Bidirectional causal relationships between IgA nephropathy and COVID-19: genetic evidence from Mendelian randomization (preprint)

Purpose Previous studies have suggested that patients with IgA nephropathy (IgAN) was associated with an increased risk of coronavirus disease 2019 (COVID-19) infection. However, the findings were inconsistent, and whether there was a causality between IgAN and COVID-19 infection remains unknown. This study was performed to estimate the casual effect between IgAN and COVID-19 infection with the implementation of bidirectional Mendelian randomization (MR) analysis.Methods Genetic summary data of IgAN was derived from a large genome-wide association study (GWAS) that consisted of 14,361 cases and 43,923 controls. The genetic data of COVID-19 comprised of three phenotypes, including hospitalization, severity and infection, which had a population more than 20 million. The methods of inverse variance weighting (IVW), MR-Egger, weight median and weighted mode were applied for causal inference in MR analysis.Results In the forward direction, the IVW’s results proved that IgAN did not have causal relationships with hospitalization COVID-19 (OR = 1.077, 95%CI: 0.953–1.217, P = 0.236), severe COVID-19 (OR = 1.059, 95%CI: 0.878–1.278, P = 0.547) and COVID-19 infection (OR = 0.973, 95%CI: 0.929–1.109, P = 0.243). Furthermore, reverse MR analysis showed no evidence of causal associations of hospitalization COVID-19 (OR = 1.017, 95%CI: 0.968–1.069, P = 0.499), severe COVID-19 (OR = 1.005, 95%CI: 0.979–1.078, P = 0.781) and COVID-19 infection (OR = 1.030, 95%CI: 0.909–1.169, P = 0.641) with the risk of IgAN.Conclusion Our study does not support a casual association of IgAN with the risk of COVID-19 infection, nor does the causality between COVID-19 infection and IgAN risk.

Absence of platelet overactivation and thrombosis formation among patients with coronary atherosclerosis disease after vaccination against SARS-CoV-2 (preprint)

Background Association of Coronavirus disease 2019 vaccines with thrombosis has raised concerns among patients with coronary atherosclerosis disease (CAD).Objectives After vaccination against SARS-CoV-2, to detect thrombosis formation in atherosclerosis ApoE−/− mice, and platelet activation, coagulation, the profile of prothrombotic antibodies, and the production of platelet factor 4 (PF4) antibodies in patients with CAD.Methods Atherosclerotic ApoE−/− mice were immunized with saline or inactivated SARS-CoV vaccines. We investigated FeCl3-induced thrombus formation in vivo, and thrombus formation under flow conditions ex vivo. Inpatients undergoing percutaneous coronary intervention (PCI) were consecutively enrolled and defined according to vaccination status. We evaluated coagulation by thrombelastograph (TEG), platelet activation makers by flow cytometry, PF4 antibody and antiphospholipid antibodies by ELISA, and SARS-CoV-2 neutralizing antibody.Results In atherosclerotic ApoE−/− mice, FeCl3-induced thrombus formation and thrombus formation under flow conditions were similar between saline-treated and inactivated SARS-CoV-2 vaccines-treated groups. A total of 182 patients undergoing PCI were included in the final analysis, of whom 92 had been vaccinated. Baseline characteristics were well balanced between unvaccinated and vaccinated groups. The expression of PAC-1 and P-selectin, the prevalence of positivity for PF4 antibodies and antiphospholipid antibodies were similar between these two groups.Conclusions Inactivated SARS-CoV-2 vaccines did not potentiate thrombosis formation in atherosclerotic mice. Inactivated SARS-CoV-2 vaccines did not enhance platelet activation, or trigger the production of PF4 and antiphospholipid antibodies in patients with CAD. Our data adds evidence to the safety profile of the inactivated SARS-CoV-2 vaccines.

