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Record W3081231483 · doi:10.1016/j.cytogfr.2020.08.003

Mechanisms of NLRP3 priming in inflammaging and age related diseases

2020· review· en· W3081231483 on OpenAlexfundno aff
Anna Gritsenko, Jack Green, David Brough, Gloria López‐Castejón

Bibliographic record

VenueCytokine & Growth Factor Reviews · 2020
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsnot available
FundersMedical Research CouncilMedical Research Council CanadaWellcome Trust
KeywordsInflammasomeInflammationPriming (agriculture)ImmunologyAgeingPathogenesisInnate immune systemMedicineImmune systemBiologyInternal medicine

Abstract

fetched live from OpenAlex

The NLRP3 inflammasome is a vital part of the innate immune response, whilst its aberrant activation drives the progression of a number of non-communicable diseases. Thus, NLRP3 inflammasome assembly must be tightly controlled at several checkpoints. The priming step of NLRP3 inflammasome activation is associated with increased NLRP3 gene expression, as well as post-translational modifications that control NLRP3 levels and licence the NLRP3 protein for inflammasome assembly. Increasing life expectancy in modern society is accompanied by a growing percentage of elderly individuals. The process of aging is associated with chronic inflammation that drives and/or worsens a range of age related non-communicable conditions. The NLRP3 inflammasome is known to contribute to pathological inflammation in many settings, but the mechanisms that prime NLRP3 for activation throughout aging and related co-morbidities have not been extensively reviewed. Here we dissect the biochemical changes that occur during aging and the pathogenesis of age related diseases and analyse the mechanisms by which they prime the NLRP3 inflammasome, thus exacerbating inflammation.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.024
GPT teacher head0.287
Teacher spread0.263 · 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

Citations125
Published2020
Admission routes1
Has abstractyes

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