Effects of renal diseases on the regulation and expression of renal and hepatic drug-metabolizing enzymes: a review
Bibliographic record
Abstract
1. The activity of drug-metabolizing enzymes (DMEs) in extrahepatic organs is highest in the kidneys. Generally, the kidneys contain most, if not all, of the DMEs found in the liver. Surprisingly, some of these DMEs show higher activity in the kidneys than in the liver. 2. Most of the renal DMEs are localized in the cortex of the kidneys, especially in the proximal tubules. DMEs are also found in the distal tubules and collecting ducts. 3. Renal diseases such as acute and chronic renal failure and renal cell carcinoma alter the regulation of both hepatic and extrahepatic phase I and II DMEs. Changes in the expression of these DMEs seem to be tissue and species specific. 4. Generally, there is significant down-regulation of most of the phase I and a few of phase II DMEs at the protein, mRNA and activity levels. Unfortunately, the mechanisms leading to the alteration in DMEs in renal diseases remain unclear, although many theories have been made. 5. The presence of some circulating factors such as cytokines, nitric oxide, parathyroid hormones and increased intracellular calcium play a role in the regulation of DMEs in renal diseases.
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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) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".