A cross-sectional survey of epidemiology workforce performance and its influencing factors during the emergency response to the COVID-19 pandemic in Guangdong, China (preprint)

Background The epidemiology workforce contributes a lot to the response to COVID-19(Corona Virus Disease 2019) pandemic. Here this study focuses on the self-evaluation of the epidemiology workforce’s capacity and their impression of the cases they interviewed during the emergency response of the COVID-19 pandemic.Methods This study was a cross-sectional, anonymous survey conducted in Guangzhou, Shenzhen, Foshan, Dongguan and Zhuhai in Guangdong province. Data collection was performed between December 5, 2020 and December 22, 2020 through convenient sampling. A total of 596 epidemiology workforce participated in this study.Results Role in the team, professional title, gender, perceived social support, enough COVID-19 related training as well as experience were significantly associated with personal skills. 72.8% (429/589) and 86.3% (164/190) of participants reported they had interviewed uncooperative Chinese and foreign COVID-19 patients, respectively.Conclusions Epidemiology workforce needs enough training and experience to perform better in the investigation. Uncooperative patients were a big obstruction during the emergency response of the COVID-19 pandemic. Our results suggest Chinese experience and strategies focusing on the improvement of the public health emergency management system, including establishing Joint Prevention and Control Mechanism, enhancing training and the like.

Asian hate speech detection on Twitter during COVID-19.

Coronavirus disease 2019 (COVID-19) started in Wuhan, China, in late 2019, and after being utterly contagious in Asian countries, it rapidly spread to other countries. This disease caused governments worldwide to declare a public health crisis with severe measures taken to reduce the speed of the spread of the disease. This pandemic affected the lives of millions of people. Many citizens that lost their loved ones and jobs experienced a wide range of emotions, such as disbelief, shock, concerns about health, fear about food supplies, anxiety, and panic. All of the aforementioned phenomena led to the spread of racism and hate against Asians in western countries, especially in the United States. An analysis of official preliminary police data by the Center for the Study of Hate & Extremism at California State University shows that Anti-Asian hate crime in 16 of America's largest cities increased by 149% in 2020. In this study, we first chose a baseline of Americans' hate crimes against Asians on Twitter. Then we present an approach to balance the biased dataset and consequently improve the performance of tweet classification. We also have downloaded 10 million tweets through the Twitter API V-2. In this study, we have used a small portion of that, and we will use the entire dataset in the future study. In this article, three thousand tweets from our collected corpus are annotated by four annotators, including three Asian and one Asian-American. Using this data, we built predictive models of hate speech using various machine learning and deep learning methods. Our machine learning methods include Random Forest, K-nearest neighbors (KNN), Support Vector Machine (SVM), Extreme Gradient Boosting (XGBoost), Logistic Regression, Decision Tree, and Naive Bayes. Our Deep Learning models include Basic Long-Term Short-Term Memory (LSTM), Bidirectional LSTM, Bidirectional LSTM with Drop out, Convolution, and Bidirectional Encoder Representations from Transformers (BERT). We also adjusted our dataset by filtering tweets that were ambiguous to the annotators based on low Fleiss Kappa agreement between annotators. Our final result showed that Logistic Regression achieved the best statistical machine learning performance with an F1 score of 0.72, while BERT achieved the best performance of the deep learning models, with an F1-Score of 0.85.

Peptidic defective interfering gene nanoparticles against Omicron, Delta SARS-CoV-2 variants and influenza A virus in vivo.

Defective interfering genes (DIGs) are short viral genomes and interfere with wild-type viral replication. Here, we demonstrate that the new designed SARS-CoV-2 DIG (CD3600) can significantly inhibit the replication of SARS-CoV-2 including Alpha, Delta, Kappa and Omicron variants in human HK-2 cells and influenza DIG (PAD4) can significantly inhibit influenza virus replication in human A549 cells. One dose of influenza DIGs prophylactically protects 90% mice from lethal challenge of A(H1N1)pdm09 virus and CD3600 inhibits SARS-CoV-2 replication in hamster lungs when DIGs are administrated to lungs one day before viral challenge. To further investigate the gene delivery vector in the respiratory tract, a peptidic TAT2-P1&LAH4, which can package genes to form small spherical nanoparticles with high endosomal escape ability, is demonstrated to dramatically increase gene expression in the lung airway. TAT2-P1&LAH4, with the dual-functional TAT2-P1 (gene-delivery and antiviral), can deliver CD3600 to significantly inhibit the replication of Delta and Omicron SARS-CoV-2 in hamster lungs. This peptide-based nanoparticle system can effectively transfect genes in lungs and deliver DIGs to inhibit SARS-CoV-2 variants and influenza virus in vivo, which provides the new insight into the drug delivery system for gene therapy against respiratory viruses.

