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Record W4403047716 · doi:10.1002/rmv.2586

Crosstalk Between Innate Immunity and Autophagy in Viral Myocarditis Leading to Dilated Cardiomyopathy

2024· review· en· W4403047716 on OpenAlexafffund
Chen Wang, Honglin Luo

Bibliographic record

VenueReviews in Medical Virology · 2024
Typereview
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsMyocarditisDilated cardiomyopathyInnate immune systemCrosstalkAutophagyImmunologyImmunityContext (archaeology)Viral MyocarditisInflammationCardiomyopathyMedicinePathogenesisHeart failureBiologyImmune systemCardiologyGenetics

Abstract

fetched live from OpenAlex

Viral myocarditis, characterised by inflammation of the heart muscle, presents a significant challenge to global public health, particularly affecting younger individuals and often progressing to dilated cardiomyopathy (DCM), a leading cause of heart failure. Despite ongoing research efforts, viable treatments for this condition remain elusive. Recent studies have shed light on the complex interplay between the innate immune response and autophagy mechanisms, revealing their pivotal roles in the pathogenesis of viral myocarditis and subsequent DCM development. This review aims to delve into the recent advancements in understanding the molecular mechanisms and pathways that intersect innate immunity and autophagy in the context of viral myocarditis. Furthermore, it explores the potential therapeutic implications of these findings, offering insights into promising avenues for the management and treatment of this debilitating condition.

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
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
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 head0.077
GPT teacher head0.449
Teacher spread0.372 · 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

Citations8
Published2024
Admission routes2
Has abstractyes

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