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Record W4394594491 · doi:10.1089/vim.2023.0138

Inflammatory Consequences: Hepatitis C Virus-Induced Inflammasome Activation and Pyroptosis

2024· article· en· W4394594491 on OpenAlexaff
Hannah L. Wallace, Rodney S. Russell

Bibliographic record

VenueViral Immunology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammasome and immune disorders
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsPyroptosisInflammasomeHepatitis C virusCirrhosisLiver diseaseMedicineImmunologyHepatitis CHepatocellular carcinomaDiseaseProinflammatory cytokineVirusInflammationVirologyCancer researchPathologyInternal medicine

Abstract

fetched live from OpenAlex

Hepatitis C virus (HCV), despite the availability of effective direct-acting antivirals (DAAs) that clear the virus from >95% of individuals treated, continues to cause significant health care burden due to disease progression that can lead to fibrosis, cirrhosis, and/or hepatocellular carcinoma. The fact that some people who are treated with DAAs still go on to develop worsening liver disease warrants further study into the immunopathogenesis of HCV. Many viral infections, including HCV, have been associated with activation of the inflammasome/pyroptosis pathway. This inflammatory cell death pathway ultimately results in cell lysis and release of inflammatory cytokines, IL-18 and IL-1β. This review will report on studies that investigated HCV and inflammasome activation/pyroptosis. This includes clinical in vivo data showing elevated pyroptosis-associated cytokines in the blood of individuals living with HCV, studies of genetic associations of pyroptosis-related genes and development of liver disease, and in vitro studies aimed at understanding the mechanism of pyroptosis induced by HCV. Finally, we discuss major gaps in understanding and outstanding questions that remain in the field of HCV-induced pyroptosis.

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)0.000
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 score0.057
Threshold uncertainty score0.826

Codex and Gemma teacher scores by category

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 communication0.0000.000
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 head0.007
GPT teacher head0.229
Teacher spread0.222 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

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