A trifunctional peptide broadly inhibits SARS-CoV-2 Delta and Omicron variants in hamsters.

The emergence of highly transmissible SARS-CoV-2 variants has led to the waves of the resurgence of COVID-19 cases. Effective antivirals against variants are required. Here we demonstrate that a human-derived peptide 4H30 has broad antiviral activity against the ancestral virus and four Variants of Concern (VOCs) in vitro. Mechanistically, 4H30 can inhibit three distinct steps of the SARS-CoV-2 life cycle. Specifically, 4H30 blocks viral entry by clustering SARS-CoV-2 virions; prevents membrane fusion by inhibiting endosomal acidification; and inhibits the release of virions by cross-linking SARS-CoV-2 with cellular glycosaminoglycans. In vivo studies show that 4H30 significantly reduces the lung viral titers in hamsters, with a more potent reduction for the Omicron variant than the Delta variant. This is likely because the entry of the Omicron variant mainly relies on the endocytic pathway which is targeted by 4H30. Moreover, 4H30 reduces syncytia formation in infected hamster lungs. These findings provide a proof of concept that a single antiviral can inhibit viral entry, fusion, and release.

S373P Mutation of Spike Protein in SARS-CoV-2 Stabilizes Omicron (preprint)

Recently, a cluster of several newly occurring mutations on Omicron, which is currently the dominant SARS-CoV-2 variant, are found at the (mechanically) stable {beta}-core region of spike protein's receptor-binding domain (RBD), where mutation rarely happened before. Notably, the binding of SARS-CoV-2 to human receptor ACE2 via RBD happens in a dynamic airway environment, where mechanical force caused by coughing or sneezing occurs and applies to the proteins. Thus, we used atomic force microscopy-based single-molecule force spectroscopy (AFM-SMFS) to measure the stability of RBDs and found that the unfolding force of Omicron RBD increased by 20% compared with the wild-type. Molecular dynamics simulations revealed that Omicron RBD showed more hydrogen bonds in the {beta}-core region due to the closing of the -helical motif caused primarily by the S373P mutation, which was further confirmed by the experiment. This work reveals the stabilizing effect of the S373P mutation and suggests mechanical stability becomes another important factor in SARS-CoV-2 mutation selection.

A global systematic analysis of the occurrence, severity, and recovery pattern of long COVID in 2020 and 2021 (preprint)

ImportanceWhile much of the attention on the COVID-19 pandemic was directed at the daily counts of cases and those with serious disease overwhelming health services, increasingly, reports have appeared of people who experience debilitating symptoms after the initial infection. This is popularly known as long COVID. ObjectiveTo estimate by country and territory of the number of patients affected by long COVID in 2020 and 2021, the severity of their symptoms and expected pattern of recovery DesignWe jointly analyzed ten ongoing cohort studies in ten countries for the occurrence of three major symptom clusters of long COVID among representative COVID cases. The defining symptoms of the three clusters (fatigue, cognitive problems, and shortness of breath) are explicitly mentioned in the WHO clinical case definition. For incidence of long COVID, we adopted the minimum duration after infection of three months from the WHO case definition. We pooled data from the contributing studies, two large medical record databases in the United States, and findings from 44 published studies using a Bayesian meta-regression tool. We separately estimated occurrence and pattern of recovery in patients with milder acute infections and those hospitalized. We estimated the incidence and prevalence of long COVID globally and by country in 2020 and 2021 as well as the severity-weighted prevalence using disability weights from the Global Burden of Disease study. ResultsAnalyses are based on detailed information for 1906 community infections and 10526 hospitalized patients from the ten collaborating cohorts, three of which included children. We added published data on 37262 community infections and 9540 hospitalized patients as well as ICD-coded medical record data concerning 1.3 million infections. Globally, in 2020 and 2021, 144.7 million (95% uncertainty interval [UI] 54.8-312.9) people suffered from any of the three symptom clusters of long COVID. This corresponds to 3.69% (1.38-7.96) of all infections. The fatigue, respiratory, and cognitive clusters occurred in 51.0% (16.9-92.4), 60.4% (18.9-89.1), and 35.4% (9.4-75.1) of long COVID cases, respectively. Those with milder acute COVID-19 cases had a quicker estimated recovery (median duration 3.99 months [IQR 3.84-4.20]) than those admitted for the acute infection (median duration 8.84 months [IQR 8.10-9.78]). At twelve months, 15.1% (10.3-21.1) continued to experience long COVID symptoms. Conclusions and relevanceThe occurrence of debilitating ongoing symptoms of COVID-19 is common. Knowing how many people are affected, and for how long, is important to plan for rehabilitative services and support to return to social activities, places of learning, and the workplace when symptoms start to wane. Key PointsO_ST_ABSQuestionC_ST_ABSWhat are the extent and nature of the most common long COVID symptoms by country in 2020 and 2021? FindingsGlobally, 144.7 million people experienced one or more of three symptom clusters (fatigue; cognitive problems; and ongoing respiratory problems) of long COVID three months after infection, in 2020 and 2021. Most cases arose from milder infections. At 12 months after infection, 15.1% of these cases had not yet recovered. MeaningThe substantial number of people with long COVID are in need of rehabilitative care and support to transition back into the workplace or education when symptoms start to wane.

