| |  Online-Ressource |
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| Verfasst von: | Zhai, Ke [VerfasserIn]  |
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| | Dong, Jinze [VerfasserIn] |
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| | Zeng, Jinfeng [VerfasserIn] |
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| | Cheng, Peiwen [VerfasserIn] |
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| | Wu, Xinsheng [VerfasserIn] |
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| | Han, Wenjie [VerfasserIn] |
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| | Chen, Yilin [VerfasserIn] |
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| | Qiu, Zekai [VerfasserIn] |
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| | Zhou, Yong [VerfasserIn] |
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| | Pu, Juan [VerfasserIn] |
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| | Jiang, Taijiao [VerfasserIn] |
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| | Du, Xiangjun [VerfasserIn] |
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| Titel: | Global antigenic landscape and vaccine recommendation strategy for low pathogenic avian influenza A (H9N2) viruses |
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| Verf.angabe: | Ke Zhai, Jinze Dong, Jinfeng Zeng, Peiwen Cheng, Xinsheng Wu, Wenjie Han, Yilin Chen, Zekai Qiu, Yong Zhou, Juan Pu, Taijiao Jiang, Xiangjun Du |
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| E-Jahr: | 2024 |
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| Jahr: | August 2024 |
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| Umfang: | 10 S. |
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| Illustrationen: | Illustrationen |
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| Fussnoten: | Gesehen am 20.01.2025 ; Online verfügbar 18 June 2024, Version des Artikels 25 June 2024 |
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| Titel Quelle: | Enthalten in: Journal of infection |
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| Ort Quelle: | Amsterdam [u.a.] : Elsevier, 1979 |
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| Jahr Quelle: | 2024 |
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| Band/Heft Quelle: | 89(2024), 2 vom: Aug., Artikel-ID 106199, Seite 1-10 |
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| ISSN Quelle: | 1532-2742 |
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| Abstract: | The sustained circulation of H9N2 avian influenza viruses (AIVs) poses a significant threat for contributing to a new pandemic. Given the temporal and spatial uncertainty in the antigenicity of H9N2 AIVs, the immune protection efficiency of vaccines remains challenging. By developing an antigenicity prediction method for H9N2 AIVs, named PREDAC-H9, the global antigenic landscape of H9N2 AIVs was mapped. PREDAC-H9 utilizes the XGBoost model with 14 well-designed features. The XGBoost model was built and evaluated to predict the antigenic relationship between any two viruses with high values of 81.1 %, 81.4 %, 81.3 %, 81.1 %, and 89.4 % in accuracy, precision, recall, F1 value, and area under curve (AUC), respectively. Then the antigenic correlation network (ACnet) was constructed based on the predicted antigenic relationship for H9N2 AIVs from 1966 to 2022, and ten major antigenic clusters were identified. Of these, four novel clusters were generated in China in the past decade, demonstrating the unique complex situation there. To help tackle this situation, we applied PREDAC-H9 to calculate the cluster-transition determining sites and screen out virus strains with the high cross-protective spectrum, thus providing an in silico reference for vaccine recommendation. The proposed model will reduce the clinical monitoring workload and provide a useful tool for surveillance and control of H9N2 AIVs. |
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| DOI: | doi:10.1016/j.jinf.2024.106199 |
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| URL: | Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.
kostenfrei: Volltext: https://doi.org/10.1016/j.jinf.2024.106199 |
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| | kostenfrei: Volltext: https://www.sciencedirect.com/science/article/pii/S0163445324001336 |
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| | DOI: https://doi.org/10.1016/j.jinf.2024.106199 |
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| Datenträger: | Online-Ressource |
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| Sprache: | eng |
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| Sach-SW: | Antigenic cluster |
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| | Avian influenza |
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| | H9N2 |
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| | Surveillance |
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| | Vaccine recommendation |
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| K10plus-PPN: | 1915105749 |
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| Verknüpfungen: | → Zeitschrift |
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Global antigenic landscape and vaccine recommendation strategy for low pathogenic avian influenza A (H9N2) viruses / Zhai, Ke [VerfasserIn]; August 2024 (Online-Ressource)
