Novel insight into the underlying dysregulation mechanisms of immune cell-to-cell communication by analyzing multitissue single-cell atlas of two COVID-19 patients.

How does SARS-CoV-2 cause lung microenvironment disturbance and inflammatory storm is still obscure. We here performed the single-cell transcriptome sequencing from lung, blood, and bone marrow of two dead COVID-19 patients and detected the cellular communication among them. Our results demonstrated that SARS-CoV-2 infection increase the frequency of cellular communication between alveolar type I cells (AT1) or alveolar type II cells (AT2) and myeloid cells triggering immune activation and inflammation microenvironment and then induce the disorder of fibroblasts, club, and ciliated cells, which may cause increased pulmonary fibrosis and mucus accumulation. Further study showed that the increase of T cells in the lungs may be mainly recruited by myeloid cells through ligands/receptors (e.g., ANXA1/FPR1, C5AR1/RPS19, and CCL5/CCR1). Interestingly, we also found that certain ligands/receptors (e.g., ANXA1/FPR1, CD74/COPA, CXCLs/CXCRs, ALOX5/ALOX5AP, CCL5/CCR1) are significantly activated and shared among lungs, blood and bone marrow of COVID-19 patients, implying that the dysregulation of ligands/receptors may lead to immune cell's activation, migration, and the inflammatory storm in different tissues of COVID-19 patients. Collectively, our study revealed a possible mechanism by which the disorder of cell communication caused by SARS-CoV-2 infection results in the lung inflammatory microenvironment and systemic immune responses across tissues in COVID-19 patients.

A study of the impact of COVID-19 on the Chinese stock market based on a new textual multiple ARMA model.

Coronavirus 2019 (COVID-19) has caused violent fluctuation in stock markets, and led to heated discussion in stock forums. The rise and fall of any specific stock is influenced by many other stocks and emotions expressed in forum discussions. Considering the transmission effect of emotions, we propose a new Textual Multiple Auto Regressive Moving Average (TM-ARMA) model to study the impact of COVID-19 on the Chinese stock market. The TM-ARMA model contains a new cross-textual term and a new cross-auto regressive (AR) term that measure the cross impacts of textual emotions and price fluctuations, respectively, and the adjacent matrix which measures the relationships among stocks is updated dynamically. We compute the textual sentiment scores by an emotion dictionary-based method, and estimate the parameter matrices by a maximum likelihood method. Our dataset includes the textual posts from the Eastmoney Stock Forum and the price data for the constituent stocks of the FTSE China A50 Index. We conduct a sliding-window online forecast approach to simulate the real-trading situations. The results show that TM-ARMA performs very well even after the attack of COVID-19.

Uncertainty index and stock volatility prediction: evidence from international markets.

This study investigates the predictability of a fixed uncertainty index (UI) for realized variances (volatility) in the international stock markets from a high-frequency perspective. We construct a composite UI based on the scaled principal component analysis (s-PCA) method and demonstrate that it exhibits significant in- and out-of-sample predictabilities for realized variances in global stock markets. This predictive power is more powerful than those of two commonly employed competing methods, namely, PCA and the partial least squares (PLS) methods. The result is robust in several checks. Further, we explain that s-PCA outperforms other dimension-reduction methods since it can effectively increase the impacts of strong predictors and decrease those of weak factors. The implications of this research are significant for investors who allocate assets globally.

Ligand/Receptor-mediated Cell Communication Alteration Causes the Lung Inflammation Microenvironment and the Redistribution of Inter-tissue Immune Cells in COVID-19 Patients (preprint)

How SARS-CoV-2 causes disturbances of the lung microenvironment and systemic immune response remains a mystery. Here, we first analyze detailedly paired single-cell transcriptome data of the lungs, blood and bone marrow of two patients who died of COVID-19. Second, our results demonstrate that SARS-CoV-2 infection significantly increases the cellular communication frequency between AT1/AT2 cells and highly inflammatory myeloid cells, and induces the pulmonary inflammation microenvironment, and drives the disorder of fibroblasts, club and ciliated cells, thereby causing the increase of pulmonary fibrosis and mucus accumulation. Third, our works reveal that the increase of the lung T cell infiltration is mainly recruited by myeloid cells through certain ligands/receptors (ANXA1/FPR1, C5AR1/RPS19 and CCL5/CCR1), rather than AT1/AT2. Fourth, we find that some ligands and receptors such as ANXA1/FPR1, CD74/COPA, CXCLs/CXCRs, ALOX5/ALOX5AP, CCL5/CCR1, are significantly activated and shared among patients’ lungs, blood and bone marrow, implying that dysregulated ligands and receptors may cause the migration, redistribution and the inflammatory storm of immune cells in different tissues. Overall, our study reveals a latent mechanism by which the disorders of ligands and receptors caused by SARS-CoV-2 infection drive cell communication alteration, the pulmonary inflammatory microenvironment and systemic immune responses across tissues in COVID-19 patients.

A Patent Review on SARS Coronavirus Main Protease (3CLpro ) Inhibitors.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic is an unprecedented global health emergency causing more than 4.2 million fatalities as of 30 July 2021. Only three antiviral therapies have been approved or granted emergency use authorization by the FDA. The SARS-CoV-2 3CL protease (3CLpro ) is deemed an attractive drug target as it plays an essential role in viral polyprotein processing and pathogenesis, although no inhibitors have been approved. This patent review discusses SARS coronavirus 3CLpro inhibitors that have been filed up to 30 July 2021, giving an overview on the types of inhibitors that have generated commercial interest, especially amongst drug companies. Insights into the common structural motifs required for active site binding is also discussed.

Analyzing master regulators and scRNA-seq of COVID-19 patients reveals an underlying anti-SARS-CoV-2 mechanism of ZNF proteins.

Studies have demonstrated that both mortality and severe illness rates exist significant difference in different gender COVID-19 patients, but the reasons are still very mysterious to date. Here, we firstly find that the survival outcome of female patients is better to male patients through analyzing the 3044 COVID-19 cases. Secondly, we identify many important master regulators [e.g. STAT1/STAT2 and zinc finger (ZNF) proteins], in particular female patients can express more ZNF proteins and stronger transcriptional activities than male patients in response to SARS-CoV-2 infection. Thirdly, we discover that ZNF protein activity is significantly negative correlation with the SARS-CoV-2 load of COVID-19 patients, and ZNF proteins as transcription factors can also activate their target genes to participate in anti-SARS-CoV-2 infection. Fourthly, we demonstrate that ZNF protein activity is positive correlation with the abundance of multiple immune cells of COVID-19 patients, implying that the highly ZNF protein activity might promote the abundance and the antiviral activity of multiple immune cells to effectively suppress SARS-CoV-2 infection. Taken together, our study proposes an underlying anti-SARS-COV-2 role of ZNF proteins, and differences in the amount and activity of ZNF proteins might be responsible for the distinct prognosis of different gender COVID-19 patients.