Random forest regression on joint role of meteorological variables, demographic factors, and policy response measures in COVID-19 daily cases: global analysis in different climate zones.

Different sources of factors in environment can affect the spread of COVID-19 by influencing the diffusion of the virus transmission, but the collective influence of which has hardly been considered. This study aimed to utilize a machine learning algorithm to assess the joint effects of meteorological variables, demographic factors, and government response measures on COVID-19 daily cases globally at city level. Random forest regression models showed that population density was the most crucial determinant for COVID-19 transmission, followed by meteorological variables and response measures. Ultraviolet radiation and temperature dominated meteorological factors, but the associations with daily cases varied across different climate zones. Policy response measures have lag effect in containing the epidemic development, and the pandemic was more effectively contained with stricter response measures implemented, but the generalized measures might not be applicable to all climate conditions. This study explored the roles of demographic factors, meteorological variables, and policy response measures in the transmission of COVID-19, and provided evidence for policymakers that the design of appropriate policies for prevention and preparedness of future pandemics should be based on local climate conditions, population characteristics, and social activity characteristics. Future work should focus on discerning the interactions between numerous factors affecting COVID-19 transmission.

High-sensitivity profiling of SARS-CoV-2 noncoding region-host protein interactome reveals the potential regulatory role of negative-sense viral RNA.

A deep understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-host interactions is crucial to developing effective therapeutics and addressing the threat of emerging coronaviruses. The role of noncoding regions of viral RNA (ncrRNAs) has yet to be systematically scrutinized. We developed a method using MS2 affinity purification coupled with liquid chromatography-mass spectrometry and designed a diverse set of bait ncrRNAs to systematically map the interactome of SARS-CoV-2 ncrRNA in Calu-3, Huh7, and HEK293T cells. Integration of the results defined the core ncrRNA-host protein interactomes among cell lines. The 5' UTR interactome is enriched with proteins in the small nuclear ribonucleoproteins family and is a target for the regulation of viral replication and transcription. The 3' UTR interactome is enriched with proteins involved in the stress granules and heterogeneous nuclear ribonucleoproteins family. Intriguingly, compared with the positive-sense ncrRNAs, the negative-sense ncrRNAs, especially the negative-sense of 3' UTR, interacted with a large array of host proteins across all cell lines. These proteins are involved in the regulation of the viral production process, host cell apoptosis, and immune response. Taken together, our study depicts the comprehensive landscape of the SARS-CoV-2 ncrRNA-host protein interactome and unveils the potential regulatory role of the negative-sense ncrRNAs, providing a new perspective on virus-host interactions and the design of future therapeutics. Given the highly conserved nature of UTRs in positive-strand viruses, the regulatory role of negative-sense ncrRNAs should not be exclusive to SARS-CoV-2. IMPORTANCE Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes COVID-19, a pandemic affecting millions of lives. During replication and transcription, noncoding regions of the viral RNA (ncrRNAs) may play an important role in the virus-host interactions. Understanding which and how these ncrRNAs interact with host proteins is crucial for understanding the mechanism of SARS-CoV-2 pathogenesis. We developed the MS2 affinity purification coupled with liquid chromatography-mass spectrometry method and designed a diverse set of ncrRNAs to identify the SARS-CoV-2 ncrRNA interactome comprehensively in different cell lines and found that the 5' UTR binds to proteins involved in U1 small nuclear ribonucleoprotein, while the 3' UTR interacts with proteins involved in stress granules and the heterogeneous nuclear ribonucleoprotein family. Interestingly, negative-sense ncrRNAs showed interactions with a large number of diverse host proteins, indicating a crucial role in infection. The results demonstrate that ncrRNAs could serve diverse regulatory functions.

