Zinc accumulation in N-methyl-N-nitrosourea-induced rat mammary tumors is accompanied by an altered expression of ZnT-1 and metallothionein.
Bibliographic record
Abstract
Zinc is essential for cell proliferation. Several human studies have shown that in breast cancer tissues, zinc concentration expressed on a per tissue weight basis is higher than that in normal breast tissues. However, the mechanisms involved are unknown. N-methyl-N-nitrosourea (MNU)-induced rat mammary tumorigenesis is one of the most widely used rodent mammary tumorigenesis models for studying human breast cancer due to their similarities in hormone dependency, pathogenesis, histological classification, and immunocytochemical markers. This study was to establish if there was an accumulation of zinc in MNU-induced rat mammary tumors and, if there was, to explore the possible mechanisms involved. Sprague-Dawley rats were sham-treated or MNU-treated (50 mg/kg; n = 12) for 100 days. In MNU-induced mammary tumors (mammary tumors), zinc concentration expressed on a per dry weight basis was 12 times of that in normal mammary glands. Moreover, the mRNA level of ZnT-1 (a transporter involved in zinc efflux) in mammary tumors was reduced by 55% as compared with that in normal mammary glands. The mRNA level of Nramp2 (a divalent cation importer) and ZnT-4 (another transporter involved in zinc efflux) was unaffected by MNU-induced mammary tumorigenesis. The mRNA and protein levels of metallothionein (a putative zinc storage protein) in mammary tumors were 1.3 and 3.5 times of that in normal mammary glands, respectively. Collectively, our observations showed that zinc is accumulated in MNU-induced rat mammary tumors and this accumulation is accompanied by an altered expression of ZnT-1 and metallothionein, suggesting that zinc homeostasis might be altered in MNU-induced rat mammary tumorigenesis. Because zinc is essential to cell proliferation and cell proliferation is increased in mammary tumors, zinc accumulation is likely a part of an integrated effort to ensure sufficient zinc supply to sustain tumor growth.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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".