Publications by authors named "F Ge"

Suraxavir marboxil (GP681) is an antiviral drug inhibiting the polymerase acidic protein (PA) of RNA polymerase, of influenza. It has shown therapeutic activity against influenza A and B virus infections in preclinical studies. In this multicenter randomized, double-blind, placebo-controlled, phase 3 trial, we aimed to investigate the efficacy and safety of single-dose suraxavir marboxil (40-mg oral dose) in otherwise healthy outpatients aged 5-65 years with uncomplicated influenza unaccompanied by severe issues.

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Article Synopsis
  • Hepatitis C Virus (HCV) is a serious bloodborne virus causing liver disease, and currently, there are no effective vaccines to prevent its spread, highlighting the importance of understanding T cell epitopes (TCEs) in immune response.
  • TCellPredX is a new prediction tool designed to identify TCEs related to HCV by using advanced machine learning techniques and a variety of feature encodings, which together improve the predictive accuracy of TCE identification.
  • The tool has demonstrated high accuracy scores (0.900 and 0.897) in identifying relevant peptides for vaccine development, establishing TCellPredX as a significant resource for future research aimed at creating an effective HCV vaccine.
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The rational design of advanced oxygen reduction reaction (ORR) catalysts is essential to improve the performance of energy conversion devices. However, it remains a huge challenge to construct hierarchical micro-/meso-/macroporous nanostructures, especially mesoporous transport channels in catalysts, to enhance catalytic capability. Herein, motivated by the characteristics of energetic metal-organic frameworks (EMOFs) that produce an abundance of gases during high-temperature pyrolysis, we prepared a unique tetrazine-based EMOF-derived electrocatalyst (denoted as FeC@NSC-900) consisting of highly dispersed FeC nanoparticles and N,S-codoped mesoporous carbon nanotubes.

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Calculating anharmonic vibrational modes of molecules for interpreting experimental spectra is one of the most interesting challenges of contemporary computational chemistry. However, the traditional QM methods are costly for this application. Machine learning techniques have emerged as a powerful tool for substituting the traditional QM methods.

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Background: Human immunodeficiency virus (HIV) is a retrovirus mainly infecting immune cells. Central nervous system diseases in HIV-infected patients can be caused by HIV or opportunistic infections. Neurological diseases associated with HIV have diverse manifestations and may occur in early or late stages.

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