The effectiveness of an augmented reality app in online civil engineering learning: Journal of the Association for Programmed Learning

In this study, an AR-based mobile learning application is proposed to assist online civil engineering course learning during the COVID-19 pandemic. A quasi-experiment has been conducted, and feedback from both the teacher and students has been analysed to examine the effectiveness of the proposed approach in terms of learning achievements. The subjects were 46 sophomores who majored in civil engineering in one class taught by one instructor in a southern U.S. state university. The quasi-experimental results showed that the proposed approach could not significantly improve the students' online learning achievements. However, the feedbacks brought some explanation to this non-significant result. They indicated that students found this mobile AR app to be an interesting, helpful, practical, and effective approach in their online learning that helped them gain more in-depth knowledge than traditional teacher-centred classroom instruction.

Correction to: An approach to MCGDM based on multi-granulation Pythagorean fuzzy rough set over two universes and its application to medical decision problem

Reports an error in "An approach to MCGDM based on multi-granulation Pythagorean fuzzy rough set over two universes and its application to medical decision problem" by Bingzhen Sun, Sirong Tong, Weimin Ma, Ting Wang and Chao Jiang (Artificial Intelligence Review, 2022[Mar], Vol 55[3], 1887-1913). In the original article, the third and fourth author's affiliation were published incorrectly and the correct affiliations are given in this correction. (The following abstract of the original article appeared in record 2021-74641-001). Exploring efficiency approaches to solve the problems of decision making under uncertainty is a mainstream direction. This article explores the rough approximation of the uncertainty information with Pythagorean fuzzy information on multi-granularity space over two universes combined with grey relational analysis. Based on grey relational analysis, we present a new approach to calculate the relative degree or the attribute weight with Pythagorean fuzzy set and give a new descriptions for membership degree and non-membership. Then, this paper proposes a multi-granulation rough sets combined with Pythagorean fuzzy set, including optimistic multi-granulation Pythagorean fuzzy rough set, pessimistic multi-granulation Pythagorean fuzzy rough set and variable precision Pythagorean fuzzy rough set. Several basic properties for the established models are investigated in detail. Meanwhile, we present an approach to solving the multiple-criteria group decision making problems with fuzzy information based on the proposed model. Eventually, a case study of psychological evaluation of health care workers in COVID-19 show the principle of the established model and is utilized to verify the availability. The main contributions have three aspects. The first contribution of an approach of calculating the attribute weight is presented based on Grey Relational Analysis and gives a new perspective for the Pythagorean fuzzy set. Then, this paper proposes a mutli-granulation rough set model with Pythagorean fuzzy set over two universes. Finally, we apply the proposed model to solving the psychological evaluation problems. (PsycInfo Database Record (c) 2023 APA, all rights reserved)

Neutrophil autophagy and NETosis in COVID-19: perspectives.

The COVID-19 pandemic has caused substantial losses worldwide in people's lives, health, and property. Currently, COVID-19 is still prominent worldwide without any specific drug treatment. The SARS-CoV-2 pathogen is the cause of various systemic diseases, mainly acute pneumonia. Within the pathological process, neutrophils are recruited to infected sites, especially in the lungs, for the first stage of removing invading SARS-CoV-2 through a range of mechanisms. Macroautophagy/autophagy, a conserved autodegradation process in neutrophils, plays a crucial role in the neutrophil phagocytosis of pathogens. NETosis refers to neutrophil cell death, while auto-inflammatory factors and antigens release NETs. This review summarizes the latest research progress and provides an in-depth explanation of the underlying mechanisms of autophagy and NETosis in COVID-19. Furthermore, after exploring the relationship between autophagy and NETosis, we discuss potential targets and treatment options. This review keeps up with the latest research on COVID-19 from neutrophil autophagy and NETosis with a new perspective, which can guide the urgent development of antiviral drugs and provide guidance for the clinical treatment of COVID-19.Abbreviations: AKT1: AKT serine/threonine kinase 1; AMPK: AMP-activated protein kinase; AP: autophagosome; ARDS: acute respiratory distress syndrome; ATG: autophagy related; BECN1: beclin 1; cfDNA: cell-free DNA; COVID-19: coronavirus disease 2019; CQ: chloroquine; DMVs: double-membrane vesicles; ELANE/NE: elastase, neutrophil expressed; F3: coagulation factor III, tissue factor; HCQ: hydroxychloroquine; MAP1LC3/LC3: microtubule associated protein 1 light chain of 3; MPO: myeloperoxidase; MTORC1: mechanistic target of rapamycin kinase complex 1; NETs: neutrophil traps; NSP: nonstructural protein; PI3K: class I phosphoinositide 3-kinase; PtdIns3K: class III phosphatidylinositol 3-kinase; PtdIns3P: phosphatidylinositol-3-phosphate; ROS: reactive oxygen species; SARS-CoV-2: severe acute respiratory syndrome coronavirus 2; SKP2: S-phase kinase associated protein 2; TCC: terminal complement complex; ULK1: unc-51 like.

