MétaCan
Menu
Back to cohort
Record W2605241944 · doi:10.1002/iub.1629

Systemic iron homeostasis and erythropoiesis

2017· review· en· W2605241944 on OpenAlexafffund
George Papanikolaou, Kostas Pantopoulos

Bibliographic record

VenueIUBMB Life · 2017
Typereview
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsMcGill UniversityJewish General Hospital
FundersCanadian Institutes of Health Research
KeywordsHepcidinErythropoiesisContext (archaeology)HomeostasisAnemiaHormoneHemochromatosisErythropoietinFerroportinIneffective erythropoiesisImmunologyBiologyPhysiologyEndocrinologyCell biologyChemistryMedicineInternal medicine

Abstract

fetched live from OpenAlex

Iron is an essential nutrient that is potentially toxic due to its redox reactivity. Insufficient iron supply to erythroid cells, the major iron consumers in the body, leads to various forms of anemia. On the other hand, iron overload (hemochromatosis) is associated with tissue damage and diseases of liver, pancreas, and heart. Physiological iron balance is tightly controlled at the cellular and systemic level by iron regulatory proteins (IRP1, IRP2) and the iron regulatory hormone hepcidin, respectively. Underlying mechanisms often intersect to achieve optimal iron utilization, to control immune responses, and to prevent iron toxicity. This review focuses on systemic iron homeostasis in the context of erythropoiesis, a highly iron-demanding process. We discuss the function and regulation of hepcidin by various stimuli, and highlight hepcidin-dependent and -independent mechanisms that link iron utilization with maturation of erythroid progenitor cells. © 2017 IUBMB Life, 69(6):399-413, 2017.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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 head0.089
GPT teacher head0.377
Teacher spread0.288 · 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

Citations120
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueIUBMB LifeSame topicIron Metabolism and DisordersFrench-language works237,207