Lower-dose Intravenous Immunoglobulin Therapy for Geriatric Inflammatory Bowel Disease Accompanied by COVID-19 Multisystem Inflammatory Syndrome: a Case Report (preprint)

Background this article presents a noteworthy case of SARS-CoV-2-associated inflammatory bowel disease (IBD) in an elderly individual who endured three hospitalizations without favorable response to conventional treatment. Ultimately, the patient's symptoms subsided following the administration of intravenous immunoglobulin (IVIg).Case presentation : the patient, an elderly individual, experienced short-term fever and sore throat after encountering the COVID-19 pandemic. Despite receiving a three-dose inactivated COVID-19 vaccine, the patient tested positive for SARS-CoV-2 antigen and developed worsening symptoms, including diarrhea and recurrent fever. Initial antibiotic treatment for bacterial enteritis proved ineffective. Further evaluation, including endoscopy and pathology, confirmed the diagnosis of IBD with concurrent multisystem inflammatory syndrome (MIS) in adults. Following lower-dose IVIg administration, the patient's symptoms improved, with resolution of fever, diarrhea, and inflammation.Conclusions the case highlights the complexity of diagnosis and treatment in geriatric with IBD and MIS, emphasizing the importance of early intervention with IVIg. Further research is needed to explore the relationship between COVID-19 infection, MIS, and acute autoimmune diseases, as well as the efficacy of IVIg in these conditions.

Model Based Reinforcement Learning with Non-Gaussian Environment Dynamics and its Application to Portfolio Optimization (preprint)

With the fast development of quantitative portfolio optimization in financial engineering, lots of AI-based algorithmic trading strategies have demonstrated promising results, among which reinforcement learning begins to manifest competitive advantages. However, the environment from real financial markets is complex and hard to be fully simulated, considering the observation of abrupt transitions, unpredictable hidden causal factors, heavy tail properties and so on. Thus, in this paper, first, we adopt a heavy-tailed preserving normalizing flows to simulate high-dimensional joint probability of the complex trading environment and develop a model-based reinforcement learning framework to better understand the intrinsic mechanisms of quantitative online trading. Second, we experiment with various stocks from three different financial markets (Dow, NASDAQ and S&P) and show that among these three financial markets, Dow gets the best performance based on various evaluation metrics under our back-testing system. Especially, our proposed method is able to mitigate the impact of unpredictable financial market crises during the COVID-19 pandemic period, resulting in a lower maximum drawdown. Third, we also explore the explanation of our RL algorithm. (1), we utilize the pattern causality method to study the interactive relation among different stocks in the environment. (2), We analyze the dynamic loss and actor loss to ensure the convergence of our strategies. (3), by visualizing high dimensional state transition data comparisons from real and virtual buffers with t-SNE, we uncover some effective patterns of better portfolio optimization strategies. (4), we also utilize eigenvalue analysis to study the convergence properties of the environmen's model.

Impact of COVID-19 lockdown on match performances in the National Basketball Association

This study aimed to compare differences in the match performances between home and away games during pre- and post-COVID-19 lockdown and to identify the key factors to match success with and without spectators. The sample consisted of 1,549 basketball matches including 971 games of the 2019–2020 regular season before the COVID-19 lockdown and 578 ghost matches of the 2020–2021 regular season after the COVID-19 pandemic. The independent t-test was used to explore the differences before and after COVID-19 while univariate and multivariable logistic regression models were used to identify the key factors to match success between matches with and without spectators. Our study identified that offensive rebounds were the only indicator differentiating between home and away games after the COVID-19 lockdown. Furthermore, home teams won more matches than away matches before the COVID-19 whereas home advantage had no impact on winning matches after the COVID-19. Our study suggested that crowd support may play a key role in winning games in the NBA. Furthermore, independently of the pre-and post-COVID19 pandemic, free throws made, three-point field goals made, defensive rebounds, assists, steals, personal fouls, and opponent quality were key factors differentiating between win and loss. Coaches and coaching staff can make informed decisions and well prepare for basketball match strategies.

Cascading impacts of global metal mining on climate change and human health caused by COVID-19 pandemic

The coronavirus disease 2019 (COVID-19) pandemic has significantly disrupted global metal mining and associated supply chains. Here we analyse the cascading effects of the metal mining disruption associated with the COVID-19 pandemic on the economy, climate change, and human health. We find that the pandemic reduced global metal mining by 10-20% in 2020. This reduction subsequently led to losses in global economic output of approximately 117 billion US dollars, reduced CO2 emissions by approximately 33 million tonnes (exceeding Hungary's emissions in 2015), and reduced human health damage by 78,192 disability-adjusted life years. In particular, copper and iron mining made the most significant contribution to these effects. China and rest-of-the-world America were the most affected. The cascading effects of the metal mining disruption associated with the pandemic on the economy, climate change, and human health should be simultaneously considered in designing green economic stimulus policies.

