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1.
Jiaotong Yunshu Gongcheng Xuebao/Journal of Traffic and Transportation Engineering ; 22(4):68-88, 2022.
Article in Chinese | Scopus | ID: covidwho-2081237

ABSTRACT

On the basis of the recent research on the optimization of passenger boarding process at civil airports, the research status and achievements in this area was analyzed from the aspects of passenger, aircraft, methodology, and COVID-19 pandemic, the methods and measures to optimize the passenger boarding process at civil airports were discussed, and the directions of future studies were explored according to the deficiency in current research. Research results show that in the passenger-oriented optimization studies, the group passengers are considered a significant factor. The minimum boarding time and boarding interference are used as the objective functions to build relevant models, and the passengers with different priorities and latecomers are often considered in groups. WilMA and RP are two boarding strategies with excellent comprehensive performance, and the new Side-Slip seat has the most significant influence on boarding time. The solution of passenger boarding optimization include model methods and simulation methods, in which models mainly include statistical physical model and mathematical model, and simulations include cellular automata and agents. In terms of the COVID-19 pandemic-oriented boarding studies, the health of passengers is the main consideration, where boarding time and health risks are the two primary indicators to evaluate the quality of passenger boarding. In future studies, the advantages of different boarding strategies should be combined to overcome the shortcomings of different individual strategies. The agent-based simulation with strong independence should be combined with the cellular automata simulation that does not highlight the individual heterogeneity. More factors should be considered in optimization models, and better heuristic algorithms should be explored to solve optimization models. Moreover, the impacts of the factors such as the safe social distance, the number of passengers wearing masks, and the number of group boarding passengers on the process of boarding should be attached more importance. It is also an important research direction to explore how to maximize passenger safety and boarding efficiency under the regular COVID-19 epidemic control. 11 tabs, 4 figs, 142 refs. © 2022 Chang'an University. All rights reserved.

2.
Wuli Xuebao/Acta Physica Sinica ; 71(16), 2022.
Article in Chinese | Scopus | ID: covidwho-2056248

ABSTRACT

Epidemic viruses seriously affect human health and the normal operation of society, so it is particularly important to effectively kill viruses. In this work, a thermoelectric air disinfection system is studied. Utilizing the characteristics of semiconductor thermoelectric sheets with both cold and hot ends, the system can simultaneously sterilize the air by heating and reduce the temperature of the air by cooling. The measurement results show that the air temperature can be increased to 80 ℃ for disinfection, and then cooled to 35 ℃, and the total energy utilization rate of the system can reach up to 1.2. In addition, combined with the measurement results and numerical calculations, the parameters such as the number of thermoelectric element series, input power, air flow, and boundary insulation can be used to analyze their effects on the system performance. The system has broad potential applications in public health, medical care, and household disinfection. © 2022 中国物理学会 Chinese Physical Society.

3.
4th International Conference on Communications, Information System and Computer Engineering, CISCE 2022 ; : 156-159, 2022.
Article in English | Scopus | ID: covidwho-2018630

ABSTRACT

Agile development has been a common methodology in software development. In response to the covid-19, most software development teams choose to work remotely. As a result of the different network environments, the company cloud center network load cannot meet the requirements of remote development and fault tolerance requirements of the agile development process. We designed a mixed-method called the Edge Development approach for improving Agile software development during the decision-making process. The extensive literature review provided us with three categories of challenges as well as solutions to support Edge Development's decision-support process. In the light of the survey, Five main software development decision-making challenges were identified in this study. In addition, we made a series of recommendations to improve the decision-making process of Edge Development from a variety of perspectives. © 2022 IEEE.

4.
Measurement Science and Technology ; 33(11), 2022.
Article in English | Web of Science | ID: covidwho-2004966

ABSTRACT

This paper proposes a novel time-frequency feature fusion method to recognise patients' behaviours based on the Frequency Modulated Continuous Wave (FMCW) radar system, which can locate patients as well as recognise their current actions and thus is expected to solve the shortage of medical staff caused by the novel coronavirus pneumonia (COVID-19). To recognise the patient's behaviour, the FMCW radar is utilised to acquire point clouds reflected by the human body, and the micro-Doppler spectrogram is generated by human motion. Then features are extracted and fused from the time-domain information of point clouds and the frequency-domain information of the micro-Doppler spectrogram respectively. According to the fused features, the patient's behaviour is recognised by a Bayesian optimisation random forest algorithm, where the role of Bayesian optimisation is to select the best hyper-parameters for the random forest, i.e. the number of random forest decision trees, the depth of leaves, and the number of features. The experimental results show that an average accuracy of 99.3% can be achieved by using the time-frequency fusion with the Bayesian optimisation random forest model to recognise six actions.