Associations of face-to-face and non-face-to-face social isolation with all-cause and cause-specific mortality: 13-year follow-up of the Guangzhou Biobank Cohort study.

BACKGROUND: Although social isolation has been associated with a higher mortality risk, little is known about the potential different impacts of face-to-face and non-face-to-face isolation on mortality. We examined the prospective associations of four types of social isolation, including face-to-face isolation with co-inhabitants and non-co-inhabitants, non-face-to-face isolation, and club/organization isolation, with all-cause and cause-specific mortality separately. METHODS: This prospective cohort study included 30,430 adults in Guangzhou Biobank Cohort Study (GBCS), who were recruited during 2003-2008 and followed up till Dec 2019. RESULTS: During an average of 13.2 years of follow-up, 4933 deaths occurred during 396,466 person-years. Participants who lived alone had higher risks of all-cause (adjusted hazard ratio (AHR) 1.24; 95% confidence interval (CI) 1.04-1.49) and cardiovascular disease (CVD) (1.61; 1.20-2.03) mortality than those who had ≥ 3 co-habitant contact after adjustment for thirteen potential confounders. Compared with those who had ≥ 1 time/month non-co-inhabitant contact, those without such contact had higher risks of all-cause (1.60; 1.20-2.00) and CVD (1.91; 1.20-2.62) mortality. The corresponding AHR (95% CI) in participants without telephone/mail contact were 1.27 (1.14-1.42) for all-cause, 1.30 (1.08-1.56) for CVD, and 1.37 (1.12-1.67) for other-cause mortality. However, no association of club/organization contact with the above mortality and no association of all four types of isolation with cancer mortality were found. CONCLUSIONS: In this cohort study, face-to-face and non-face-to-face isolation were both positively associated with all-cause, CVD-, and other-cause (but not cancer) mortality. Our finding suggests a need to promote non-face-to-face contact among middle-aged and older adults.

Epidemiological characteristics of traumatic spinal cord injuries in a multicenter retrospective study in northwest China, 2017-2020.

Background: Traumatic spinal cord injuries (TSCIs) are worldwide public health problems that are difficult to cure and impose a substantial economic burden on society. There has been a lack of extensive multicenter review of TSCI epidemiology in northwest China during the Corona Virus Disease 2019 (COVID-19) pandemic. Method: A multicenter retrospective study of 14 selected hospitals in two provinces in northwest China was conducted on patients admitted for TSCI between 2017 and 2020. Variables assessed included patient demographics, etiology, segmental distribution, treatment, waiting time for treatment, and outcomes. Results: The number of patients with TSCI showed an increasing trend from 2017 to 2019, while there were 12.8% fewer patients in 2020 than in 2019. The male-to-female ratio was 3.67:1, and the mean age was 48 ± 14.9 years. The primary cause of TSCI was high falls (38.8%), slip falls/low falls (27.7%), traffic accidents (23.9%), sports (2.6%), and other factors (7.0%). The segmental distribution showed a bimodal pattern, peak segments were C6 and L1 vertebra, L1 (14.7%), T12 (8.2%), and C6 (8.2%) were the most frequently injured segments. In terms of severity, incomplete injury (72.8%) occurred more often than complete injury (27.2%). The American Spinal Injury Association impairment scale of most patients did not convert before and after treatment in the operational group (71.6%) or the conservative group (80.6%). A total of 975 patients (37.2%) from urban and 1,646 patients (62.8%) from rural areas were included; almost all urban residents could rush to get treatment after being injured immediately (<1 h), whereas most rural patients get the treatment needed 4-7 h after injury. The rough annual incidence from 2017 to 2020 is 112.4, 143.4, 152.2, and 132.6 per million people, calculated by the coverage rate of the population of the sampling hospital. Conclusion: The incidence of TSCI in northwest China is high and on the rise. However, due to pandemic policy reasons, the incidence of urban residents decreased in 2020. The promotion of online work may be an effective primary prevention measure for traumatic diseases. Also, because of the further distance from the good conditional hospital, rural patients need to spend more time there, and the timely treatment of patients from remote areas should be paid attention to.

