CRISPR‐Cas Biochemistry and CRISPR‐Based Molecular Diagnostics

Polymerase chain reaction (PCR)‐based nucleic acid testing has played a critical role in disease diagnostics, pathogen surveillance, and many more. However, this method requires a long turnaround time, expensive equipment, and trained personnel, limiting its widespread availability and diagnostic capacity. On the other hand, the clustered regularly interspaced short palindromic repeats (CRISPR) technology has recently demonstrated capability for nucleic acid detection with high sensitivity and specificity. CRISPR‐mediated biosensing holds great promise for revolutionizing nucleic acid testing procedures and developing point‐of‐care diagnostics. This review focuses on recent developments in both fundamental CRISPR biochemistry and CRISPR‐based nucleic acid detection techniques. Four ongoing research hotspots in molecular diagnostics‐target preamplification‐free detection, microRNA (miRNA) testing, non‐nucleic‐acid detection, and SARS‐CoV‐2 detection‐are also covered.

CRISPR-Cas Biochemistry and CRISPR-Based Molecular Diagnostics.

Polymerase chain reaction (PCR)-based nucleic acid testing has played a critical role in disease diagnostics, pathogen surveillance, and many more. However, this method requires a long turnaround time, expensive equipment, and trained personnel, limiting its widespread availability and diagnostic capacity. On the other hand, the clustered regularly interspaced short palindromic repeats (CRISPR) technology has recently demonstrated capability for nucleic acid detection with high sensitivity and specificity. CRISPR-mediated biosensing holds great promise for revolutionizing nucleic acid testing procedures and developing point-of-care diagnostics. This review focuses on recent developments in both fundamental CRISPR biochemistry and CRISPR-based nucleic acid detection techniques. Four ongoing research hotspots in molecular diagnostics-target preamplification-free detection, microRNA (miRNA) testing, non-nucleic-acid detection, and SARS-CoV-2 detection-are also covered.

Engineered LwaCas13a with enhanced collateral activity for nucleic acid detection.

Clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 13 (Cas13) has been rapidly developed for nucleic-acid-based diagnostics by using its characteristic collateral activity. Despite the recent progress in optimizing the Cas13 system for the detection of nucleic acids, engineering Cas13 protein with enhanced collateral activity has been challenging, mostly because of its complex structural dynamics. Here we successfully employed a novel strategy to engineer the Leptotrichia wadei (Lwa)Cas13a by inserting different RNA-binding domains into a unique active-site-proximal loop within its higher eukaryotes and prokaryotes nucleotide-binding domain. Two LwaCas13a variants showed enhanced collateral activity and improved sensitivity over the wild type in various buffer conditions. By combining with an electrochemical method, our variants detected the SARS-CoV-2 genome at attomolar concentrations from both inactive viral and unextracted clinical samples, without target preamplification. Our engineered LwaCas13a enzymes with enhanced collateral activity are ready to be integrated into other Cas13a-based platforms for ultrasensitive detection of nucleic acids.

Motivation and Its Effect on Language Achievement: Sustainable Development of Chinese Middle School Students' Second Language Learning

The spread of COVID-19 has changed the traditional education pattern, and prolonged home isolation and online learning have brought unprecedented challenges to second language teaching and learning. A sample of 1036 Chinese students from four representative middle schools participated in the research. The results indicated four motivations: intrinsic interest, learning situation, personal development, and immediate achievement. There were significant gender differences in English learning motivation. Moreover, intrinsic interest and personal development motivation had a significantly positive impact on English learning achievement, while learning situation had no significant impact, and immediate achievement motivation had a significantly negative impact. The findings highlight the cultivation of students' learning autonomy and school-family interaction to promote the sustainable development of middle school students' second language learning.

COVID-19 Chest CT Image Segmentation Network by Multi-Scale Fusion and Enhancement Operations.

