Inhibition of MCL-1 to eliminate senescent cells and mitigate renal fibrosis in aristolochic acid nephropathy
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The role of tubular epithelial cells (TEC) senescence in the progression from acute kidney injury (AKI) to chronic kidney disease (CKD) remains debated due to the complexity of senescent cell populations and their pro-survival mechanisms. To directly assess the contribution of TEC senescence to AKI-to-CKD progression, we employed an aristolochic acid nephropathy (AAN) mouse model. Here, we demonstrated that AAI-induced DNA damage specifically drives TEC senescence during AKI-to-CKD progression. Concomitant with the emergence of senescence, immunofluorescence staining revealed the expression of anti-apoptotic proteins, including BCL-2, BCL-xL, and MCL-1, within KIM1⁺ tubules—a marker of tubular injury. To further characterize these senescent cells, we integrated this model with snRNA-Seq data and identified a distinct population of KIM1 + senescent TEC exhibiting resistance to apoptosis through upregulation of pro-survival proteins such as MCL-1, BCL-2, and BCL-xL. To evaluate the therapeutic potential of targeting these pathways, we treated AAN mice with the MCL-1-specific inhibitor UMI-77 and the senolytic ABT-263 (targeting BCL-2/BCL-xL) during both the acute and late phases. Interestingly, only UMI-77 administration during the acute phase effectively reduced tubular senescence and mitigated fibrosis. In contrast, late-phase treatment had only marginal benefits. Notably, ABT-263 failed to eliminate senescent cells and instead exacerbated fibrosis, suggesting that while senescent TEC relies on pro-survival mechanisms to evade apoptosis, their dependency on specific anti-apoptotic proteins varies. Our study provides a high-resolution molecular framework for understanding TEC senescence and identifies MCL-1 inhibition as a precise and effective therapeutic strategy to prevent AKI-to-CKD progression, with early intervention being critical for therapeutic success.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 it