IL-37 possesses both anti-inflammatory and antiviral effects against Middle East respiratory syndrome coronavirus infection.

BACKGROUND: The aim was to elucidate the function of IL-37 in middle east respiratory syndrome coronavirus (MERS-CoV) infection, thereby providing a novel therapeutic strategy for managing the clinical treatment of inflammatory response caused by respiratory virus infection. METHODS: We investigated the development of MERS by infecting hDPP4 mice with hCoV-EMC (107 TCID50 [50% tissue culture infectious dose]) intranasally. We infected A549 cells with MERS-CoV, which concurrently interfered with IL-37, detecting the viral titer, viral load, and cytokine expression at certain points postinfection. Meanwhile, we administered IL-37 (12.5 µg/kg) intravenously to hDPP4 mice 2 h after MERS-CoV-2 infection and collected the serum and lungs 5 days after infection to investigate the efficacy of IL-37 in MERS-CoV infection. RESULTS: The viral titer of MERS-CoV-infected A549 cells interfering with IL-37 was significantly reduced by 4.7-fold, and the viral load of MERS-CoV-infected hDPP4 mice was decreased by 59-fold in lung tissue. Furthermore, the administration of IL-37 suppressed inflammatory cytokine and chemokine (monocyte chemoattractant protein 1, interferon-γ, and IL-17A) expression and ameliorated the infiltration of inflammatory cells in hDPP4 mice. CONCLUSION: IL-37 exhibits protective properties in severe pneumonia induced by MERS-CoV infection. This effect is achieved through attenuation of lung viral load, suppression of inflammatory cytokine secretion, reduction in inflammatory cell infiltration, and mitigation of pulmonary injury.

Infection with SARS-CoV-2 can cause pancreatic impairment.

Evidence suggests associations between COVID-19 patients or vaccines and glycometabolic dysfunction and an even higher risk of the occurrence of diabetes. Herein, we retrospectively analyzed pancreatic lesions in autopsy tissues from 67 SARS-CoV-2 infected non-human primates (NHPs) models and 121 vaccinated and infected NHPs from 2020 to 2023 and COVID-19 patients. Multi-label immunofluorescence revealed direct infection of both exocrine and endocrine pancreatic cells by the virus in NHPs and humans. Minor and limited phenotypic and histopathological changes were observed in adult models. Systemic proteomics and metabolomics results indicated metabolic disorders, mainly enriched in insulin resistance pathways, in infected adult NHPs, along with elevated fasting C-peptide and C-peptide/glucose ratio levels. Furthermore, in elder COVID-19 NHPs, SARS-CoV-2 infection causes loss of beta (ß) cells and lower expressed-insulin in situ characterized by islet amyloidosis and necrosis, activation of α-SMA and aggravated fibrosis consisting of lower collagen in serum, an increase of pancreatic inflammation and stress markers, ICAM-1 and G3BP1, along with more severe glycometabolic dysfunction. In contrast, vaccination maintained glucose homeostasis by activating insulin receptor α and insulin receptor ß. Overall, the cumulative risk of diabetes post-COVID-19 is closely tied to age, suggesting more attention should be paid to blood sugar management in elderly COVID-19 patients.

A cross-subject decoding algorithm for patients with disorder of consciousness based on P300 brain computer interface.

Background: Brain computer interface (BCI) technology may provide a new way of communication for some patients with disorder of consciousness (DOC), which can directly connect the brain and external devices. However, the DOC patients' EEG differ significantly from that of the normal person and are difficult to collected, the decoding algorithm currently only is trained based on a small amount of the patient's own data and performs poorly. Methods: In this study, a decoding algorithm called WD-ADSTCN based on domain adaptation is proposed to improve the DOC patients' P300 signal detection. We used the Wasserstein distance to filter the normal population data to increase the training data. Furthermore, an adversarial approach is adopted to resolve the differences between the normal and patient data. Results: The results showed that in the cross-subject P300 detection of DOC patients, 7 of 11 patients achieved an average accuracy of over 70%. Furthermore, their clinical diagnosis changed and CRS-R scores improved three months after the experiment. Conclusion: These results demonstrated that the proposed method could be employed in the P300 BCI system for the DOC patients, which has important implications for the clinical diagnosis and prognosis of these patients.

Sparse Bayesian Learning for End-to-End EEG Decoding.

