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A human-infecting H10N5 avian influenza virus: clinical features, virus reassortment, receptor-binding affinity, and possible transmission routes.
J Infect
March 2025
State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China. Electronic address:
Background: In late 2023, the first human case caused by an H10N5 avian influenza virus (AIV) was diagnosed in China. H10Ny AIVs have been identified in various poultry and wild birds in Eurasia, the Americas, and Oceania.
Methods: We analyzed the clinical data of the H10N5 AIV-infected patient, isolated the virus, and evaluated the virus receptor-binding properties together with the H10N8 and H10N3 AIVs identified in humans and poultry.
Call to include breastfeeding as a synergistic approach to vaccines for prevention of respiratory syncytial virus disease.
Int Breastfeed J
March 2025
Chair of Public Health and Health Services Research, Institute for Biostatistics, Epidemiology, Medical Information Processing, Medical Faculty, Ludwig-Maximilians-Universität München (LMU Munich), Munich, Germany.
Background: Infections with respiratory syncytial virus (RSV) in infancy and early childhood are very common. RSV is the leading cause of bronchiolitis and pneumonia and substantially contributes to the morbidity and mortality of infants and young children worldwide. Until very recently, there have been no vaccines available for prevention and there are no curative treatments for RSV.
View Article and Find Full Text PDFAuto-Pairing Positives Through Implicit Relation Circulation for Discriminative Self-Learning.
IEEE Trans Pattern Anal Mach Intell
April 2025
Contrastive learning, a discriminative self-learning framework, is one of the most popular representation learning methods which has a wide range of application scenarios. Although relative techniques have been continuously updated in recent years, designing and seeking positive pairs are still inevitable. Just because of the requirement of explicit positive pairs, the utilization of contrastive learning is restricted in dense, multi-modal, and other scenarios where positive pairs are difficult to obtain.
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