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1.
129th ASEE Annual Conference and Exposition: Excellence Through Diversity, ASEE 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2045686

ABSTRACT

This paper introduces a new set of infrastructures and online interactive tools that can be employed to motivate students to learn programming languages. The tools were used to experiment in one of the introductory first-year engineering courses. The final project of the course requires implementing an AI program for a game called “Reversi''. Reversi is a medium to hard level programming project that has been used in the course for several years requiring an immediate restructuring. Furthermore, due to COVID-19 and the restriction of in-person teaching, it has been a challenge for educators to excite, support, and encourage students. The new infrastructure provided an interactive platform for the students to familiarize themselves with the Reversi game project. It also provided a leaderboard, an interactive scoreboard, allowing students to compete with their classmates. The tools can instantaneously synchronize to students' code submission to help students check their latest ranking among their classmates in real-time. This increased students' level of engagement and learning. In addition, it allowed students to collaborate with their fellow classmates and discuss their algorithms. The tools and platform developed can also be employed in other courses as well other programming games. The result from students' surveys and the active trend of the class online discussion forum indicates that the new online interactive system created a positive atmosphere and increased students' motivation in learning programming languages. © American Society for Engineering Education, 2022.

2.
Nan Fang Yi Ke Da Xue Xue Bao ; 42(6): 955-956, 2022 Jun 20.
Article in Chinese | MEDLINE | ID: covidwho-1924684

ABSTRACT

As a member of the dibenzyl isoquinoline alkaloid family, cepharathine is an alkaloid from the traditional Chinese medicine cepharathine, which is mainly used for treatment of leukopenia and other diseases. Recent studies of the inhibitory effect of cepharathine against SARS-CoV-2 have attracted widespread attention and aroused heated discussion. As the original discoverer of the anti-SARS-CoV-2 activity of cepharanthine, here we briefly summarize the discovery of cepharanthine and review important progress in relevant studies concerning the discovery and validation of anti-SARS-CoV-2 activity of cepharathine, its antiviral mechanisms and clinical trials of its applications in COVID-19 therapy.


Subject(s)
Benzylisoquinolines , COVID-19 , Antiviral Agents/pharmacology , Antiviral Agents/therapeutic use , Benzylisoquinolines/pharmacology , Benzylisoquinolines/therapeutic use , Humans , SARS-CoV-2
3.
iScience ; 25(7): 104612, 2022 Jul 15.
Article in English | MEDLINE | ID: covidwho-1895109

ABSTRACT

The coronavirus disease-19 (COVID-19) pandemic has ravaged global healthcare with previously unseen levels of morbidity and mortality. In this study, we performed large-scale integrative multi-omics analyses of serum obtained from COVID-19 patients with the goal of uncovering novel pathogenic complexities of this disease and identifying molecular signatures that predict clinical outcomes. We assembled a network of protein-metabolite interactions through targeted metabolomic and proteomic profiling in 330 COVID-19 patients compared to 97 non-COVID, hospitalized controls. Our network identified distinct protein-metabolite cross talk related to immune modulation, energy and nucleotide metabolism, vascular homeostasis, and collagen catabolism. Additionally, our data linked multiple proteins and metabolites to clinical indices associated with long-term mortality and morbidity. Finally, we developed a novel composite outcome measure for COVID-19 disease severity based on metabolomics data. The model predicts severe disease with a concordance index of around 0.69, and shows high predictive power of 0.83-0.93 in two independent datasets.

4.
Journal of Environmental Protection and Ecology ; 23(2):454-461, 2022.
Article in English | Web of Science | ID: covidwho-1865979

ABSTRACT

In the context of the global outbreak of COVID-19, health issues have attracted worldwide attention. Building a healthy ecological environment is particularly important for human beings, and among the ecological environmental factors, air quality is particularly prominent. The study takes the air quality of newly-built immigrant relocation communities in Western China as the research object, and adopts a number of technical methods, such as professional laboratory test report, instrument test, calculation test and so on. Obtain the data of regional ambient air quality and building indoor air quality, and comprehensively judge the regional environment and building ventilation efficiency of the experimental point. So as to comprehensively grade the air quality of the experimental point. A number of technologies and methods are studied and integrated to form a comprehensive three-dimensional air quality detection technology integration. From the perspective of air quality inspection, provide technical support for the healthy and sustainable development of relocated new rural communities. It is of great practical significance to supervise and urge the construction of a healthy and sustainable new township village.

