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Record W2416666529 · doi:10.1172/jci83005

Metabolic regulation of immune responses: therapeutic opportunities

2016· review· en· W2416666529 on OpenAlexaff
Nadine Aßmann, David K. Finlay

Bibliographic record

VenueJournal of Clinical Investigation · 2016
Typereview
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsTrinity College
FundersTrinity College DublinScience Foundation Ireland
KeywordsImmune systemBiologyCell metabolismMetabolic pathwayCell biologySignal transductionImmunityMetabolismCellular metabolismCellMetabolic control analysisT cellImmunologyBiochemistryBiotechnology

Abstract

fetched live from OpenAlex

Immune cell metabolism is dynamically regulated in parallel with the substantial changes in cellular function that accompany immune cell activation. While these changes in metabolism are important for facilitating the increased energetic and biosynthetic demands of activated cells, immune cell metabolism also has direct roles in controlling the functions of immune cells and shaping the immune response. A theme is emerging wherein nutrients, metabolic enzymes, and metabolites can act as an extension of the established immune signal transduction pathways, thereby adding an extra layer of complexity to the regulation of immunity. This Review will outline the metabolic configurations adopted by different immune cell subsets, describe the emerging roles for metabolic enzymes and metabolites in the control of immune cell function, and discuss the therapeutic implications of this emerging immune regulatory axis.

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 score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.268
GPT teacher head0.422
Teacher spread0.155 · 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

Citations97
Published2016
Admission routes1
Has abstractyes

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