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Record W2991203943 · doi:10.3389/fmolb.2019.00116

The Role of Iron Regulation in Immunometabolism and Immune-Related Disease

2019· review· en· W2991203943 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

VenueFrontiers in Molecular Biosciences · 2019
Typereview
Languageen
FieldMedicine
TopicErythrocyte Function and Pathophysiology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsImmune systemBiologyOxidative phosphorylationCell biologyInflammationMetabolic pathwayGlycolysisImmune dysregulationCell growthImmunologyMetabolismBiochemistry

Abstract

fetched live from OpenAlex

Immunometabolism explores how the intracellular metabolic pathways in immune cells can regulate their function under different micro-environmental and (patho-)-physiological conditions (Pearce, 2010; Buck et al., 2015; O'Neill and Pearce, 2016). In the last decade great advances have been made in studying and manipulating metabolic programs in immune cells. Immunometabolism has primarily focused on glycolysis, the TCA cycle and oxidative phosphorylation (OXPHOS) as well as free fatty acid synthesis and oxidation. These pathways are important for providing the energy needs of cell growth, membrane rigidity, cytokine production and proliferation. In this review, we will however, highlight the specific role of iron metabolism at the cellular and organismal level, as well as how the bioavailability of this metal orchestrates complex metabolic programs in immune cell homeostasis and inflammation. We will also discuss how dysregulation of iron metabolism contributes to alterations in the immune system and how these novel insights into iron regulation can be targeted to metabolically manipulate immune cell function under pathophysiological conditions, providing new therapeutic opportunities for autoimmunity and cancer.

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)0.000
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: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.262
Teacher spread0.253 · 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