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Record W4383710907 · doi:10.1111/imr.13235

Ferroptosis in immunostimulation and immunosuppression

2023· review· en· W4383710907 on OpenAlexfundno aff
Daolin Tang, Guido Kroemer, Rui Kang

Bibliographic record

VenueImmunological Reviews · 2023
Typereview
Languageen
FieldMedicine
TopicFerroptosis and cancer prognosis
Canadian institutionsnot available
FundersInstitut National Du CancerInstitut Universitaire de FranceLigue Contre le CancerFondation pour la Recherche MédicaleAgence Nationale de la RechercheUniversité de ParisAssociation pour la Recherche sur le CancerSeerave FoundationCentre National de la Recherche ScientifiqueNational Institutes of HealthEquipexNational Cancer InstituteLabex Immuno-OncologyCNIBEuropean Commission
KeywordsImmune systemContext (archaeology)BiologyProgrammed cell deathImmunosuppressionImmunologyInflammationImmunityLytic cycleImmune toleranceMulticellular organismCell biologyCellApoptosisVirusGenetics

Abstract

fetched live from OpenAlex

Ferroptosis is a form of iron-dependent regulated cell death characterized by the accumulation of toxic lipid peroxides, particularly in the plasma membrane, leading to lytic cell death. While it plays a crucial role in maintaining the overall health and proper functioning of multicellular organisms, it can also contribute to tissue damage and pathological conditions. Although ferroptotic damage is generally recognized as an immunostimulatory process associated with the release of damage-associated molecular patterns (DAMPs), the occurrence of ferroptosis in immune cells or the release of immunosuppressive molecules can result in immune tolerance. Consequently, there is ongoing exploration of targeting the upstream signals or the machinery of ferroptosis to therapeutically enhance or inhibit the immune response. In addition to introducing the core molecular mechanisms of ferroptosis, we will focus on the immune characteristics of ferroptosis in pathological conditions, particularly in the context of infection, sterile inflammation, and tumor immunity.

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)0.001
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 score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.229
GPT teacher head0.442
Teacher spread0.212 · 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

Citations103
Published2023
Admission routes1
Has abstractyes

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