The Ste20-like kinase SLK promotes p53 transactivation and apoptosis
Bibliographic record
Abstract
Expression and activity of the germinal center kinase [corrected] SLK are increased during kidney development and recovery from renal ischemia-reperfusion injury. SLK promotes apoptosis, in part, via pathway(s) involving apoptosis signal-regulating kinase-1 and p38 mitogen-activated protein kinase. This study addresses the role of p53 as a potential effector of SLK. p53 transactivation was measured after transient transfection of a luciferase reporter plasmid that contains a p53 cis-acting enhancer element. Overexpression of SLK in COS-1 cells and cotransfection of SLK and p53-wild type (wt) cDNAs in glomerular epithelial cells (GECs) stimulated p53 transactivational activity, as measured by a p53 response element-driven luciferase reporter. In GECs, chemical anoxia followed by glucose reexposure (in vitro ischemia-reperfusion) increased p53 reporter activity, and this increase was amplified by overexpression of SLK. Expression of SLK induced p53 phosphorylation on serine (S)-33 and S315. In GECs, cotransfection of SLK with p53-wt, p53-S33A, p53-S315A, or p53-S33A+S315A mutants showed that only the double mutation abolished the SLK-induced increase in p53 reporter activity. SLK-induced stimulation of p53 reporter activity was attenuated by inhibition of JNK. Overexpression of SLK amplified apoptosis induced by subjecting cells to in vitro ischemia-reperfusion injury, while ectopic expression of a dominant negative SLK mutant attenuated the ischemia-reperfusion-induced apoptosis. The p53 transactivation inhibitor pifithrin-alpha significantly attenuated the amount of apoptosis after ischemia-reperfusion and SLK overexpression. Thus SLK induces p53 phosphorylation and transactivation, which enhances apoptosis after in vitro ischemia-reperfusion injury.
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How this classification was reachedexpand
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".