5.
IEEE Access ; 2022.
Article in English | Scopus | ID: covidwho-1794860

ABSTRACT

Under the severe situation of the COVID-19 pandemic, masks cover most of the effective facial features of users, and their head pose changes significantly in a complex environment, which makes the accuracy of head pose estimation in some systems such as safe driving systems and attention detection systems impossible to guarantee. To this end, we propose a powerful four-branch feature selective extraction network (FSEN) structure, in which three branches are used to extract three independent discriminative features of pose angles, and one branch is used to extract composite features corresponding to multiple pose angles. By reducing the dimension of high-dimensional features, our method significantly reduces the amount of computation while improving the estimation accuracy. Our convolution method is an improved spatial channel dynamic convolution (SCDC) that initially enhances the extracted features. Additionally, we embed a regional information exchange network (RIEN) after each convolutional layer in each branch to fully mine the potential semantic correlation between regions from multiple perspectives and learn and fuse this correlation to further enhance feature expression. Finally, we fuse the independent discriminative features of each pose angle and composite features from the three directions of channel, space, and pixel to obtain perfect feature expression for each pose angle, and then obtain the head pose angle. We conducted extensive experiments on the controlled environment datasets and a self-built real complex environment dataset (RCE) and the results showed that our method outperforms state-of-the-art single-modality methods and performs on par with multimodality-based methods. This shows that our network meets the requirements of accurate head-pose estimation in real complex environments such as complex illumination and partial occlusion. Author

6.
Biosens Bioelectron ; 209: 114237, 2022 Aug 01.
Article in English | MEDLINE | ID: covidwho-1778012

ABSTRACT

Kinetics measurements of antigen-antibody binding interactions are critical to understanding the functional efficiency of SARS-CoV-2 antibodies. Previously reported chaotrope-based avidity assays that rely on artificial disruption of binding do not reflect the natural binding kinetics. This study developed a chaotrope- and label-free biolayer interferometry (BLI) assay for the real-time monitoring of receptor binding domain (RBD) binding kinetics with SARS-CoV-2 spike protein in convalescent COVID-19 patients. An improved conjugation biosensor probe coated with streptavidin-polysaccharide (SA-PS) led to a six-fold increase of signal intensities and two-fold reduction of non-specific binding (NSB) compared to streptavidin only probe. Furthermore, by utilizing a separate reference probe and biotin-human serum albumin (B-HSA) blocking process to subtracted NSB signal in serum, this BLI biosensor can measure a wide range of the dissociation rate constant (koff), which can be measured without knowledge of the specific antibody concentrations. The clinical utility of this improved BLI kinetics assay was demonstrated by analyzing the koff values in sera of 24 pediatric (≤18 years old) and 63 adult (>18 years old) COVID-19 convalescent patients. Lower koff values for SARS-CoV-2 serum antibodies binding to RBD were measured in samples from children. This rapid, easy to operate and chaotrope-free BLI assay is suitable for clinical use and can be readily adapted to characterize SARS-CoV-2 antibodies developed by COVID-19 patients and vaccines.


Subject(s)
Biosensing Techniques , COVID-19 , Adolescent , Adult , Antibodies, Neutralizing , Antibodies, Viral , Child , Humans , Immunologic Techniques , Interferometry , SARS-CoV-2 , Spike Glycoprotein, Coronavirus , Streptavidin
7.
Ieee Transactions on Computational Social Systems ; : 12, 2022.
Article in English | Web of Science | ID: covidwho-1714076

