Macrophage Differentiation Involves Activation of the Unfolded Protein Response
Bibliographic record
Abstract
To determine if the unfolded protein response (UPR) is activated during macrophage differentiation and is cytoprotective to macrophages in atherosclerosis, human peripheral blood monocytes were treated with macrophage colony stimulating factor to induce differentiation. Differentiation was assessed as well as UPR activation. UPR markers upregulated during differentiation included the protein folding chaperones GRP78, GRP94 and calnexin and XBP‐1 mRNA splicing. However, the expression of these UPR markers was temporally distinct from ER stress‐induced UPR, did not saturate as further induction occurred with ER stress and did not involve oxidative stress. A dramatic increase in protein synthesis (31‐fold), measured by 35 S‐ methionine incorporation, preceded UPR activation. Cytoprotection against ER stress followed UPR activation or plasmid‐mediated GRP78 overexpression. In early atherosclerotic lesions of apoE −/− mice, GRP78 was markedly increased in resident macrophages, but not monocytes. Our findings demonstrate that UPR activation occurs as a physiological response to increased protein synthesis during macrophage differentiation and is cytoprotective. This may represent an important mechanism for macrophage survival in atherosclerotic lesions, contributing to lesion development and progression. Supported by the Heart and Stroke Foundation of Ontario (T‐5385) and the CIHR (MOP‐74477).
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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 | 0.000 |
| 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 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".