Endothelin‐1–Mediated Alteration of Metallothionein and Trace Metals in the Liver and Kidneys of Chronically Diabetic Rats
Bibliographic record
Abstract
In the present study, the role of endothelin-1 (ET-1) on alterations of hepatic and renal metallothionein (MT) and trace metals (Zn, Cu, and Fe) were investigated in streptozotocin (STZ)-induced diabetic rats. Diabetic rats, age- and sex-matched controls, as well as control and diabetic animals on a dual ETA/ETB receptor blocker, bosentan, were investigated after 6 months of follow-up. MT was measured by cadmium-heme assay. Metals were measured by atomic absorption spectrometer. ET-1 mRNA was analyzed by reverse transcriptase-polymerase chain reaction (RT-PCR) technique. Hepatic and renal ET-1 mRNA was increased in diabetic rats as compared to control rats, along with an increase in both hepatic and renal MT proteins. The increased hepatic MT protein level was associated with decreases in hepatic Cu and Fe, whereas increased renal MT was associated with increases in renal Cu and Fe accumulation. Zn levels were unaltered in both organs in diabetic rats. Bosentan treatment partially prevented the increase in MT levels in both liver and kidney, along with reduced serum creatinine and increased urinary creatinine levels. Further bosentan treatment corrected the increased Cu and Fe levels in the kidney in diabetic rats, but reduced hepatic Cu and Fe levels. No significant effects of bosentan treatment on nondiabetic rats were observed. The data suggest that the possible effects of ET antagonism in diabetes may be mediated via changes in MT and trace metals.
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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 | 0.001 | 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) | 0.001 | 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".