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1.
Communications Biology ; 5(1):1004, 2022.
Article in English | MEDLINE | ID: covidwho-2036925

ABSTRACT

Wearing a face mask has become essential to contain the spread of COVID-19 and has become mandatory when collecting fMRI data at most research institutions. Here, we investigate the effects of wearing a surgical mask on fMRI data in n = 37 healthy participants. Activations during finger tapping, emotional face matching, working memory tasks, and rest were examined. Preliminary fMRI analyses show that despite the different mask states, resting-state signals and task activations were relatively similar. Resting-state functional connectivity showed negligible attenuation patterns in mask-on compared with mask-off. Task-based ROI analysis also demonstrated no significant difference between the two mask states under each contrast investigated. Notwithstanding the overall insignificant effects, these results indicate that wearing a face mask during fMRI has little to no significant effect on resting-state and task activations.

2.
Frontiers in Immunology ; 13:972499, 2022.
Article in English | MEDLINE | ID: covidwho-2029965

ABSTRACT

Porcine Deltacoronavirus (PDCoV), an enveloped positive-strand RNA virus that causes respiratory and gastrointestinal diseases, is widely spread worldwide, but there is no effective drug or vaccine against it. This study investigated the optimal Selenium Nano-Particles (SeNPs) addition concentration (2 - 10 mug/mL) and the mechanism of PDCoV effect on ST (Swine Testis) cell apoptosis, the antagonistic effect of SeNPs on PDCoV. The results indicated that 4 mug/mL SeNPs significantly decreased PDCoV replication on ST cells. SeNPs relieved PDCoV-induced mitochondrial division and antagonized PDCoV-induced apoptosis via decreasing Cyt C release and Caspase 9 and Caspase 3 activation. The above results provided an idea and experimental basis associated with anti-PDCoV drug development and clinical use.

3.
Int J Public Health ; 67:1604979, 2022.
Article in English | PubMed | ID: covidwho-2023043

ABSTRACT

Objectives: The study aimed at analyzing the prevalence of five psychological outcomes (depression, anxiety, stress, post-traumatic stress disorder (PTSD), and suicidal ideation) among Chinese healthcare workers (HCWs), and measured the total possible negative psychological impact 1 year after the COVID-19 initial outbreak. Methods: A cross-sectional nationwide multi-center study was performed between November 2020 and March 2021 in China. A self-report questionnaire was applied, and three psychological scales were used. Binary logistic regression was performed to analyze the risk factors associated with each psychological outcome. Results: The findings demonstrated that the COVID-19 pandemic had a negative psychological impact on HCWs, which was still evident 1 year after the initial outbreak. Nurses showed higher depression and anxiety than other HCWs. Female gender, passive coping, long working hours, having a chronic disease, and experiencing violence, among other factors, were all risk factors for psychological impairment. Conclusion: Developing and promoting programs to improve mental health among HCWs, and identifying those who might need psychological support is still relevant 1 year after the initial outbreak.

4.
Front Med (Lausanne) ; 9:988133, 2022.
Article in English | PubMed | ID: covidwho-2022785

ABSTRACT

PURPOSE: The purpose of this study was to investigate the hotspots and research trends of ophthalmology research. METHOD: Ophthalmology research literature published between 2017 and 2021 was obtained in the Web of Science Core Collection database. The bibliometric analysis and network visualization were performed with the VOSviewer and CiteSpace. Publication-related information, including publication volume, citation counts, countries, journals, keywords, subject categories, and publication time, was analyzed. RESULTS: A total of 10,469 included ophthalmology publications had been cited a total of 7,995 times during the past 5 years. The top countries and journals for the number of publications were the United States and the Ophthalmology. The top 25 global high-impact documents had been identified using the citation ranking. Keyword co-occurrence analysis showed that the hotspots in ophthalmology research were epidemiological characteristics and treatment modalities of ocular diseases, artificial intelligence and fundus imaging technology, COVID-19-related telemedicine, and screening and prevention of ocular diseases. Keyword burst analysis revealed that "neural network," "pharmacokinetics," "geographic atrophy," "implementation," "variability," "adverse events," "automated detection," and "retinal images" were the research trends of research in the field of ophthalmology through 2021. The analysis of the subject categories demonstrated the close cooperation relationships that existed between different subject categories, and collaborations with non-ophthalmology-related subject categories were increasing over time in the field of ophthalmology research. CONCLUSIONS: The hotspots in ophthalmology research were epidemiology, prevention, screening, and treatment of ocular diseases, as well as artificial intelligence and fundus imaging technology and telemedicine. Research trends in ophthalmology research were artificial intelligence, drug development, and fundus diseases. Knowledge from non-ophthalmology fields is likely to be more involved in ophthalmology research.

