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1.
The Lancet Regional Health - Western Pacific ; : 100660, 2022.
Article in English | ScienceDirect | ID: covidwho-2165672

ABSTRACT

Summary Background The ongoing outbreak of SARS-CoV-2 Omicron BA.2 infections in Hong Kong, the model city of universal masking of the world, has resulted in a major public health crisis. Although the third vaccination resulted in strong boosting of neutralization antibody, vaccine efficacy and correlate of immune protection against the major circulating Omicron BA.2 remain to be investigated. Methods We investigated the vaccine efficacy against the Omicron BA.2 breakthrough infection among 470 public servants who had received different SARS-CoV-2 vaccine regimens including two-dose BNT162b2 (2 × BNT, n = 169), three-dose BNT162b2 (3 × BNT, n = 168), two-dose CoronaVac (2 × CorV, n = 34), three-dose CoronaVac (3 × CorV, n = 67) and third-dose BNT162b2 following 2 × CorV (2 × CorV+1BNT, n = 32). Humoral and cellular immune responses after three-dose vaccination were further characterized and correlated with clinical characteristics of BA.2 infection. Findings During the BA.2 outbreak, 27.7% vaccinees were infected. The timely third-dose vaccination provided significant protection with lower incidence rates of breakthrough infections (2 × BNT 46.2% vs 3 × BNT 13.1%, p < 0.0001;2 × CorV 44.1% vs 3 × CorV 19.4%, p = 0.003). Investigation of immune responses on blood samples derived from 90 subjects in three-dose vaccination cohorts collected before the BA.2 outbreak revealed that the third-dose vaccination activated spike (S)-specific memory B cells and Omicron cross-reactive T cell responses, which correlated with reduced frequencies of breakthrough infections and disease severity rather than with types of vaccines. Moreover, the frequency of S-specific activated memory B cells was significantly lower in infected vaccinees than uninfected vaccinees before vaccine-breakthrough infection whereas IFN-γ+ CD4 T cells were negatively associated with age and viral clearance time. Critically, BA.2 breakthrough infection boosted cross-reactive memory B cells with enhanced cross-neutralizing antibodies to Omicron sublineages, including BA.2.12.1 and BA.4/5, in all vaccinees tested. Interpretation Our results imply that the timely third vaccination and immune responses are likely required for vaccine-mediated protection against Omicron BA.2 pandemic. Although BA.2 conferred the highest neutralization resistance compared with variants of concern tested before the emergence of BA.2.12.1 and BA.4/5, the third dose vaccination-activated S-specific memory B cells and Omicron cross-reactive T cell responses contributed to reduced frequencies of breakthrough infection and disease severity. Neutralizing antibody potency enhanced by BA.2 breakthrough infection in vaccinees with prior 3 doses of CoronaVac or BNT162b2 may reduce the risk of infection against ongoing BA.2.12.1 and BA.4/5. Funding Hong Kong Research Grants Council Collaborative Research Fund, Health and Medical Research Fund, Wellcome Trust, Shenzhen Science and Technology Program, the Health@InnoHK, Innovation and Technology Commission of Hong Kong, China, National Program on Key Research Project, Emergency Key Program of Guangzhou Laboratory, donations from the Friends of Hope Education Fund and the Hong Kong Theme-Based Research Scheme.

