ATG7 vs. ATG5: Distinct Autophagy Pathways Shaping TGF-β Signaling and Endothelial Function
Bibliographic record
Abstract
Abstract Autophagy and transforming growth factor-beta (TGF-β) signalling are critical cellular processes that maintain homeostasis and regulate various physiological functions, including endothelial cell function. This study explores the distinct roles of two essential autophagy regulators, autophagy-related gene 5 (ATG5) and ATG7, in modulating TGF-β signalling and endothelial function. To this end, ATG5 and ATG7 were selectively silenced in endothelial cells, with knockdown efficiency confirmed via RT-qPCR and Western blot analyses. Gene expression profiling revealed differential regulation of TGF-β signalling components following ATG5 or ATG7 silencing. Functional assays demonstrated that ATG5 knockdown enhanced endothelial cell proliferation and migration, whereas ATG7 silencing produced distinct, less pronounced effects. Furthermore, downstream effectors of the TGF-β pathway exhibited gene-specific modulation, underscoring divergent roles of ATG5 and ATG7 in this signalling cascade. Collectively, these findings highlight the non-redundant functions of ATG5 and ATG7 in coordinating TGF-β signalling pathways, offering new insights into their contribution to endothelial physiology and potential as therapeutic targets in vascular pathologies.
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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".