D4F alleviates macrophage-derived foam cell apoptosis by inhibiting CD36 expression and ER stress-CHOP pathway
Bibliographic record
Abstract
This study was designed to explore the protective effect of D4F, an apoA-I mimetic peptide, on oxidized LDL (ox-LDL)-induced endoplasmic reticulum (ER) stress-CCAAT/enhancer-binding protein (C/EBP) homologous protein (CHOP) pathway-mediated apoptosis in macrophages. Our results showed that treating apoE knockout mice with D4F decreased the serum ox-LDL level and apoptosis in atherosclerotic lesions with concomitant downregulation of cluster of differentiation 36 (CD36) and inhibition of ER stress. In vitro, D4F inhibited macrophage-derived foam cell formation. Furthermore, like ER stress inhibitor 4-phenylbutyric acid (PBA), D4F inhibited ox-LDL- or tunicamycin (TM, an ER stress inducer)-induced reduction in cell viability and increase in lactate dehydrogenase leakage, caspase-3 activation, and apoptosis. Additionally, like PBA, D4F inhibited ox-LDL- or TM-induced activation of ER stress response as assessed by the reduced nuclear translocation of activating transcription factor 6 and the decreased phosphorylation of protein kinase-like ER kinase and eukaryotic translation initiation factor 2α, as well as the downregulation of glucose-regulated protein 78 and CHOP. Moreover, D4F mitigated ox-LDL uptake by macrophages and CD36 upregulation induced by ox-LDL or TM. These data indicate that D4F can alleviate the formation and apoptosis of macrophage-derived foam cells by suppressing CD36-mediated ox-LDL uptake and subsequent activation of the ER stress-CHOP pathway.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".