2.
Computers in Biology and Medicine ; 153:106517, 2023.
Article in English | ScienceDirect | ID: covidwho-2165195

ABSTRACT

The growing and aging of the world population have driven the shortage of medical resources in recent years, especially during the COVID-19 pandemic. Fortunately, the rapid development of robotics and artificial intelligence technologies help to adapt to the challenges in the healthcare field. Among them, intelligent speech technology (IST) has served doctors and patients to improve the efficiency of medical behavior and alleviate the medical burden. However, problems like noise interference in complex medical scenarios and pronunciation differences between patients and healthy people hamper the broad application of IST in hospitals. In recent years, technologies such as machine learning have developed rapidly in intelligent speech recognition, which is expected to solve these problems. This paper first introduces IST's procedure and system architecture and analyzes its application in medical scenarios. Secondly, we review existing IST applications in smart hospitals in detail, including electronic medical documentation, disease diagnosis and evaluation, and human-medical equipment interaction. In addition, we elaborate on an application case of IST in the early recognition, diagnosis, rehabilitation training, evaluation, and daily care of stroke patients. Finally, we discuss IST's limitations, challenges, and future directions in the medical field. Furthermore, we propose a novel medical voice analysis system architecture that employs active hardware, active software, and human-computer interaction to realize intelligent and evolvable speech recognition. This comprehensive review and the proposed architecture offer directions for future studies on IST and its applications in smart hospitals.

3.
IEEE Transactions on Intelligent Transportation Systems ; 23(12):25062-25076, 2022.
Article in English | ProQuest Central | ID: covidwho-2152549

ABSTRACT

As transportation system plays a vastly important role in combatting newly-emerging and severe epidemics like the coronavirus disease 2019 (COVID-19), the vehicle routing problem (VRP) in epidemics has become an emerging topic that has attracted increasing attention worldwide. However, most existing VRP models are not suitable for epidemic situations, because they do not consider the prevention cost caused by issues such as viral tests and quarantine during the traveling. Therefore, this paper proposes a multi-objective VRP model for epidemic situations, named VRP4E, which considers not only the traditional travel cost but also the prevention cost of the VRP in epidemic situations. To efficiently solve the VRP4E, this paper further proposes a novel algorithm named multi-objective ant colony system algorithm for epidemic situations, termed MOACS4E, together with three novel designs. First, by extending the efficient “multiple populations for multiple objectives” framework, the MOACS4E adopts two ant colonies to optimize the travel and prevention costs respectively, so as to improve the search efficiency. Second, a pheromone fusion-based solution generation method is proposed to fuse the pheromones from different colonies to increase solution diversity effectively. Third, a solution quality improvement method is further proposed to improve the solutions for the prevention cost objective. The effectiveness of the MOACS4E is verified in experiments on 25 generated benchmarks by comparison with six state-of-the-art and modern algorithms. Moreover, the VRP4E in different epidemic situations and a real-world case in the Beijing-Tianjin-Hebei region, China, are further studied to provide helpful insights for combatting COVID-19-like epidemics.

5.
International journal of biological macromolecules ; 2022.
Article in English | EuropePMC | ID: covidwho-2147794

ABSTRACT

Alginate derivatives have been demonstrated remarkable antiviral activities. Here we firstly identified polymannuronate phosphate (PMP) as a highly potential anti-SARS-CoV-2 agent. The structure-activity relationship showed polymannuronate monophosphate (PMPD, Mw: 5.8 kDa, P%: 8.7 %) was the most effective component to block the interaction of spike to ACE2 with an IC50 of 85.5 nM. Surface plasmon resonance study indicated that PMPD could bind to spike receptor binding domain (RBD) with the KD value of 78.59 nM. Molecular docking further suggested that the probable binding site of PMPD to spike RBD protein is the interaction interface between spike and ACE2. PMPD has the potential to inhibit the SARS-CoV-2 infection in an independent manner of heparan sulfate proteoglycans. In addition, polyguluronate sulfate (PGS) and propylene glycol alginate sodium sulfate (PSS) unexpectedly showed 3CLpro inhibition with an IC50 of 1.20 μM and 1.42 μM respectively. The polyguluronate backbone and sulfate group played pivotal roles in the 3CLpro inhibition. Overall, this study revealed the potential of PMPD as a novel agent against SARS-CoV-2. It also provided a theoretical basis for further study on the role of PGS and PSS as 3CLpro inhibitors. Graphical Unlabelled Image

