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Revealing novel CD8 T-cell epitopes from the H5N1 avian influenza virus in HBW/B1 haplotype ducks.

Vet Res

December 2024

National and Regional Joint Engineering Laboratory for Medicament of Zoonosis Prevention and Control, Guangdong Provincial Key Laboratory of Zoonosis Prevention and Control, College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, China.

The duck CD8 T-cell response effectively defends against H5N1 highly pathogenic avian influenza virus (HPAIV) infection, but the recognized peptide is rarely identified. Here, we found that the ratio of CD8 T cells and the expression of IFN-γ and cytotoxicity-associated genes, including granzyme A/K, perforin and IL2, at 7 days post-infection in peripheral blood mononuclear cells (PBMCs) from B1 haplotype ducks significantly increased in the context of defending against H5N1 AIV infection in vivo. Moreover, similar results were observed in cultured and sorted H5N1 AIV-stimulated duck CD8 T cells in vitro.

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Introduction: Coronaviruses and influenza viruses are significant respiratory pathogens that cause severe disease burdens and economic losses for society. Due to their diversity and evolution, vaccines typically require periodic updating to remain effective. An additional challenge is imposed by the possible coinfection of SARS-CoV-2 and influenza, which could increase disease severity.

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The circulation of seasonal influenza A viruses (IAVs) in humans relies on effective evasion and subversion of the host immune response. While the evolution of seasonal H1N1 and H3N2 viruses to avoid humoral immunity is well characterized, relatively little is known about the evolution of innate immune antagonism phenotypes in these viruses. Numerous studies have established that only a small subset of infected cells is responsible for initiating the type I and type III interferon (IFN) response during IAV infection, emphasizing the importance of single cell studies to accurately characterize the IFN response during infection.

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Examining the Influenza A Virus Sialic Acid Binding Preference Predictions of a Sequence-Based Convolutional Neural Network.

Influenza Other Respir Viruses

December 2024

Department of Infectious Disease and Global Health, Cummings School of Veterinary Medicine, Tufts University, North Grafton, Massachusetts, USA.

Background: Though receptor binding specificity is well established as a contributor to host tropism and spillover potential of influenza A viruses, determining receptor binding preference of a specific virus still requires expensive and time-consuming laboratory analyses. In this study, we pilot a machine learning approach for prediction of binding preference.

Methods: We trained a convolutional neural network to predict the α2,6-linked sialic acid preference of influenza A viruses given the hemagglutinin amino acid sequence.

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