5.
Dig Dis Sci ; : 1-17, 2022.
Article in English | PubMed | ID: covidwho-2014217

ABSTRACT

BACKGROUND: The COVID-19 pandemic has brought new problems to patients infected with hepatitis B virus (HBV). AIM: We aim to know the effects of HBV infection on patients with COVID-19. METHODS: We searched PubMed, Embase, and Web of Science for data and utilized Stata 14.0 software for this meta-analysis with a random-effects model. This paper was conducted in alignment with the preferred reporting items for systematic review and meta-analysis (PRISMA) guideline. RESULTS: In total, 37,696 patients were divided into two groups: 2591 COVID-19 patients infected with HBV in the experimental group and 35,105 COVID-19 patients not infected with HBV in the control group. Our study showed that the in-hospital mortality of the experimental group was significant higher than that of the control group (OR = 2.04, 95% CI 1.49-2.79). We also found that COVID-19 patients infected with HBV were more likely to develop severe disease (OR = 1.90, 95% CI 1.32-2.73) than COVID-19 patients not infected with HBV. Upon measuring alanine aminotransferase (SMD = 0.62, 95% CI 0.25-0.98), aspartate aminotransferase (SMD = 0.60, 95% CI 0.30-0.91), total bilirubin (SMD = 0.45, 95% CI 0.23-0.67), direct bilirubin (SMD = 0.36, 95% CI 0.24-0.47), lactate dehydrogenase (SMD = 0.32, 95% CI 0.18-0.47), we found that HBV infection led to significantly higher laboratory results in COVID-19 patients. CONCLUSION: COVID-19 patients infected with HBV should receive more attention, and special attention should be given to various liver function indices during treatment.

6.
Annals of Translational Medicine ; 0(0):0-0, 2022.
Article in English | Web of Science | ID: covidwho-1998118

ABSTRACT

Background: Artificial intelligence (AI) has been extensively applied in the individualized diagnosis and treatment of critical illness, and numerous studies have been published on this topic. Therefore, a bibliometric analysis of these publications should be performed to provide a direction of hot topics and future research trends. Methods: A bibliometric analysis was performed on the research articles to identify the hot topics and any unsolved issues regarding the use of AI in individualized diagnosis and treatment of critical illness. Articles published from January 2011 to December 2021 were retrieved from the Web of Science (WOS) core collection database for bibliometric analysis, and a cross-sectional analysis of the relevant studies that had been registered at ClinicalTrials.gov was also conducted.Results: The number of articles published showed an annually increasing trend, with a worldwide geographic distribution over the past decade. Ultimately, 427 research articles were included in the bibliometric analysis. The relevant articles were divided into four separate clusters that focused on AI application aspects, prediction model establishment, coronavirus disease 2019 (COVID-19) treatment and outcome assessments, respectively. "Machine learning" was the most frequent keyword (147 occurrences, 165 links, and 395 total link strengths) followed by "risk", "models", and "mortality". With 205 articles, the United States of America (USA) had interacted the most with other countries (20 links, and 94 total link strength), while the domestic research institutes in China had infrequently collaborated with others. Approximately 130 trials focusing on the application of AI in the intensive care unit (ICU) and emergency department (ED) had been registered at ClinicalTrial.gov, and most of them (n=71, 54.6%) were interventional. The main research objectives of these trials were to provide decision making assistance and establish prediction models. However, only 3.8% (5 trials) of them had reached exact conclusions which favored the application of AI.Conclusions: The application of AI has raised great interest in critical illness and has mainly been focused on decision making assistance and prediction model establishment. Cooperation between agencies engaged in AI research needs to be strengthened. An increasing number of trials have been registered at ClinicalTrial.gov, and the results of them are promising.

