P53 mediated regulation of metallothionein transcription in breast cancer cells
Bibliographic record
Abstract
Recent studies have shown that only breast cancer epithelial cells with intact p53 can induce metallothionein (MT) synthesis after exposure to metals. In this study, the potential role of p53 on regulation of MT was investigated. Results demonstrate that zinc and copper increased metal response elements (MREs) activity and MTF-1 expression in p53 positive MN1 and parental MCF7 cells. However, inactivation of p53 by treatment with pifithrin-alpha or the presence of inactive p53 inhibited MRE-dependent reporter gene expression in response to metals. MTF-1 levels remained unchanged after treatment with zinc in cells with nonfunctional p53. The introduction of wild-type p53 in MDD2 cells, containing nonfunctional p53, enhanced the ability of zinc to increase MRE-dependent reporter gene expression. The cellular level of p21Cip1/WAF1 was increased in MDD2 cells after p53 transfection, confirming the presence of active p53. The treatment of MN1 and parental MCF7 with trichostatin A led to a sixfold increase in the MRE activity in response to zinc. On the contrary, MRE activity remained unaltered in MDD2 cells with inactive p53. The above results demonstrate that activation of p53 is an important factor in metal regulation of MT.
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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 | 0.001 |
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".