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Record W2113211898 · doi:10.1681/asn.2009080815

Reduced Hepatic Synthesis of Calcidiol in Uremia

2010· article· en· W2113211898 on OpenAlexafffund
Josée Michaud, Judith Naud, Denis Ouimet, Christian Demers, Jean-Luc Petit, Alain Bonnardeaux, Marielle Gascon‐Barré, Vincent Pichette

Bibliographic record

VenueJournal of the American Society of Nephrology · 2010
Typearticle
Languageen
FieldMedicine
TopicVitamin D Research Studies
Canadian institutionsHôpital Saint-LucCentre Hospitalier de l’Université de MontréalUniversité de MontréalHôpital Maisonneuve-Rosemont
FundersCanadian Institutes of Health Research
KeywordsUremiaInternal medicineEndocrinologySecondary hyperparathyroidismCalcitriolParathyroid hormoneVitamin D and neurologyParathyroidectomyHyperparathyroidismVitaminMedicineChemistryCalcium

Abstract

fetched live from OpenAlex

Calcidiol insufficiency is highly prevalent in chronic kidney disease (CKD), but the reasons for this are incompletely understood. CKD associates with a decrease in liver cytochrome P450 (CYP450) enzymes, and specific CYP450 isoforms mediate vitamin D(3) C-25-hydroxylation, which forms calcidiol. Abnormal levels of parathyroid hormone (PTH), which also modulates liver CYP450, could also contribute to the decrease in liver CYP450 associated with CKD. Here, we evaluated the effects of PTH and uremia on liver CYP450 isoforms involved in calcidiol synthesis in rats. Uremic rats had 52% lower concentrations of serum calcidiol than control rats (P < 0.002). Compared with controls, uremic rats produced 71% less calcidiol and 48% less calcitriol after the administration of vitamin D(3) or 1alpha-hydroxyvitamin D(3), respectively, suggesting impaired C-25-hydroxylation of vitamin D(3). Furthermore, uremia associated with a reduction of liver CYP2C11, 2J3, 3A2, and 27A1. Parathyroidectomy prevented the uremia-associated decreases in calcidiol and liver CYP450 isoforms. In conclusion, these data suggest that uremia decreases calcidiol synthesis secondary to a PTH-mediated reduction in liver CYP450 isoforms.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.884
Threshold uncertainty score0.640

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.319
Teacher spread0.302 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations109
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueJournal of the American Society of NephrologySame topicVitamin D Research StudiesFrench-language works237,207