Klotho protects INS-1 pancreatic β-cells from senescence and enhances mitochondrial function
Bibliographic record
Abstract
Aging is an important contributing factor for β-cell failure which could lead to the development of type 2 diabetes (T2D). Aging β-cell exhibits signs of senescence and develops senescence-associated secretory phenotype (SASP), causing the senescence and dysfunction of neighboring cells through paracrine action. Klotho is recognized as an anti-aging gene, and the corresponding protein is α-Klotho (KL). KL exerts potent anti-aging effects on multiple cell types, but its role in β-cell aging remains unclear. Here we showed that pancreatic INS-1 cell (a rat insulinoma cell line commonly used to study pancreatic β-cell function) developed the typical hallmarks of senescent cells when treated with doxorubicin in vitro , and this was accompanied by downregulation of endogenous KL expression. Supplementation with exogenous KL protein protected pancreatic INS-1 cell against senescence, as indicated by downregulation of senescent markers and SA-β-gal staining. Notably, these effects were associated with improved mitochondrial ATP production and mitochondrial dynamic balance, as well as reduced ROS production. Our study further revealed that INS-1 cell treated with doxorubicin exhibited a reduced insulin secretion response to glucose stimulation, while supplementation with KL could reverse this effect. Our results indicate the important role of KL in regulating β-cell senescence and provide new mechanistic insights into its role in β-cell aging.
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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".