Regulated necrosis in COVID-19: A double-edged sword.

COVID-19 caused by SARS-CoV-2 can cause various systemic diseases such as acute pneumonia with cytokine storm. Constituted of necroptosis, pyroptosis, and ferroptosis, regulated necrosis constitutes the cell death patterns under the low apoptosis condition commonly observed in COVID-19. Regulated necrosis is involved in the release of cytokines like TNF-α, IL-1 ß, and IL-6 and cell contents such as alarmins, PAMPs, and DAMPs, leading to more severe inflammation. Uncontrolled regulated necrosis may explain the poor prognosis and cytokine storm observed in COVID-19. In this review, the pathophysiology and mechanism of regulated necrosis with the double-edged sword effect in COVID-19 are thoroughly discussed in detail. Furthermore, this review also focuses on the biomarkers and potential therapeutic targets of the regulated necrosis pathway in COVID-19, providing practical guidance to judge the severity, prognosis, and clinical treatment of COVID-19 and guiding the development of clinical anti-SARS-CoV-2 drugs.

Real-time monitoring of isothermal nucleic acid amplification on a smartphone by using a portable electrochemical device for home-testing of SARS-CoV-2.

Home-testing of SARS-CoV-2 is an ideal approach for controlling the pandemic of COVID-19 and alleviating the shortage of medical resource caused by this acute infectious disease. Herein, a portable device that enables real-time monitoring of isothermal nucleic acid amplification tests (INAATs) through the electrochemistry method was fabricated for home-testing of SARS-CoV-2. First, a disposable plug-and-play pH-sensitive potentiometric sensor that matches this electrochemical INAATs (E-INAATs) device was designed to allow the label-free pH sensing detection of nucleic acid. By applying Nafion film on the polyaniline-based working electrode, this sensor exhibited an excellent linear potentiometric response to pH value in the range of 6.0-8.5 with a slope of -37.45 ± 1.96 mV/pH unit. A Bluetooth module was integrated into this device to enable the users real-time monitoring INAATs on their smartphones at home. Moreover, by presetting criteria, the detection results could be automatically judged by the device to avoid human errors. Finally, the utility of this E-INAATs device was demonstrated by detecting the presence of SARS-CoV-2 nucleocapsid protein gene in artificial samples with a sensitivity of 2 × 102 copies/test within 25 min, which was comparable with fluorescence and colorimetric assay. This portable, easy-operated, sensitive, and affordable device is particularly desirable for the full integration of household SARS-CoV-2 detection products and will open a new prospect for the control of infectious diseases via electrochemical NAATs.

Deep Denoising of Raw Biomedical Knowledge Graph From COVID-19 Literature, LitCovid, and Pubtator: Framework Development and Validation.