5.
Gastroenterology ; 162(7):S-68-S-69, 2022.
Article in English | EMBASE | ID: covidwho-1967239

ABSTRACT

Introduction: Gut dysbiosis is associated with immune dysfunction and severity in COVID- 191-2. This study aimed to determine targeting dysbiosis as a therapy and its effect on antibody formation, gut dysbiosis and immune profile in patients with COVID-19. Material & Methods: In an open-label study, 25 consecutive hospitalized patients with COVID- 19 received a novel microbiome immunity formula (SIM01) for 28 days;30 patients who did not receive the intervention acted as controls. We collected fecal and blood samples at baseline and week 5 and followed subjects from admission up to five weeks. We performed multi-omics analysis using data from peripheral blood mononuclear cell (PBMC) transcriptome, fecal metagenomic sequencing and fecal metabolomic profiling (Figure 1A). Results: Significantly more COVID-19 patients on SIM01 developed anti-SARS-CoV-2 IgG than the control group at 2 weeks (Figure 1B). Patients on SIM01 (but not controls) showed a significant reduction of plasma levels of interleukin (IL)-6, macrophage colony-stimulating factor (M-CSF), tumour necrosis factor (TNF-a), IL-1RA (Figure 1C) and downregulated COVID-19 related signalling pathway in PBMC at Week 5. Fecal samples of subjects on SIM01 were enriched in commensal bacteria and reduced in opportunistic pathogens at week 4 and 5. Elevated plasma acetic acid in SIM01 group showed a negative correlation with SARS-CoV-2 viral load in nasopharyngeal samples (Figure 2A). Increased relative abundance of Bifidobacteria adolescentis and Coprococcus comes in fecal samples in SIM01 group positively correlated with plasma acetic acid levels (Figure 2B). Conclusion: We showed for the first time a novel microbiome formula SIM01 was effective in hastening antibody formation against SARS-CoV-2, reduced pro-inflammatory immune markers and restored gut dysbiosis in hospitalised COVID-19 patients. References: 1. Zuo T, Zhang F, Lui GCY, et al. Alterations in gut microbiota of patients with COVID-19 during time of hospitalization. Gastroenterology 2020;159:944-955 e8. 2. Yeoh YK, Zuo T, Lui GC, et al. Gut microbiota composition reflects disease severity and dysfunctional immune responses in patients with COVID- 19. Gut 2021;70:698-706. (Figure Presented) (Figure Presented)

6.
Academic Journal of Second Military Medical University ; 42(12):1444-1448, 2021.
Article in Chinese | EMBASE | ID: covidwho-1897231

ABSTRACT

Objective: To observe the protective effects of 2 kinds of protective stickers made from different materials on facial injury/discomfort caused by wearing protective appliances of military medical members in the medical team supporting Hubei, so as to provide reference for developing convenient and effective protective measures. Methods Totally 147 military medical members in the medical team supporting Hubei were surveyed by the self-designed questionnaire of facial injury/discomfort caused by wearing protective appliances. Cross-sectional survey of the facial injury/discomfort before and after using the protective gel stickers (Haishen stickers, developed by the Faculty of Pharmacy, Naval Medical University [Second Military Medical University]) or 3M hydrophilic dressing was conducted, and the protective effects of the 2 kinds of protective stickers on facial injury/discomfort were compared. Results A total of 78 medical members finished the questionnaires (62 cases with Haishen stickers and 16 cases with 3M hydrophilic dressings). The scores of facial injury/discomfort were significantly reduced in both groups after using the protective stickers (both, P<0.05);however, there was no significant difference between the 2 groups before or after using the protective stickers (both, P>0.05). The top 4 moderate-to-severe facial injury/discomfort were fogging of protective glasses/masks (85.9%, 67/78), skin indentation (80.8%, 63/78), pain at the contact sites (74.4%, 58/78) and sultry (71.8%, 56/78), and the overall proportion of moderate-to-severe injury/discomfort was 80.8% (63/78);after using the protective stickers, the top 4 moderate-to-severe facial injury/discomfort were fogging of glasses/masks (53.8%, 42/78), sultry (41.0%, 32/78), respiratory resistance (41.0%, 32/78) and skin indentation (38.5%, 30/78), with the overall proportion of moderate to severe injury/discomfort being 43.6% (34/78);and the top 4 improvement rates of facial injury/discomfort after using protective stickers were skin erosion (76.5%), skin redness (67.3%), pain at the contact sites (63.8%), and itching at the contact site (52.9%). Conclusion These 2 kinds of protective stickers made from different materials can improve the facial injury/discomfort caused by protective appliances, which is worth popularizing.

