Evidence map›Paper›PMID 30593632›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2019

Live Cell Imaging of Hepatitis C Virus Trafficking in Hepatocytes.

Yasmine Baktash, Glenn Randall

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Yasmine BaktashDepartment of Microbiology, The University of Chicago, Chicago, IL, USA.
Glenn RandallDepartment of Microbiology, The University of Chicago, Chicago, IL, USA. grandall@bsd.uchicago.edu.

Funding

Molecular And Cellular Biology Training ProgramT32GM007183 · NIGMS · UNIVERSITY OF CHICAGO · PI GLICK, BENJAMIN S, RICE, PHOEBE A · 1985 to 2021
$23.9M
Hepatitis C Virus Trafficking in HepatocytesR01AI137514 · NIAID · UNIVERSITY OF CHICAGO · PI Glenn C Randall · 2019 to 2026
$2.7M
Hepatitis C Virus Trafficking in Infected HepatocytesR01AI080703 · NIAID · UNIVERSITY OF CHICAGO · PI RANDALL, GLENN C · 2010 to 2014
$1.7M
Hepatitits C Virus Trafficking in Infected HepatocytesR56AI080703 · NIAID · UNIVERSITY OF CHICAGO · PI RANDALL, GLENN C · 2009 to 2017
$777k
NIAID NIH HHS R01 AI080703NIAID NIH HHS R01 AI137514NIAID NIH HHS R56 AI080703NIGMS NIH HHS T32 GM007183
6 · The paper itself

Abstract

Standard fixed cell confocal microscopy is inherently limited in visualizing dynamic processes involving two- and three-dimensional movement. To overcome these limitations, live cell imaging approaches have been developed to study hepatitis C virus (HCV) entry, replicase protein trafficking, virion assembly, and egress. These studies have relied on fluorescent labeling of viral proteins by epitope tag insertion, genome labeling via nucleophilic dyes, or using lipophilic dyes to label the virion envelope. In this method review, we describe two approaches to study HCV virion trafficking in live cells. Lipophilic labeling of the envelope allows for study of the early events (through virion uncoating/fusion) in the HCV lifecycle. Tetracysteine (TC) tag insertion into the capsid protein permits study of virion assembly and capsid trafficking via binding of a fluorogenic biarsenical dye.

Indexed as

Virus AssemblyVirus InternalizationVirus ReleaseCell LineHepacivirusHepatocytesHumansImage Processing, Computer-AssistedMicroscopy, ConfocalOptical ImagingProtein TransportStaining and LabelingDiDFluorescent labelingHepatitis C virusLive cell imagingTC-coreTetracysteine tagViral entry

Identifiers

PMID30593632
PMCPMC7021324

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.