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Record W4220978255 · doi:10.3390/nu14061312

Mechanisms of Feedback Regulation of Vitamin A Metabolism

2022· review· en· W4220978255 on OpenAlexafffund
C.M. O'Connor, Parisa Varshosaz, Alexander R. Moise

Bibliographic record

VenueNutrients · 2022
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRetinoids in leukemia and cellular processes
Canadian institutionsLaurentian UniversityNOSM University
FundersNatural Sciences and Engineering Research Council of CanadaNational Institutes of Health
KeywordsRetinoic acidRetinoidVitaminBiologyHomeostasisImmune systemVitamin D and neurologyMetaboliteMetabolismCell biologyBiochemistryEndocrinologyImmunologyGene

Abstract

fetched live from OpenAlex

Vitamin A is an essential nutrient required throughout life. Through its various metabolites, vitamin A sustains fetal development, immunity, vision, and the maintenance, regulation, and repair of adult tissues. Abnormal tissue levels of the vitamin A metabolite, retinoic acid, can result in detrimental effects which can include congenital defects, immune deficiencies, proliferative defects, and toxicity. For this reason, intricate feedback mechanisms have evolved to allow tissues to generate appropriate levels of active retinoid metabolites despite variations in the level and format, or in the absorption and conversion efficiency of dietary vitamin A precursors. Here, we review basic mechanisms that govern vitamin A signaling and metabolism, and we focus on retinoic acid-controlled feedback mechanisms that contribute to vitamin A homeostasis. Several approaches to investigate mechanistic details of the vitamin A homeostatic regulation using genomic, gene editing, and chromatin capture technologies are also discussed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.951
Threshold uncertainty score0.871

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.020
GPT teacher head0.277
Teacher spread0.257 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations53
Published2022
Admission routes2
Has abstractyes

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