Adipocyte death defines macrophage localization and function in adipose tissue of obese mice and humans
Bibliographic record
Abstract
Macrophage infiltration of white adipose tissue (WAT) is implicated in the metabolic complications of obesity. The precipitating event(s) and function(s) of macrophage infiltration into WAT are unknown. We demonstrate that >90% of all macrophages in WAT of obese mice and humans are localized to dead adipocytes, where they fuse to form syncytia that sequester and scavenge the residual "free" adipocyte lipid droplet and ultimately form multinucleate giant cells, a hallmark of chronic inflammation. Adipocyte death increases in obese (db/db) mice (30-fold) and humans and exhibits ultrastructural features of necrosis (but not apoptosis). These observations identify necrotic-like adipocyte death as a pathologic hallmark of obesity and suggest that scavenging of adipocyte debris is an important function of WAT macrophages in obese individuals. The frequency of adipocyte death is positively correlated with increased adipocyte size in obese mice and humans and in hormone-sensitive lipase-deficient (HSL-/-) mice, a model of adipocyte hypertrophy without increased adipose mass. WAT of HSL-/- mice exhibited a 15-fold increase in necrotic-like adipocyte death and formation of macrophage syncytia, coincident with increased tumor necrosis factor-alpha gene expression. These results provide a novel framework for understanding macrophage recruitment, function, and persistence in WAT of obese individuals.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".