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Record W4296425610 · doi:10.3390/pathogens11091005

MicroRNA-122 Regulation of HCV Infections: Insights from Studies of miR-122-Independent Replication

2022· review· en· W4296425610 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuePathogens · 2022
Typereview
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsUniversity of Saskatchewan
FundersCanadian Institutes of Health ResearchUniversity of Saskatchewan
KeywordsmicroRNAVirologyHepatitis C virusMiR-122Untranslated regionViral replicationBiologyVirusTranslation (biology)Three prime untranslated regionViral life cycleRNAMessenger RNAGeneGenetics

Abstract

fetched live from OpenAlex

Despite the advancement in antiviral therapy, Hepatitis C remains a global health challenge and one of the leading causes of hepatitis related deaths worldwide. Hepatitis C virus, the causative agent, is a positive strand RNA virus that requires a liver specific microRNA called miR-122 for its replication. Unconventional to the canonical role of miRNAs in translation suppression by binding to 3'Untranslated Region (UTR) of messenger RNAs, miR-122 binds to two sites on the 5'UTR of viral genome and promotes viral propagation. In this review, we describe the unique relationship between the liver specific microRNA and HCV, the current knowledge on the mechanisms by which the virus uses miR-122 to promote the virus life cycle, and how miR-122 impacts viral tropism and pathogenesis. We will also discuss the use of anti-miR-122 therapy and its impact on viral evolution of miR-122-independent replication. This review further provides insight into how viruses manipulate host factors at the initial stage of infection to establish a successful infection.

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.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.188
GPT teacher head0.430
Teacher spread0.243 · 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