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Record W3212177669 · doi:10.1684/vir.2021.0920

Flaviviridae and mitochondria: Everything you always wanted to know about their relationship but were afraid to ask

2021· review· en· W3212177669 on OpenAlexaff
Wesley Freppel, Marie Roy, Laurent Chatel‐Chaix

Bibliographic record

VenueVirologie · 2021
Typereview
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsFlaviviridaeBiologyEndoplasmic reticulumMitochondrionVirologyViral replicationZika virusHepatitis C virusVirusOrganelleCell biology

Abstract

fetched live from OpenAlex

Infections with Flaviviridae constitute a major public health concern, especially considering the limited availability of prophylactic and therapeutic treatments. Most notably, the recent emergence of Zika virus in the Americas was associated with the dramatic increase of severe symptoms such as congenital microcephaly, while hepatitis C virus causes the death of approximately 300,000 individuals annually. Flaviviridae have evolved to hijack cellular organelles and to favor their replication, often by divergent molecular mechanisms. In addition to the remodeling of the endoplasmic reticulum, which is required for the replication of the viral genome and the assembly of the neosynthetized virions, Flaviviridae induce drastic morphological alterations of the mitochondria. This is associated with the viral co-opting of several key mitochondrial functions in apoptosis, innate immunity and metabolism. This review recapitulates the current knowledge about the morphological and functional relationship between Flaviviridae and mitochondria and explains how this contributes to the establishment of a cytoplasmic environment which is favorable to viral replication.

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)0.001
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.052
GPT teacher head0.340
Teacher spread0.288 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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