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Record W4408885196 · doi:10.1093/hmg/ddae177

Dual faces of itaconate and its derivatives: exploring diverse biological functions in immunity and infectious diseases

2025· article· en· W4408885196 on OpenAlexaff
Cecilie Poulsen, Dominic G. Roy, David Olagnier

Bibliographic record

VenueHuman Molecular Genetics · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune cells in cancer
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de MontréalInstitute for Research in Immunology and Cancer
FundersFrimodt-Heineke FondenDanmarks Frie ForskningsfondLundbeckfondenHørslev-FondenKræftens Bekæmpelse
KeywordsBiologyImmunityImmunologyComputational biologyVirologyImmune system

Abstract

fetched live from OpenAlex

The intersection of immunology and infectious diseases has been revolutionized by the emergence of immunometabolism, highlighting the critical role of metabolic processes in regulating immune responses. In recent years, itaconate alongside its derivatives dimethyl-itaconate (DMI) and 4-octyl-itaconate (4-OI), have received attention for their potent immunomodulatory and antimicrobial properties. This review examines the unique roles of itaconate and its derivatives in modulating immune functions and their implications in infectious diseases. We also explore their structural and functional discrepancies. Notably, while itaconate generally exhibits anti-inflammatory and antimicrobial effects, its derivatives may operate through distinct mechanisms, often exhibiting enhanced electrophilic properties. This review of recent research underscores the potential of itaconate and its derivatives as therapeutic agents, paving the way for future clinical applications in managing inflammation and infectious diseases.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.038
GPT teacher head0.273
Teacher spread0.235 · 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 designBench or experimental
Domainnot available
GenreEmpirical

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

Citations4
Published2025
Admission routes1
Has abstractyes

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