6.
Vaccines ; 10(12):2035, 2022.
Article in English | MDPI | ID: covidwho-2143787

ABSTRACT

Coronavirus disease (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has spread to more than 230 countries and territories worldwide since its outbreak in late 2019. In less than three years, infection by SARS-CoV-2 has resulted in over 600 million cases of COVID-19 and over 6.4 million deaths. Vaccines have been developed with unimaginable speed, and 11 have already been approved by the World Health Organization and given Emergency Use Listing. The administration of several first-generation SARS-CoV-2 vaccines has successfully decelerated the spread of COVID-19 but not stopped it completely. In the ongoing fight against viruses, genetic mutations frequently occur in the viral genome, resulting in a decrease in vaccine-induced antibody neutralization and widespread breakthrough infection. Facing the evolution and uncertainty of SARS-CoV-2 in the future, and the possibility of the spillover of other coronaviruses to humans, the need for vaccines with a broad spectrum of antiviral variants against multiple coronaviruses is recognized. It is imperative to develop a universal coronavirus or pan-coronavirus vaccine or drug to combat the ongoing COVID-19 pandemic as well as to prevent the next coronavirus pandemic. In this review, in addition to summarizing the protective effect of approved vaccines, we systematically summarize current work on the development of vaccines aimed at suppressing multiple SARS-CoV-2 variants of concern as well as multiple coronaviruses.

7.
Biol Methods Protoc ; 7(1): bpac029, 2022.
Article in English | MEDLINE | ID: covidwho-2134855

ABSTRACT

Background: It's critical to identify COVID-19 patients with a higher death risk at early stage to give them better hospitalization or intensive care. However, thus far, none of the machine learning models has been shown to be successful in an independent cohort. We aim to develop a machine learning model which could accurately predict death risk of COVID-19 patients at an early stage in other independent cohorts. Methods: We used a cohort containing 4711 patients whose clinical features associated with patient physiological conditions or lab test data associated with inflammation, hepatorenal function, cardiovascular function, and so on to identify key features. To do so, we first developed a novel data preprocessing approach to clean up clinical features and then developed an ensemble machine learning method to identify key features. Results: Finally, we identified 14 key clinical features whose combination reached a good predictive performance of area under the receiver operating characteristic curve 0.907. Most importantly, we successfully validated these key features in a large independent cohort containing 15 790 patients. Conclusions: Our study shows that 14 key features are robust and useful in predicting the risk of death in patients confirmed SARS-CoV-2 infection at an early stage, and potentially useful in clinical settings to help in making clinical decisions.

8.
Annals of Translational Medicine ; 10(21):1154-1154, 2022.
Article in English | Web of Science | ID: covidwho-2124167

ABSTRACT

Background: The number of Chinese clinical trials has continued to grow throughout the coronavirus disease 2019 (COVID-19) pandemic, but we know little about clinical trial team members' perceptions and attitudes toward the impacts of the pandemic. This study aimed to assess the impact of the COVID-19 pandemic on clinical trials in China from the perspective of research staff to provide a deeper understanding and some recommendations for the ongoing and upcoming clinical trials during the pandemic.Methods: A nationwide cross-sectional questionnaire was distributed to respondents throughout mainland China between September 2021 and October 2021. The participants assessed the impact of the COVID-19 pandemic on clinical trials based on a 5-point Likert-type scale, and exploratory factor analysis (EFA) was used to confirm the factor structure. Descriptive statistical analysis and the Mann-Whitney test were used to discover the differences between different groups.Results: A total of 2,393 questionnaires from 272 hospitals were collected in mainland China. Factor analysis resulted in 4 factors, with a cumulative explained variance of 64.93%, as follows: subject enrollment, patient care, study supplies and data management, and research milestones and quality management. The research team members, predominantly represented by clinical research coordinators (CRCs), basically agreed with all but 3 preset scenarios of the impact of COVID-19 on clinical trials. Most respondents did not agree that the pandemic was associated with more serious adverse events (SAEs), missed reports of safety events, or any increase of unscheduled unblinding. In addition, significant differences were revealed in different age, gender, and role groups of respondents based on their views on the impact of the pandemic.Conclusions: The current pandemic situation has had a negative impact on clinical trials, especially in terms of subject recruitment and protocol compliance, yet research team members feel confident that some of the effective measures proposed in the study can moderate the negative impact.

