Induction of PDCD4 by albumin in proximal tubule epithelial cells potentiates proteinuria-induced dysfunctional autophagy by negatively targeting Atg5
Bibliographic record
Abstract
Autophagy dysfunction is a hallmark of type 1 diabetes. However, the precise molecular mechanism of proteinuria-induced dysfunctional autophagy remains unclear. Herein, we investigated the role of programmed cell death 4 (PDCD4) in the regulation of autophagy in the pathogenesis of diabetic kidney disease (DKD) in vivo and in vitro. RT-qPCR, immunohistochemistry (IHC), and western blotting demonstrated an upregulation of Pdcd4 mRNA and protein in streptozotocin (STZ)-induced DKD rats, as compared to the control. In addition, IHC and western blotting of a unilateral ureteral obstruction mouse model showed an upregulation of PDCD4 in the disease group, as compared to their respective controls. IHC analysis of kidney biopsy samples of human DKD patients showed an upregulation of PDCD4 compared to the control. Western blotting of the STZ-induced DKD rat tissues displayed a low microtubule-associated protein 1A/1B-light chain 3 (LC3)-II, as compared to the control. It was found that albumin overload in cultured PTECs upregulated the expression of PDCD4 and p62 and decreased the expression of LC3-II and autophagy-related 5 (Atg5) proteins. The knockout of Pdcd4 in cultured PTECs could reduce albumin-induced dysfunctional autophagy, as evidenced by the recovery of Atg5 and LC3-II protein. The forced expression of PDCD4 could further suppress the expression of the crucial autophagy-related gene Atg5. Evidence suggests that endogenous PDCD4 promotes proteinuria-induced dysfunctional autophagy by negatively regulating Atg5. Therefore, PDCD4 may be a potential therapeutic target in DKD.
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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".