A novel coronavirus disease 2019 (COVID-19) was detected and has spread rapidly across various countries around the world since the end of the year 2019. Computed Tomography (CT) images have been used as a crucial alternative to the time-consuming RT-PCR test. However, pure manual segmentation of CT images faces a serious challenge with the increase of suspected cases, resulting in urgent requirements for accurate and automatic segmentation of COVID-19 infections. Unfortunately, since the imaging characteristics of the COVID-19 infection are diverse and similar to the backgrounds, existing medical image segmentation methods cannot achieve satisfactory performance. In this article, we try to establish a new deep convolutional neural network tailored for segmenting the chest CT images with COVID-19 infections. We first maintain a large and new chest CT image dataset consisting of 165,667 annotated chest CT images from 861 patients with confirmed COVID-19. Inspired by the observation that the boundary of the infected lung can be enhanced by adjusting the global intensity, in the proposed deep CNN, we introduce a feature variation block which adaptively adjusts the global properties of the features for segmenting COVID-19 infection. The proposed FV block can enhance the capability of feature representation effectively and adaptively for diverse cases. We fuse features at different scales by proposing Progressive Atrous Spatial Pyramid Pooling to handle the sophisticated infection areas with diverse appearance and shapes. The proposed method achieves state-of-the-art performance. Dice similarity coefficients are 0.987 and 0.726 for lung and COVID-19 segmentation, respectively. We conducted experiments on the data collected in China and Germany and show that the proposed deep CNN can produce impressive performance effectively. The proposed network enhances the segmentation ability of the COVID-19 infection, makes the connection with other techniques and contributes to the development of remedying COVID-19 infection.

SARS-CoV-2 Spike Protein Dictates Syncytium-mediated Lymphocyte Elimination (preprint)

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus is highly contagious and causes lymphocytopenia, but the underlying mechanisms are poorly understood. We demonstrate here that heterotypic cell-in-cell structures with lymphocytes inside multinucleate syncytia are prevalent in the lung tissues of coronavirus disease 2019 (COVID-19) patients. These unique cellular structures are a direct result of SARS-CoV-2 infection, as the expression of the SARS-CoV-2 spike glycoprotein is sufficient to induce a rapid (approximately 45.1 nm/sec) membrane fusion to produce syncytium, which could readily internalize multiple lines of lymphocytes to form typical cell-in-cell structures, remarkably leading to the death of internalized cells. This membrane fusion is dictated by a bi-arginine motif within the polybasic S1/S2 cleavage site, which is frequently present in the surface glycoprotein of most highly contagious viruses. Moreover, candidate anti-viral drugs could efficiently inhibit spike glycoprotein processing, membrane fusion, and cell-in-cell formation. Together, we delineate a molecular and cellular rationale for SARS-CoV-2 pathogenesis and identify novel targets for COVID-19 therapy.

AI-assisted CT imaging analysis for COVID-19 screening: Building and deploying a medical AI system.

The sudden outbreak of novel coronavirus 2019 (COVID-19) increased the diagnostic burden of radiologists. In the time of an epidemic crisis, we hope artificial intelligence (AI) to reduce physician workload in regions with the outbreak, and improve the diagnosis accuracy for physicians before they could acquire enough experience with the new disease. In this paper, we present our experience in building and deploying an AI system that automatically analyzes CT images and provides the probability of infection to rapidly detect COVID-19 pneumonia. The proposed system which consists of classification and segmentation will save about 30%-40% of the detection time for physicians and promote the performance of COVID-19 detection. Specifically, working in an interdisciplinary team of over 30 people with medical and/or AI background, geographically distributed in Beijing and Wuhan, we are able to overcome a series of challenges (e.g. data discrepancy, testing time-effectiveness of model, data security, etc.) in this particular situation and deploy the system in four weeks. In addition, since the proposed AI system provides the priority of each CT image with probability of infection, the physicians can confirm and segregate the infected patients in time. Using 1,136 training cases (723 positives for COVID-19) from five hospitals, we are able to achieve a sensitivity of 0.974 and specificity of 0.922 on the test dataset, which included a variety of pulmonary diseases.