Epidemiological and etiological analysis of a case cluster caused by norovirus in a nursing home in Lanzhou

Objective To understand the epidemiology and etiology of a cluster of cases with gastroenteritis in a nursing home in Anning district of Lanzhou, and to provide a scientific evidence for the prevention and control of norovirus diarrhea in community nursing centers. Methods From January 28 to February 4 2021, an epidemiological investigation was conducted on all diarrhea cases, nursing staff and chefs in a nursing home in Anning district, Lanzhou city.Samples of patients′ anal swabs, feces, vomitus were collected for norovirus detection by real-time fluorescent PCR.ORF1/ORF2 junction region of norovirus in some selected positive samples（Ct value ≤ 25） was sequenced.MEGA-X software was used to construct a phylogenetic tree for genetic evolution analysis using the neighboring method. Results The first case was confirmed on January20,2021,and the number of cases peaked during January 25and 29.A total of 58clinically diagnosed cases were reported,57were older people,with an incidence of（57/360,15.83%）.Diarrhea（50/58,86.21%）,vomiting（35/58,60.34%）,nausea（13/58,22.41%）and abdominal pain（6/58,10.34%）were common symptoms,all cases were mild.Fifty-three asymptomatic cases were detected among chefs,housekeepers and nurses.A total of 163specimens were tested,the positive rate of norovirus GⅡwas 49.08%（80/163）.The positive rate of fecal samples collected from nurses,chefs and housekeepers was 48.62%（53/109）,and was11.11%（2/18）in environmental surface swabs.The possibility of other pathogenic infections such as SARS-CoV-2was ruled out by further tests.Thirteen positive samples were selected for sequencing,and 9were successfully sequenced,they were all recombinant GⅡ.4Sydney＿2012 [P16]genotypes,forming an independent cluster,while in a large evolutionary branch with the 2020GⅡ.10 [P16]and 2019GⅡ.2 [P16]virus strains in Lanzhou city,showing a relative close genetic connection. Conclusions GⅡ.4Sydney＿2012[P16]genotype of norovirus is found to be causative pathogen of this outbreak,and close contact is the main reason of the outbreak and persistence of the infection,so asymptomatic infections of norovirus play an important role in the disease spreading.Therefore,public health management in nursing homes and other centralized nursing facilities should be strengthened especially for asymptomatic workers in order to prevent virus transmission.

Research progress of herpes zoster vaccine

Herpes zoster is a cluster blister disease that often occurs on the skin of the elderly, immunocompromised individuals and patients with chronic diseases, which is caused by the reactivation of varicella zoster virus dormant in neurons.The persistent pain of herpes zoster tortures patients and is responsible for serious mental and economic burden.With no effective drug treatment for patients, vaccination becomes more important in disease prevention.Now live attenuated vaccine and recombinant protein vaccine with adjuvant are clinically available abroad.Based on the clinical data, recombinant protein vaccine with adjuvant is the preferred one recommended by CDC.In China, many enterprises perform clinical studies on the two vaccines.However, due to the limitation of adjuvant supply, recombinant protein vaccines have not been widely provided.With the global pandemic of COVID-19, mRNA vaccine becomes a hotspot worldwide.Domestic biological enterprises should actively develop new herpes zoster vaccine to fill the vaccine vacancies in China and to enhance market competitiveness.This article briefly reviews the research progress and development of herpes zoster vaccine in various vaccine platforms.

Live-attenuated pediatric parainfluenza vaccine expressing 6P-stabilized SARS-CoV-2 spike protein is protective against SARS-CoV-2 variants in hamsters (preprint)

The pediatric live-attenuated bovine/human parainfluenza virus type 3 (B/HPIV3)-vectored vaccine expressing the prefusion-stabilized SARS-CoV-2 spike (S) protein (B/HPIV3/S-2P) was previously evaluated in vitro and in hamsters. To improve its immunogenicity, we generated B/HPIV3/S-6P, expressing S further stabilized with 6 proline mutations (S-6P). Intranasal immunization of hamsters with B/HPIV3/S-6P reproducibly elicited significantly higher serum anti-S IgA/IgG titers than B/HPIV3/S-2P; hamster sera efficiently neutralized variants of concern (VoCs), including Omicron variants. B/HPIV3/S-2P and B/HPIV3/S-6P immunization protected hamsters against weight loss and lung inflammation following SARS-CoV-2 challenge with the vaccine-matched strain WA1/2020 or VoCs B.1.1.7/Alpha or B.1.351/Beta and induced near-sterilizing immunity. Three weeks post-challenge, B/HPIV3/S-2P- and B/HPIV3/S-6P-immunized hamsters exhibited a robust anamnestic serum antibody response with increased neutralizing potency to VoCs, including Omicron sublineages. B/HPIV3/S-6P primed for stronger anamnestic antibody responses after challenge with WA1/2020 than B/HPIV3/S-2P. B/HPIV3/S-6P will be evaluated as an intranasal vaccine to protect infants against both HPIV3 and SARS-CoV-2.