Fusion-inhibition peptide broadly inhibits influenza virus and SARS-CoV-2, including Delta and Omicron variants.

Pandemic influenza virus and SARS-CoV-2 vaiants have posed major global threats to public health. Broad-spectrum antivirals blocking viral entry can be an effective strategy for combating these viruses. Here, we demonstrate a frog-defensin-derived basic peptide (FBP), which broadly inhibits the influenza virus by binding to haemagglutinin so as to block low pH-induced HA-mediated fusion and antagonizes endosomal acidification to inhibit the influenza virus. Moreover, FBP can bind to the SARS-CoV-2 spike to block spike-mediated cell-cell fusion in 293T/ACE2 cells endocytosis. Omicron spike shows a weak cell-cell fusion mediated by TMPRSS2 in Calu3 cells, making the Omicron variant sensitive to endosomal inhibitors. In vivo studies show that FBP broadly inhibits the A(H1N1)pdm09 virus in mice and SARS-CoV-2 (HKU001a and Delta)in hamsters. Notably, FBP shows significant inhibition of Omicron variant replication even though it has a high number of mutations in spike. In conclusion, these results suggest that virus-targeting FBP with a high barrier to drug resistance can be an effective entry-fusion inhibitor against influenza virus and SARS-CoV-2 in vivo.

The Impact of Electroacupuncture Early Intervention on the Brain Lipidome in a Mouse Model of Post-traumatic Stress Disorder.

The neuroprotective effect of electroacupuncture (EA) treatment has been well studied; growing evidence suggests that changes in lipid composition may be involved in the pathogenesis of post-traumatic stress disorder (PTSD) and may be a target for treatment. However, the influence of early EA intervention on brain lipid composition in patients with PTSD has never been investigated. Using a modified single prolonged stress (mSPS) model in mice, we assessed the anti-PTSD-like effects of early intervention using EA and evaluated changes in lipid composition in the hippocampus and prefrontal cortex (PFC) using a mass spectrometry-based lipidomic approach. mSPS induced changes in lipid composition in the hippocampus, notably in the content of sphingolipids, glycerolipids, and fatty acyls. These lipid changes were more robust than those observed in the PFC. Early intervention with EA after mSPS ameliorated PTSD-like behaviors and partly normalized mSPS-induced lipid changes, notably in the hippocampus. Cumulatively, our data suggest that EA may reverse mSPS-induced PTSD-like behaviors due to region-specific regulation of the brain lipidome, providing new insights into the therapeutic mechanism of EA.

SARS-CoV-2 Omicron variant shows less efficient replication and fusion activity when compared with Delta variant in TMPRSS2-expressed cells.

The novel SARS-CoV-2 Omicron variant (B.1.1.529), first found in early November 2021, has sparked considerable global concern and it has >50 mutations, many of which are known to affect transmissibility or cause immune escape. In this study, we sought to investigate the virological characteristics of the Omicron variant and compared it with the Delta variant which has dominated the world since mid-2021. Omicron variant replicated more slowly than the Delta variant in transmembrane serine protease 2 (TMPRSS2)-overexpressing VeroE6 (VeroE6/TMPRSS2) cells. Notably, the Delta variant replicated well in Calu3 cell line which has robust TMPRSS2 expression, while the Omicron variant replicated poorly in this cell line. Competition assay showed that Delta variant outcompeted Omicron variant in VeroE6/TMPRSS2 and Calu3 cells. To confirm the difference in entry pathway between the Omicron and Delta variants, we assessed the antiviral effect of bafilomycin A1, chloroquine (inhibiting endocytic pathway), and camostat (inhibiting TMPRSS2 pathway). Camostat potently inhibited the Delta variant but not the Omicron variant, while bafilomycin A1 and chloroquine could inhibit both Omicron and Delta variants. Moreover, the Omicron variant also showed weaker cell-cell fusion activity when compared with Delta variant in VeroE6/TMPRSS2 cells. Collectively, our results suggest that Omicron variant infection is not enhanced by TMPRSS2 but is largely mediated via the endocytic pathway. The difference in entry pathway between Omicron and Delta variants may have an implication on the clinical manifestations or disease severity.