Invasive Mechanical Ventilation May Be an Important Factor of Mortality in Severe/Critical COVID-19 Pneumonia: A Retrospective Cohort Study (preprint)

Background: Many of severe COVID-19 patients are admitted to the hospital or even to the Intensive Care Unit(ICU). The present study was aimed to investigated the risk factors in death from COVID-19.Methods: In this retrospective study, all inpatients confirmed severe or critical COVID-19 from two tertiary hospital in Huangshi were included, who had been discharged or died by March19,2020. Demographic,clinical,treatment,laboratory data and information were extracted from electronic medical records and compared between survivors group and non-survivors group. The univariable and multivariable logistic regression analysis was used to analyze the risk factors associated with in-hospital death.Results: 81 patients were included in this study, of whom 55 were discharged and 26 died in hospital. In all patients, 36(44.4%) patients had comorbidity, including hypertension(27[33.3%]), diabetes(11[13.6%]) and coronary heart disease (CHD)(11[13.6%]), and 16(19.8%) patients accompanied with more than 2 kinds of underlying diseases. The proportion of CHD in non-survivors group was significantly higher than that in survivors group(26.9% vs 7.3%, P=0.032), but there were no differences in hypertension, diabetes and COPD between the non-survivors group and the survivors group. Multivariable logistic regression analysis showed increasing odds of in-hospital death associated with aspartate aminotransferase(AST) and invasive mechanical ventilation (IMV) (P<0.001)(P=0.017）.Conclusions: Invasive Mechanical Ventilation may contribute to mortality of severe/critical COVID-19 pneumonia, and with higher AST at admission was one of the indicators of poor prognosis.Trial registration: Chinese Clinical Trial Registration; ChiCTR2000031494; Registered 02 April 2020; http://www.medresman.org

Treatment of Severe COVID-19 with Human Umbilical Cord Mesenchymal Stem Cells (preprint)

Background: COVID-19 is a highly infectious respiratory disease. No therapeutics have yet been proven effective for treating severe COVID-19. Objectives: To determine whether human umbilical cord mesenchymal stem cell infusion may be effective and safe for the treatment of severe COVID-19. Methods: Patients with severe COVID-19 were randomly divided into 2 groups: the standard treatment group and the standard treatment plus hUC-MSC infusion group. The incidence of progression from severe to critical illness, 28-day mortality, clinical symptom improvement, time to clinical symptom improvement, hematologic indicators including C-reactive protein, lymphocyte number, and interleukin 6, and imaging changes were observed and compared between the two groups. Measurements and Main Results: The incidence of progression from severe to critical illness and the 28-day mortality rate were 0 in the hUC-MSC treatment group, while 4 patients in the control group deteriorated to critical condition and received invasive ventilation; 3 of them died, and the 28-day mortality rate was 10.34% . In the hUC-MSC treatment group, the time to clinical improvement was shorter than that in the control group. Clinical symptoms of weakness and fatigue, shortness of breath, and low oxygen saturation obviously improved beginning on the third day of stem cell infusion and reached a significant difference on day 7. CRP and IL-6 levels were significantly lower from day 3 of infusion, the time for the lymphocyte count to return to the normal range was significantly faster, and lung inflammation absorption was significantly shorter on CT imaging in the hUC-MSC group than in the control group. Conclusions: Intravenous transplantation of hUC-MSCs is a safe and effective method that can be considered a salvage and priority treatment option for severe COVID-19.

Baidu Jieduan granule, traditional Chinese medicine, in the treatment of moderate coronavirus disease-2019 (COVID-19): study protocol for an open-label randomized controlled clinical trial (preprint)

Background: Currently, coronavirus disease-2019 (COVID-19) is continuously and rapidly circulating, resulting in serious and extensive impact on human health. Due to the absence of antiviral medicine for COVID-19 thus far, it is desperately need to develop the effective medicine. Traditional Chinese medicine (TCM) has been widely applied in the treatment of epidemic diseases in China, hoping to produce clinical efficacy and decrease the use of antibiotics and glucocorticoid. The aim of this study is to evaluate the efficacy and safety of Baidu Jieduan granule in curing COVID-19. Methods/design: This multicenter, open-label randomized controlled trial is conducted 300 cases with COVID-19. The patients will be randomly (1:1) divided into treatment group or control group. All cases will receive standard therapy at the same time. The experiment group will receive Baidu Jieduan granule treatment twice a day for 14 days. The outcomes are assessed at baseline and at 3, 5, 7, 14 days after treatment initiation. The primary outcome is the rate of symptom (fever, fatigue, and coughing) recovery. Adverse events (AEs) will be monitored throughout the trial.Discussion: The study will provide a high-quality clinical evidence to support the efficacy and safety of Baidu Jieduan granule in treatment of moderate COVID-19, and also enrich the theory and practice of TCM in treating COVID-19. Trial registration: Chinese Clinical Trial Registry, ChiCTR2000029869. Registered on 15 February 2020