BACKGROUND: Multiple types of biomedical associations of knowledge graphs, including COVID-19-related ones, are constructed based on co-occurring biomedical entities retrieved from recent literature. However, the applications derived from these raw graphs (eg, association predictions among genes, drugs, and diseases) have a high probability of false-positive predictions as co-occurrences in the literature do not always mean there is a true biomedical association between two entities. OBJECTIVE: Data quality plays an important role in training deep neural network models; however, most of the current work in this area has been focused on improving a model's performance with the assumption that the preprocessed data are clean. Here, we studied how to remove noise from raw knowledge graphs with limited labeled information. METHODS: The proposed framework used generative-based deep neural networks to generate a graph that can distinguish the unknown associations in the raw training graph. Two generative adversarial network models, NetGAN and Cross-Entropy Low-rank Logits (CELL), were adopted for the edge classification (ie, link prediction), leveraging unlabeled link information based on a real knowledge graph built from LitCovid and Pubtator. RESULTS: The performance of link prediction, especially in the extreme case of training data versus test data at a ratio of 1:9, demonstrated that the proposed method still achieved favorable results (area under the receiver operating characteristic curve >0.8 for the synthetic data set and 0.7 for the real data set), despite the limited amount of testing data available. CONCLUSIONS: Our preliminary findings showed the proposed framework achieved promising results for removing noise during data preprocessing of the biomedical knowledge graph, potentially improving the performance of downstream applications by providing cleaner data.

COVID-19-Related Brain Injury: The Potential Role of Ferroptosis.

The COVID-19 pandemic has caused devastating loss of life and a healthcare crisis worldwide. SARS-CoV-2 is the causative pathogen of COVID-19 and is transmitted mainly through the respiratory tract, where the virus infects host cells by binding to the ACE2 receptor. SARS-CoV-2 infection is associated with acute pneumonia, but neuropsychiatric symptoms and different brain injuries are also present. The possible routes by which SARS-CoV-2 invades the brain are unclear, as are the mechanisms underlying brain injuries with the resultant neuropsychiatric symptoms in patients with COVID-19. Ferroptosis is a unique iron-dependent form of non-apoptotic cell death, characterized by lipid peroxidation with high levels of glutathione consumption. Ferroptosis plays a primary role in various acute and chronic brain diseases, but to date, ferroptosis in COVID-19-related brain injuries has not been explored. This review discusses the mechanisms of ferroptosis and recent evidence suggesting a potential pathogenic role for ferroptosis in COVID-19-related brain injury. Furthermore, the possible routes through which SARS-CoV-2 could invade the brain are also discussed. Discoveries in these areas will open possibilities for treatment strategies to prevent or reduce brain-related complications of COVID-19.

An approach to MCGDM based on multi-granulation Pythagorean fuzzy rough set over two universes and its application to medical decision problem.

Exploring efficiency approaches to solve the problems of decision making under uncertainty is a mainstream direction. This article explores the rough approximation of the uncertainty information with Pythagorean fuzzy information on multi-granularity space over two universes combined with grey relational analysis. Based on grey relational analysis, we present a new approach to calculate the relative degree or the attribute weight with Pythagorean fuzzy set and give a new descriptions for membership degree and non-membership. Then, this paper proposes a multi-granulation rough sets combined with Pythagorean fuzzy set, including optimistic multi-granulation Pythagorean fuzzy rough set, pessimistic multi-granulation Pythagorean fuzzy rough set and variable precision Pythagorean fuzzy rough set. Several basic properties for the established models are investigated in detail. Meanwhile, we present an approach to solving the multiple-criteria group decision making problems with fuzzy information based on the proposed model. Eventually, a case study of psychological evaluation of health care workers in COVID-19 show the principle of the established model and is utilized to verify the availability. The main contributions have three aspects. The first contribution of an approach of calculating the attribute weight is presented based on Grey Relational Analysis and gives a new perspective for the Pythagorean fuzzy set. Then, this paper proposes a mutli-granulation rough set model with Pythagorean fuzzy set over two universes. Finally, we apply the proposed model to solving the psychological evaluation problems.

Tannin Supplementation Improves Oocyte Cytoplasmic Maturation and Subsequent Embryo Development in Pigs.

