MétaCan
Menu
Back to cohort
Record W4318208179 · doi:10.3390/v15020351

Mitochondria Dysfunction at the Heart of Viral Myocarditis: Mechanistic Insights and Therapeutic Implications

2023· review· en· W4318208179 on OpenAlexafffund
Yasir Mohamud, Boaz Li, Amirhossein Bahreyni, Honglin Luo

Bibliographic record

VenueViruses · 2023
Typereview
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BCNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaSt. Paul's Foundation
KeywordsMitochondrionMyocarditisCrosstalkViral MyocarditisDilated cardiomyopathyCardiomyopathyBiologyPathogenesisInflammationVirusImmunologyMedicineCell biologyHeart failureInternal medicine

Abstract

fetched live from OpenAlex

The myocardium/heart is the most mitochondria-rich tissue in the human body with mitochondria comprising approximately 30% of total cardiomyocyte volume. As the resident "powerhouse" of cells, mitochondria help to fuel the high energy demands of a continuously beating myocardium. It is no surprise that mitochondrial dysfunction underscores the pathogenesis of many cardiovascular ailments, including those of viral origin such as virus-induced myocarditis. Enteroviruses have been especially linked to injuries of the myocardium and its sequelae dilated cardiomyopathy for which no effective therapies currently exist. Intriguingly, recent mechanistic insights have demonstrated viral infections to directly damage mitochondria, impair the mitochondrial quality control processes of the cell, such as disrupting mitochondrial antiviral innate immune signaling, and promoting mitochondrial-dependent pathological inflammation of the infected myocardium. In this review, we briefly highlight recent insights on the virus-mitochondria crosstalk and discuss the therapeutic implications of targeting mitochondria to preserve heart function and ultimately combat viral myocarditis.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.981
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.131
GPT teacher head0.401
Teacher spread0.270 · 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 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

Citations35
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueVirusesSame topicViral Infections and Immunology ResearchFrench-language works237,207