The Essential Autophagy Gene ATG7 Modulates Organ Fibrosis via Regulation of Endothelial-to-Mesenchymal Transition
Bibliographic record
Abstract
Pulmonary fibrosis is a progressive disease characterized by fibroblast proliferation and excess deposition of collagen and other extracellular matrix components. Although the origin of fibroblasts is multifactorial, recent data implicate endothelial-to-mesenchymal transition as an important source of fibroblasts. We report herein that loss of the essential autophagy gene ATG7 in endothelial cells (ECs) leads to impaired autophagic flux accompanied by marked changes in EC architecture, loss of endothelial, and gain of mesenchymal markers consistent with endothelial-to-mesenchymal transition. Loss of ATG7 also up-regulates TGFβ signaling and key pro-fibrotic genes in vitro. In vivo , EC-specific ATG7 knock-out mice exhibit a basal reduction in endothelial-specific markers and demonstrate an increased susceptibility to bleomycin-induced pulmonary fibrosis and collagen accumulation. Our findings help define the role of endothelial autophagy as a potential therapeutic target to limit organ fibrosis, a condition for which presently there are no effective available treatments. Background: Endothelial-to-mesenchymal transition (EndMT) is implicated in the development of organ fibrosis. Results: Loss of the autophagy gene ATG7 promotes EndMT and up-regulates TGFβ signaling and the associated pro-fibrotic genes. Endothelial-specific ATG7 knock-out mice exhibited increased bleomycin-induced pulmonary fibrosis. Conclusion: ATG7 is a novel regulator of EndMT-induced organ fibrosis. Significance: Intact endothelial autophagy prevents aberrant EndMT and represents a potential target to limit organ fibrosis.
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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) | 0.001 | 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".