However, the effects of lipoprotein hydrolysis products generated by LPL on macrophage-derived foam cell formation are not clearly understood. Thus, we analyzed the transcriptomic response to hydrolysis products via microarray analyses on RNA isolated from human THP-1 macrophages incubated with total lipoprotein hydrolysis products generated by LPL. The expression of 183 transcripts was significantly upregulated and 133 transcripts were significantly downregulated. Bioinformatics analyses revealed that there was a significant over-representation of genes involved in cell cycling, stress response, type I interferon signaling, cellular metal ion homeostasis, sterol metabolism, and nuclease activity. Interestingly, transcripts for 63 small nucleolar RNA were significantly upregulated. We verified the microarray data by quantitative real-time PCR and found that the expression of SNORA56, as well as the expression of genes associated with the cell cycle (PCNA and DKC1 variant 3), stress response (ATF3), type I interferon signaling (IFITM1), and lipid metabolism (CD36 and PLIN2) were significantly affected by LPL hydrolysis products. To determine if the free fatty acid (FFA) component of total lipoprotein hydrolysis products is sufficient to alter the expression of these genes, THP-1 macrophages were also incubated with the total FFA or individual classes of the FFA component. The gene regulation by the FFA component did not mimic that of the hydrolysis products, suggesting that the regulation of gene expression in THP-1 macrophages depends on the specific combination and concentration of lipid species present in the hydrolysis products, and not solely on FFA.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".