7.
Academic Journal of Second Military Medical University ; 43(3):239-245, 2022.
Article in Chinese | EMBASE | ID: covidwho-1887362

ABSTRACT

Objective To study the dynamic trajectories of quantitative immunoglobulin G (IgG) titers of hospitalized coronavirus disease 2019 (COVID-19) patients and reveal the immune process of the organism after infection. Methods The clinical data and quantitative IgG titers at different time points of hospitalized COVID-19 patients in Wuhan Huoshenshan Hospital and Guanggu Branch of Maternity and Child Healthcare Hospital of Hubei Province from Feb. 5 to Apr. 15, 2020 were retrospectively analyzed. Group-based trajectory modeling was used to identify the subgroups from time-series data of patients’ antibody titers, and then the clinical characteristics and outcomes were compared among these trajectory groups. Results Totally, 734 patients who met the criteria were included. Three IgG trajectory groups were identified from the antibody data: group 1 (consistently low group, 60 cases[8.17%]), group 2 (moderate group, 38 cases [5.18%]) and group 3 (high group, 636 cases[86.65%]). The hospitalization days and the virus clearance time of patients in the 3 groups were significantly different (both P<0.001), those in group 1 were the shortest, while the all-cause mortality and disease deterioration rate had no significant difference in the 3 groups (both P>0.05). Conclusion Patients with different IgG antibody developmental trajectories may have heterogeneous prognosis and immune process. Patients with consistently higher longitudinal antibody titers may require more medical attention.

8.
Topics in Antiviral Medicine ; 30(1 SUPPL):88-89, 2022.
Article in English | EMBASE | ID: covidwho-1881034

ABSTRACT

Background: Rapid and large-scale deployment of COVID-19 mRNA vaccines highlights the potential utility of developing nucleic acid vaccines (such as RNA and DNA vaccines) against infectious diseases, including HIV-1. However, as compared to SARS-CoV-2, HIV-1 pose some unique challenges-induction of neutralizing antibodies (NAbs) against HIV-1 (frequently a correlate of protection) requires presentation of trimeric and highly conformational epitopes to the immune system, and whether nucleic acid vaccines can enable direct in vivo production of antigens that retain critical antigenic profile has not yet been elucidated. Additionally, it was previously reported that Tier 2 NAbs cannot be induced in mice due to a lack of antibody repertoire, and vaccine studies were suggested to be performed in larger mammals such as rabbits/NHPs, inadvertently slowing down and increasing the costs of preclinical HIV-1 vaccine studies. Methods: In our study, we used the Antigen Conformation Tracing In Vivo by ELISA (ACTIVE) assay developed in house to characterize antigenic profiles of vaccines produced in vivo (from transfected muscle tissues). We analyzed induced cellular responses, using stimulation with overlapping peptides followed by intracellular cytokine staining and IFN-g ELIspot assays. We analyzed induced humoral responses by using both binding ELISA assays and TZM-BL based neutralizing assays, and attempted to map induced NAb epitopes by engineering selectively mutated pseudovirus. We performed antigen-specific B-cell sorting, and used the 10x genomics pipeline to characterize antibody sequences of proliferating B-cell clones. Results: We confirmed that in vivo produced vaccines retained key trimeric conformational epitopes and glycan profiles. Compared to protein vaccination, DNA vaccination uniquely and strongly induced both TFH, CD4+, CD8+ T-cell responses, and Tier 2 NAbs mapped to a previously unreported Env C3/V5 epitope. 5 unique NAbs were isolated, and confirmed to bind to the epitope using a Cryo-EM structure of NAb-MD39 complex at 3.8Å resolution. Conclusion: Our study confirmed that with appropriate vaccine delivery technology, murine models can be appropriately used for HIV-1 vaccine studies aimed at generating NAb responses. In addition, beyond potential functional immunity gains, DNA vaccines permit in vivo folding of structured antigens and provide significant cost and speed advantages for enabling rapid evaluation of new HIV vaccines.