To investigate the effects of tannins (TA) on porcine oocyte in vitro maturation (IVM), different concentrations of TA (0, 1, 10 and 100 µg/mL) were supplemented with a maturation medium and the COCs and subsequent embryonic development were examined. The results showed that 10 µg/mL TA significantly improved the cumulus expansion index (CEI), cumulus-expansion-related genes (PTGS1, PTGS2, PTX-3, TNFAIP6 and HAS2) expression and blastocyst formation rates after parthenogenetic activation (PA), in vitro fertilization (IVF) and somatic cell nuclear transfer (SCNT) compared to the control groups, but not oocyte nuclear maturation. Nevertheless, 10 µg/mL TA dramatically enhanced the mRNA expression of oocyte-development-related genes (BMP15, GDF9, CDC2 and CYCLIN B1), GSH, ATP, SOD1, PGC1α, BMP15, GDF9 and CDC2 levels and reduced intracellular ROS level in porcine oocytes. These results indicated that porcine oocyte cytoplasmic maturation was improved by 10 µg/mL TA treatment during IVM. In contrast, a high concentration of TA (100 µg/mL) significantly decreased the CEI and PTGS1, PTGS2, PTX-3 and HAS2 mRNA expressions in cumulus cells, and reduced oocyte nuclear maturation and the total cell numbers/blastocyst. In general, these data showed that 10 µg/mL TA supplementation has beneficial effects on oocyte cytoplasmic maturation and subsequent embryonic development in pigs.

Chinese Color Nest Project : An accelerated longitudinal brain-mind cohort.

The ongoing Chinese Color Nest Project (CCNP) was established to create normative charts for brain structure and function across the human lifespan, and link age-related changes in brain imaging measures to psychological assessments of behavior, cognition, and emotion using an accelerated longitudinal design. In the initial stage, CCNP aims to recruit 1520 healthy individuals (6-90 years), which comprises three phases: developing (devCCNP: 6-18 years, N = 480), maturing (matCCNP: 20-60 years, N = 560) and aging (ageCCNP: 60-84 years, N = 480). In this paper, we present an overview of the devCCNP, including study design, participants, data collection and preliminary findings. The devCCNP has acquired data with three repeated measurements from 2013 to 2017 in Southwest University, Chongqing, China (CCNP-SWU, N = 201). It has been accumulating baseline data since July 2018 and the second wave data since September 2020 in Chinese Academy of Sciences, Beijing, China (CCNP-CAS, N = 168). Each participant in devCCNP was followed up for 2.5 years at 1.25-year intervals. The devCCNP obtained longitudinal neuroimaging, biophysical, social, behavioral and cognitive data via MRI, parent- and self-reported questionnaires, behavioral assessments, and computer tasks. Additionally, data were collected on children's learning, daily life and emotional states during the COVID-19 pandemic in 2020. We address data harmonization across the two sites and demonstrated its promise of characterizing the growth curves for the overall brain morphometry using multi-center longitudinal data. CCNP data will be shared via the National Science Data Bank and requests for further information on collaboration and data sharing are encouraged.

Orthogonal genome-wide screens of bat cells identify MTHFD1 as a target of broad antiviral therapy.

Bats are responsible for the zoonotic transmission of several major viral diseases, including those leading to the 2003 SARS outbreak and likely the ongoing COVID-19 pandemic. While comparative genomics studies have revealed characteristic adaptations of the bat innate immune system, functional genomic studies are urgently needed to provide a foundation for the molecular dissection of the viral tolerance in bats. Here we report the establishment of genome-wide RNA interference (RNAi) and CRISPR libraries for the screening of the model megabat, Pteropus alecto. We used the complementary RNAi and CRISPR libraries to interrogate P. alecto cells for infection with two different viruses: mumps virus and influenza A virus, respectively. Independent screening results converged on the endocytosis pathway and the protein secretory pathway as required for both viral infections. Additionally, we revealed a general dependence of the C1-tetrahydrofolate synthase gene, MTHFD1, for viral replication in bat cells and human cells. The MTHFD1 inhibitor, carolacton, potently blocked replication of several RNA viruses, including SARS-CoV-2. We also discovered that bats have lower expression levels of MTHFD1 than humans. Our studies provide a resource for systematic inquiry into the genetic underpinnings of bat biology and a potential target for developing broad-spectrum antiviral therapy.