Decoding brain activity from non-invasive electroencephalography (EEG) is crucial for brain-computer interfaces (BCIs) and the study of brain disorders. Notably, end-to-end EEG decoding has gained widespread popularity in recent years owing to the remarkable advances in deep learning research. However, many EEG studies suffer from limited sample sizes, making it difficult for existing deep learning models to effectively generalize to highly noisy EEG data. To address this fundamental limitation, this paper proposes a novel end-to-end EEG decoding algorithm that utilizes a low-rank weight matrix to encode both spatio-temporal filters and the classifier, all optimized under a principled sparse Bayesian learning (SBL) framework. Importantly, this SBL framework also enables us to learn hyperparameters that optimally penalize the model in a Bayesian fashion. The proposed decoding algorithm is systematically benchmarked on five motor imagery BCI EEG datasets ( N=192) and an emotion recognition EEG dataset ( N=45), in comparison with several contemporary algorithms, including end-to-end deep-learning-based EEG decoding algorithms. The classification results demonstrate that our algorithm significantly outperforms the competing algorithms while yielding neurophysiologically meaningful spatio-temporal patterns. Our algorithm therefore advances the state-of-the-art by providing a novel EEG-tailored machine learning tool for decoding brain activity.

Bioactive compounds from Huashi Baidu decoction possess both antiviral and anti-inflammatory effects against COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic is an ongoing global health concern, and effective antiviral reagents are urgently needed. Traditional Chinese medicine theory-driven natural drug research and development (TCMT-NDRD) is a feasible method to address this issue as the traditional Chinese medicine formulae have been shown effective in the treatment of COVID-19. Huashi Baidu decoction (Q-14) is a clinically approved formula for COVID-19 therapy with antiviral and anti-inflammatory effects. Here, an integrative pharmacological strategy was applied to identify the antiviral and anti-inflammatory bioactive compounds from Q-14. Overall, a total of 343 chemical compounds were initially characterized, and 60 prototype compounds in Q-14 were subsequently traced in plasma using ultrahigh-performance liquid chromatography with quadrupole time-of-flight mass spectrometry. Among the 60 compounds, six compounds (magnolol, glycyrrhisoflavone, licoisoflavone A, emodin, echinatin, and quercetin) were identified showing a dose-dependent inhibition effect on the SARS-CoV-2 infection, including two inhibitors (echinatin and quercetin) of the main protease (Mpro), as well as two inhibitors (glycyrrhisoflavone and licoisoflavone A) of the RNA-dependent RNA polymerase (RdRp). Meanwhile, three anti-inflammatory components, including licochalcone B, echinatin, and glycyrrhisoflavone, were identified in a SARS-CoV-2-infected inflammatory cell model. In addition, glycyrrhisoflavone and licoisoflavone A also displayed strong inhibitory activities against cAMP-specific 3',5'-cyclic phosphodiesterase 4 (PDE4). Crystal structures of PDE4 in complex with glycyrrhisoflavone or licoisoflavone A were determined at resolutions of 1.54 Å and 1.65 Å, respectively, and both compounds bind in the active site of PDE4 with similar interactions. These findings will greatly stimulate the study of TCMT-NDRD against COVID-19.

A novel semi-supervised meta learning method for subject-transfer brain-computer interface.

The brain-computer interface (BCI) provides a direct communication pathway between the human brain and external devices. However, the models trained for existing subjects perform poorly on new subjects, which is termed the subject calibration problem. In this paper, we propose a semi-supervised meta learning (SSML) method for subject-transfer calibration. The proposed SSML learns a model-agnostic meta learner with existing subjects and then fine-tunes the meta learner in a semi-supervised learning manner, i.e. using a few labelled samples and many unlabelled samples of the target subject for calibration. It is significant for BCI applications in which labelled data are scarce or expensive while unlabelled data are readily available. Three different BCI paradigms are tested: event-related potential detection, emotion recognition and sleep staging. The SSML achieved classification accuracies of 0.95, 0.89 and 0.83 in the benchmark datasets of three paradigms. The runtime complexity of SSML grows linearly as the number of samples of target subject increases so that is possible to apply it in real-time systems. This study is the first attempt to apply semi-supervised model-agnostic meta learning methodology for subject calibration. The experimental results demonstrated the effectiveness and potential of the SSML method for subject-transfer BCI applications.

Chemical Constituents of the Mushroom Dictyophora indusiata and Their Anti-Inflammatory Activities.

