Trace metals and over-expression of metallothioneins in bladder tumoral lesions: a case-control study
Bibliographic record
Abstract
Previous studies have provided some evidence of a possible association between cancer and metallothioneins. Whether this relates to an exposure to carcinogenic metals remains unclear. In order to examine the association between the expression of metallothioneins and bladder tumors, and to compare the levels of arsenic, cadmium, chromium, lead and nickel in animals with bladder tumors and animals without bladder tumors, 37 cases of bovine bladder tumors and 17 controls were collected. The detection and quantification of metallothioneins in bladder tissue of both cases and controls was performed by immunohistochemistry. And the quantification of metals in tissue and hair was assessed by inductively coupled plasma – mass spectrometry. Increased expression of metallothioneins was associated with bladder tumors when compared with non-tumoral bladder tissue (OR = 9.3, 95% CI: 1.0 – 480). The concentrations of cadmium, chromium, lead and nickel in hair of cases were significantly higher than those of controls. However, as for the concentration of metals in bladder tissue, the differences were not significant. Though the sample size was small, the present study shows an association between bladder tumors and metallothioneins. Moreover, it shows that concentrations of metals such as cadmium, chromium, lead and nickel in hair may be used as a biomarker of exposure.
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How this classification was reachedexpand
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 | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".