10.
60th IEEE Conference on Decision and Control (CDC) ; : 2830-2835, 2021.
Article in English | Web of Science | ID: covidwho-1868524

ABSTRACT

Pandemics can bring a range of devastating consequences to public health and the world economy. Identifying the most effective control strategies has been the imperative task all around the world. Various public health control strategies have been proposed and tested against pandemic diseases (e.g., COVID-19). We study two specific pandemic control models: the susceptible, exposed, infectious, recovered (SEIR) model with vaccination control;and the SEIR model with shield immunity control. We express the pandemic control requirement in metric temporal logic (MTL) formulas. We then develop an iterative approach for synthesizing the optimal control strategies with MTL specifications. We provide simulation results in two different scenarios for robust control of the COVID-19 pandemic: one for vaccination control, and another for shield immunity control, with the model parameters estimated from data in Lombardy, Italy. The results show that the proposed synthesis approach can generate control inputs such that the time-varying numbers of individuals in each category (e.g., infectious, immune) satisfy the MTL specifications with robustness against initial state and parameter uncertainties.

11.
Multidisciplinary Microfluidic and Nanofluidic Lab-on-a-Chip: Principles and Applications ; : 199-233, 2021.
Article in English | Scopus | ID: covidwho-1838476

ABSTRACT

Microfluidic- and nanofluidics-based nucleic acid sensing and analysis have become of interest to the public, especially during the current COVID pandemic. In this chapter, we provide a comprehensive review of recent research dedicated to the advances of nucleic acid analysis and detection including various polymerase chain reaction platforms, isothermal target amplification methods, and emerging amplification-free methods, such as optofluidics sensing, electrochemical sensing, thermal sensing, and advanced microscopy for label-free DNA/RNA analysis. The future advancement and prospects of nucleic acid analysis are also discussed. © 2022 Elsevier B.V. All rights reserved.

12.
Chinese Journal of Evidence-Based Medicine ; 22(4):457-462, 2022.
Article in Chinese | EMBASE | ID: covidwho-1818645

ABSTRACT

Objective To assess the methodological quality of pediatric COVID-19 guidelines using the AGREE Ⅱ. Methods Domestic and foreign pediatric COVID-19 guidelines from inception to 1st Oct 2021 were electronically searched in PubMed, CBM, CNKI, VIP, WanFang Data, Medlive, NGC, GIN, and NICE databases and relevant websites. Two researchers independently assessed the methodological quality of the guidelines by using AGREE Ⅱ. Results A total of 21 guidelines were included. The AGREE Ⅱ results revealed that the average scores of included guidelines in 6 domains (scope and purpose, stakeholder involvement, rigor of development, clarity of presentation, applicability, and editorial independence) were 62.70%, 36.24%, 20.34%, 50.42%, 22.12% and 53.17%, respectively. Conclusion The methodological quality of pediatric COVID-19 guidelines is poor. Guideline developers should follow the requirements of AGREE Ⅱ in guideline development.

13.
Molecular Immunology ; 141:222-223, 2022.
Article in English | Web of Science | ID: covidwho-1801749
14.
PubMed; 2020.
Preprint in English | PubMed | ID: ppcovidwho-333517

ABSTRACT

PURPOSE: Conjunctival signs and symptoms are observed in a subset of patients with COVID-19, and SARS-CoV-2 has been detected in tears, raising concerns regarding the eye both as a portal of entry and carrier of the virus. The purpose of this study was to determine whether ocular surface cells possess the key factors required for cellular susceptibility to SARS-CoV-2 entry/infection. METHODS: We analyzed human post-mortem eyes as well as surgical specimens for the expression of ACE2 (the receptor for SARS-CoV-2) and TMPRSS2, a cell surface-associated protease that facilitates viral entry following binding of the viral spike protein to ACE2. RESULTS: Across all eye specimens, immunohistochemical analysis revealed expression of ACE2 in the conjunctiva, limbus, and cornea, with especially prominent staining in the superficial conjunctival and corneal epithelial surface. Surgical conjunctival specimens also showed expression of ACE2 in the conjunctival epithelium, especially prominent in the superficial epithelium, as well as the substantia propria. All eye and conjunctival specimens also expressed TMPRSS2. Finally, western blot analysis of protein lysates from human corneal epithelium obtained during refractive surgery confirmed expression of ACE2 and TMPRSS2. CONCLUSIONS: Together, these results indicate that ocular surface cells including conjunctiva are susceptible to infection by SARS-CoV-2, and could therefore serve as a portal of entry as well as a reservoir for person-to-person transmission of this virus. This highlights the importance of safety practices including face masks and ocular contact precautions in preventing the spread of COVID-19 disease.