9.
Zhongguo Bingdubing Zazhi = Chinese Journal of Viral Diseases ; - (5):339, 2022.
Article in English | ProQuest Central | ID: covidwho-2118667

ABSTRACT

Effectively blocking the transmission route of coronavirus and protecting the susceptible population play significant roles in the control of COVID-19 pandemic.Strengthening home-based medical observation is one of the key points in preventing the spread of SARS-CoV-2 virus in families and communities.Therefore, in order to meet the needs for COVID-19 prevention and control in Beijing, a group of experts organized by Beijing Association of Preventive Medicine developed the Guidelines for medical observation management of close contacts with COVID-19 cases Part 3: home-based medical observation(T/BPMA007.3-2020), which offers the specific provisions for close contacts of COVID-19 cases who need home-based medical observation as well as home environmental condition, prevention and control requirements, waste disposal, disinfection, community prevention and control work requirements, basic requirements for training and education and management guidelines.It provides standard support for home-based medical observation of close contacts with COVID-19 cases.

10.
Front Public Health ; 10: 974848, 2022.
Article in English | MEDLINE | ID: covidwho-2099265

ABSTRACT

Background: The coronavirus disease (COVID-19) pandemic, which has been ongoing for more than 2 years, has become one of the largest public health issues. Vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is one of the most important interventions to mitigate the COVID-19 pandemic. Our objective is to investigate the relationship between vaccination status and time to seroconversion. Methods: We conducted a cross-sectional observational study during the SARS-CoV-2 B.1.617.2 outbreak in Jiangsu, China. Participants who infected with the B.1.617.2 variant were enrolled. Cognitive performance, quality of life, emotional state, chest computed tomography (CT) score and seroconversion time were evaluated for each participant. Statistical analyses were performed using one-way ANOVA, univariate and multivariate regression analyses, Pearson correlation, and mediation analysis. Results: A total of 91 patients were included in the analysis, of whom 37.3, 25.3, and 37.3% were unvaccinated, partially vaccinated, and fully vaccinated, respectively. Quality of life was impaired in 30.7% of patients, especially for mental component summary (MCS) score. Vaccination status, subjective cognitive decline, and depression were risk factors for quality-of-life impairment. The chest CT score mediated the relationship of vaccination status with the MCS score, and the MCS score mediated the relationship of the chest CT score with time to seroconversion. Conclusion: Full immunization course with an inactivated vaccine effectively lowered the chest CT score and improved quality of life in hospitalized patients. Vaccination status could influence time to seroconversion by affecting CT score and MCS score indirectly. Our study emphasizes the importance of continuous efforts in encouraging a full vaccination course.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Pandemics , COVID-19 Vaccines , Seroconversion , COVID-19/prevention & control , Mental Health , Cross-Sectional Studies , Quality of Life , Tomography, X-Ray Computed , Vaccination
11.
Front Med (Lausanne) ; 9: 928637, 2022.
Article in English | MEDLINE | ID: covidwho-2099168

ABSTRACT

Background: SARS-CoV-2 causes coronavirus disease 2019 (COVID-19), a new coronavirus pneumonia, and containing such an international pandemic catastrophe remains exceedingly difficult. Asthma is a severe chronic inflammatory airway disease that is becoming more common around the world. However, the link between asthma and COVID-19 remains unknown. Through bioinformatics analysis, this study attempted to understand the molecular pathways and discover potential medicines for treating COVID-19 and asthma. Methods: To investigate the relationship between SARS-CoV-2 and asthma patients, a transcriptome analysis was used to discover shared pathways and molecular signatures in asthma and COVID-19. Here, two RNA-seq data (GSE147507 and GSE74986) from the Gene Expression Omnibus were used to detect differentially expressed genes (DEGs) in asthma and COVID-19 patients to find the shared pathways and the potential drug candidates. Results: There were 66 DEGs in all that were classified as common DEGs. Using a protein-protein interaction (PPI) network created using various bioinformatics techniques, five hub genes were found. We found that asthma has some shared links with the progression of COVID-19. Additionally, protein-drug interactions with common DEGs were also identified in the datasets. Conclusion: We investigated possible links between COVID-19 and asthma using bioinformatics databases, which might be useful in treating COVID-19 patients. More studies on populations affected by these diseases are needed to elucidate the molecular mechanism behind their association.

