TGF-β1-containing exosomes from cardiac microvascular endothelial cells mediate cardiac fibroblast activation under high glucose conditions
Bibliographic record
Abstract
Cardiac fibroblast (CF)-mediated extracellular matrix (ECM) remodeling is the key pathological basis for the occurrence and development of diabetic cardiomyopathy (DCM); its specific regulatory mechanisms have been widely studied but remain unclear. Exosomes are a type of stable signal transmission medium, and exosome-mediated cell-cell interactions play an important role in DCM. Endothelial cells form an important barrier between circulation and cardiomyocytes, in addition to being an important endocrine organ of the heart and an initial target for hyperglycemia, a key aspect in the development of DCM. We previously showed that exosomes derived from cardiac microvascular endothelial cells (CMECs) under high glucose conditions can be taken up by cardiomyocytes and regulate autophagy, apoptosis, and glucose metabolism. Consequently, in the present study, we focused on how exosomes mediate the interaction between CMECs and CFs. Surprisingly, exosomes derived from CMECs under high glucose were rich in TGF-β1 mRNA, which significantly promoted the activation of CFs. Additionally, exosomes derived from CMECs under high glucose conditions aggravated perivascular and interstitial fibrosis in mice treated with streptozotocin. Herein, we demonstrated for the first time the capacity of exosomes, released by CMECs under high glucose, to mediate fibroblast activation through TGF-β1 mRNA, which may be potentially beneficial in the development of exosome-targeted therapies to control DCM.
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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".