Predominance of a Proinflammatory Phenotype in Monocyte-Derived Macrophages From Subjects With Low Plasma HDL-Cholesterol
Bibliographic record
Abstract
OBJECTIVE: Reduced plasma concentrations of high-density lipoprotein-cholesterol (HDL-C) are a significant risk factor for cardiovascular disease. Mechanisms that regulate HDL-C concentrations represent an important area of investigation. METHODS AND RESULTS: Comparative transcriptome analyses of monocyte-derived macrophages (MDM) from a large population of low HDL-C subjects and age- and sex-matched controls revealed a cluster of inflammatory genes highly expressed in low HDL-C subjects. The expression levels of peroxisome proliferator activated receptor (PPAR) gamma and several antioxidant metallothionein genes were decreased in MDM from all low HDL-C groups compared with controls, as was the expression of other genes regulated by PPARgamma, including CD36, adipocyte fatty acid binding protein (FABP4), and adipophilin (ADFP). In contrast, PPARdelta expression was increased in MDM from low HDL-C groups. Quantitative RT-PCR corroborated all major findings from the microarray analysis in two separate patient cohorts. Expression of several inflammatory cytokine genes including interleukin 1beta, interleukin 8, and tumor necrosis factor alpha were highly increased in low HDL-C subjects. CONCLUSIONS: The activated proinflammatory state of monocytes and MDM in low HDL-C subjects constitutes a novel parameter of risk associated with HDL deficiency, related to altered expression of metallothionein genes and the reciprocal regulation of PPARgamma and PPARdelta.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".