ABSTRACT

COVID-19 has spread all over the world, accounting for countless death and enormous economic loss. Since the World Health Organization (WHO) declared COVID-19 as a pandemic, governments from different countries have made various policies to prevent the pandemic from becoming worse. However, civilian reactions to the pandemic vary when they face similar situations. This behavioral variation creates a challenge when it comes to policy-making. Such differences are generally implicit, hidden in ones' social lives. As a result, it is challenging to analyze such differences when the governments make policies. In this work, we investigate social media posts on Twitter and Weibo in order to effectively explore the difference in reactions across various countries, with the aim to understand national differences. To this end, we employ natural language processing (NLP) methods and Linguistic Inquiry and Word Count (LIWC) tools to process six languages in different countries, including the USA, Germany, France, Italy, the U.K., and China. We provide a comprehensive analysis of public reaction differences from the emotional perspective. Our findings verify that the reactions vary noticeably among various countries for some policies. Therefore, sentiment analysis can significantly influence policy-making. Our work sheds light on the mechanism of detecting the reaction differences in various countries, which can be utilized to conduct effective communication and make appropriate policy decisions.

8.
COVID-19 AND INTERNATIONAL BUSINESS: Change of Era ; : 307-320, 2021.
Article in English | Web of Science | ID: covidwho-1688376
9.
COVID-19 AND INTERNATIONAL BUSINESS: Change of Era ; : 321-329, 2021.
Article in English | Web of Science | ID: covidwho-1688375
10.
Data Intelligence ; 4(1):66-87, 2022.
Article in English | Web of Science | ID: covidwho-1677464

ABSTRACT

Since the end of 2019, the COVID-19 outbreak worldwide has not only presented challenges for government agencies in addressing public health emergency, but also tested their capacity in dealing with public opinion on social media and responding to social emergencies. To understand the impact of COVID-19 related tweets posted by the major public health agencies in the United States on public emotion, this paper studied public emotional diffusion in the tweets network, including its process and characteristics, by taking Twitter users of four official public health systems in the United States as an example. We extracted the interactions between tweets in the COVID-19-TweetIds data set and drew the tweets diffusion network. We proposed a method to measure the characteristics of the emotional diffusion network, with which we analyzed the changes of the public emotional intensity and the proportion of emotional polarity, investigated the emotional influence of key nodes and users, and the emotional diffusion of tweets at different tweeting time, tweet topics and the tweet posting agencies. The results show that the emotional polarity of tweets has changed from negative to positive with the improvement of pandemic management measures. The public's emotional polarity on pandemic related topics tends to be negative, and the emotional intensity of management measures such as pandemic medical services turn from positive to negative to the greatest extent, while the emotional intensity of pandemic related knowledge changes the most. The tweets posted by the Centers for Disease Control and Prevention and the Food and Drug Administration of the United States have a broad impact on public emotions, and the emotional spread of tweets' polarity eventually forms a very close proportion of opposite emotions.

12.
Information Technology and People ; 2021.
Article in English | Scopus | ID: covidwho-1566140

ABSTRACT

Purpose: Despite the huge potential of social media, its functionality and impact for enhanced risk communication remain unclear. Drawing on dialogic theory by integrating both “speak from power” and “speak to power” measurements, the article aims to propose a systematic framework to address this issue. Design/methodology/approach: The impact of social media on risk communication is measured by the correlation between “speak from power” and “speak to power” levels, where the former primarily spoke to two facets of the risk communication process – rapidness and attentiveness, and the latter was benchmarked against popularity and commitment. The framework was empirically validated with data relating to coronavirus disease (COVID-19) risk communication in 25,024 selected posts on 17 official provincial Weibo accounts in China. Findings: The analysis results suggest the relationship between the “speak from power” and “speak to power” is mixed rather than causality, which confirms that neither the outcome-centric nor the process-centric method alone can render a full picture of government–public interconnectivity. Besides, the proposed interconnectivity matrix reveals that two provinces have evidenced the formation of government–public mutuality, which provides empirical evidence that dialogic relationships could exist in social media during risk communication. Originality/value: The authors' study proposed a prototype framework that underlines the need that the impact of social media on risk communication should and must be assessed through a combination of process and outcome or interconnectivity. The authors further divide the impact of social media on risk communication into dialogue enabler, “speak from power” booster, “speak to power” channel and mass media alternative. © 2021, Emerald Publishing Limited.