12.
Journal of Pharmaceutical and Biomedical Analysis ; : 115118, 2022.
Article in English | ScienceDirect | ID: covidwho-2083231

ABSTRACT

Coronavirus disease (COVID-19) caused by SARS-COV-2 infection has been widely prevalent in many countries and has become a common challenge facing mankind. Traditional Chinese medicine (TCM) has played a prominent role in this pandemic, and especially TCM with the function of “heat-clearing and detoxifying” has shown an excellent role in anti-virus. Fufang Shuanghua oral liquid (FFSH) has been used to treat the corresponding symptoms of influenza such as fever, nasal congestion, runny nose, sore throat, and upper respiratory tract infections in clinic, which are typical symptoms of COVID-19. The content of chlorogenic acid, andrographolide and dehydrated andrographolide as the quality control components of FFSH is not less than 1.0mg/mL, 60μg/mL and 60μg/mL respectively. In this study, UPLC-Q-TOF-MS/MS was employed to describe the chemical profile of FFSH. Virtual screening and fluorescence resonance energy transfer (FRET) were used to screen the effective components of FFSH acting on SARS-CoV-2 main protease (Mpro). As a result, 214 compounds in FFSH were identified or preliminarily characterized by UPLC-Q-TOF-MS/MS, and 61 active ingredients with potential inhibitory effects on Mpro were selected through receptor-based and ligand-based virtual screening. In particular, quercetin, forsythoside A, and linoleic acid showed a good inhibitory effect on Mpro in FRET evaluation with IC50 values of 26.15μM, 22.26μM and 47.09μM respectively, and had a strong binding affinity with the receptor Mpro (6LU7) in molecular docking. CYS145 and HIS41 were the main amino acid residues affected by small molecules in the protein binding domain. In brief, we characterized, for the first time, 214 chemical components in FFSH, and three of them, including quercetin, forsythoside A and linoleic acid, were screened out to exert beneficial anti-COVID-19 effects through CYS145 and HIS41 sites, which may provide a new research strategy for TCM to develop new therapeutic drugs against COVID-19.

13.
JMIR Bioinform Biotech ; 3(1): e36660, 2022.
Article in English | MEDLINE | ID: covidwho-2079966

ABSTRACT

Background: The COVID-19 pandemic is becoming one of the largest, unprecedented health crises, and chest X-ray radiography (CXR) plays a vital role in diagnosing COVID-19. However, extracting and finding useful image features from CXRs demand a heavy workload for radiologists. Objective: The aim of this study was to design a novel multiple-inputs (MI) convolutional neural network (CNN) for the classification of COVID-19 and extraction of critical regions from CXRs. We also investigated the effect of the number of inputs on the performance of our new MI-CNN model. Methods: A total of 6205 CXR images (including 3021 COVID-19 CXRs and 3184 normal CXRs) were used to test our MI-CNN models. CXRs could be evenly segmented into different numbers (2, 4, and 16) of individual regions. Each region could individually serve as one of the MI-CNN inputs. The CNN features of these MI-CNN inputs would then be fused for COVID-19 classification. More importantly, the contributions of each CXR region could be evaluated through assessing the number of images that were accurately classified by their corresponding regions in the testing data sets. Results: In both the whole-image and left- and right-lung region of interest (LR-ROI) data sets, MI-CNNs demonstrated good efficiency for COVID-19 classification. In particular, MI-CNNs with more inputs (2-, 4-, and 16-input MI-CNNs) had better efficiency in recognizing COVID-19 CXRs than the 1-input CNN. Compared to the whole-image data sets, the efficiency of LR-ROI data sets showed approximately 4% lower accuracy, sensitivity, specificity, and precision (over 91%). In considering the contributions of each region, one of the possible reasons for this reduced performance was that nonlung regions (eg, region 16) provided false-positive contributions to COVID-19 classification. The MI-CNN with the LR-ROI data set could provide a more accurate evaluation of the contribution of each region and COVID-19 classification. Additionally, the right-lung regions had higher contributions to the classification of COVID-19 CXRs, whereas the left-lung regions had higher contributions to identifying normal CXRs. Conclusions: Overall, MI-CNNs could achieve higher accuracy with an increasing number of inputs (eg, 16-input MI-CNN). This approach could assist radiologists in identifying COVID-19 CXRs and in screening the critical regions related to COVID-19 classifications.