7.
Psychological Medicine ; 2022.
Article in English | Scopus | ID: covidwho-1991457

ABSTRACT

Background: Persistent psychological distress associated with the COVID-19 pandemic has been well documented. This study aimed to identify pre-COVID brain functional connectome that predicts pandemic-related distress symptoms among young adults. Methods: Baseline neuroimaging studies and assessment of general distress using the Depression, Anxiety and Stress Scale were performed with 100 healthy individuals prior to wide recognition of the health risks associated with the emergence of COVID-19. They were recontacted for the Impact of Event Scale-Revised and the Posttraumatic Stress Disorder Checklist at the period of community-level outbreaks, and for follow-up distress evaluation again one year later. We employed the network-based statistic approach to identify connectome that predicted the increase of distress based on 136-region-parcellation with assigned network membership. Predictive performance of connectome features and causal relations were examined by cross-validation and mediation analyses. Results: The connectome features that predicted emergence of distress after COVID contained 70 neural connections. Most within-network connections were located in the default mode network (DMN), and affective network-DMN and dorsal attention network-DMN links largely constituted between-network pairs. The hippocampus emerged as the most critical hub region. Predictive models of the connectome remained robust in cross-validation. Mediation analyses demonstrated that COVID-related posttraumatic stress partially explained the correlation of connectome to the development of general distress. Conclusions: Brain functional connectome may fingerprint individuals with vulnerability to psychological distress associated with the COVID pandemic. Individuals with brain neuromarkers may benefit from corresponding interventions to reduce the risk or severity of distress related to fear of COVID-related challenges. © 2022 Cambridge University Press. All rights reserved.

8.
Journal of Enterprise Information Management ; : 27, 2022.
Article in English | Web of Science | ID: covidwho-1985375

ABSTRACT

Purpose Building supply chain resilience is increasingly recognized as an effective strategy to deal with supply chain challenges, risks and disruptions. Nevertheless, it remains unclear how to build supply chain resilience and whether supply chain resilience could achieve a competitive advantage. Design/methodology/approach By analyzing the data collected from 216 firms in China, the current study empirically examines how information technology (IT) capability and supply chain collaboration affect different forms of supply chain resilience (external resilience and internal resilience) and examines the performance implications of these two forms of supply chain resilience. Findings Results show that IT capability is positively related to external resilience, whereas supply chain collaboration is positively related to internal resilience. The combination of IT capability and supply chain collaboration is positively related to external resilience. In addition, internal resilience is positively related to firm performance. Research limitations/implications This study used only cross-sectional data from China for hypothesis testing. Future studies could utilise longitudinal data and research other countries/regions. Practical implications The findings systematically assess how IT capability and supply chain collaboration contribute to supply chain resilience and firm performance. The results provide a benchmark of supply chain resilience improvement that can be expected from IT capability and supply chain collaboration. Originality/value The study findings advance the understanding of supply chain resilience and provide practical implications for supply chain managers.

9.
Discrete and Continuous Dynamical Systems-Series B ; 0(0):35, 2022.
Article in English | Web of Science | ID: covidwho-1979473

ABSTRACT

To investigate the impact of the number of hospital beds on the control of infectious diseases and help allocate the limited medical resources in a region, a SEIHR epidemic model including exposed and hospitalized classes is established. Different from available models, the hospitalization rate is expressed as a function of the number of empty beds. The existence and stability of the equilibria are analyzed, and it is proved that the system undergoes backward bifurcation, Hopf bifurcation, and Bogdanov-Takens bifurcation of codimension 2 under certain conditions by using the center manifold theory and normal form theory. In particular, our results show that there is a threshold value for the capacity of hospital beds in a region. If the capacity of hospital beds is lower than this threshold value, there will be a backward bifurcation, which means that even if the basic reproduction number, R0, is less than unity, it is not enough to prevent the outbreaks. Before taking disease control measures, one should compare the number of beds with the threshold value to avoid misjudgment and try to increase the capacity of hospital beds above this threshold value. The method to estimate the threshold value is also given. In addition, the impacts of the duration of the exposed period on the basic reproduction number and disease transmission are investigated.

