Hippo-deficient cardiac fibroblasts differentiate into osteochondroprogenitors
Bibliographic record
Abstract
Abstract Cardiac fibrosis, a common pathophysiology associated with various heart diseases, occurs from the excess deposition of extracellular matrix (ECM) 1 . Cardiac fibroblasts (CFs) are the primary cells that produce, degrade, and remodel ECM during homeostasis and tissue repair 2 . Upon injury, CFs gain plasticity to differentiate into myofibroblasts 3 and adipocyte-like 4,5 and osteoblast-like 6 cells, promoting fibrosis and impairing heart function 7 . How CFs maintain their cell state during homeostasis and adapt plasticity upon injury are not well defined. Recent studies have shown that Hippo signalling in CFs regulates cardiac fibrosis and inflammation 8–11 . Here, we used single-nucleus RNA sequencing (snRNA-seq) and spatially resolved transcriptomic profiling (ST) to investigate how the cell state was altered in the absence of Hippo signaling and how Hippo-deficient CFs interact with macrophages during cardiac fibrosis. We found that Hippo-deficient CFs differentiate into osteochondroprogenitors (OCPs), suggesting that Hippo restricts CF plasticity. Furthermore, Hippo-deficient CFs colocalized with macrophages, suggesting their intercellular communications. Indeed, we identified several ligand-receptor pairs between the Hippo-deficient CFs and macrophages. Blocking the Hippo-deficient CF-induced CSF1 signaling abolished macrophage expansion. Interestingly, blocking macrophage expansion also reduced OCP differentiation of Hippo-deficient CFs, indicating that macrophages promote CF plasticity.
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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".