lmmunohistochemical detection of metallothionein in liver, duodenum and kidney after dietary copper-overload in rats
Bibliographic record
Abstract
Metallothionein (MT) has been used in immunohistochemical techniques to indicate presence and distribution of heavy metals within biological tissues.This study describes a comparison of the pattern of MT-immunostaining in the liver, duodenum and kidney during dietary copper overload in rats.Sixteen male 10-week-old Wistar rats were randomly allocated into groups of four.Two groups were fed a pelleted diet containing 1,500 mgkg copper and two control groups received a rodent diet containing 10 mgkg copper.After 6 weeks samples of liver, kidney and duodenum were collected for immunohistochemistry and histology.An indirect immunoperoxidase technique, using monoclonal antibody E9 against horse MT and polyclonal sera against rabbit MT, was employed.Copper-loaded rats had marked MT-immunoreactivity within the nucleus and cytoplasm of many periportal hepatocytes, renal proximal convoluted tubule epithelial cells, intestinal columnar epithelial cells and Paneth cells.Immunohistochemical staining was similar using either mouse anti-MT polyclonal serum, or monoclonal antibody E9.Hepatocytes surrounding inflammatory foci were positive for MT, supporting the proposed role of this protein in free radical scavenging.The presence of MT in the kidney appears to be associated with renal excretion o copper-metallothionein (Cu-MT) in copperloaded rats.Paneth cells were easily detected using MTimmunostaining.MT may play a part in absorption of copper from intestinal contents and possible storage as CU-MT in Paneth cells.The function of Paneth cells remains unknown but the presence of marked MTimmunoreactivity in these cells, observed in copperloaded rats, suggests their involvement in homeostasis and metabolism o copper.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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 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".