As an edible and medicinal fungus, Dictyophora indusiata is well-known for its morphological elegance, distinctive taste, high nutritional value, and therapeutic properties. In this study, eighteen compounds (1-18) were isolated and identified from the ethanolic extract of D. indusiata; four (1-4) were previously undescribed. Their molecular structures and absolute configurations were determined via a comprehensive analysis of spectroscopic data (1D/2D NMR, HRESIMS, ECD, and XRD). Seven isolated compounds were examined for their anti-inflammatory activities using an in vitro model of lipopolysaccharide (LPS)-simulated BV-2 microglial cells. Compound 3 displayed the strongest inhibitory effect on tumor necrosis factor-α (TNF-α) expression, with an IC50 value of 11.9 µM. Compound 16 exhibited the highest inhibitory activity on interleukin-6 (IL-6) production, with an IC50 value of 13.53 µM. Compound 17 showed the most potent anti-inflammatory capacity by inhibiting the LPS-induced generation of nitric oxide (NO) (IC50: 10.86 µM) and interleukin-1ß (IL-1ß) (IC50: 23.9 µM) and by significantly suppressing induced nitric oxide synthase (iNOS) and phosphorylated nuclear factor-kappa B inhibitor-α (p-IκB-α) expression at concentrations of 5 µM and 20 µM, respectively (p < 0.01). The modes of interactions between the isolated compounds and the target inflammation-related proteins were investigated in a preliminary molecular docking study. These results provided insight into the chemodiversity and potential anti-inflammatory activities of metabolites with small molecular weights in the mushroom D. indusiata.

Comparison of the replication and neutralization of different SARS-CoV-2 Omicron subvariants in vitro.

BACKGROUND: New Omicron subvariants are emerging rapidly from BA.1 to BA.4 and BA.5. Their pathogenicity has changed from that of wild-type (WH-09) and Omicron variants have over time become globally dominant. The spike proteins of BA.4 and BA.5 that serve as the target for vaccine-induced neutralizing antibodies have also changed compared to the previous subvariants, which is likely to cause immune escape and the reduction of the protective effect of the vaccine. Our study addresses the above issues and provides a basis for formulating relevant prevention and control strategies. METHODS: We collected cellular supernatant and cell lysates and measured the viral titers, viral RNA loads, and E subgenomic RNA (E sgRNA) loads in different Omicron subvariants grown in Vero E6 cells, using WH-09 and Delta variants as a reference. Additionally, we evaluated the in vitro neutralizing activity of different Omicron subvariants and compared it to the WH-09 and Delta variants using macaque sera with different types of immunity. RESULTS: As the SARS-CoV-2 evolved into Omicron BA.1, the replication ability in vitro began to decrease. Then with the emergence of new subvariants, the replication ability gradually recovered and became stable in the BA.4 and BA.5 subvariants. In WH-09-inactivated vaccine sera, geometric mean titers of neutralization antibodies against different Omicron subvariants declined by 3.7~15.4-fold compared to those against WH-09. In Delta-inactivated vaccine sera, geometric mean titers of neutralization antibodies against Omicron subvariants declined by 3.1~7.4-fold compared to those against Delta. CONCLUSION: According to the findings of this research, the replication efficiency of all Omicron subvariants declined compared with WH-09 and Delta variants, and was lower in BA.1 than in other Omicron subvariants. After two doses of inactivated (WH-09 or Delta) vaccine, cross-neutralizing activities against various Omicron subvariants were seen despite a decline in neutralizing titers.

Two new sesquiterpenoids from Dictyophora indusiata.

Two new sesquiterpenoids, named 9,10-dihydroxy-albaflavenone (1) and 5-hydroxy-albaflavenone (2) were isolated from Dictyophora indusiata. Their structures and absolute configurations were determined by NMR, ECD and HRESIMS. Compounds 1 and 2 showed anti-inflammatory activity by inhibiting TNF-α and NO secretion to varying degrees.

Microbial production of the plant-derived fungicide physcion.

Physcion is a characteristic component of the traditional herb rhubarb with diverse pharmacological activities that has been commercially approved as an herbal fungicide. Nevertheless, its extremely low contents, costly purification procedure and geographically restricted planting severely hinder its application. Here, a cell factory was constructed in the filamentous fungus Aspergillus terreus for physcion production via microbial fermentation by integrating a pathway-modified emodin accumulation module and a position-selective emodin methylation module. Specifically, 1.71 g/L emodin accumulated when the transcriptional activator GedR and the emodin-1-OH-O-methyltransferase GedA in the geodin biosynthetic pathway were overexpressed and knocked out, respectively. Subsequently, potential emodin-3-OH-O-methyltransferase candidates were enzymatically screened in vitro and introduced into the emodin-accumulating mutant in vivo to generate a physcion-producing strain showing the highest titre of 6.3 g/L in fed-batch fermentation. Thus, our study provides an alternative strategy for the highly efficient, economical production of physcion and a representative example for microbial synthetic biology.