15.
Journal of Image and Graphics ; 27(3):827-837, 2022.
Article in Chinese | Scopus | ID: covidwho-1789675

ABSTRACT

Objective: The corona virus disease 2019 (COVID-19), also known as severe acute respiratory syndrome coronavirus (SARS-CoV-2), has rapidly spread throughout the world as a result of the increased mobility of populations in a globalized world, wreaking havoc on people's daily lives, the global economy, and the global healthcare system. The novelty and dissemination speed of COVID-19 compelled researchers around the world to move quickly, using all resources and capabilities to analyse and characterize the novel coronavirus in terms of transmission routes and viral latency. Early and effective screening of COVID-19 patients and corresponding medical treatment, care and isolation to cut off the transmission route of the novel coronavirus are the key to prevent the spread of the epidemic. Due to the rapid infection of COVID-19, it is very important to screen COVID-19 threats based on precise segmenting lesions in lung CT images, which can be a low cost and quick response method nowadays. Rapid and accurate segmentation of coronavirus pneumonia CT images is of great significance for auxiliary diagnosis and patient monitoring. Currently, the main method for COVID-19 screening is the reverse transcription polymerase chain reaction like reverse transcription-polymerase chain reaction(RT-PCR) analysis. But, RT-PCR is time consuming to provide the diagnosis results, and the false negative rate is relatively high. Another effective method for COVID-19 screening is computed tomography (CT) technology. The CT scanning technology has high sensitivity and enhanced three-dimensional representation of infection visualization. Computed tomography (CT) has been used as an important method for the diagnosis and treatment of patients with COVID-19, the chest CT images of patients with COVID-19 mostly show multifocal, patchy, peripheral distribution, and ground glass opacity (GGO) which is mostly seen in the lower lobes of both lungs;a high degree of suspicion for novel coronavirus's infection can be obtained if more GGO than consolidation is found on CT images;therefore, detection of GGO in CT slices regions can provide clinicians with important information and help in the fight against COVID-19. The current analysis of COVID-19 pneumonia lesions has low segmentation accuracy and insufficient attention to false negatives. Method: Our accurate segmentation model based on small data set. In view of the complexity and variability of the targeted area of COVID-19 pneumonia, we improved Inf-Net and proposed a multi-scale encoding and decoding network (MED-Net) based on deep learning method. The computational cost may be caused by multi-scale encoding and decoding. The network extends the encoder-decoder structure in FC-Net, in which the decoder part is on the left column;The middle column is atrous spatial pyramid pooling (ASPP) structure;The right column is a multi-scale parallel decoder which is based on the improvement of parallel partial decoder. In this network structure, HarDNet68 is adopted as the backbone in terms of high resource utilization and fast computing speed, which can be as a simplified version of DenseNet, reduces DenseNet based hierarchical connections to get cascade loss deduction. HardNet68 is mainly composed of five harmonious dense blocks (HDB). Based on 5 different scales, We extract multiscale features from the first convolution layer and the 5 HDB sequential steps of HarDNet68 via a five atrous spatial pyramid pooling (ASPP). Meanwhile, as a new decoding component, a multiscale parallel partial decoder (MPPD) is based on the parallel decoder (PPD), which can aggregate the features between different levels in parallel. By decoding the branches of three different receptive fields, we have dealt with information loss issues in the encoder part and the difficulty of small lesions segmentation. Our deep supervision mechanism has melted the multi-scale decoder into the true positive and true negative samples analyses, for improving the sensitivity of the model. Result: Current COVID-19 CT Segmentation provides compl ted segmentation labels as a small data set. This research is improved based on Inf-Net, and the model structure is simple, the edge attention module(EA) is not introduced, and the reverse attention module(RA) is not quoted, only one MPPD is used to optimize the network stricture. The quantitative results show that MED-Net can effectively cope with the problems of fewer samples in the small dataset, the texture, size and position of the segmentation target vary greatly. On the data set with only 50 training images and 50 test images, the Dice coefficient is 73.8%, the sensitivity is 77.7%, and the specificity is 94.3%. Compared with the previous work, it has increased by 8.21%, 12.28% and 7.76% respectively. Among them, Dice coefficient and sensitivity have reached the most advanced level based on the same division mode of this data set. Simultaneously the qualitative results address that the segmentation result of the proposed model is closer to ground-truth in this experiment. We also conducted ablation experiments, that the use of MPPD has obvious effects to deal with small lesions area segmentation and improving segmentation accuracy. Conclusion: Our analysis shows that the proposed method can effectively improve the segmentation accuracy of the lesions in the CT images of the COVID-19 derived lungs disease. Our segmentation accuracy of MED-Net is qualified. The quantitative and qualitative results demonstrate that MED-Net is relatively effective in controlling edges and details, which can capture rich context information, and improve sensitivity. MED-Net can also effectively resolve the small lesions segmentation issue. For COVID-19 CT Segmentation data set, it has several of qualified evaluation indicators based on end-to-end learning. The potential of automatic segmentation of COVID-19 pneumonia is further facilitated. © 2022, Editorial Office of Journal of Image and Graphics. All right reserved.