10.
Mathematical Biosciences and Engineering ; 19(10):10361-10373, 2022.
Article in English | Scopus | ID: covidwho-1974986

ABSTRACT

The COVID-19 pandemic caused multiple waves of mortality in South Africa, where three genetic variants of SARS-COV-2 and their ancestral strain dominated consecutively. State-of-the-art mathematical modeling approach was used to estimate the time-varying transmissibility of SARS-COV-2 and the relative transmissibility of Beta, Delta, and Omicron variants. The transmissibility of the three variants were about 73%, 87%, and 276% higher than their preceding variants. To the best of our knowledge, our model is the first simple model that can simulate multiple mortality waves and three variants' replacements in South Africa. The transmissibility of the Omicron variant is substantially higher than that of previous variants. © 2022 American Institute of Mathematical Sciences. All rights reserved.

11.
Israeli Journal of Aquaculture - Bamidgeh ; 74, 2022.
Article in English | Scopus | ID: covidwho-1965181

ABSTRACT

We analyzed the supply and demand for tilapia in China while assessing the future developmental trends. China has become the world’s largest producer, exporter, and consumer of tilapia. China entered a period of rapid aquaculture development in the 1990s, and the tilapia supply has increased yearly. Tilapia products are mainly supplied to the international market, especially in the US. The global market for the Chinese tilapia has grown dramatically, but a downward trend occurred in 2019–2020. The Chinese domestic market demand is relatively stable, and even the COVID-19 epidemic did not significantly impact the supply and demand of tilapia. Internationally, it is expected that the demand for tilapia will decline considerably in the near future. However, this decline could be alleviated after the impact of the COVID-19 epidemic passes, and increasing demand will resume. The increased supply of Chinese tilapia might slow down or even decrease due to market uncertainty, the increasing constraints on natural resources, and the Chinese government's requirements for high-quality aquaculture environments. © 2022, Israeli Journal of Aquaculture - Bamidgeh. All rights reserved.

12.
10th International Conference on Bioinformatics and Computational Biology, ICBCB 2022 ; : 148-153, 2022.
Article in English | Scopus | ID: covidwho-1961389

ABSTRACT

Since the COVID-19 pandemic broke out in early 2020, the global community has been living in fear, stress, and isolation. The COVID-19 vaccine might provide a solution to the ongoing global crisis. This study seeks to monitor the trends of depression that have been discussed on Twitter before and after the COVID-19 vaccine was released and explores whether such differences were universal or geographical. Specifically, this paper investigates the variations in sentiment in different geographic regions and the change of sentiments before and after the vaccine release. We collect tweets containing keywords "COVID-19"and 'depression' and rely on releasing date of the COVID-19 vaccine as a division point. The experiment results reveal that topics related to depression varied significantly across different regions before and after the COVID-19 vaccine was released. For example, tweets posted in America are focused on social lockdown and infection with COVID-19 when referring to depression. In contrast, tweets from European countries discuss more typical depression symptoms and Brexit. The tweets posted in Asian, African, and Oceanian contain more discussions on stress. Our analysis further indicates that Asian users' stress is mainly from the study while Oceanian and African users' stress is primarily from family. Another interesting finding in our paper is that tweets show a common desire for normal social activities after the vaccine release, regardless of geographical locations. © 2022 IEEE.

