The 3′-untranslated region of the Ste20-like kinase SLK regulates SLK expression
Bibliographic record
Abstract
Ste20-like kinase, SLK, a germinal center kinase found in kidney epithelial cells, signals to promote apoptosis. Expression of SLK mRNA and protein and kinase activity are increased during kidney development and recovery from ischemic acute renal failure. The 3'-untranslated region (3'-UTR) of SLK mRNA contains multiple adenine and uridine-rich elements, suggesting that 3'-UTR may regulate mRNA stability. This was confirmed in COS cell transient transfection studies, which showed that expression of the SLK open-reading frame plus 3'-UTR mRNA was reduced by 35% relative to the open-reading frame alone. To further characterize the SLK-3'-UTR, this nucleotide sequence was subcloned downstream of enhanced green fluorescent protein (EGFP) cDNA. In COS, 293T, and glomerular epithelial cells, expression of EGFP mRNA and protein was markedly reduced in the presence of the SLK-3'-UTR. After transfection and subsequent addition of actinomycin D, EGFP mRNA remained stable in cells for at least 6 h, whereas EGFP-SLK-3'-UTR mRNA decayed with a half-life of approximately 4 h. A region containing five AUUUA motifs within the SLK-3'-UTR destabilized EGFP mRNA. Deletion of this region from the SLK-3'-UTR, in part, restored mRNA stability. By UV cross-linking and SDS-PAGE, the SLK-3'-UTR bound to protein(s) of approximately 30 kDa in extracts of COS cells, glomerular epithelial cells, and kidney. Cotransfection of HuR (a RNA binding protein of approximately 30 kDa) increased the steady-state mRNA level of EGFP-SLK-3'-UTR but not EGFP. Thus the SLK-3'-UTR may interact with kidney RNA-binding proteins to regulate expression of SLK mRNA during kidney development and after ischemic injury.
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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) | 0.002 | 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".