16.
Open Forum Infectious Diseases ; 8(SUPPL 1):S1, 2021.
Article in English | EMBASE | ID: covidwho-1746817

ABSTRACT

Background. The mechanisms associated with COVID-19 in children are not well understood. We sought to define the differences in nasopharyngeal (NP) cytokine profiles according to clinical presentation in children with COVID-19. Methods. Single-center, prospective study in 137 children and adolescents < 21 years of age hospitalized with COVID-19, and 35 age, sex and race matched pre-pandemic (2016-2019) healthy controls. Children with COVID-19 were categorized according to their clinical presentation in: COVID-19-symptomatic;COVID-19-screening, and multisystem inflammatory syndrome (MIS-C). NP swabs were obtained within 24 hours of admission to measure SARS-CoV-2 loads by rt-PCR, and a 92-cytokine panel. Unsupervised and supervised analysis adjusted for multiple comparisons were performed. Results. From 3/2020 to 1/2021, we enrolled 76 COVID-19-symptomatic children (3.5 [0.2-15.75] years);45 COVID-19-screening (11.1 [4.2-16.1] years), and 16 MIS-C (11.2 [5.9-14.6] years). Median NP SARS-CoV-2 loads were higher in COVID-19-symptomatic versus screening and MIS-C (6.8 vs 3.5 vs 2.82 log10 copies/mL;p< 0.001). Statistical group comparisons identified 15 cytokines that consistently differed between groups and were clustered in three functional categories: (1) antiviral/regulatory, (2) pro-inflammatory/chemotactic, and (3) a combination of (1) and (2);(Fig 1). All 15 cytokines were higher in COVID-19-symptomatic versus controls (p< 0.05). Similarly, and except for TNF, CCL3, CCL4 and CCL23, which were comparable in COVID-19-symptomatic and screening patients, the remaining cytokines were higher in symptomatic children (p< 0.05). PDL-1 (p=0.01) and CCL3 (p=0.03) were the only cytokines significantly decreased in children with MIS-C versus symptomatic COVID-19 children. The 15 cytokines identified by multiple comparisons were correlated using Person's in R software. Red reflects a positive correlation and blue a negative correlation with the intensity of the color indicating the strength of the association. Conclusion. Children with symptomatic COVID-19 demonstrated higher viral loads and greater mucosal cytokines concentrations than those identified via screening, whereas in MIS-C concentrations of regulatory cytokines were decreased. Simultaneous evaluation of viral loads and mucosal immune responses using non-invasive sampling could aid with the stratification of children and adolescents with COVID-19 in the clinical setting.

