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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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.088
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