Plant polysaccharides with anti-lung injury effects as a potential therapeutic strategy for COVID-19

When coronavirus disease 2019 (COVID-19) develops into the severe phase, lung injury, acute respiratory distress syndrome, and/or respiratory failure could develop within a few days. As a result of pulmonary tissue injury, pathomorphological changes usually present endothelial dysfunction, inflammatory cell infiltration of the lung interstitium, defective gas exchange, and wall leakage. Consequently, COVID-19 may progress to tremendous lung injury, ongoing lung failure, and death. Exploring the treatment drugs has important implications. Recently, the application of traditional Chinese medicine had better performance in reducing fatalities, relieving symptoms, and curtailing hospitalization. Through constant research and study, plant polysaccharides may emerge as a crucial resource against lung injury with high potency and low side effects. However, the absence of a comprehensive understanding of lung-protective mechanisms impedes further investigation of polysaccharides. In the present article, a comprehensive review of research into plant polysaccharides in the past 5 years was performed. In total, 30 types of polysaccharides from 19 kinds of plants have shown lung-protective effects through the pathological processes of inflammation, oxidative stress, apoptosis, autophagy, epithelial–mesenchymal transition, and immunomodulation by mediating mucin and aquaporins, macrophage, endoplasmic reticulum stress, neutrophil, TGF-β1 pathways, Nrf2 pathway, and other mechanisms. Moreover, the deficiencies of the current studies and the future research direction are also tentatively discussed. This research provides a comprehensive perspective for better understanding the mechanism and development of polysaccharides against lung injury for the treatment of COVID-19. Graphical

Rare predicted loss-of-function variants of type I IFN immunity genes are associated with critical COVID-19 (preprint)

Background We previously reported inborn errors of TLR3- and TLR7-dependent type I interferon (IFN) immunity in 1-5% of unvaccinated patients with life-threatening COVID-19, and autoantibodies against type I IFN in another 15-20% of cases. Methods We report here a genome-wide rare variant burden association analysis in 3,269 unvaccinated patients with life-threatening COVID-19 (1,301 previously reported and 1,968 new patients), and 1,373 unvaccinated SARS-CoV-2-infected individuals without pneumonia. A quarter of the patients tested had antibodies against type I IFN (234 of 928) and were excluded from the analysis. Results No gene reached genome-wide significance. Under a recessive model, the most significant gene with at-risk variants was TLR7, with an OR of 27.68 (95%CI:1.5-528.7, P=1.1x10-4), in analyses restricted to biochemically loss-of-function (bLOF) variants. We replicated the enrichment in rare predicted LOF (pLOF) variants at 13 influenza susceptibility loci involved in TLR3-dependent type I IFN immunity (OR=3.70 [95%CI:1.3-8.2], P=2.1x10-4). Adding the recently reported TYK2 COVID-19 locus strengthened this enrichment, particularly under a recessive model (OR=19.65 [95%CI:2.1-2635.4]; P=3.4x10-3). When these 14 loci and TLR7 were considered, all individuals hemizygous (n=20) or homozygous (n=5) for pLOF or bLOF variants were patients (OR=39.19 [95%CI:5.2-5037.0], P=4.7x10-7), who also showed an enrichment in heterozygous variants (OR=2.36 [95%CI:1.0-5.9], P=0.02). Finally, the patients 13 with pLOF or bLOF variants at these 15 loci were significantly younger (mean age [SD]=43.3 [20.3] years) than the other patients (56.0 [17.3] years; P=1.68x10-5). Conclusions Rare variants of TLR3- and TLR7-dependent type I IFN immunity genes can underlie lifethreatening COVID-19, particularly with recessive inheritance, in patients under 60 years old.