Electromagnetic Source Imaging via a Data-Synthesis-Based Convolutional Encoder-Decoder Network.

Electromagnetic source imaging (ESI) requires solving a highly ill-posed inverse problem. To seek a unique solution, traditional ESI methods impose various forms of priors that may not accurately reflect the actual source properties, which may hinder their broad applications. To overcome this limitation, in this article, a novel data-synthesized spatiotemporally convolutional encoder-decoder network (DST-CedNet) method is proposed for ESI. The DST-CedNet recasts ESI as a machine learning problem, where discriminative learning and latent-space representations are integrated in a CedNet to learn a robust mapping from the measured electroencephalography/magnetoencephalography (E/MEG) signals to the brain activity. In particular, by incorporating prior knowledge regarding dynamical brain activities, a novel data synthesis strategy is devised to generate large-scale samples for effectively training CedNet. This stands in contrast to traditional ESI methods where the prior information is often enforced via constraints primarily aimed for mathematical convenience. Extensive numerical experiments as well as analysis of a real MEG and epilepsy EEG dataset demonstrate that the DST-CedNet outperforms several state-of-the-art ESI methods in robustly estimating source signals under a variety of source configurations.

Characteristics of animal models for COVID-19.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the causative agent of coronavirus disease 2019 (COVID-19), the most consequential pandemic of this century, threatening human health and public safety. SARS-CoV-2 has been continuously evolving through mutation of its genome and variants of concern have emerged. The World Health Organization R&D Blueprint plan convened a range of expert groups to develop animal models for COVID-19, a core requirement for the prevention and control of SARS-CoV-2 pandemic. The animal model construction techniques developed during the SARS-CoV and MERS-CoV pandemics were rapidly deployed and applied in the establishment of COVID-19 animal models. To date, a large number of animal models for COVID-19, including mice, hamsters, minks and nonhuman primates, have been established. Infectious diseases produce unique manifestations according to the characteristics of the pathogen and modes of infection. Here we classified animal model resources around the infection route of SARS-CoV-2, and summarized the characteristics of the animal models constructed via transnasal, localized, and simulated transmission routes of infection.

Distinct Responses to Pathogenic and Symbionic Microorganisms: The Role of Plant Immunity.

Plants must balance both beneficial (symbiotic) and pathogenic challenges from microorganisms, the former benefitting the plant and agriculture and the latter causing disease and economic harm. Plant innate immunity describes a highly conserved set of defense mechanisms that play pivotal roles in sensing immunogenic signals associated with both symbiotic and pathogenic microbes and subsequent downstream activation of signaling effector networks that protect the plant. An intriguing question is how the innate immune system distinguishes "friends" from "foes". Here, we summarize recent advances in our understanding of the role and spectrum of innate immunity in recognizing and responding to different microbes. In addition, we also review some of the strategies used by microbes to manipulate plant signaling pathways and thus evade immunity, with emphasis on the use of effector proteins and micro-RNAs (miRNAs). Furthermore, we discuss potential questions that need addressing to advance the field of plant-microbe interactions.

Enhancement of lower limb motor imagery ability via dual-level multimodal stimulation and sparse spatial pattern decoding method.

Recently, motor imagery brain-computer interfaces (MI-BCIs) with stimulation systems have been developed in the field of motor function assistance and rehabilitation engineering. An efficient stimulation paradigm and Electroencephalogram (EEG) decoding method have been designed to enhance the performance of MI-BCI systems. Therefore, in this study, a multimodal dual-level stimulation paradigm is designed for lower-limb rehabilitation training, whereby visual and auditory stimulations act on the sensory organ while proprioceptive and functional electrical stimulations are provided to the lower limb. In addition, upper triangle filter bank sparse spatial pattern (UTFB-SSP) is proposed to automatically select the optimal frequency sub-bands related to desynchronization rhythm during enhanced imaginary movement to improve the decoding performance. The effectiveness of the proposed MI-BCI system is demonstrated on an the in-house experimental dataset and the BCI competition IV IIa dataset. The experimental results show that the proposed system can effectively enhance the MI performance by inducing the α, ß and γ rhythms in lower-limb movement imagery tasks.

