Label-Free Analysis of Binding and Inhibition of SARS-Cov-19 Spike Proteins to ACE2 Receptor with ACE2-Derived Peptides by Surface Plasmon Resonance.

SARS-CoV-2 has been shown to enter and infect human cells via interactions between spike protein (S glycoprotein) and angiotensin-converting enzyme 2 (ACE2). As such, it may be possible to suppress the infection of the virus via the blocking of this binding interaction through the use of specific peptides that can mimic the human ACE 2 peptidase domain (PD) α 1-helix. Herein, we report the use of competitive assays along with surface plasmon resonance (SPR) to investigate the effect of peptide sequence and length on spike protein inhibition. The characterization of these binding interactions helps us understand the mechanisms behind peptide-based viral blockage and develop SPR methodologies to quickly screen disease inhibitors. This work not only helps further our understanding of the important biological interactions involved in viral inhibition but will also aid in future studies that focus on the development of therapeutics and drug options. Two peptides of different sequence lengths, [30-42] and [22-44], based on the α 1-helix of ACE2 PD were selected for this fundamental investigation. In addition to characterizing their inhibitory behavior, we also identified the critical amino acid residues of the RBD/ACE2-derived peptides by combining experimental results and molecular docking modeling. While both investigated peptides were found to effectively block the RBD residues known to bind to ACE2 PD, our investigation showed that the shorter peptide was able to reach a maximal inhibition at lower concentrations. These inhibition results matched with molecular docking models and indicated that peptide length and composition are key in the development of an effective peptide for inhibiting biophysical interactions. The work presented here emphasizes the importance of inhibition screening and modeling, as longer peptides are not always more effective.

Molecular insight into pentraxin-3: Update advances in innate immunity, inflammation, tissue remodeling, diseases, and drug role.

Pentraxin-3 (PTX3) is the prototype of the long pentraxin subfamily, an acute-phase protein consisting of a C-terminal pentraxin domain and a unique N-terminal domain. PTX3 was initially isolated from human umbilical vein endothelial cells and human FS-4 fibroblasts. It was subsequently found to be also produced by synoviocytes, chondrocytes, osteoblasts, smooth muscle cells, myeloid dendritic cells, epithelial cells, and tumor cells. Various modulatory factors, such as miRNAs, cytokines, drugs, and hypoxic conditions, could regulate the expression level of PTX3. PTX3 is essential in regulating innate immunity, inflammation, angiogenesis, and tissue remodeling. Besides, PTX3 may play dual (pro-tumor and anti-tumor) roles in oncogenesis. PTX3 is involved in the occurrence and development of many non-cancerous diseases, including COVID-19, and might be a potential biomarker indicating the prognosis, activity,and severity of diseases. In this review, we summarize and discuss the potential roles of PTX3 in the oncogenesis and pathogenesis of non-cancerous diseases and potential targeted therapies based on PTX3.

Characterizing the Dynamic Evolution of Interagency Collaborative Decision-Making Networks in Response to COVID-19 in China: A Policy Document Analysis.

Collaborative decision-making across multiple government agencies is considered a critical and effective strategy to combat public health crisis; however, we know little about how the collaborative decision-making works and evolves during periods of crisis. To fill this lacuna, this study uncovers the structure and evolving dynamics of the network by employing a policy document analysis. Based on the policy documents, jointly issued by the agencies of Chinese central government in four phases regarding COVID-19 control, we first constructed a co-occurrence matrix of policy-issuing agencies to outline the network structure, then drew a breadth-depth matrix to identify the role evolution of agencies, and lastly built a two-mode network consisting of policy topics and agencies to determine the evolution mechanisms of policy attentions for each agency. It was found that the network structure of interagency collaboration involves three forms: discrete structure in the early phase, subgroup structure in the middle phase, and connected structure in the latter phase. Agencies embedded in the network can be categorized into three types: leading agencies, key agencies, and auxiliary agencies, with their constituent members changed as the pandemic risks are gradually becoming under control. Furthermore, each type has its own primary policy attentions, but shares some common foci in all four phases and shifts attention in the emergency management process. This study contributes to shedding light on the formation of and variations in collaborative networks in health emergencies and provides policy implications for other countries that have struggled against COVID-19.

The determination of Sulfobutylether ß-Cyclodextrin Sodium (SBECD) by LC-MS/MS and its application in remdesivir pharmacokinetics study for pediatric patients.

SBECD (Captisol®) with an average degree of substitution of 6.5 sulfobutylether functional groups (SBE = 6.5), is a solubility enhancer for remdesivir (RDV) and a major component in Veklury, which was approved by FDA for the treatment of patients with COVID-19 over 12 years old and weighing over 40 kg who require hospitalization. SBECD is cleared mainly by renal filtration, thus, potential accumulation of SBECD in the human body is a concern for patients dosed with Veklury with compromised renal function. An LC-MS/MS method was developed and validated for specific, accurate, and precise determination of SBECD concentrations in human plasma. In this method, the hexa-substituted species, SBE6, was selected for SBECD quantification, and the mass transition from its dicharged molecular ion [(M-2H)/2]2-, Molecular (parent) Ion (Q1)/Molecular (parent) Ion (Q3) of m/z 974.7/974.7, was selected for quantitative analysis of SBECD. Captisol-G (SBE-γ-CD, SBE = 3) was chosen as the internal standard. With 25 µL of formic-acid-treated sample and with a calibration range of 10.0-1000 µg/mL, the method was validated with respect to pre-established criteria based on regulatory guidelines and was applied to determine SBECD levels in plasma samples collected from pediatric patients during RDV clinical studies.

Understanding the Evolution of Government Attention in Response to COVID-19 in China: A Topic Modeling Approach.

The effective control over the outbreak of COVID-19 in China showcases a prompt government response, in which, however, the allocation of attention, as an essential parameter, remains obscure. This study is designed to clarify the evolution of the Chinese government's attention in tackling the pandemic. To this end, 674 policy documents issued by the State Council of China are collected to establish a text corpus, which is then used to extract policy topics by applying the latent dirichlet allocation (LDA) model, a topic modelling approach. It is found that the response policies take different tracks in a four-stage controlling process, and five policy topics are identified as major government attention areas in all stages. Moreover, a topic evolution path is highlighted to show internal relationships between different policy topics. These findings shed light on the Chinese government's dynamic response to the pandemic and indicate the strength of applying adaptive governance strategies in coping with public health emergencies.

Topic Relevance of Public Health Emergencies Influence on Internet Public Opinion Resonance: Simulation Based on Langevin’s Equation

Public health emergencies occurred frequently, which usually result in the negative Internet public opinion events. In the complex network information ecological environment, multiple public opinion events may be aggregated to generate public opinion resonance due to the topic category, the mutual correlation of the subject involved, and the compound accumulation of specific emotions. In order to reveal the phenomenon and regulations of the public opinion resonance, we firstly analyze the influence factors of the Internet public opinion events in the public health emergencies. Then, based on Langevin’s equation, we propose the Internet public opinion stochastic resonance model considering the topic relevance. Furthermore, three exact public health emergencies in China are provided to reveal the regulations of evoked events “revival” caused by original events. We observe that the Langevin stochastic resonance model considering topic relevance can effectively reveal the resonance phenomenon of Internet public opinion caused by public health emergencies. For the original model without considering the topic relevance, the new model is more sensitive. Meanwhile, it is found that the degree of topic relevance between public health emergencies has a significant positive correlation with the intensity of Internet public opinion resonance.