Evidence map›Paper›PMID 24022374›Full record

ArticleNature communications2013

Visualizing influenza virus infection in living mice.

Weiqi Pan, Zhenyuan Dong, Feng Li, Weixu Meng, Liqiang Feng, Xuefeng Niu, Chufang Li, Qinfang Luo, Zhengfeng Li, Caijun Sun and 1 more

Open access · hybridAbstract read
In one paragraph

Article in Nature communications, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 88 papers.

0numbers the graph read from it
0cells of the map it votes in
88citing papers in PubMed
6.9field-weighted citation impact, top 2% 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

88 citing papers in PubMed, 119 citations in OpenAlex.

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28 more citing papers are in PubMed but not listed here.

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

11 authors at 5 institutions in 2 countries.

Weiqi Pan1] State Key Laboratory of Respiratory Disease, Guangzhou Institutes of Biomedicine and Health, Chinese Academy of Sciences, Guangzhou 510530, China [2] The First Affiliated Hospital, Guangzhou Medical University, Guangzhou 510210, China [3].
Zhenyuan Dong
Feng Li
Weixu Meng
Liqiang Feng
Xuefeng Niu
Chufang Li
Qinfang Luo
Zhengfeng Li
Caijun Sun
Ling Chen
First Affiliated Hospital of Guangzhou Medical University · CNChinese Academy of Sciences · CNGuangzhou Medical University · CNState Key Laboratory of Respiratory Disease · CNGuangzhou Institutes of Biomedicine and Health · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Preventing and treating influenza virus infection remain a challenge because of incomplete understanding of the host-pathogen interactions, limited therapeutics and lack of a universal vaccine. So far, methods for monitoring the course of infection with influenza virus in real time in living animals are lacking. Here we report the visualization of influenza viral infection in living mice using an engineered replication-competent influenza A virus carrying luciferase reporter gene. After intranasal inoculation, bioluminescence can be detected in the chest and nasopharyngeal passage of living mice. The intensity of bioluminescence in the chest correlates with the dosage of infection and the viral load in the lung. Bioluminescence in the chest of infected mice diminishes on antiviral treatment. This work provides a novel approach that enables real-time study of influenza virus infection and effects of antiviral therapeutics in living animals.

Indexed as

Administration, IntranasalAnimalsAntiviral AgentsBody WeightChickensComputer SystemsDogsFemaleGenes, ReporterHEK293 CellsHumansImaging, Three-DimensionalInfluenza A virusLuciferasesLuminescent MeasurementsLungAntiviral AgentsLuciferases

Identifiers

PMID24022374
PMCPMC3778511
OpenAlexW2098526680

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.