Vitamin D Metabolites; Protective versus Toxic Properties: Molecular and Cellular Perspectives
Bibliographic record
Abstract
Vitamin D plays an essential role in bone metabolism. The discovery that the vitamin D receptor (VDR), a member of the nuclear receptor superfamily, is expressed in most tissues led researchers to investigate other biological actions of vitamin D. These effects were found to include anti-inflammatory effects and anti-atherogenesis, decreased renin activity and biosynthesis, induction of cell differentiation, inhibition of cell growth, and immunomodulation. In spite of the plethora of evidence on the protective effects of vitamin D, the reports on its intoxication still are considerably few. Therefore, in this review we aim to summarize the molecular and cellular bases of the protect-ive and toxic vitamin D actions that are mediated mostly by VDR. This review will also shed light on vitamin D metabolites other than the active metabolite calcitriol and particularly 25-hydroxy vitamin D (25(OH)D), putting emphasis on its magnifying role in vitamin D intoxication. One of the important themes we discuss is defining serum levels of beneficial or toxic effects of other exogenous vitamin D administration and its impact on 25(OH)D serum levels in animals and human subjects.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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 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".