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

BACKGROUND: Currently, coronavirus disease-2019 (COVID-19) is continuously and rapidly circulating, resulting in serious and extensive effects on human health. Due to the absence of antiviral medicine for COVID-19 thus far, there is a desperate need to develop effective medicine. Traditional Chinese medicine (TCM) has been widely applied in the treatment of epidemic diseases in China, with the aim of achieving clinical efficacy and decreasing the use of antibiotics and glucocorticoids. The aim of this study was to evaluate the efficacy and safety of Baidu Jieduan granules in treating COVID-19. METHODS/DESIGN: This multicentre, open-label, randomized controlled trial will be conducted in 300 patients with COVID-19. The patients will be randomly (1:1) divided into a treatment group and a control group. All patients will receive standard therapy at the same time. Patients in the experimental group will receive Baidu Jieduan granule treatment twice a day for 14 days. The outcomes will be assessed at baseline and at 3, 5, 7 and 14 days after treatment initiation. The primary outcome will be the rate of symptom (fever, fatigue and coughing) recovery. Adverse events (AEs) will be monitored throughout the trial. DISCUSSION: The study will provide high-quality clinical evidence to support the efficacy and safety of Baidu Jieduan granules in the treatment of moderate COVID-19, and enrich the theory and practice of TCM in treating COVID-19. TRIAL REGISTRATION: Chinese Clinical Trial Registry ChiCTR2000029869 . Registered on 15 February 2020.

Patient-derived SARS-CoV-2 mutations impact viral replication dynamics and infectivity in vitro and with clinical implications in vivo.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread globally with more than 33 million patients diagnosed, taking more than a million lives. Abundant mutations were observed but the functional consequences of these mutations are largely unknown. We report the mutation spectrum, replication dynamics, and infectivity of 11 patient-derived viral isolates in diverse cell lines, including the human lung cancer cell line Calu-3. We observed 46 mutations, including 9 different mutations in the spike gene. Importantly, these viral isolates show significant and consistent variations in replication dynamics and infectivity in tested cell lines, up to a 1500-fold difference in viral titers at 24 h after infecting Calu-3 cells. Moreover, we show that the variations in viral titers among viral isolates are positively correlated with blood clotting function but inversely correlated with the amount of red blood cell and hemoglobin in patients. Therefore, we provide direct evidence that naturally occurring mutations in SARS-CoV-2 can substantially change its replication dynamics and infectivity in diverse human cell lines, with clinical implications in vivo.

Shenhuang granule in the treatment of severe coronavirus disease 2019 (COVID-19): study protocol for an open-label randomized controlled clinical trial.

BACKGROUND: Currently, coronavirus disease 2019 (COVID-19) is continuously and rapidly circulating, causing heavy damage on public health. No effective antiviral treatment has been proved thus far. Traditional Chinese medicine (TCM) has been widely applied in the treatment of a variety of infection diseases in China, hoping to produce clinical effects and reduce the use of antibiotics and glucocorticoid. The aim of this study is to evaluate the efficacy and safety of Shenhuang granule in treatment of severe COVID-19. METHODS/DESIGN: This multicenter, open-label randomized controlled trial is conducted in 160 participants with severe COVID-19. The participants will be randomly (1:1) divided into treatment group or control group. All participants are given standard therapy at the same time. The experiment will receive Shenhuang granule treatment twice a day for 14 days. The clinical indicators of patients will be assessed at baseline and at 3, 5, 7, and 14 days after treatment initiation. The primary outcome is 14-day clinical outcome. Adverse events will be monitored throughout the trial. DISCUSSION: This will be the first randomized controlled trial, which evaluate the effect of Shenhuang granule in patients with severe COVID-19 in China. The results of this trial may not only provide evidence-based recommendations to clinicians to treat severe COVID-19, but also enrich the theory and practice of TCM in treating infectious diseases. TRIAL REGISTRATION: Chinese Clinical Trial Registry, ChiCTR2000029777. Registered on 13 February 2020.