Functional regulation of macrophages by Ces1d-mediated lipid signaling in immunometabolism
Bibliographic record
Abstract
OBJECTIVE: Macrophage accumulation in metabolically active tissues during obesity is common in both animals and humans, but the lipid signaling mechanisms that trigger macrophage inflammation remain unclear. This study investigates the role of Ces1d, an unconventional lipase, in regulating macrophage inflammation under nutritional stress. METHODS: , WT) and KO mice were assessed for migration, polarization, and activation. For in vivo experiments, WT and KO mice were induced to obesity via a high-fat diet (HFD) and subjected to metabolic characterization. Adipose tissue, liver, and serum samples were analyzed histologically and biochemically. Endogenous macrophages and T cells from adipose tissue were isolated and analyzed for functional interactions by flow cytometry. RESULTS: Ces1d expression changes during the differentiation of monocytes into macrophages in both mice and humans. Loss of Ces1d causes larger lipid droplets, with increased accumulation of triacylglycerol (TAG) and diacylglycerol (DAG), and impaired lipid signaling in KO macrophages. Lipid dysregulation in macrophages triggers pro-inflammatory activation, enhancing migration, activation, and polarization toward an M1-like phenotype. The pro-inflammatory macrophages further promote CD3+CD8+ T cell accumulation in obese adipose tissue, which contributes to worsened metabolic disorders, including more severe fatty liver, increased local inflammation in adipose tissue, and impaired systemic glucose tolerance in KO mice on a high-fat diet. CONCLUSIONS: This study demonstrates Ces1d is a crucial factor in maintaining lipid homeostasis in macrophages. Loss of Ces1d leads to metabolic dysregulation in macrophages and other immune cells during 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".