14.
JMIR bioinformatics and biotechnology ; 3(1), 2022.
Article in English | EuropePMC | ID: covidwho-2073355

ABSTRACT

Background The COVID-19 pandemic is becoming one of the largest, unprecedented health crises, and chest X-ray radiography (CXR) plays a vital role in diagnosing COVID-19. However, extracting and finding useful image features from CXRs demand a heavy workload for radiologists. Objective The aim of this study was to design a novel multiple-inputs (MI) convolutional neural network (CNN) for the classification of COVID-19 and extraction of critical regions from CXRs. We also investigated the effect of the number of inputs on the performance of our new MI-CNN model. Methods A total of 6205 CXR images (including 3021 COVID-19 CXRs and 3184 normal CXRs) were used to test our MI-CNN models. CXRs could be evenly segmented into different numbers (2, 4, and 16) of individual regions. Each region could individually serve as one of the MI-CNN inputs. The CNN features of these MI-CNN inputs would then be fused for COVID-19 classification. More importantly, the contributions of each CXR region could be evaluated through assessing the number of images that were accurately classified by their corresponding regions in the testing data sets. Results In both the whole-image and left- and right-lung region of interest (LR-ROI) data sets, MI-CNNs demonstrated good efficiency for COVID-19 classification. In particular, MI-CNNs with more inputs (2-, 4-, and 16-input MI-CNNs) had better efficiency in recognizing COVID-19 CXRs than the 1-input CNN. Compared to the whole-image data sets, the efficiency of LR-ROI data sets showed approximately 4% lower accuracy, sensitivity, specificity, and precision (over 91%). In considering the contributions of each region, one of the possible reasons for this reduced performance was that nonlung regions (eg, region 16) provided false-positive contributions to COVID-19 classification. The MI-CNN with the LR-ROI data set could provide a more accurate evaluation of the contribution of each region and COVID-19 classification. Additionally, the right-lung regions had higher contributions to the classification of COVID-19 CXRs, whereas the left-lung regions had higher contributions to identifying normal CXRs. Conclusions Overall, MI-CNNs could achieve higher accuracy with an increasing number of inputs (eg, 16-input MI-CNN). This approach could assist radiologists in identifying COVID-19 CXRs and in screening the critical regions related to COVID-19 classifications.

15.
Molecules ; 27(19)2022 Oct 09.
Article in English | MEDLINE | ID: covidwho-2066288

ABSTRACT

With the increasing understanding of various disease-related noncoding RNAs, ncRNAs are emerging as novel drugs and drug targets. Nucleic acid drugs based on different types of noncoding RNAs have been designed and tested. Chemical modification has been applied to noncoding RNAs such as siRNA or miRNA to increase the resistance to degradation with minimum influence on their biological function. Chemical biological methods have also been developed to regulate relevant noncoding RNAs in the occurrence of various diseases. New strategies such as designing ribonuclease targeting chimeras to degrade endogenous noncoding RNAs are emerging as promising approaches to regulate gene expressions, serving as next-generation drugs. This review summarized the current state of noncoding RNA-based theranostics, major chemical modifications of noncoding RNAs to develop nucleic acid drugs, conjugation of RNA with different functional biomolecules as well as design and screening of potential molecules to regulate the expression or activity of endogenous noncoding RNAs for drug development. Finally, strategies of improving the delivery of noncoding RNAs are discussed.


