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Record W4381033527 · doi:10.1016/j.bj.2023.100624

Sterile inflammation and the NLRP3 inflammasome in cardiometabolic disease

2023· review· en· W4381033527 on OpenAlexafffund
Sungji Cho, Ying Fan, Gary Sweeney

Bibliographic record

VenueBiomedical Journal · 2023
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsYork University
FundersCanadian Institutes of Health Research
KeywordsInflammasomePyrin domainInflammationSteatohepatitisMedicineDiseaseNodNALP3Caspase 1ImmunologyFamilial Mediterranean feverDiabetes mellitusBioinformaticsBiologyFatty liverInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Inflammation plays an important role in the pathophysiology of cardiometabolic diseases. Sterile inflammation, a non-infectious and damage-associated molecular pattern (DAMP)-induced innate response, is now well-established to be closely associated with development and progression of cardiometabolic diseases. The NOD-like receptor (NLR) family pyrin domain-containing 3 (NLRP3) inflammasome is well-established as a major player in sterile inflammatory responses. It is a multimeric cytosolic protein complex which regulates the activation of caspase-1 and subsequently promotes cleavage and release of interleukin (IL)-1 family cytokines, which have a deleterious impact on the development of cardiometabolic diseases. Therefore, targeting NLRP3 itself or the downstream consequences of NLRP3 activation represent excellent potential therapeutic targets in inflammatory cardiometabolic diseases. Here, we review our current understanding of the role which NLRP3 inflammasome regulation plays in cardiometabolic diseases such as obesity, diabetes, non-alcoholic steatohepatitis (NASH), atherosclerosis, ischemic heart disease and cardiomyopathy. Finally, we highlight the potential of targeting NLPR3 or related signaling molecules as a therapeutic approach.

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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.002

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 head0.020
GPT teacher head0.303
Teacher spread0.283 · 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

Citations44
Published2023
Admission routes2
Has abstractyes

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