Preadipocyte apoptosis is prevented by macrophage-conditioned medium in a PDGF-dependent manner
Bibliographic record
Abstract
Obesity is associated with macrophage accumulation and inflammation in adipose tissue. Macrophage-secreted factors have been reported to inhibit the differentiation of preadipocytes into adipocytes and to modulate adipogenic extracellular matrix gene expression. To enlarge our understanding of macrophages and the scope of their interactions with preadipocytes, we investigated their effect on preadipocyte survival. Acute exposure of 3T3-L1 preadipocytes to J774A.1 macrophage-conditioned medium (MacCM) stimulated platelet-derived growth factor receptor (PDGFR) tyrosine phosphorylation by 4.1-fold. There were significant increases in the phosphocontent of downstream PDGFR targets Akt and ERK1/2 (5.3-fold and 2.4-fold, respectively) that were inhibited by PDGF immunoneutralization or by the selective PDGFR inhibitor imatinib. Serum-free J774A.1-MacCM or RAW264.7-MacCM completely prevented 3T3-L1 preadipocyte apoptosis normally induced by serum deprivation. Addition of PDGF alone to serum-free control medium was sufficient to prevent 3T3-L1 preadipocyte apoptosis. Inhibition of PDGFR activation by MacCM, either by addition of imatinib or by PDGF immunodepletion of MacCM, effectively disrupted the prosurvival effect. In summary, our data indicate that MacCM promotes preadipocyte survival in a PDGF-dependent manner.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".