13.
33rd International Conference for High Performance Computing, Networking, Storage and Analysis: Science and Beyond, SC 2021 ; 2021.
Article in English | Scopus | ID: covidwho-1551077

ABSTRACT

Structure-based Deep Fusion modelswere recently shown to outperform several physicsand machine learning-based protein-ligand binding affinity prediction methods. As part of a multi-institutional COVID-19 pandemic response, over 500 million small molecules were computationally screened against four protein structures from the novel coronavirus (SARS-CoV-2), which causes COVID-19. Three enhancements to Deep Fusion were made in order to evaluate more than 5 billion docked poses on SARS-CoV-2 protein targets. First, the Deep Fusion concept was refined by formulating the architecture as one, coherently backpropagated model (Coherent Fusion) to improve bindingaffinity prediction accuracy. Secondly, the model was trained using a distributed, genetic hyper-parameter optimization. Finally, a scalable, high-Throughput screening capability was developed to maximize the number of ligands evaluated and expedite the path to experimental evaluation. In this work, we present both the methods developed for machine learning-based high-Throughput screening and results from using our computational pipeline to find SARS-CoV-2 inhibitors. © 2021 IEEE Computer Society. All rights reserved.

14.
PubMed; 2021.
Preprint in English | PubMed | ID: ppcovidwho-291777

ABSTRACT

Messenger RNA-based medicines hold immense potential, as evidenced by their rapid deployment as COVID-19 vaccines. However, worldwide distribution of mRNA molecules has been limited by their thermostability, which is fundamentally limited by the intrinsic instability of RNA molecules to a chemical degradation reaction called in-line hydrolysis. Predicting the degradation of an RNA molecule is a key task in designing more stable RNA-based therapeutics. Here, we describe a crowdsourced machine learning competition ("Stanford OpenVaccine") on Kaggle, involving single-nucleotide resolution measurements on 6043 102-130-nucleotide diverse RNA constructs that were themselves solicited through crowdsourcing on the RNA design platform Eterna. The entire experiment was completed in less than 6 months. Winning models demonstrated test set errors that were better by 50% than the previous state-of-the-art DegScore model. Furthermore, these models generalized to blindly predicting orthogonal degradation data on much longer mRNA molecules (504-1588 nucleotides) with improved accuracy over DegScore and other models. Top teams integrated natural language processing architectures and data augmentation techniques with predictions from previous dynamic programming models for RNA secondary structure. These results indicate that such models are capable of representing in-line hydrolysis with excellent accuracy, supporting their use for designing stabilized messenger RNAs. The integration of two crowdsourcing platforms, one for data set creation and another for machine learning, may be fruitful for other urgent problems that demand scientific discovery on rapid timescales.

15.
JCI Insight ; 6(20)2021 10 22.
Article in English | MEDLINE | ID: covidwho-1484165

ABSTRACT

Longitudinal studies are needed to evaluate the SARS-CoV-2 mRNA vaccine antibody response under real-world conditions. This longitudinal study investigated the quantity and quality of SARS-CoV-2 antibody response in 846 specimens from 350 patients, comparing BNT162b2-vaccinated individuals (19 previously diagnosed with COVID-19, termed RecoVax; and 49 never diagnosed, termed NaiveVax) with 122 hospitalized unvaccinated (HospNoVax) and 160 outpatient unvaccinated (OutPtNoVax) COVID-19 patients. NaiveVax experienced delay in generating SARS-CoV-2 total antibodies (TAb) and surrogate neutralizing antibodies (SNAb) after the first vaccine dose (D1) but rapid increase in antibody levels after the second dose (D2). However, these never reached RecoVax's robust levels. In fact, NaiveVax TAb and SNAb levels decreased 4 weeks after D2. For the most part, RecoVax TAb persisted, after reaching maximal levels 2 weeks after D2, but SNAb decreased significantly about 6 months after D1. Although NaiveVax avidity lagged behind that of RecoVax for most of the follow-up periods, NaiveVax did reach similar avidity by about 6 months after D1. These data suggest that 1 vaccine dose elicits maximal antibody response in RecoVax and may be sufficient. Also, despite decreasing levels in TAb and SNAb over time, long-term avidity may be a measure worth evaluating and possibly correlating to vaccine efficacy.