Label-Free SARS-CoV-2 Detection on Flexible Substrates (preprint)

One of the most important strategies for mitigation and managing pandemics is widespread, rapid and inexpensive testing and isolation of infected patients. In this study, we demonstrate large area, label-free, and rapid testing sensor platforms fabricated on both rigid and flexible substrates for fast and accurate detection of SARS-CoV-2. SERS enhancing metal insulator metal (MIM) nanostructures are modeled using finite element simulations and then fabricated using nanoimprint lithography (NIL) and transfer printing. The SERS signal of various viral samples, including spiked saliva, was analyzed using machine learning classifiers. We observe that our approach can obtain the test results typically within 25 minutes with a detection accuracy of at least 83% for the viral samples. We envision that this approach which features large area nanopatterning, fabrication in both rigid and flexible formats for wearables, SERS spectroscopy and machine learning can enable new types of rapid, label-free biosensors for screening pathogens and managing current and future pandemics.

Ultra-Wideband Positioning Sensor with Application to an Autonomous Ultraviolet-C Disinfection Vehicle.

Due to the COVID-19 virus being highly transmittable, frequently cleaning and disinfecting facilities is common guidance in public places. However, the more often the environment is cleaned, the higher the risk of cleaning staff getting infected. Therefore, strong demand for sanitizing areas in automatic modes is undoubtedly expected. In this paper, an autonomous disinfection vehicle with an Ultraviolet-C (UVC) lamp is designed and implemented using an ultra-wideband (UWB) positioning sensor. The UVC dose for 90% inactivation of the reproductive ability of COVID-19 is 41.7 J/m2, which a 40 W UVC lamp can achieve within a 1.6 m distance for an exposure time of 30 s. With this UVC lamp, the disinfection vehicle can effectively sterilize in various scenarios. In addition, the high-accuracy UWB positioning system, with the time difference of arrival (TDOA) algorithm, is also studied for autonomous vehicle navigation in indoor environments. The number of UWB tags that use a synchronization protocol between UWB anchors can be unlimited. Moreover, this proposed Gradient Descent (GD), which uses Taylor method, is a high-efficient algorithm for finding the optimal position for real-time computation due to its low error and short calculating time. The generalized traversal path planning procedure, with the edge searching method, is presented to improve the efficiency of autonomous navigation. The average error of the practical navigation demonstrated in the meeting room is 0.10 m. The scalability of the designed system to different application scenarios is also discussed and experimentally demonstrated. Hence, the usefulness of the proposed UWB sensor applied to UVC disinfection vehicles to prevent COVID-19 infection is verified by employing it to sterilize indoor environments without human operation.

Pathogenic characteristics of sputum and bronchoalveolar lavage fluid samples from patients with lower respiratory tract infection in a large teaching hospital in China: a retrospective study.

BACKGROUND: Lower respiratory tract infection (LRIs) is very common both in terms of community-acquired infection and hospital-acquired infection. Sputum and bronchoalveolar lavage fluid (BALF) are the most important specimens obtained from patients with LRI. The choice of antibiotic with which to treat LRI usually depends on the antimicrobial sensitivity of bacteria isolated from sputum and BALF. However, differences in the antimicrobial sensitivity of pathogens isolated from sputum and BALF have not been evaluated. METHODS: A retrospective study was conducted to analyze the differences between sputum and BALF samples in terms of pathogen isolation and antimicrobial sensitivity in hospitalized patients with LRI. RESULTS: Between 2013 and 2015, quality evaluation of sputum samples was not conducted before performing sputum culture; however, between 2016 and 2018, quality evaluation of sputum samples was conducted first, and only quality-assured samples were cultured. The numbers of sputum and BALF in 2013-2015 were 15,549 and 1671, while those in 2016-2018 were 12,055 and 3735, respectively. The results of pathogen culture showed that Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiella pneumoniae, Staphylococcus aureus, Hemophilus influenzae, Escherichia coli, Stenotrophomonas maltophilia, and Streptococcus pneumoniae were in the top ten pathogens isolated from sputum and BALF. An antimicrobial susceptibility test showed that the susceptibility of BALF isolates to most antibiotics was higher compared with the susceptibility of sputum isolates, especially after quality control of sputum samples (2016-2018). CONCLUSIONS: Our findings suggest that caution is needed in making therapeutic choices for patients with LRI when using antimicrobial sensitivity results from sputum isolates as opposed to BALF isolates.