Clinical Outcomes of BCMA CAR-T Cells in a Multiple Myeloma Patient With Central Nervous System Invasion.

Background: Multiple myeloma (MM) is the second most common hematological malignancy that still lacks effective clinical treatments. In particular, MM with central nervous system (CNS) invasion occurs rarely. Although B-cell maturation antigen (BCMA)-targeted chimeric antigen receptor-T (CAR-T) cell therapy has shown great promise for the treatment of relapsed/refractory MM, few studies have reported whether BCMA CAR-T could inhibit MM with CNS invasion. Case Presentation: In this study, we report a special case of a 63-year-old male patient who suffered MM with CNS invasion and presented rapid extramedullary disease (EMD) progression into multiple organs. Before CAR-T cell infusion, this patient received five cycles of bortezomib, Adriamycin, and dexamethasone (PAD) and an autologous transplant as the front-line treatment, followed by two cycles of bortezomib, lenalidomide, and dexamethasone (VRD) as the second-line regimen, and daratumumab, bortezomib, dexamethasone (DVD) as the third-line regimen. Since the patient still showed rapid progressive disease (PD), BCMA CAR-T cells were infused, and 1 month later, a stringent complete response (sCR) was achieved, and the response lasted for 4 months. Meanwhile, only grade 1 cytokine release syndrome (CRS) was observed. Conclusion: This case report demonstrated that BCMA CAR-T could effectively eradicate CNS-involved MM with low adverse events, suggesting that CAR-T cell therapy could be a feasible therapeutic option for this kind of refractory disease. Clinical Trial Registration: https://ClinicalTrials.gov, identifier: NCT04537442.a.

Structural and functional analysis of a potent human neutralizing antibody against enterovirus A71.

Enterovirus A71 (EV-A71) causes major outbreaks of hand, foot, and mouth disease (HFMD) in many countries, most frequently affecting children, and a small proportion of cases may lead to death. Currently, no vaccine is available in most endemic regions, and no licenced treatments for EV-A71 infection are available. Here, we characterize a human monoclonal antibody (HuMAb), E1, by screening a Fab antibody phage library derived from patients who recovered from EV-A71 infection. E1 exhibits strong neutralizing activity against EV-A71 virus in cells. The cryo-electron microscopy (cryo-EM) structures of the EV-A71 virion in complex with E1 Fab fragments demonstrated that E1 recognized an epitope formed by residues in the BC and HI loops of VP1. In a mouse model, E1 effectively protected against lethal EV-A71 challenge in both prophylactic and therapeutic treatment. In particular, E1 significantly reduces virus titers and muscle damage. E1 might represent a potential adjunct to EV-A71 treatment.

The m6A Methyltransferase METTL3-Mediated N6-Methyladenosine Modification of DEK mRNA to Promote Gastric Cancer Cell Growth and Metastasis.

Gastric cancer (GC) is the fifth most common cancer and the third deadliest cancer in the world, and the occurrence and development of GC are influenced by epigenetics. Methyltransferase-like 3 (METTL3) is a prominent RNA n6-adenosine methyltransferase (m6A) that plays an important role in tumor growth by controlling the work of RNA. This study aimed to reveal the biological function and molecular mechanism of METTL3 in GC. The expression level of METTL3 in GC tissues and cells was detected by qPCR, Western blot and immunohistochemistry, and the expression level and prognosis of METTL3 were predicted in public databases. CCK-8, colony formation, transwell and wound healing assays were used to study the effect of METTL3 on GC cell proliferation and migration. In addition, the enrichment effect of METTL3 on DEK mRNA was detected by the RIP experiment, the m6A modification effect of METTL3 on DEK was verified by the MeRIP experiment and the mRNA half-life of DEK when METTL3 was overexpressed was detected. The dot blot assay detects m6A modification at the mRNA level. The effect of METTL3 on cell migration ability in vivo was examined by tail vein injection of luciferase-labeled cells. The experimental results showed that METTL3 was highly expressed in GC tissues and cells, and the high expression of METTL3 was associated with a poor prognosis. In addition, the m6A modification level of mRNA was higher in GC tissues and GC cell lines. Overexpression of METTL3 in MGC80-3 cells and AGS promoted cell proliferation and migration, while the knockdown of METTL3 inhibited cell proliferation and migration. The results of in vitro rescue experiments showed that the knockdown of DEK reversed the promoting effects of METTL3 on cell proliferation and migration. In vivo experiments showed that the knockdown of DEK reversed the increase in lung metastases caused by the overexpression of METTL3 in mice. Mechanistically, the results of the RIP experiment showed that METTL3 could enrich DEK mRNA, and the results of the MePIP and RNA half-life experiments indicated that METTL3 binds to the 3'UTR of DEK, participates in the m6A modification of DEK and promotes the stability of DEK mRNA. Ultimately, we concluded that METTL3 promotes GC cell proliferation and migration by stabilizing DEK mRNA expression. Therefore, METTL3 is a potential biomarker for GC prognosis and a therapeutic target.