Subject(s)
Antibody Formation , COVID-19 Vaccines/immunology , COVID-19/immunology , COVID-19/prevention & control , Vaccines, Synthetic/immunology , Adult , Aged , Antibodies, Neutralizing/immunology , Antibodies, Viral/immunology , Cohort Studies , Female , Humans , Longitudinal Studies , Male , Middle Aged , SARS-CoV-2 , Vaccination
18.
Blood ; 136:2-3, 2020.
Article in English | EMBASE | ID: covidwho-1348307

ABSTRACT

Background: Influenza A virus (IAV) infections are associated with a high healthcare burden around the world and there is an urgent need to develop more effective therapies. Natural killer (NK) cells provide the first line of innate defense against IAV by killing infected epithelial cells, by producing antiviral cytokines and affecting adaptive immunity. Preclinical studies have demonstrated that NK cells play a pivotal role in reducing IAV-induced pulmonary infection;however, little is known about the therapeutic potential of adoptively transferred NK cells for IAV infections. Celularity Inc. is developing human placental hematopoietic stem cell-derived allogeneic, off-the-shelf NK cell therapy (CYNK-001) for the treatment of viral infections, including coronavirus disease of 2019. Here, we report the evaluation of antiviral activities of CYNK-001 against IAV infection. Methods: In vitro antiviral activities of CYNK-001 were evaluated using human alveolar epithelial cell line A549, infected with IAV strain A/PR/8/34 (H1N1) at variable multiplicity of infection (MOI). The expression of ligands for NK cell receptors was analyzed on infected A549 cells using Fc-coupled recombinant proteins. CYNK-001 was added to A549 cells 16 hours post infection. CYNK-001 degranulation was measured after 4 hours of coculture, and CYNK-001 cytotoxicity against IAV-infected A549 was measured real-time using impedance-based xCELLigence platform. In vivo antiviral and immunomodulatory activities of CYNK-001 were assessed in A/PR/8/34 (H1N1)-induced severe acute lung injury mouse model. Mice were intranasally infected with 2500 PFU IAV. PBS or 1 x 107 CYNK-001 cells were intravenously administered twice at 1 and 3 days post infection (dpi). At 6 dpi, lungs were collected for the evaluation of viral load by qPCR, lung injury and immune cell profiling by histology. Bronchoalveolar lavage fluid (BALF) was collected at 6 dpi for cytokine analysis by multiplex assays, total protein concentration by ELISA and immune cell profiling by flow cytometry. Results: In vitro, IAV infection corresponded with dose-dependent expression of ligands to NK cell-activating receptors, including NKp44, NKp46 and NKG2D. CYNK-001 cells exhibited increased IFNγ, TNFα and GM-CSF production, and elevated level of degranulation upon coculture with IAV-infected A549 cells. Cytokines in culture supernatant and CD107a expression in CYNK-001 cells were upregulated in a virus dose-dependent manner. Consistent with this finding, CYNK-001 cytotoxicity against IAV-infected A549 cells increased from 35% at 0 MOI to 50%, 60% and 75% at 0.001, 0.01 and 0.1 MOI, respectively. These data indicate that CYNK-001 cells recognize virally infected cells, resulting in specific cytotoxic elimination of the source of infection. In vivo, treatment of IAV-infected mice with CYNK-001 reduced weight loss and increased their likelihood of survival. PBS control group developed a severe disease and 37.5% mortality was observed as early as day 4. In the group treated with CYNK-001, disease onset was delayed by 2 days. qPCR analysis of viral RNA showed that CYNK-001-treated mice had lower viral load in the lung than vehicle-treated mice, demonstrating antiviral function of CYNK-001 in vivo. CYNK-001-treated mice had reduced lung injury as assessed by lower total protein concentration in BALF. Moreover, CYNK-001 reduced BALF murine cytokines and chemokines, including IFNγ (p<0.001), IL-6, TNFα, MCP-1 (p<0.05), CXCL2 and CXCL9. Lastly, immunohistochemical analysis of the lung showed that CYNK-001-treated mice had an altered immune response to IAV with higher number of CD68+ macrophages and CD8+ T cells at 6 dpi. Conclusions: Our in vitro and in vivo data show the promising antiviral activities of CYNK-001 against IAV infection. In a severe IAV infection mouse model, CYNK-001 treatment demonstrates lower mortality rate, lower weight loss, lower lung viral load and reduced lung injury along with reduced inflammation. These results support our hypothesis that the adoptive transfer of CYNK-001 cou d reduce the burden of viral infection through the elimination of infected epithelial cells, coordinate a more effective immune response, and result in a clinical benefit in patients with severe viral infection. Disclosures: He: Celularity Inc.: Current Employment. Mahlakõiv: Celularity Inc.: Current Employment. Gleason: Celularity Inc.: Current Employment, Current equity holder in private company. Van Der Touw: Celularity Inc.: Current Employment. Kang: Celularity Inc.: Current Employment. Hariri: Celularity Inc.: Current Employment, Current equity holder in private company. Zhang: Celularity Inc.: Current Employment, Current equity holder in private company.

