Monocytes increase human cardiac myofibroblast-mediated extracellular matrix remodeling through TGF-β<sub>1</sub>
Bibliographic record
Abstract
Following myocardial infarction (MI), cardiac myofibroblasts remodel the extracellular matrix (ECM), preventing mechanical complications. However, prolonged myofibroblast activity leads to dysregulation of the ECM, maladaptive remodeling, fibrosis, and heart failure (HF). Chronic inflammation is believed to drive persistent myofibroblast activity; however, the mechanisms are unclear. We assessed the influence of peripheral blood monocytes on human cardiac myofibroblast activity in a three-dimensional (3D) ECM microenvironment. Human cardiac myofibroblasts isolated from surgical biopsies of the right atrium and left ventricle were seeded into 3D collagen matrices. Peripheral blood monocytes were isolated from healthy human donors and cocultured with myofibroblasts. Monocytes increased myofibroblast activity measured by collagen gel contraction (baseline: 57.6 ± 5.9% vs. coculture: 65.2 ± 7.1% contraction; P < 0.01) and increased local ECM remodeling quantified by confocal microscopy. Under coculture conditions that allow indirect cellular interaction via paracrine factors but prevent direct cell-cell contact, monocytes had minimal effects on myofibroblast activity (17.9 ± 11.1% vs. 6.4 ± 7.0% increase, respectively; P < 0.01). When cells were cultured under direct contact conditions, multiplex analysis of the coculture media revealed an increase in the paracrine factors TGF-β1 and matrix metalloproteinase 9 compared with baseline (122.9 ± 10.1 pg/ml and 3,496.0 ± 190.4 pg/ml, respectively, vs. 21.5 ± 16.3 pg/ml and 183.3 ± 43.9 pg/ml; P < 0.001). TGF-β blockade abolished the monocyte-induced increase in cardiac myofibroblast activity. These data suggest that direct cell-cell interaction between monocytes and cardiac myofibroblasts stimulates TGF-β-mediated myofibroblast activity and increases remodeling of local matrix. Peripheral blood monocyte interaction with human cardiac myofibroblasts stimulates myofibroblast activity through release of TGF-β1. These data implicate inflammation as a potential driver of cardiac fibrosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 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".