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Record W2118295898 · doi:10.4049/jimmunol.1001512

Cutting Edge: Proteolytic Inactivation of Poly(ADP-Ribose) Polymerase 1 by the Nlrp3 and Nlrc4 Inflammasomes

2010· article· en· W2118295898 on OpenAlexaff
R. K. Subbarao Malireddi, Sirish K. Ippagunta, Mohamed Lamkanfi, Thirumala‐Devi Kanneganti

Bibliographic record

VenueThe Journal of Immunology · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsBiotechnology Research Institute
FundersNational Institute of Arthritis and Musculoskeletal and Skin DiseasesTakeda OncologyNational Cancer InstituteYale UniversityNational Institutes of HealthAmerican Lebanese Syrian Associated CharitiesNational Institute of Allergy and Infectious DiseasesVlaamse regering
KeywordsInflammasomePyroptosisNLRC4Poly ADP ribose polymeraseAIM2Caspase 1Cell biologyPARP1ApoptosisCaspaseNLRP1ChemistryProgrammed cell deathBiologyPolymeraseMolecular biologyBiochemistryDNA

Abstract

fetched live from OpenAlex

Caspase-mediated cleavage of the DNA damage sensor poly(ADP-ribose) polymerase 1 (PARP1) is a hallmark of apoptosis. However, it remains unclear whether PARP1 is processed during pyroptosis, a specialized cell-death program that occurs upon activation of caspase-1 in inflammasome complexes. In this article, we show that activation of the Nlrp3 and Nlrc4 inflammasomes induces processing of full-length PARP1 into a fragment of 89 kDa in a stimulus-dependent manner. Macrophages deficient for caspase-1 and those lacking the inflammasome adaptors Nlrp3, Nlrc4, and ASC were highly resistant to cleavage, whereas macrophages lacking the downstream inflammasome effector caspase-7 were partially protected. A modest, but statistically significant, reduction in Nlrp3 inflammasome-induced pyroptosis was observed in PARP1 knockout macrophages. Thus, protease-mediated inactivation of PARP1 is a shared feature of apoptotic, necrotic, and pyroptotic cells.

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 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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.304

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.003
GPT teacher head0.213
Teacher spread0.209 · 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 teacher head, 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

Citations137
Published2010
Admission routes1
Has abstractyes

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