Cross-linking peptide and repurposed drugs inhibit both entry pathways of SARS-CoV-2.

Up to date, effective antivirals have not been widely available for treating COVID-19. In this study, we identify a dual-functional cross-linking peptide 8P9R which can inhibit the two entry pathways (endocytic pathway and TMPRSS2-mediated surface pathway) of SARS-CoV-2 in cells. The endosomal acidification inhibitors (8P9R and chloroquine) can synergistically enhance the activity of arbidol, a spike-ACE2 fusion inhibitor, against SARS-CoV-2 and SARS-CoV in cells. In vivo studies indicate that 8P9R or the combination of repurposed drugs (umifenovir also known as arbidol, chloroquine and camostat which is a TMPRSS2 inhibitor), simultaneously interfering with the two entry pathways of coronaviruses, can significantly suppress SARS-CoV-2 replication in hamsters and SARS-CoV in mice. Here, we use drug combination (arbidol, chloroquine, and camostat) and a dual-functional 8P9R to demonstrate that blocking the two entry pathways of coronavirus can be a promising and achievable approach for inhibiting SARS-CoV-2 replication in vivo. Cocktail therapy of these drug combinations should be considered in treatment trials for COVID-19.

Mutation N501Y in RBD of Spike Protein Strengthens the Interaction between COVID-19 and its Receptor ACE2 (preprint)

Coronavirus disease-19 (COVID-19) is spreading around the world for the past year. Enormous efforts have been taken to understand its mechanism of transmission. It is well established now that the SARS-CoV-2 receptor-binding domain (RBD) of the spike protein binds to the human angiotensin-converting enzyme 2 (ACE2) as its first step of entry. Being a single-stranded RNA virus, SARS-CoV-2 is evolving rapidly. Recently, two variants, B.1.1.7 and B.1.351, both with a key mutation N501Y on the RBD, appear to be more infectious to humans. To understand its mechanism, we combined kinetics assay, single-molecule technique, and computational method to compare the interaction between these RBD (mutations) and ACE2. Remarkably, RBD with the N501Y mutation exhibited a considerably stronger inter-action characterized from all these methodologies, while the other two mutations from B.1.351 contributed to a less effect. Surface plasmon resonance and fluorescence-activated cell scan (FACS) assays found that both RBD mutations are of higher binding affinity to ACE2 than the wild type. In addition, atomic force microscopy-based single-molecule force microscopy quantify their strength on living cells, showing a higher binding probability and unbinding force for both mutations. Finally, Steered Molecular Dynamics (SMD) simulations on the dissociation of RBD-ACE2 complexes revealed the possible structural details for the higher force/interaction. Taking together, we suggested that the stronger inter-action from N501Y mutation in RBD should play an essential role in the higher transmission of COVID-19 variants.

Ecological damage of submerged macrophytes by fresh cyanobacteria (FC) and cyanobacterial decomposition solution (CDS)

To investigate the deleterious ecological effects of cyanobacteria on submerged macrophytes, this study investigated the effects of different concentrations of fresh cyanobacteria (FC) and cyanobacteria decomposition solution (CDS) on an experimental group of submerged macrophytes (Vallisneria natans (Lour.) Hara and Myriophyllum verticillatum Linn.). The results showed that FC and CDS not only lead to decrease in biomass and significant changes in enzyme activity and chlorophyll content in tissue, but also affected the permeability of cell membranes. The extent of damage was in the order CDS >FC, and the comprehensive stress resistance of Vallisneria natans (2.994) was more than that of Myriophyllum verticillatum (2.895). In addition, semi-permeable membranes can reduce plant damage by FC and CDS, but cannot completely prevent it. FC and CDS mainly affected the relative distribution of microbial genera on the surface of aquatic plants (p <0.05). Furthermore, CDS caused irreversible damage to plant cells and induced programmed cell death (PCD) of plants to accelerate their decline. Therefore, FC and CDS may be one of the main reasons for the decline in submerged vegetation. This study provides a scientific basis for evaluating the harmful effects of cyanobacteria on submerged macrophytes.