SARS-CoV-2 infection causes a wide spectrum of clinical manifestations in humans, and olfactory dysfunction is one of the most predictive and common symptoms in COVID-19 patients. However, the underlying mechanism by which SARS-CoV-2 infection leads to olfactory disorders remains elusive. Herein, we demonstrate that intranasal inoculation with SARS-CoV-2 induces robust viral replication in the olfactory epithelium (OE), not the olfactory bulb (OB), resulting in transient olfactory dysfunction in humanized ACE2 (hACE2) mice. The sustentacular cells and Bowman’s gland cells in the OE were identified as the major target cells of SARS-CoV-2 before invasion into olfactory sensory neurons (OSNs). Remarkably, SARS-CoV-2 infection triggers massive cell death and immune cell infiltration and directly impairs the uniformity of the OE structure. Combined transcriptomic and quantitative proteomic analyses revealed the induction of antiviral and inflammatory responses, as well as the downregulation of olfactory receptor (OR) genes in the OE from the infected animals. Overall, our mouse model recapitulates olfactory dysfunction in COVID-19 patients and provides critical clues for understanding the physiological basis for extrapulmonary manifestations of COVID-19.

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Graphene oxide (GO) contains numerous functional groups that facilitate the intercalation of polar solvents. The properties and applications of GO are closely related to its interlayer spacing. We report on the changes in the interlayer spacing of GO after the adsorption of water molecules and the polar organic solvents C 2 H 6 O 2 (EG), C 3 H 7 NO (DMF), C 5 H 9 NO (NMP). Experiments were conducted to investigate the variations in the functional groups and structure of GO after solvent adsorption, and they play a vital role in modeling and verifying the results of molecular dynamics simulation. The most stable GO structures are obtained through molecular dynamics simulation. The expansion of the interlayer spacing of GO after the adsorption of monolayer solvent molecules corresponds to the minimum three-dimensional size of the solvent molecules. The spatial arrangement of solvent molecules also contributes to the changes in interlayer spacing. Most adsorbed molecules are oriented parallel to the carbon plane of GO. However, as additional molecules are adsorbed into the interlaminations of GO, the adsorbed molecules are oriented perpendicular to the carbon plane of GO, and a large space forms between two GO interlayers. In addition, the role of large molecules in increasing interlayer spacing becomes more crucial than that of water molecules in the adsorption of binary solvent systems by GO.

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Strict tolerance space of three-dimensional (3D) crystalline structures is still a great challenge in switching dielectrics compared to lower-dimensional structures. Generally, the function of crystalline materials can be given or...

A high-dimensional quantum key distribution (QKD), which adopts degrees of freedom of the orbital angular momentum (OAM) states, is beneficial to realize secure and high-speed QKD. However, the helical phase of a vortex beam that carries OAM is sensitive to the atmospheric turbulence and easily distorted. In this paper, an adaptive compensation method using deep learning technology is developed to improve the performance of OAM-encoded QKD schemes. A convolutional neural network model is first trained to learn the mapping relationship of intensity profiles of inputs and the turbulent phase, and such mapping is used as feedback to control a spatial light modulator to generate a phase screen to correct the distorted vortex beam. Then an OAM-encoded QKD scheme with the capability of real-time phase correction is designed, in which the compensation module only needs to extract the intensity distributions of the Gaussian probe beam and thus ensures that the information encoded on OAM states would not be eavesdropped. The results show that our method can efficiently improve the mode purity of the encoded OAM states and extend the secure distance for the involved QKD protocols in the free-space channel, which is not limited to any specific QKD protocol.