Psychological resilience of emergency nurses during COVID-19 epidemic in Shanghai: A qualitative study

Background In early 2022, an outbreak of Coronavirus Disease 2019 (COVID-19) occurred in Shanghai, China. The spread of the epidemic put a large amount of stress on the local healthcare system, especially emergency nurses (ENs), which may affect their well-being and performance. Enhancing the psychological resilience of ENs during COVID-19 pandemic may improve job satisfaction, retention, and public health emergency response. However, few studies have researched the perception and psychological resilience of ENs during COVID-19 pandemic. Objective To understand ENs' perception and psychological resilience and their coping strategies with adversity during COVID-19 in Shanghai, as well as factors associated with psychological resilience. Methods This qualitative study was conducted using a phenomenological approach. A total of 17 ENs from a 3rd level hospital in Shanghai were selected using a method of purposive sampling. Between April and May 2022, in-depth semi-structured interviews and Colaizzi seven-step method were performed for data collection and analysis. Results The investigation discovered three themes and nine subthemes. The first theme is “risk factors.” Risk factors for ENs to remain resilience are sudden multiplication of workload, stressful of screening of infected patients, and the support nurses being unfamiliar with the procedure. The second theme is “promoting factors.” ENs emphasized the importance of management assurance and humanistic care, as well as social support. They recognized adversity and resilience, and used self-management strategies to cope with the situation. The third theme is “motivated by altruism.” ENs were driven by altruism to respond to adversity with a positive attitude. They realized their self-worth by helping patients with a sense of sacred mission. Conclusions Psychological resilience is not a stable psychological characteristic but a constantly changing process that is affected by internal and external factors. Enhancing resilience of ENs during the COVID-19 pandemic may improve work satisfaction, retention, and public health emergency response. Adequate preparation before a pandemic, reasonable arrangement, a trustworthy working atmosphere, encouragement and improvement of individual and collective strategies for nurses to cope with adversity, timely rewards, and nurse empowerment, as well as counseling and training, can be used to enhance psychological resilience of ENs.

Risk Factors for postoperative medical morbidity and 3-month mortality in elderly patients with hip fracture following hip arthroplasty during COVID-19 pandemic (preprint)

Background The purpose of the current study was to investigate the incidence of postoperative medical complications and 3-month mortality in patients ≥ 70 years old with hip fracture following hip arthroplasty (HA) and independent risk factors associated with postoperative medical complications and 3-month mortality during the Coronavirus Disease 2019 (COVID-19) pandemic. Methods A multicenter retrospective study was conducted, patients ≥ 70 years old with HA for hip fracture under general anesthesia were included during COVID-19 and before COVID-19 pandemic. The outcome was defined as postoperative medical complications and 3-month mortality. The baseline characteristics and risk factors were collected, multivariable logistic regression was used to identify independent risk factors for postoperative medical complications and 3-month mortality. Results A total of 1096 patients were included during COVID-19 pandemic and 1149 were included before COVID-19 pandemic in the study. Patients ≥ 70 years with hip fracture for HA had longer fracture to operation duration, and the incidence of postoperative medical complications and 3-month mortality was higher during COVID-2019 pandemic. Multivariate logistic regression analysis showed that dementia (OR,2.73; 95%CI, 1.37–5.44; P = 0.004), chronic obstructive pulmonary disease(COPD) (OR,3.00; 95%CI, 1.92–4.71; P < 0.001), longer fracture to operation duration (OR,1.24; 95%CI, 1.19–1.30; P < 0.001) were associated with increased a risk for postoperative medical complications. COPD (OR,2.10; 95%CI, 1.05–4.17; P = 0.035), dementia (OR,3.00; 95%CI, 1.11–7.94; P = 0.031), postoperative medical complications (OR,4.99; 95%CI, 2.68–9.28; P < 0.001), longer fracture to operation duration (OR,1.11; 95%CI, 1.04–1.19; P = 0.002) were associated with increased a risk for 3-month mortality. Conclusions In conclusion, we found that postoperative medical morbidity and 3-month mortality in patients with hip fracture underwent THA was 21.90% and 5.20%, respectively during the COVID-19. COPD, dementia, and longer fracture to operation duration were associated with negative outcome in patients with hip fracture underwent HA during the COVID-19.

