Fibrotic extracellular matrix induces release of extracellular vesicles with pro-fibrotic miRNA from fibrocytes
Bibliographic record
Abstract
RATIONALE: Extracellular vesicles (EVs) are small lipid vesicles, and EV-coupled microRNAs (miRNAs) are important modulators of biological processes. Fibrocytes are circulating bone marrow-derived cells that migrate into the injured lungs and contribute to fibrogenesis. The question of whether EV-coupled miRNAs derived from fibrocytes are able to regulate pulmonary fibrosis has not been addressed yet. METHODS: Pulmonary fibrosis was induced in rats by intratracheal administration of an adenoviral gene vector encoding active transforming growth factor-β1 (TGF-β1) or control vector. Primary fibrocytes and fibroblasts were cultured from rat lungs and were sorted by anti-CD45 magnetic beads. Human circulating fibrocytes and fibrocytes in bronchoalveolar lavage fluid (BALF) were isolated by fibronectin-coated dishes. Fibrocytes were cultured on different stiffness plates or decellularised lung scaffolds. We also determined the effects of extracellular matrix (ECM) and recombinant TGF-β1 on the cellular and EV-coupled miRNA expression of fibrocytes. RESULTS: of fibroblasts. Culturing on rigid plates or fibrotic decellularised lung scaffolds increased miR-21-5 p expression compared with soft plates or normal lung scaffolds. Dissolved ECM collected from fibrotic lungs and recombinant TGF-β1 increased miR-21-5 p expression on fibrocytes, and these effects were attenuated on soft plates. Fibrocytes from BALF collected from fibrotic interstitial pneumonia patients showed higher miR-21-5 p expression than those from other patients. CONCLUSIONS: Our results indicate that ECM contributes to fibrogenesis through biomechanical and biochemical effects on miRNA expression in fibrocytes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".