Subject(s)
MicroRNAs , RNA, Untranslated , MicroRNAs/genetics , MicroRNAs/metabolism , Pharmaceutical Preparations , RNA, Small Interfering/genetics , RNA, Untranslated/genetics , Ribonucleases
16.
Transport policy ; 2022.
Article in English | EuropePMC | ID: covidwho-2058690

ABSTRACT

The COVID-19 pandemic has stifled international trade and the global maritime industry. Its impact on the routing of the regional vessel traffic flow provides supportive data to port authorities, ship owners, shippers, and consignees. This study proposes a spatiotemporal dynamic graph neural network (STDGNN) model that includes the usual primary part of the vessel flow and an auxiliary part of newly confirmed COVID-19 cases near the port. The primary part consists of a time-embedding (TE) block, two dynamic graph neural network (DGNN) blocks, and a gated recurrent unit block, to capture the spatiotemporal dependence in the regional vessel traffic flow. The auxiliary part is made of multiple blocks to exploit the dynamic temporal relationships in hours, days, and weeks. Moreover, the performance of the STDGNN model is verified by utilising real vessel traffic flow data (i.e. inflow, outflow, and volume) and the new cases of COVID-19 near the port of New York, USA, provided by the automatic identification system and the Johns Hopkins University Centre for Systems Science and Engineering. The 2-h prediction result shows a 37.7%, 17.23%, and 11.4% improvement in the mean absolute error (MAE) over the gated recurrent unit (GRU), STGCN, and TGCN models, respectively. The delicate and adaptable prediction of vessel traffic flow could help the port relieve congestion, enhance efficiency, and further assist the recovery of regional maritime industries in the post-COVID era.

17.
Viruses ; 14(9)2022 08 27.
Article in English | MEDLINE | ID: covidwho-2055387

ABSTRACT

Universal antiretroviral therapy (ART, "treat all") was recommended by the World Health Organization in 2015; however, HIV-1 transmission is still ongoing. This study characterizes the drivers of HIV transmission in the "treat all" era. Demographic and clinical information and HIV pol gene were collected from all newly diagnosed cases in Shenyang, the largest city in Northeast China, during 2016 to 2019. Molecular networks were constructed based on genetic distance and logistic regression analysis was used to assess potential transmission source characteristics. The cumulative ART coverage in Shenyang increased significantly from 77.0% (485/630) in 2016 to 93.0% (2598/2794) in 2019 (p < 0.001). Molecular networks showed that recent HIV infections linked to untreated individuals decreased from 61.6% in 2017 to 28.9% in 2019, while linking to individuals with viral suppression (VS) increased from 9.0% to 49.0% during the same time frame (p < 0.001). Undiagnosed people living with HIV (PLWH) hidden behind the links between index cases and individuals with VS were likely to be male, younger than 25 years of age, with Manchu nationality (p < 0.05). HIV transmission has declined significantly in the era of "treat all". Undiagnosed PLWH may drive HIV transmission and should be the target for early detection and intervention.


Subject(s)
HIV Infections , HIV-1 , China/epidemiology , Female , Genes, pol , HIV Infections/diagnosis , HIV Infections/drug therapy , HIV Infections/epidemiology , HIV-1/genetics , Humans , Male , Specimen Handling
18.
Transbound Emerg Dis ; 69(5): e2122-e2131, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-2053007

ABSTRACT

The ongoing enzootic circulation of the Middle East respiratory syndrome coronavirus (MERS-CoV) in the Middle East and North Africa is increasingly raising the concern about the possibility of its recombination with other human-adapted coronaviruses, particularly the pandemic SARS-CoV-2. We aim to provide an updated picture about ecological niches of MERS-CoV and associated socio-environmental drivers. Based on 356 confirmed MERS cases with animal contact reported to the WHO and 63 records of animal infections collected from the literature as of 30 May 2020, we assessed ecological niches of MERS-CoV using an ensemble model integrating three machine learning algorithms. With a high predictive accuracy (area under receiver operating characteristic curve = 91.66% in test data), the ensemble model estimated that ecologically suitable areas span over the Middle East, South Asia and the whole North Africa, much wider than the range of reported locally infected MERS cases and test-positive animal samples. Ecological suitability for MERS-CoV was significantly associated with high levels of bareland coverage (relative contribution = 30.06%), population density (7.28%), average temperature (6.48%) and camel density (6.20%). Future surveillance and intervention programs should target the high-risk populations and regions informed by updated quantitative analyses.