Epidemiological characteristics of 123 confirmed COVID-19 cases in Shangrao City, Jiangxi

Objective: To describe the epidemiological characteristics of confirmed COVID-19 cases in Shangrao City, and provide scientific evidence for the development of prevention and control strategies.

Stock Trading Optimization through Model-based Reinforcement Learning with Resistance Support Relative Strength (preprint)

Reinforcement learning (RL) is gaining attention by more and more researchers in quantitative finance as the agent-environment interaction framework is aligned with decision making process in many business problems. Most of the current financial applications using RL algorithms are based on model-free method, which still faces stability and adaptivity challenges. As lots of cutting-edge model-based reinforcement learning (MBRL) algorithms mature in applications such as video games or robotics, we design a new approach that leverages resistance and support (RS) level as regularization terms for action in MBRL, to improve the algorithm's efficiency and stability. From the experiment results, we can see RS level, as a market timing technique, enhances the performance of pure MBRL models in terms of various measurements and obtains better profit gain with less riskiness. Besides, our proposed method even resists big drop (less maximum drawdown) during COVID-19 pandemic period when the financial market got unpredictable crisis. Explanations on why control of resistance and support level can boost MBRL is also investigated through numerical experiments, such as loss of actor-critic network and prediction error of the transition dynamical model. It shows that RS indicators indeed help the MBRL algorithms to converge faster at early stage and obtain smaller critic loss as training episodes increase.

Intranasal pediatric parainfluenza virus-vectored SARS-CoV-2 vaccine candidate is protective in macaques (preprint)

SUMMARY Pediatric SARS-CoV-2 vaccines are needed that elicit immunity directly in the airways, as well as systemically. Building on pediatric parainfluenza virus vaccines in clinical development, we generated a live-attenuated parainfluenza virus-vectored vaccine candidate expressing SARS-CoV-2 prefusion-stabilized spike (S) protein (B/HPIV3/S-6P) and evaluated its immunogenicity and protective efficacy in rhesus macaques. A single intranasal/intratracheal dose of B/HPIV3/S-6P induced strong S-specific airway mucosal IgA and IgG responses. High levels of S-specific antibodies were also induced in serum, which efficiently neutralized SARS-CoV-2 variants of concern. Furthermore, B/HPIV3/S-6P induced robust systemic and pulmonary S-specific CD4 + and CD8 + T-cell responses, including tissue-resident memory cells in lungs. Following challenge, SARS-CoV-2 replication was undetectable in airways and lung tissues of immunized macaques. B/HPIV3/S-6P will be evaluated clinically as pediatric intranasal SARS-CoV-2/parainfluenza virus type 3 vaccine. One-Sentence Summary Intranasal parainfluenza virus-vectored COVID-19 vaccine induces anti-S antibodies, T-cell memory and protection in macaques.

Genome-wide detection of human variants that disrupt intronic branchpoints (preprint)

ABSTRACT Pre-mRNA splicing is initiated with the recognition of a single-nucleotide intronic branchpoint (BP) within a BP motif by spliceosome elements. Fifty-six rare variants in 44 human genes have been reported to alter splicing and cause disease by disrupting BP. However, until now, no computational approach has been available to efficiently detect such variants in next-generation sequencing (NGS) data. We established a comprehensive human genome-wide BP database by integrating existing BP data, and by generating new BP data from RNA-seq of lariat debranching enzyme DBR1-mutated patients and from machine-learning predictions. We in-depth characterize multiple features of BP in major and minor introns, and find that BP and BP-2 (two-nucleotides upstream of BP) positions exhibit a lower rate of variation in human populations and higher evolutionary conservation than the intronic background, whilst being comparable to the exonic background. We develop BPHunter as a genome-wide computational approach to systematically and efficiently detect intronic variants that may disrupt BP recognition in NGS data. BPHunter retrospectively identifies 48 of the 56 known pathogenic BP mutations in which we summarize a strategy for prioritizing BP mutation candidates, and the remaining 8 all create AG dinucleotides between BP and acceptor site which is probably the reason for mis-splicing. We demonstrate the utility of BPHunter prospectively by using it to identify a novel germline heterozygous BP variant of STAT2 in a patient with critical COVID-19 pneumonia, and a novel somatic intronic 59-nucleotide deletion of ITPKB in a lymphoma patient, both of which we validate experimentally. BPHunter is publicly available from https://hgidsoft.rockefeller.edu/BPHunter and https://github.com/casanova-lab/BPHunter .

