Metformin inhibits the senescence‐associated secretory phenotype by interfering with <scp>IKK</scp>/<scp>NF</scp>‐κ<scp>B</scp> activation
Bibliographic record
Abstract
We show that the antidiabetic drug metformin inhibits the expression of genes coding for multiple inflammatory cytokines seen during cellular senescence. Conditioned medium (CM) from senescent cells stimulates the growth of prostate cancer cells but treatment of senescent cells with metformin inhibited this effect. Bioinformatic analysis of genes downregulated by metformin suggests that the drug blocks the activity of the transcription factor NF-κB. In agreement, metformin prevented the translocation of NF-κB to the nucleus and inhibited the phosphorylation of IκB and IKKα/β, events required for activation of the NF-κB pathway. These effects were not dependent on AMPK activation or on the context of cellular senescence, as metformin inhibited the NF-κB pathway stimulated by lipopolysaccharide (LPS) in ampk null fibroblasts and in macrophages. Taken together, our results provide a novel mechanism for the antiaging and antineoplastic effects of metformin reported in animal models and in diabetic patients taking this drug.
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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".