Evidence map›Paper›PMID 24205826›Full record

ArticleJournal of viral hepatitis2014

Identification of novel human kinases that suppress hepatitis C virus infection.

A Lee, S Liu, T Wang

Open access · greenAbstract read
In one paragraph

Article in Journal of viral hepatitis, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.6field-weighted citation impact, top 31% of its field
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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. Review
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

3 authors at 1 institution in 1 country.

A LeeDepartments of Infectious Diseases and Microbiology, University of Pittsburgh, Pittsburgh, PA, USA.
S Liu
T Wang
University of Pittsburgh · US

Funding

Tight Junction: Gate to HCV Tropism, Therapeutics and PathogenesisR01DK088787 · NIDDK · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI STEIN, PAUL L · 2010 to 2019
$4.2M
NIDDK NIH HHS R01 DK088787NIDDK NIH HHS R01DK088787
6 · The paper itself

Abstract

The human kinome includes between 500 and 600 known kinases and open reading frames (ORFs) that play key roles in regulating many cellular processes. Past studies adopting loss-of-function approaches have identified some kinases whose activities are required for hepatitis C virus (HCV) life cycle. Here, by screening a retroviral cDNA library of 192 active human kinases, we found that three of them, namely cyclin-dependent kinases regulatory subunit 1 (CKS1B), mitogen-activated protein kinase kinase 5 (MAP2K5) and protein kinase C and casein kinase substrate in neurons 1 (PACSIN1), potently suppressed HCV infection. The expression of these kinases did not induce the production of type I interferon (IFN) and interferon-stimulated genes (ISGs); instead, they inhibited HCV at postentry stages. Specifically, CKS1B and MAP2K5 significantly inhibited viral RNA replication. PACSIN1, by contrast, inhibited HCV infection by decreasing the level of HCV p7. Altogether, the identification of human protein kinases that exert an anti-HCV activity highlighted the potential of combating HCV infection by activating specific kinase-mediated pathways, offering an alternative strategy of treatment.

Indexed as

Host-Pathogen InteractionsVirus ReplicationAdaptor Proteins, Signal TransducingCDC2-CDC28 KinasesHepacivirusHepatitis CHumansInterferon Type IMAP Kinase Kinase 5Adaptor Proteins, Signal TransducingCDC2-CDC28 KinasesCKS1B protein, humanInterferon Type IMAP2K5 protein, humanMAP Kinase Kinase 5PACSIN1 protein, humanhepatitis C virushuman kinaseviral hepatitis

Identifiers

PMID24205826
PMCPMC4130908
OpenAlexW2021340663

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.