Systemic Analysis of Tissue Cells Potentially Vulnerable to Sars-Cov-2 Infection by the Protein-Proofed Single-Cell Rna Profiling of Ace2, Tmprss2 and Furin Proteases (preprint)

Single-cell RNA profiling of ACE2, the SARS-CoV-2 receptor, had proposed multiple tissue cells as the potential targets of SARS-CoV-2, the novel coronavirus causing the COVID-19 pandemic. However, most were not echoed by the patients’ clinical manifestations, largely due to the lack of protein expression information of ACE2 and co-factors. Here, we incorporated the protein information to analyse the expression of ACE2, together with TMPRSS2 and Furin, two proteases assisting SARS-CoV-2 infection, at single cell level in situ, which we called protein-proofed single-cell RNA (pscRNA) profiling. Systemic analysis across 36 tissues revealed a rank list of candidate cells potentially vulnerable to SARS-CoV-2. The top targets are lung AT2 cells and macrophages, then cardiomyocytes and adrenal gland stromal cells, followed by stromal cells in testis, ovary and thyroid. Whereas, the polarized kidney proximal tubule cells, liver cholangiocytes and intestinal enterocytes are less likely to be the primary SARS-CoV-2 targets as ACE2 localizes at the apical region of cells, where the viruses may not readily reach. These findings are in concert with the clinical characteristics of prominent lung symptoms, frequent heart injury, and uncommon intestinal symptoms and acute kidney injury. Together, we provide a comprehensive view on the potential SARS-CoV-2 targets by pscRNA profiling, and propose that, in addition to acute respiratory distress syndrome, attentions should also be paid to the potential injuries in cardiovascular, endocrine and reproductive systems during the treatment of COVID-19 patients.

Systemic analysis of tissue cells potentially vulnerable to SARS-CoV-2 infection by the protein-proofed single-cell RNA profiling of ACE2, TMPRSS2 and Furin proteases (preprint)

Single-cell RNA profiling of ACE2, the SARS-CoV-2 receptor, had proposed multiple tissue cells as the potential targets of SARS-CoV-2, the novel coronavirus causing the COVID-19 pandemic. However, most were not echoed by the patients clinical manifestations, largely due to the lack of protein expression information of ACE2 and co-factors. Here, we incorporated the protein information to analyse the expression of ACE2, together with TMPRSS2 and Furin, two proteases assisting SARS-CoV-2 infection, at single cell level in situ, which we called protein-proofed single-cell RNA (pscRNA) profiling. Systemic analysis across 36 tissues revealed a rank list of candidate cells potentially vulnerable to SARS-CoV-2. The top targets are lung AT2 cells and macrophages, then cardiomyocytes and adrenal gland stromal cells, followed by stromal cells in testis, ovary and thyroid. Whereas, the polarized kidney proximal tubule cells, liver cholangiocytes and intestinal enterocytes are less likely to be the primary SARS-CoV-2 targets as ACE2 localizes at the apical region of cells, where the viruses may not readily reach. Actually, the stomach may constitute a physical barrier against SARS-CoV-2 as the acidic environment in normal stomach (pH < 2.0) could completely inactivate SARS-CoV-2 pseudo-viruses. These findings are in concert with the clinical characteristics of prominent lung symptoms, frequent heart injury, and uncommon intestinal symptoms and acute kidney injury. Together, we provide a comprehensive view on the potential SARS-CoV-2 targets by pscRNA profiling, and propose that, in addition to acute respiratory distress syndrome, attentions should also be paid to the potential injuries in cardiovascular, endocrine and reproductive systems during the treatment of COVID-19 patients.