13.
Atmosphere ; 13(5), 2022.
Article in English | Scopus | ID: covidwho-1933965

ABSTRACT

Mass suspension of anthropogenic activities is extremely rare, the quarantine due to the coronavirus disease 2019 (COVID-19) represents a natural experiment to investigate the impact of anthropogenic activities on air quality. The mitigation of air pollution during the COVID-19 lock-down has been reported from a global perspective;however, the air pollution levels vary in different regions. This study initiated a novel synthesis of multiple-year satellite observations, national ground measurements towards SO2, NO2 and O3 and meteorological conditions to evaluate the impact of the COVID-19 lockdown in Beihai, a specific city in a less developed area in southwest China, to reveal the potential implications of control strategies for air pollution. The levels of the major air pollutants during the COVID-19 lockdown (LP) and during the same period of previous years (SP) were compared and a series of statistical tools were applied to analyze the sources of air pollution in Beihai. The results show that air pollutant levels decreased with substantial diversity during the LP. Satellite-retrieved NO2 and SO2 levels during the LP decreased by 5.26% and 22.06%, while NO2, SO2, PM2.5 and PM10 from ground measurements during the LP were 25.6%, 2.7%, 22.2% and 22.2% lower than during SP, respectively. Ground measured SO2 concentrations during the LP were only 2.7% lower than during the SP, which may be attributed to uninterrupted essential industrial activ-ities, such as power plants. Polar plots analysis shows that NO2 concentrations were strongly associated with local emission sources, such as automobiles and local industry. Additionally, the much lower levels of NO2 concentrations during the LP and the absence of an evening peak may highlight the significant impact of the traffic sector on NO2. The decrease in daily mean O3 concentrations during the LP may be associated with the reduction in NO2 concentrations. Indications in this study could be beneficial for the formulation of atmospheric protection policies. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.

14.
IEEE Transactions on Affective Computing ; : 1-15, 2022.
Article in English | Scopus | ID: covidwho-1922769

ABSTRACT

The long-lasting global pandemic of Coronavirus disease 2019 (COVID-19) has changed our daily life in many ways and put heavy burden on our mental health. Having a predictive model of negative emotions during COVID-19 is of great importance for identifying potential risky population. To establish a neural predictive model achieving both good interpretability and predictivity, we have utilized a large-scale (n =542) longitudinal dataset, alongside two independent samples for external validation. We built a predictive model based on psychologically meaningful resting state neural activities. The whole-brain resting-state neural activity and social-psychological profile of the subjects were obtained from Sept. to Dec. 2019 (Time 1). Their negative emotions were tracked and re-assessed twice, on Feb 22 (Time 2) and Apr 24 (Time 3), 2020, respectively. We first applied canonical correlation analysis on both the neural profiles and psychological profiles collected on Time 1, this step selects only the psychological meaningful neural patterns for later model construction. We then trained the neural predictive model using those identified features on data obtained on Time 2. It achieved a good prediction performance (r =0.44, p =8.13 ×10-27). The two most important neural predictors are associated with self-control and social interaction. This study established an effective neural prediction model of negative emotions, achieving good interpretability and predictivity. It will be useful for identifying potential risky population of emotional disorders related to COVID-19. IEEE

16.
Antibiotiki i Khimioterapiya ; 66(3-4):40-48, 2021.
Article in Russian | EMBASE | ID: covidwho-1870317

ABSTRACT

Objective. To evaluate the effect of sodium meglumine succinate on the severity of the systemic inflammatory response syndrome when used in complex therapy in patients with severe COVID-19. Material and Methods. The clinical and laboratory data of 12 patients with the diagnosis & Novel coronavirus infection COVID-19 complicated by community-acquired bilateral polysegmental interstitial pneumonia» were analyzed. All patients underwent intensive therapy with a limited volume of water load in the intensive care unit in accordance with the recommendations of the Ministry of Health of the Russian Federation. Seven patients (observation group) received a polyelectrolyte solution containing meglumine sodium succinate (Reamberin) as part of the therapy at a daily dose of 5 ml/kg during the entire period of stay in theICU (3-10 days).The control group included 5 patients who received a similar volume of a conventional polyelectrolyte solution containing no metabolically active substrates. The study was pilot in nature due to the small number of patients. The laboratory parameters of arterial and venous blood were measured at the following stages: 1) upon admission to the ICU;2) 2-4 hours after the completion of Reamberin infusion;3)8-12 hours after drug administration;4) 24 hours after the start of intensive care. Mor-tality rate and the incidence of thrombotic complications in the groups were assessed on the 28th day of observation. The pres¬ence of the therapeutic intervention effect was established using multivariate analysis of variance (MANOVA). Results. A positive effect of the study drug on the severity of systemic inflammatory response syndrome (SIRS) against the background of ongoing etiotropic therapy was noted. Efficiency criteria were the correction of hyperfibrinogenemia, nor-malization of the platelet count, decrease in the level of C-reactive protein, ferritin, and leukocytosis. A significant decrease in the frequency of thromboembolic events was observed within 28 days of treatment, as well as a reduction in the length of time the patients spent in the ICU. Conclusion. Based on the results of the pilot study, it can be assumed that the antihypoxic and antiradical effects of the drug contribute to the reduction of pulmonary and systemic endotheliitis, which is characteristic of severe forms of the disease and, as a result, inhibits the development of the systemic inflammatory response syndrome. The data obtained can serve as a basis for further in-depth studies.