Characterization and Structural Analysis of Emodin-O-Methyltransferase from Aspergillus terreus.

All O-methylated derivatives of emodin, including physcion, questin, and 1-O-methylemodin, show potential antifungal activities. Notably, emodin and questin are two pivotal intermediates of geodin biosynthesis in Aspergillus terreus. Although most of the geodin biosynthetic steps have been investigated, the key O-methyltransferase (OMT) responsible for the O-methylation of emodin to generate questin has remained unidentified. Herein, through phylogenetic tree analysis and in vitro biochemical assays, the long-sought class II emodin-O-methyltransferase GedA has been functionally characterized. Additionally, the catalytic mechanism and key residues at the catalytic site of GedA were elucidated by enzyme-substrate-methyl donor analogue ternary complex crystal structure determination and site-directed mutagenesis. As we demonstrate, GedA adopts a typical general acid/base (E446/H373)-mediated transmethylation mechanism. In particular, residue D374 is also crucial for efficient catalysis through blocking the formation of intramolecular hydrogen bonds in emodin. This study will facilitate future engineering of GedA for the production of physcion or other site-specific O-methylated anthraquinone derivatives with potential applications as biopesticides.

Sequential immunizations confer cross-protection against variants of SARS-CoV-2, including Omicron in Rhesus macaques.

Variants of concern (VOCs) like Delta and Omicron, harbor a high number of mutations, which aid these viruses in escaping a majority of known SARS-CoV-2 neutralizing antibodies (NAbs). In this study, Rhesus macaques immunized with 2-dose inactivated vaccines (Coronavac) were boosted with an additional dose of homologous vaccine or an RBD-subunit vaccine, or a bivalent inactivated vaccine (Beta and Delta) to determine the effectiveness of sequential immunization. The booster vaccination significantly enhanced the duration and levels of neutralizing antibody titers against wild-type, Beta, Delta, and Omicron. Animals administered with an indicated booster dose and subsequently challenged with Delta or Omicron variants showed markedly reduced viral loads and improved histopathological profiles compared to control animals, indicating that sequential immunization could protect primates against Omicron. These results suggest that sequential immunization of inactivated vaccines or polyvalent vaccines could be a potentially effective countermeasure against newly emerging variants.

Differential transcriptomic landscapes of multiple organs from SARS-CoV-2 early infected rhesus macaques.

SARS-CoV-2 infection causes complicated clinical manifestations with variable multi-organ injuries, however, the underlying mechanism, in particular immune responses in different organs, remains elusive. In this study, comprehensive transcriptomic alterations of 14 tissues from rhesus macaque infected with SARS-CoV-2 were analyzed. Compared to normal controls, SARS-CoV-2 infection resulted in dysregulation of genes involving diverse functions in various examined tissues/organs, with drastic transcriptomic changes in cerebral cortex and right ventricle. Intriguingly, cerebral cortex exhibited a hyperinflammatory state evidenced by significant upregulation of inflammation response-related genes. Meanwhile, expressions of coagulation, angiogenesis and fibrosis factors were also up-regulated in cerebral cortex. Based on our findings, neuropilin 1 (NRP1), a receptor of SARS-CoV-2, was significantly elevated in cerebral cortex post infection, accompanied by active immune response releasing inflammatory factors and signal transmission among tissues, which enhanced infection of the central nervous system (CNS) in a positive feedback way, leading to viral encephalitis. Overall, our study depicts a multi-tissue/organ transcriptomic landscapes of rhesus macaque with early infection of SARS-CoV-2, and provides important insights into the mechanistic basis for COVID-19-associated clinical complications.