19.
Preprint in English | medRxiv | ID: ppmedrxiv-21261713

ABSTRACT

IntroductionSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza virus are contagious respiratory pathogens with similar symptoms but require different treatment and management strategies. This study investigated whether laboratory blood tests can discriminate between SARS-CoV-2 and influenza infections at emergency department (ED) presentation. Methods723 influenza A/B positive (2018/1/1 to 2020/3/15) and 1,281 SARS-CoV-2 positive (2020/3/11 to 2020/6/30) ED patients were retrospectively analyzed. Laboratory test results completed within 48 hours prior to reporting of virus RT-PCR results, as well as patient demographics were included to train and validate a random forest (RF) model. The dataset was randomly divided into training (2/3) and testing (1/3) sets with the same SARS-CoV-2/influenza ratio. The Shapley Additive Explanations technique was employed to visualize the impact of each laboratory test on the differentiation. ResultsThe RF model incorporating results from 15 laboratory tests and demographic characteristics discriminated SARS-CoV-2 and influenza infections, with an area under the ROC curve value 0.90 in the independent testing set. The overall agreement with the RT-PCR results was 83% (95% CI: 80-86%). The test with the greatest impact on the differentiation was serum total calcium level. Further, the model achieved an AUC of 0.82 in a new dataset including 519 SARS-CoV-2 ED patients (2020/12/1 to 2021/2/28) and the previous 723 influenza positive patients. Serum calcium level remained the most impactful feature on the differentiation. ConclusionWe identified characteristic laboratory test profiles differentiating SARS-CoV-2 and influenza infections, which may be useful for the preparedness of overlapping COVID-19 resurgence and future seasonal influenza.

20.
Preprint in English | medRxiv | ID: ppmedrxiv-21261561

ABSTRACT

Longitudinal studies are needed to evaluate the SARS-CoV-2 mRNA vaccine antibody response under "real-world" conditions. This longitudinal study investigated the quantity and quality of SARS-CoV-2 antibody response in 846 specimens from 350 subjects: comparing BNT162b2-vaccinated individuals (19 previously diagnosed with COVID-19 [RecoVax]; 49 never been diagnosed [NaiveVax]) to 122 hospitalized unvaccinated (HospNoVax) and 160 outpatient unvaccinated (OutPtNoVax) COVID-19 patients. NaiveVax experienced a delay in generating SARS-CoV-2 total antibody levels (TAb) and neutralizing antibodies (SNAb) after the 1st vaccine dose (D1), but a rapid increase in antibody levels was observed after the 2nd dose (D2). However, these never reached the robust levels observed in RecoVax. In fact, NaiveVax TAb and SNAb levels decreased 4-weeks post-D2 (p=0.003;p<0.001). For the most part, RecoVax TAb persisted throughout this study, after reaching maximal levels 2-weeks post-D2; but SNAb decreased significantly [~]6-months post-D1 (p=0.002). Although NaiveVax avidity lagged behind that of RecoVax for most of the follow-up periods, NaiveVax did reach similar avidity by [~]6-months post-D1. These data suggest that one vaccine dose elicits maximal antibody response in RecoVax and may be sufficient. Also, despite decreasing levels in TAb and SNAb overtime, long-term avidity maybe a measure worth evaluating and possibly correlating to vaccine efficacy.

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