17.
Annals of Behavioral Medicine ; 56(SUPP 1):S156-S156, 2022.
Article in English | Web of Science | ID: covidwho-1849468
18.
2022 IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2022 ; : 667-670, 2022.
Article in English | Scopus | ID: covidwho-1831760

ABSTRACT

Several problems were found in the attempt and practice of bilingual teaching in Food safety, mainly including inconsistent foreign language quality of students, messy textbooks and teaching content, inadequate bilingual ability of teachers and lack of supervision of English auxiliary teachers, lack of online network construction, and single teaching methods and other issues. Through summing up experience, it is found that a series of methods, such as combining social hot spots and conducting scientific research hot spots introduction teaching, rationally using English textbooks and correspondingly constructing teaching content, can solve the above problems and promote English teaching of Food safety. During pandemic (COVID-19/Corona Virus Disease 2019) period, we boldly carried out bilingual and online teaching attempts, this time also carried out a summary, hoping to provide some guidance for the teaching reform of Food safety © 2022 IEEE.

19.
Embase; 2022.
Preprint in English | EMBASE | ID: ppcovidwho-334973

ABSTRACT

It is becoming increasingly clear that individuals recovered from acute coronavirus disease 2019 (COVID-19) can develop into long-term sequelae (post-acute sequala of SARS-CoV-2 infection, PACS). While antibody response kinetics against viral particles is well studied in natural infection and vaccine, the molecular mechanisms governing disease formation remain elusive. We investigated plasma and saliva samples from COVID-19 and healthy control subjects to understand early immune responses globally after exposure to the virus. Antibody analyses showed robust IgA and IgG responses, neutralizing functions to the SARS-CoV-2, and positive correlations between matched plasma and saliva fluids. Shotgun proteomics revealed persistent inflammatory patterns in convalescent samples including dysfunction of neutrophil-fibrinogen axis, and dysregulated immune and clotting functions. Our study suggests saliva as fluid to monitor serology and immune functions to detect early and chronic signs of disease development. Further delineation of the pathophysiology in saliva may lead to discovery of novel biomarkers and therapeutic targets to patients at risk to develop PASC and chronic conditions.

20.
Journal of Environmental Sciences (China) ; 125:603-615, 2023.
Article in English | Scopus | ID: covidwho-1783484

ABSTRACT

Wuhan Tianhe International Airport (WUH) was suspended to contain the spread of COVID-19, while Shanghai Hongqiao International Airport (SHA) saw a tremendous flight reduction. Closure of a major international airport is extremely rare and thus represents a unique opportunity to straightforwardly observe the impact of airport emissions on local air quality. In this study, a series of statistical tools were applied to analyze the variations in air pollutant levels in the vicinity of WUH and SHA. The results of bivariate polar plots show that airport SHA and WUH are a major source of nitrogen oxides. NOx, NO2 and NO diminished by 55.8%, 44.1%, 76.9%, and 40.4%, 33.3% and 59.4% during the COVID-19 lockdown compared to those in the same period of 2018 and 2019, under a reduction in aircraft activities by 58.6% and 61.4%. The concentration of NO2, SO2 and PM2.5 decreased by 77.3%, 8.2%, 29.5%, right after the closure of airport WUH on 23 January 2020. The average concentrations of NO, NO2 and NOx scatter plots at downwind of SHA after the lockdown were 78.0%, 47.9%, 57.4% and 62.3%, 34.8%, 41.8% lower than those during the same period in 2018 and 2019. However, a significant increase in O3 levels by 50.0% and 25.9% at WUH and SHA was observed, respectively. These results evidently show decreased nitrogen oxides concentrations in the airport vicinity due to reduced aircraft activities, while amplified O3 pollution due to a lower titration by NO under strong reduction in NOx emissions. © 2022

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