Evidence map›Paper›PMID 37211247›Full record

ArticleVirologica Sinica2023

Development of PREDAC-H1pdm to model the antigenic evolution of influenza A/(H1N1) pdm09 viruses.

Mi Liu, Jingze Liu, Wenjun Song, Yousong Peng, Xiao Ding, Lizong Deng, Taijiao Jiang

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

Article in Virologica Sinica, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.5field-weighted citation impact, top 17% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. Exploring molecular characterization circulating influenza A and B viruses in Tehran, Iran.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2026
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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

7 authors at 4 institutions in 1 country.

Mi LiuJiangsu Institute of Clinical Immunology, The First Affiliated Hospital of Soochow University, Suzhou, 215006, China.
Jingze LiuInstitute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China; Suzhou Institute of Systems Medicine, Suzhou, 215123, China.
Wenjun SongGuangzhou Laboratory, Guangzhou, 510005, China.
Yousong PengBioinformatics Center, College of Biology, Hunan Provincial Key Laboratory of Medical Virology, Hunan University, Changsha, 410082, China.
Xiao DingInstitute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China; Suzhou Institute of Systems Medicine, Suzhou, 215123, China.
Lizong DengInstitute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100005, China; Suzhou Institute of Systems Medicine, Suzhou, 215123, China.
Taijiao JiangSuzhou Institute of Systems Medicine, Suzhou, 215123, China; Guangzhou Laboratory, Guangzhou, 510005, China; State Key Laboratory of Respiratory Disease, the First Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou, 510120, China. Electronic address: jiang_taijiao@gzlab.ac.cn.
Chinese Academy of Medical Sciences & Peking Union Medical College · CNGuangzhou Experimental Station · CNHunan University · CNSoochow University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The Influenza A (H1N1) pdm09 virus caused a global pandemic in 2009 and has circulated seasonally ever since. As the continual genetic evolution of hemagglutinin in this virus leads to antigenic drift, rapid identification of antigenic variants and characterization of the antigenic evolution are needed. In this study, we developed PREDAC-H1pdm, a model to predict antigenic relationships between H1N1pdm viruses and identify antigenic clusters for post-2009 pandemic H1N1 strains. Our model performed well in predicting antigenic variants, which was helpful in influenza surveillance. By mapping the antigenic clusters for H1N1pdm, we found that substitutions on the Sa epitope were common for H1N1pdm, whereas for the former seasonal H1N1, substitutions on the Sb epitope were more common in antigenic evolution. Additionally, the localized epidemic pattern of H1N1pdm was more obvious than that of the former seasonal H1N1, which could make vaccine recommendation more sophisticated. Overall, the antigenic relationship prediction model we developed provides a rapid determination method for identifying antigenic variants, and the further analysis of evolutionary and epidemic characteristics can facilitate vaccine recommendations and influenza surveillance for H1N1pdm.

Indexed as

Influenza A Virus, H1N1 SubtypeInfluenza, HumanInfluenza VaccinesEpitopesEvolution, MolecularHemagglutinin Glycoproteins, Influenza VirusHumansPhylogenyEpitopesHemagglutinin Glycoproteins, Influenza VirusInfluenza VaccinesAntigenic evolutionAntigenic relationship predictionH1N1pdm virusVaccine recommendation

Identifiers

PMID37211247
PMCPMC10436056
OpenAlexW4377091502

What OpenQuestion holds

Textmetadata
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.