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Record W2053188966 · doi:10.1196/annals.1306.001

Iron Metabolism and the IRE/IRP Regulatory System: An Update

2004· review· en· W2053188966 on OpenAlexaff
Kostas Pantopoulos

Bibliographic record

VenueAnnals of the New York Academy of Sciences · 2004
Typereview
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsTransferrin receptorFerritinInternal ribosome entry siteCell biologyChemistryTransferrinIron–sulfur clusterMetabolismReceptorTranslation (biology)BiochemistryBiologyMessenger RNAGeneEnzyme

Abstract

fetched live from OpenAlex

Cellular iron homeostasis is accomplished by the coordinated regulated expression of the transferrin receptor and ferritin, which mediate iron uptake and storage, respectively. The mechanism is posttranscriptional and involves two cytoplasmic iron regulatory proteins, IRP1 and IRP2. Under conditions of iron starvation, IRPs stabilize the transferrin receptor and inhibit the translation of ferritin mRNAs by binding to "iron responsive elements" (IREs) within their untranslated regions. The IRE/IRP system also controls the expression of additional IRE-containing mRNAs, encoding proteins of iron and energy metabolism. The activities of IRP1 and IRP2 are regulated by distinct posttranslational mechanisms in response to cellular iron levels. Thus, in iron-replete cells, IRP1 assembles a cubane iron-sulfur cluster, which prevents IRE binding, while IRP2 undergoes proteasomal degradation. IRP1 and IRP2 also respond, albeit differentially, to iron-independent signals, such as hydrogen peroxide, hypoxia, or nitric oxide. Basic principles of the IRE/IRP system and recent advances in understanding the regulation and the function of IRP1 and IRP2 are 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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0020.003
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.004

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.

Opus teacher head0.088
GPT teacher head0.365
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), 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

Citations502
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueAnnals of the New York Academy of SciencesSame topicIron Metabolism and DisordersFrench-language works237,207