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To analyze a case of severe avian influenza A (H5N6) virus infection resulting in severe pneumonia and acute respiratory distress syndrome (ARDS) was admitted to Guilin Municipal Hospital of Traditional Chinese Medicine on July 6, 2023. The clinical data and treatment of this patient were analyzed retrospectively. The initial clinical manifestations of the patient were fever, cough, and expectoration, and the antigen test for influenza A virus was positive. Chest CT showed: double lung texture increased and thickened, and multiple patchy high-density shadows with air-containing bronchial shadows were found in the left lung, especially in the left upper lobe; a few patchy increased-density shadows were also seen in the lower lobe of the right lung, along with left-sided pleural effusion. Metagenomic next-generation metagenomic sequencing (mNGS) of bronchoalveolar lavage fluid was performed to identify the pathogen as influenza A virus H5N6. On the 4th day of admission, the patient's condition rapidly progressed to ARDS, which could not be improved by high-flow oxygen therapy, mechanical ventilation, and prone position ventilation. Subsequently, with the assistance of veno-venous extracorporeal membrane oxygenation (VV-ECMO), the patient's lung function gradually improved. Extracorporeal membrane oxygenation (ECMO) was withdrawn after 25 days, and the patient recovered and was discharged after a hospital stay of 41 days. Patients with severe avian influenza A (H5N6) usually have critical illness and rapid progression, often rapidly progressing to ARDS. When conventional mechanical ventilation cannot correct hypoxemia, VV-ECMO auxiliary treatment should be administered as early as possible. In addition, mNGS can help to quickly identify the diagnosis and differential diagnosis of avian influenza A (H5N6) in the early stage of the disease, particularly suitable for the diagnosis of severe and emergency infections. [ABSTRACT FROM AUTHOR]

Artificial intelligence underwent remarkable advancement in the past decade, revolutionizing our way of thinking and unlocking unprecedented opportunities across various fields, including drug development. The emergence of large pretrained models, such as ChatGPT, has even begun to demonstrate human-level performance in certain tasks.However, the difficulties of deploying and utilizing AI and pretrained model for nonexpert limited its practical use. To overcome this challenge, here we presented three highly accessible online tools based on a large pretrained model for chemistry, the Uni-Mol, for drug development against CNS diseases, including those targeting NMDA receptor: the blood-brain barrier (BBB) permeability prediction, the quantitative structure-activity relationship (QSAR) analysis system, and a versatile interface of the AI-based molecule generation model named VD-gen. We believe that these resources will effectively bridge the gap between cutting-edge AI technology and NMDAR experts, facilitating rapid and rational drug development., (© 2024. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)