Subject(s)
COVID-19 , Middle East Respiratory Syndrome Coronavirus , Animals , COVID-19/epidemiology , COVID-19/veterinary , Camelus , Humans , Machine Learning , SARS-CoV-2
19.
Nat Commun ; 13(1): 5552, 2022 09 22.
Article in English | MEDLINE | ID: covidwho-2036823

ABSTRACT

One major limitation of neutralizing antibody-based COVID-19 therapy is the requirement of costly cocktails to reduce emergence of antibody resistance. Here we engineer two bispecific antibodies (bsAbs) using distinct designs and compared them with parental antibodies and their cocktail. Single molecules of both bsAbs block the two epitopes targeted by parental antibodies on the receptor-binding domain (RBD). However, bsAb with the IgG-(scFv)2 design (14-H-06) but not the CrossMAb design (14-crs-06) shows increased antigen-binding and virus-neutralizing activities against multiple SARS-CoV-2 variants as well as increased breadth of neutralizing activity compared to the cocktail. X-ray crystallography and cryo-EM reveal distinct binding models for individual cocktail antibodies, and computational simulations suggest higher inter-spike crosslinking potentials by 14-H-06 than 14-crs-06. In mouse models of infections by SARS-CoV-2 and multiple variants, 14-H-06 exhibits higher or equivalent therapeutic efficacy than the cocktail. Rationally engineered bsAbs represent a cost-effective alternative to antibody cocktails and a promising strategy to improve potency and breadth.


Subject(s)
Antibodies, Bispecific , COVID-19 , Animals , Antibodies, Neutralizing , Antibodies, Viral , COVID-19/drug therapy , Epitopes , Immunoglobulin G , Mice , SARS-CoV-2 , Spike Glycoprotein, Coronavirus
20.
Int J Infect Dis ; 122: 38-45, 2022 Sep.
Article in English | MEDLINE | ID: covidwho-2036061

ABSTRACT

OBJECTIVES: Selenium deficiency can be associated with increased susceptibility to some viral infections and even more severe diseases. In this study, we aimed to examine whether this association applies to severe fever with thrombocytopenia syndrome (SFTS). METHOD: An observational study was conducted based on the data of 13,305 human SFTS cases reported in mainland China from 2010 to 2020. The associations among incidence, case fatality rate of SFTS, and crop selenium concentration at the county level were explored. The selenium level in a cohort of patients with SFTS was tested, and its relationship with clinical outcomes was evaluated. RESULTS: The association between selenium-deficient crops and the incidence rate of SFTS was confirmed by multivariate Poisson analysis, with an estimated incidence rate ratio (IRR, 95% confidence interval [CI]) of 4.549 (4.215-4.916) for moderate selenium-deficient counties and 16.002 (14.706-17.431) for severe selenium-deficient counties. In addition, a higher mortality rate was also observed in severe selenium-deficient counties with an IRR of 1.409 (95% CI: 1.061-1.909). A clinical study on 120 patients with SFTS showed an association between serum selenium deficiency and severe SFTS (odds ratio, OR: 2.94; 95% CI: 1.00-8.67) or fatal SFTS (OR: 7.55; 95% CI: 1.14-50.16). CONCLUSION: Selenium deficiency is associated with increased susceptibility to SFTS and poor clinical outcomes.


Subject(s)
Bunyaviridae Infections , Phlebovirus , Selenium , Severe Fever with Thrombocytopenia Syndrome , Thrombocytopenia , China/epidemiology , Fever/epidemiology , Humans , Thrombocytopenia/epidemiology
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