Phosphorylation Is Involved in the Activation of Metal-regulatory Transcription Factor 1 in Response to Metal Ions
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Bibliographic record
Abstract
We have studied the role of phosphorylation in the activation of metal-regulatory transcription factor-1 (MTF-1) and metallothionein (MT) gene expression. We showed that MTF-1 is phosphorylated in vivo and that zinc stimulates MTF-1 phosphorylation 2-4-fold. Several kinase inhibitors were used to examine the possible involvement of kinase cascades in the activation of MTF-1. Metal-induced MT gene expression was abrogated by protein kinase C (PKC), c-Jun N-terminal kinase (JNK), phosphoinositide 3-kinase, and tyrosine-specific protein kinases inhibitors, as assayed by Northern analysis and by cotransfection experiments using a metal regulatory element-luciferase reporter plasmid. The extracellular signal-activated protein kinase and the p38 kinase cascades did not appear to be essential for the activation of MT gene transcription by metals. By using dominant-negative mutants of PKC, JNK, mitogen-activated kinase kinase 4 (MKK4), and MKK7, we provide further evidence supporting a role for PKC and JNK in the activation of MTF-1 in response to metals. Notably, increased MTF-1 DNA binding in response to zinc and MTF-1 nuclear localization was not inhibited in cells preincubated with the different kinase inhibitors despite strong inhibition of MTF-1-mediated gene expression. This suggests that phosphorylation is essential for MTF-1 transactivation function. We hypothesize that metal-induced phosphorylation of MTF-1 is one of the primary events leading to increased MTF-1 activity. Thus, metal ions such as cadmium could activate MTF-1 and induce MT gene expression by stimulating one or several kinases in the MTF-1 signal transduction pathway.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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 it