Negative Regulation of Mixed Lineage Kinase 3 by Protein Kinase B/AKT Leads to Cell Survival
Bibliographic record
Abstract
Mixed lineage kinase 3 (MLK3) is a mitogen-activated protein kinase kinase kinase (MAPKKK) that activates c-jun N-terminal kinase (JNK) and can induce cell death in neurons. By contrast, the activation of phosphatidylinositol 3-kinase and AKT/protein kinase B (PKB) acts to suppress neuronal apoptosis. Here, we report a functional interaction between MLK3 and AKT1/PKBalpha. Endogenous MLK3 and AKT1 interact in HepG2 cells, and this interaction is regulated by insulin. The interaction domain maps to the C-terminal half of MLK3 (amino acids 511-847), and this region also contains a putative AKT phosphorylation consensus sequence. Endogenous JNK, MKK7, and MLK3 kinase activities in HepG2 cells are significantly attenuated by insulin treatment, whereas the phosphatidylinositol 3-kinase inhibitors LY294002 and wortmannin reversed the effect. Finally, MLK3-mediated JNK activation is inhibited by AKT1. AKT phosphorylates MLK3 on serine 674 both in vitro and in vivo. Furthermore, the expression of activated AKT1 inhibits MLK3-mediated cell death in a manner dependent on serine 674 phosphorylation. Thus, these data provide the first direct link between MLK3-mediated cell death and its regulation by a cell survival signaling protein, AKT1.
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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) | 0.002 | 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".