Evidence map›Paper›PMID 34208793›Full record

ArticleViruses2021

Differential Diagnosis for Highly Pathogenic Avian Influenza Virus Using Nanoparticles Expressing Chemiluminescence.

Jihee Kim, Jae-Yeon Park, Jihoon Ryu, Hyun-Jin Shin, Jung-Eun Park

Open access · goldAbstract read
In one paragraph

Article in Viruses, 2021. 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
0.2field-weighted citation impact, top 50% 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, 1 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

5 authors at 1 institution in 1 country.

Jihee KimLaboratory of Veterinary Public Health, College of Veterinary Medicine, Chungnam National University, Daejeon 34134, Korea.
Jae-Yeon ParkLaboratory of Veterinary Infectious Diseases, College of Veterinary Medicine, Chungnam National University, Daejeon 34134, Korea.
Jihoon RyuLaboratory of Veterinary Infectious Diseases, College of Veterinary Medicine, Chungnam National University, Daejeon 34134, Korea.ORCID 0000-0003-4663-3076
Hyun-Jin ShinLaboratory of Veterinary Infectious Diseases, College of Veterinary Medicine, Chungnam National University, Daejeon 34134, Korea.ORCID 0000-0002-6805-4924
Jung-Eun ParkLaboratory of Veterinary Public Health, College of Veterinary Medicine, Chungnam National University, Daejeon 34134, Korea.
Chungnam National University · KR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Highly pathogenic avian influenza (HPAI) virus is a causative agent of systemic disease in poultry, characterized by high mortality. Rapid diagnosis is crucial for the control of HPAI. In this study, we aimed to develop a differential diagnostic method that can distinguish HPAI from low pathogenic avian influenza (LPAI) viruses using dual split proteins (DSPs). DSPs are chimeras of an enzymatic split, Renilla luciferase (RL), and a non-enzymatic split green fluorescent protein (GFP). Nanoparticles expressing DSPs, sialic acid, and/or transmembrane serine protease 2 (TMPRSS2) were generated, and RL activity was determined in the presence of HPAI or LPAI pseudotyped viruses. The RL activity of nanoparticles containing both DSPs was approximately 2 × 10

Indexed as

LuminescenceAnimalsAnimals, WildBirdsDiagnosis, DifferentialFecesGreen Fluorescent ProteinsHEK293 CellsHumansInfluenza A virusInfluenza in BirdsLuminescent MeasurementsNanoparticlesSensitivity and SpecificityGreen Fluorescent Proteinsavian influenzachemiluminescencedifferential diagnosisnanoparticle

Identifiers

PMID34208793
PMCPMC8310176
OpenAlexW3173499024

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.