17.
Open Forum Infectious Diseases ; 8(SUPPL 1):S51-S52, 2021.
Article in English | EMBASE | ID: covidwho-1746790

ABSTRACT

Background. Almost 4 million children have tested positive for Coronavirus Disease 2019 (COVID-19) as of June 3 2021, representing 14% of all cases in USA. Children present with diverse clinical findings including the multisystem inflammatory syndrome in children (MIS-C). In this study, we measured serum cytokine concentrations in children with COVID-19 to identify differences in immune profiles according to clinical presentations. Methods. A total of 133 children 0-21 years of age with COVID-19 were enrolled at Nationwide Children's Hospital, in Columbus, Ohio. Nasopharyngeal swab RT-PCR testing was used for SARS-CoV-2 detection and quantification. Clinical and laboratory information were obtained, and blood samples were collected for measurement of cytokines with a 92-plex inflammation assay (Olink). Normalized cytokine expression levels in patients were compared with serum samples from 66 pre-pandemic agematched healthy controls. Results. COVID-19 children included: 1) those identified by universal screening (n=47);2) moderate disease (ward;n=48);3) severe disease (PICU;n=20);4) MIS-C (n=18). Children identified by universal screening were hospitalized for trauma, appendicitis or new onset diabetes among others. Children with symptomatic COVID-19 had significantly higher SARS-CoV-2 viral loads than children with MIS-C or those identified via universal screening. Concentrations of interferon (IFN) related cytokines (IFNg, CXCL9, CXCL10, CXCL11), interleukins (IL6, IL8, IL10, IL17A, IL18, IL24) and other inflammatory cytokines (TGF, TNF, VEGF, MCP, CD40) were significantly increased in children with acute COVID-19 and MIS-C compared with children identified by universal screening and healthy controls. These cytokines were positively correlated with C-reactive protein, D-dimer and disease severity in COVID-19, but negatively correlated with viral loads (Fig 1). MIS-C showed stronger inflammatory response than acute COVID-19 (Fig 2). Correlation of Age-adjusted cytokine expression values with viral load, disease severity, CRP and D-dimer. Pearson correlation coefficient is shown for each pair. Red: positive correlation;blue: negative correlation Cytokines that differentiate MIS-C from acute COVID-19 Heatmap shows the differential expressed cytokines between MIS-C and acute severe COVID-19 (padj<0.05, FC>2). The age-adjusted expression values are normalized the median of healthy controls. Red: up-regulation, blue: down-regulation. Conclusion. We identified three cytokine clusters in children with COVID-19 according to clinical presentations. Correlations of serum cytokines with clinical/laboratory parameters could be used to identify potential biomarkers associated with disease severity in COVID-19.

18.
2021 IEEE International Conference on Engineering, Technology and Education, TALE 2021 ; : 42-47, 2021.
Article in English | Scopus | ID: covidwho-1741274

ABSTRACT

Domain-Specific Architectures (DSAs) and hardware-software co-design are greatly emphasized in the CS community, which demands a significant number of participants with Computer System (CSys) capabilities and skills. Conventional CSys courses in a lecture-lab format are limited in physical resources and inherently difficult to cultivate talents at a large scale. Online teaching is a potential alternative to instantly enlarge the face-to-face class size. Unfortunately, simply putting the lecture contents in CSys courses online lacks 1) personal attention, 2) learner-instructor interactions, and 3) real-hardware experimental environments. To tackle the above challenges, we introduce a four phase online CSys course program and the related teaching methods for a cloud-based teaching platform. The four-phase course program included two basic/required stages and two advanced/optional stages to promote students' knowledge and skill level with appropriate personal attention. We studied if online interaction methods, such as in-class chat and one-on-one online grading interview, can strengthen the connections between teachers and students in both lectures and labs. We created a heterogeneous cloud platform to enable students nationwide to reliably conduct labs or projects on remote programmable hardware. We believe that our proposed course design methodology is beneficial to other CScourses in the post-COVID-19-era. © 2021 IEEE.

19.
21st IEEE International Conference on Data Mining Workshops, ICDMW 2021 ; 2021-December:517-526, 2021.
Article in English | Scopus | ID: covidwho-1730932

ABSTRACT

COVID-19 has been a public health emergency of international concern since early 2020. Reliable forecasting is critical to diminish the impact of this disease. To date, a large number of different forecasting models have been proposed, mainly including statistical models, compartmental models, and deep learning models. However, due to various uncertain factors across different regions such as economics and government policy, no forecasting model appears to be the best for all scenarios. In this paper, we perform quantitative analysis of COVID-19 forecasting of confirmed cases and deaths across different regions in the United States with different forecasting horizons, and evaluate the relative impacts of the following three dimensions on the predictive performance (improvement and variation) through different evaluation metrics: model selection, hyperparameter tuning, and the length of time series required for training. We find that if a dimension brings about higher performance gains, if not well-tuned, it may also lead to harsher performance penalties. Furthermore, model selection is the dominant factor in determining the predictive performance. It is responsible for both the largest improvement and the largest variation in performance in all prediction tasks across different regions. While practitioners may perform more complicated time series analysis in practice, they should be able to achieve reasonable results if they have adequate insight into key decisions like model selection. © 2021 IEEE.

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