AKI-Induced Senescence as a Key Player in CKD Progression: Insights from an Aristolochic Acid Mouse Model
Bibliographic record
Abstract
Background: Senescence is a persistent cell cycle arrest accompanied by a senescence-associated secretory phenotype (SASP). The role of tubular senescence in driving chronic kidney disease (CKD) following acute kidney injury (AKI) remains controversial due to the multiple animal models used and different timepoints of senescent cell depletion. To accurately represent a direct injury induction of tubular senescence, we utilized a mouse model of Aristolochic acid (AA), a nephrotoxicant known in the clinical setting to promote DNA damage specifically in tubular epithelial cells (TECs). Our model of persistent injury following AA-induction of AKI leads to tubular senescence and allows to study diverse timepoints of CKD progression. Methods: An AKI to CKD model was created by a single intraperitoneal injection of 5 mg/kg of AA into male C57BL/6 mice. In vitro studies utilized 1-10ug/ml AA, and HK-2 (human proximal tubule cell line), mTECs (primary mouse TECs), and NRK-49F (kidney fibroblast cell line). Senolytics (ABT-263) were used to eradicate senescent cells, while senomorphics (Metformin) inhibited SASP. Results: In vivo: Compared to the control, AA-induced tubular senescence as early as 7 days post-injury, as shown by increased p53, p21, p16, γH2AX expression, and β-Gal activity in tubules. AA-treated mice displayed CKD signs of tubular damage and tubulointerstitial fibrosis. Timing of senolytic treatment affected therapeutic outcomes, with early clearance of senescent cells post AA injection protecting against fibrosis. Clearance of SASP factors using Metformin from day 3 post AA injection mitigated renal fibrosis and senescent burden. In vitro: AA-induced senescence in HK-2 and mTECs. Senescent HK-2 cell-derived conditioned medium promoted epithelial-to-mesenchymal transition in HK-2 cells and fibroblast-to-myofibroblast transition in NRK-49F cells, which was reversed by Metformin treatment. Conclusions: Using a model of specific tubular DNA damage, our data reveal that: i) TEC senescence is a key link in the AKI to CKD transition; ii) Precise timing of senescent cell removal by senolytic treatment is critical to achieving therapeutic benefits; iii) Therapeutic inhibition of SASP by senomorphics reduces renal fibrosis and senescence, offering a potential alternative to senolytics. Funding: Government Support - Non-U.S.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".