Abstract 107: Selective Igf-1 Production By Resident Cardiac Macrophages Orchestrates Adaptive Cardiomyocyte Growth During Hypertensive Stress
Bibliographic record
Abstract
Objective: Adaptive cardiomyocyte growth is an essential compensatory response to hypertension. While hypertension activates cardiac immune cells, their role in adaptation is unclear. Here, we define the transcriptional heterogeneity and functional role of cardiac resident macrophages (RMs) in vivo in hypertensive heart disease. Methods: We performed flow cytometry, immunofluorescence, and single-cell transcriptomics on fate-mapped cardiac RMs isolated from mice with angiotensin II infusion in acute (day 4) and chronic hypertensive stress (day 28). Following inducible depletion of RMs or specific genetic deletion of Igf1 in RMs during hypertension in mice, functional outcomes were tested with echocardiography and immunohistochemistry. Lastly, we also performed single-cell RNA sequencing on human cardiac macrophages from healthy and diseased samples. Results: Cardiac RMs possess numerous transcriptionally diverse cell states with a core repertoire of reparative gene programs that includes high expression of Igf1 in normotensive animals. Individual cell states were differentially responsive during hypertension while all maintained their original transcriptional identity. Hypertension drove selective in situ proliferation and numerical expansion of some cardiac RMs, directly correlating with increased cardiomyocyte size. Inducible ablation of RMs, or selective deletion of RM-derived IGF-1 caused complete absence of adaptive cardiomyocyte growth and development of cardiac dysfunction. Single-cell transcriptomics further identified a conserved IGF1 -expressing macrophage subpopulation in human cardiomyopathy. Conclusions: Here, we defined the absolute requirement of cardiac RM-produced IGF-1 in adaptive cardiomyocyte growth during hypertension, identifying a novel and essential pathway of RM-directed cardiac adaptation to disease.
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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) | 0.002 | 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".