Analysis of Continuous Mutation and Evolution on Circulating SARS-CoV-2

Monitoring the mutation and evolution of the virus is important for tracing its ongoing transmission and facilitating effective vaccine development. A total of 342 complete genomic sequences of SARS-CoV-2 were analyzed in this study. Compared to the reference genome reported in December 2019, 465 mutations were found, among which, 347 occurred in only 1 sequence, while 26 occurred in more than 5 sequences. For these 26 further identified as SNPs, 14 were closely linked and were grouped into 5 profiles. Phylogenetic analysis revealed the sequences formed 2 major groups. Most of the sequences in late period (March and April) constituted the Cluster II, while the sequences before March in this study and the reported S/L and A/B/C types in previous studies were all in Cluster I. The distributions of some mutations were specific geographically or temporally, the potential effect of which on the transmission and pathogenicity of SARS-CoV-2 deserves further evaluation and monitoring. Two mutations were found in the receptor-binding domain (RBD) but outside the receptor-binding motif (RBM), indicating that mutations may only have marginal biological effects but merit further attention. The observed novel sequence divergence is of great significance to the study of the transmission, pathogenicity, and development of an effective vaccine for SARS-CoV-2.

Extremely potent monoclonal antibodies neutralize Omicron and other SARS-CoV-2 variants (preprint)

The ongoing coronavirus disease 2019 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has triggered a devastating global health, social and economic crisis. The RNA nature and broad circulation of this virus facilitate the accumulation of mutations, leading to the continuous emergence of variants of concern with increased transmissibility or pathogenicity1. This poses a major challenge to the effectiveness of current vaccines and therapeutic antibodies1,2. Thus, there is an urgent need for effective therapeutic and preventive measures with a broad spectrum of action, especially against variants with an unparalleled number of mutations such as the recently emerged Omicron variant, which is rapidly spreading across the globe3. Here, we used combinatorial antibody phage-display libraries from convalescent COVID-19 patients to generate monoclonal antibodies against the receptor-binding domain of the SARS-CoV-2 spike protein with ultrapotent neutralizing activity. One such antibody, NE12, neutralizes an early isolate, the WA-1 strain, as well as the Alpha and Delta variants with half-maximal inhibitory concentrations at picomolar level. A second antibody, NA8, has an unusual breadth of neutralization, with picomolar activity against both the Beta and Omicron variants. The prophylactic and therapeutic efficacy of NE12 and NA8 was confirmed in preclinical studies in the golden Syrian hamster model. Analysis by cryo-EM illustrated the structural basis for the neutralization properties of NE12 and NA8. Potent and broadly neutralizing antibodies against conserved regions of the SARS-CoV-2 spike protein may play a key role against future variants of concern that evade immune control.

Automated assessment of disease severity of COVID-19 using artificial intelligence with synthetic chest CT (preprint)

Background: Triage of patients is important to control the pandemic of coronavirus disease 2019 (COVID-19), especially during the peak of the pandemic when clinical resources become extremely limited. Purpose: To develop a method that automatically segments and quantifies lung and pneumonia lesions with synthetic chest CT and assess disease severity in COVID-19 patients. Materials and Methods: In this study, we incorporated data augmentation to generate synthetic chest CT images using public available datasets (285 datasets from "Lung Nodule Analysis 2016"). The synthetic images and masks were used to train a 2D U-net neural network and tested on 203 COVID-19 datasets to generate lung and lesion segmentations. Disease severity scores (DL: damage load; DS: damage score) were calculated based on the segmentations. Correlations between DL/DS and clinical lab tests were evaluated using Pearson's method. A p-value < 0.05 was considered as statistical significant. Results: Automatic lung and lesion segmentations were compared with manual annotations. For lung segmentation, the median values of dice similarity coefficient, Jaccard index and average surface distance, were 98.56%, 97.15% and 0.49 mm, respectively. The same metrics for lesion segmentation were 76.95%, 62.54% and 2.36 mm, respectively. Significant (p << 0.05) correlations were found between DL/DS and percentage lymphocytes tests, with r-values of -0.561 and -0.501, respectively. Conclusion: An AI system that based on thoracic radiographic and data augmentation was proposed to segment lung and lesions in COVID-19 patients. Correlations between imaging findings and clinical lab tests suggested the value of this system as a potential tool to assess disease severity of COVID-19.