Metallothionein‐dependent regulation of the abundance of the labile intracellular pool of zinc in 3T3 cells
Bibliographic record
Abstract
Abundance of the labile intracellular pool of zinc critically influences cell proliferation and apoptosis. Homeostasis of the labile intracellular pool of zinc remains to be delineated. The objective of this study was to establish the role of metallothionein (MT) in the homeostasis of the labile intracellular pool of zinc. MT1 was first cloned into pEGSH and subsequently transfected into ER‐NIH 3T3 cells. ER‐NIH 3T3 (3T3; the control), ER‐NIH 3T3:pEGSH (3T3pEGSH; the plasmid control), and ER‐NIH 3T3:pEGSH‐MT1 (3T3MT1) cells were cultured in DMEM containing 10% FBS and L‐Gln at 37°C in 5% CO 2 for 6 days (1.0 × 10 5 cells/T75). MT1 mRNA abundance in 3T3MT1 cells was significantly higher than in 3T3 (2‐folds) and 3T3pEGSH (3‐folds) cells. MT1 protein level in 3T3MT1 cells was significantly increased compared to its level in 3T3 (1.9‐folds) and 3T3pEGSH (1.4‐folds) cells. 3T3MT1 cells also contained more total zinc than 3T3 (40%) and 3T3pEGSH (20%) cells. The labile intracellular pool of zinc in 3T3MT1 cells was clearly more abundant than in the controls. In summary, higher MT1 expression increased the abundance of the labile intracellular pool of zinc in 3T3 cells, demonstrating that MT1 plays a direct role in the homeostasis of the labile intracellular pool of zinc. (Supported by NSERC)
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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) | 0.001 | 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".