TREM2hi resident macrophages protect the septic heart by maintaining cardiomyocyte homeostasis
Bibliographic record
Abstract
Abstract Sepsis-induced cardiomyopathy (SICM) is common in septic patients with a high mortality and is characterized by an abnormal immune response. Owing to cellular heterogeneity, understanding the roles of immune cell subsets in SICM has been challenging. Here we identify a unique subpopulation of cardiac-resident macrophages termed CD163 + RETNLA + (Mac1), which undergoes self-renewal during sepsis and can be targeted to prevent SICM. By combining single-cell RNA sequencing with fate mapping in a mouse model of sepsis, we demonstrate that the Mac1 subpopulation has distinct transcriptomic signatures enriched in endocytosis and displays high expression of TREM2 (TREM2 hi ). TREM2 hi Mac1 cells actively scavenge cardiomyocyte-ejected dysfunctional mitochondria. Trem2 deficiency in macrophages impairs the self-renewal capability of the Mac1 subpopulation and consequently results in defective elimination of damaged mitochondria, excessive inflammatory response in cardiac tissue, exacerbated cardiac dysfunction and decreased survival. Notably, intrapericardial administration of TREM2 hi Mac1 cells prevents SICM. Our findings suggest that the modulation of TREM2 hi Mac1 cells could serve as a therapeutic strategy for SICM.
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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 | 0.000 |
| 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".