The activation state of macrophages alters their ability to suppress preadipocyte apoptosis
Bibliographic record
Abstract
Adipose tissue contains macrophages whose state of activation is regulated as obesity develops. Macrophage-secreted factors influence critical processes involved in adipose tissue homeostasis, including preadipocyte proliferation and differentiation into adipocytes. Macrophage-conditioned medium (MacCM) from J774A.1 macrophages protects 3T3-L1 preadipocytes from apoptosis through platelet-derived growth factor (PDGF) signaling. Here, we investigated the effect of macrophage activation on MacCM-dependent preadipocyte survival. MacCM was prepared following activation of either J774A.1 macrophages with lipopolysaccharide (LPS) or human primary monocyte-derived macrophages (MD-macrophages) with LPS or interleukin 4 (IL4). 3T3-L1 and human primary preadipocytes were induced to undergo apoptosis in MacCM, and apoptosis was quantified by cell enumeration or Hoechst nuclear staining. Preadipocyte PDGF signaling was assessed by immunoblot analysis of phosphorylated PDGF receptor, Akt, and ERK1/2. Pro-inflammatory activation of J774A.1 macrophages with LPS inhibited the pro-survival activity of MacCM on 3T3-L1 preadipocytes, despite intact PDGF signaling. Upregulation of macrophage tumor necrosis factor a (TNFα) expression occurred in response to LPS, and TNFα was demonstrated to be responsible for the inability of LPS-J774A.1-MacCM to inhibit preadipocyte apoptosis. Furthermore, MacCM from human MD-macrophages (MD-MacCM) inhibited apoptosis of primary human preadipocytes. MD-MacCM from LPS-treated macrophages, but not IL4-treated anti-inflammatory macrophages, was unable to protect human preadipocytes from cell death. In both murine cell lines and human primary cells, pro-inflammatory activation of macrophages inhibits their pro-survival activity, favoring preadipocyte death. These findings may be relevant to preadipocyte fate and adipose tissue remodeling in obesity.
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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) | 0.000 | 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) | 0.000 | 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".