Cytochrome P450-mediated metabolism of vitamin D
Bibliographic record
Abstract
The vitamin D signal transduction system involves a series of cytochrome P450-containing sterol hydroxylases to generate and degrade the active hormone, 1α,25-dihydroxyvitamin D3, which serves as a ligand for the vitamin D receptor-mediated transcriptional gene expression described in companion articles in this review series. This review updates our current knowledge of the specific anabolic cytochrome P450s involved in 25- and 1α-hydroxylation, as well as the catabolic cytochrome P450 involved in 24- and 23-hydroxylation steps, which are believed to initiate inactivation of the vitamin D molecule. We focus on the biochemical properties of these enzymes; key residues in their active sites derived from crystal structures and mutagenesis studies; the physiological roles of these enzymes as determined by animal knockout studies and human genetic diseases; and the regulation of these different cytochrome P450s by extracellular ions and peptide modulators. We highlight the importance of these cytochrome P450s in the pathogenesis of kidney disease, metabolic bone disease, and hyperproliferative diseases, such as psoriasis and cancer; as well as explore potential future developments in the field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".