Choline metabolism underpins macrophage IL-4 polarization <i>in vitro</i> and <i>in vivo</i>
Bibliographic record
Abstract
Abstract Choline homeostasis in macrophage biology is important for LPS-polarized inflammation. In macrophages, choline mainly supports phosphatidylcholine (PC) synthesis, which is crucial for membrane production and cytokine secretion. Here, we examined choline metabolism in IL-4 polarized macrophages in vitro and in vivo. Like LPS, IL-4 increased choline transporter-like protein 1 (CTL1) expression, choline uptake and the incorporation of choline into PC. Targeted lipidomics analysis revealed increased PC content in IL-4-polarized macrophages, with an enrichment in low-saturated species. Pharmacological inhibition of choline uptake/choline kinase with hemicholinium-3 or RSM-932a showed no effect on certain hallmark IL-4-induced macrophage genes (Chil3, Mrc1, Arg1) but significantly reduced the transcript and protein expression of RELMα. Consistent with the function of RELMα in wound healing, 3T3-L1 cells healed more slowly in a scratch wound assay with conditioned media from IL-4 polarized macrophages in which choline metabolism was inhibited compared to vehicle-treated conditioned media. In addition, inhibiting choline metabolism completely prevented PD-L2 upregulation and increased PD-L1 expression on IL-4-polarized macrophages, together with suppressed cellular respiration and increased glycolysis. Furthermore, in vivo administration of RSM-932a (3 mg/kg i.p.) in C57BL/6J mice lowered RELMα in macrophages, decreased PD-L2 and increased PD-L1, and resulted in a loss of resident peritoneal F4/80hi macrophages. Choline represents an underappreciated regulator of macrophage immunometabolism and strategies to target macrophage choline uptake or choline metabolism may be therapeutically valuable.
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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".