Evidence map›Paper›PMID 36090813›Full record

ArticleComputational and structural biotechnology journal2022

Univ-flu: A structure-based model of influenza A virus hemagglutinin for universal antigenic prediction.

Jingxuan Qiu, Xinxin Tian, Yaxing Liu, Tianyu Lu, Hailong Wang, Zhuochen Shi, Sihao Lu, Dongpo Xu, Tianyi Qiu

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computational and structural biotechnology journal, 2022. 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 49% 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. 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

9 authors at 2 institutions in 1 country.

Jingxuan QiuSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Xinxin TianSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Yaxing LiuSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Tianyu LuSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Hailong WangSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Zhuochen ShiSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Sihao LuSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Dongpo XuSchool of Health Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China.
Tianyi QiuZhongshan Hospital, Fudan University, Shanghai 200032, China.
University of Shanghai for Science and Technology · CNSun Yat-sen University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The rapid mutations on hemagglutinin (HA) of influenza A virus (IAV) can lead to significant antigenic variance and consequent immune mismatch of vaccine strains. Thus, rapid antigenicity evaluation is highly desired. The subtype-specific antigenicity models have been widely used for common subtypes such as H1 and H3. However, the continuous emerging of new IAV subtypes requires the construction of universal antigenic prediction model which could be applied on multiple IAV subtypes, including the emerging or re-emerging ones. In this study, we presented Univ-Flu, series structure-based universal models for HA antigenicity prediction. Initially, the universal antigenic regions were derived on multiple subtypes. Then, a radial shell structure combined with amino acid indexes were introduced to generate the new three-dimensional structure based descriptors, which could characterize the comprehensive physical-chemical property changes between two HA variants within or across different subtypes. Further, by combining with Random Forest classifier and different training datasets, Univ-Flu could achieve high prediction performances on intra-subtype (average AUC of 0.939), inter-subtype (average AUC of 0.771), and universal-subtype (AUC of 0.978) prediction, through independent test. Results illustrated that the designed descriptor could provide accurate universal antigenic description. Finally, the application on high-throughput antigenic coverage prediction for circulating strains showed that the Univ-Flu could screen out virus strains with high cross-protective spectrum, which could provide

Indexed as

Antigenic predictionHemagglutininInfluenza virusIn-silico model

Identifiers

PMID36090813
PMCPMC9436755
OpenAlexW4293577920

What OpenQuestion holds

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LicenceCC BY-NC-ND
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.