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1.
Chinese Traditional and Herbal Drugs ; JOUR(20):6573-6582, 53.
Article in Chinese | Scopus | ID: covidwho-2100334

ABSTRACT

In recent years, with the frequent occurrence of viral diseases accompanied by high morbidity and mortality rates, there has been an increasing awareness of importance of antiviral drugs research. Traditional Chinese medicine contain biologically structurally diverse bioactive substances that provide important template structures for pharmaceutical research. Because of its novelty, multicomponent and multi-target characteristics, it is a valuable source for new drug development. The antiviral mechanisms of active components of traditional Chinese medicines include inhibition of viral replication, block binding of virus with receptor, directly killing virus, enhancement of the immune system and inhibition of cytokines/chemokines responses, etc. The active components of traditional Chinese medicine with antiviral active ingredients based on the mechanism of antiviral action were reviewed in this paper, in order to provide a basis for development of antiviral natural drugs to cope with the virus epidemic including the new variant of SARS-CoV-2 and other virus outbreaks that may occur in the future. © 2022 Editorial Office of Chinese Traditional and Herbal Drugs. All rights reserved.

2.
31st International Conference on Artificial Neural Networks, ICANN 2022 ; 13532 LNCS:781-792, 2022.
Article in English | Scopus | ID: covidwho-2048133

ABSTRACT

Medical image segmentation is one of the most fundamental tasks concerning medical information analysis. Various solutions have been proposed so far, including many deep learning-based techniques, such as U-Net, FC-DenseNet, etc. However, high-precision medical image segmentation remains a highly challenging task due to the existence of inherent magnification and distortion in medical images as well as the presence of lesions with similar density to normal tissues. In this paper, we propose TFCNs (Transformers for Fully Convolutional denseNets) to tackle the problem by introducing ResLinear-Transformer (RL-Transformer) and Convolutional Linear Attention Block (CLAB) to FC-DenseNet. TFCNs is not only able to utilize more latent information from the CT images for feature extraction, but also can capture and disseminate semantic features and filter non-semantic features more effectively through the CLAB module. Our experimental results show that TFCNs can achieve state-of-the-art performance with dice scores of 83.72% on the Synapse dataset. In addition, we evaluate the robustness of TFCNs for lesion area effects on the COVID-19 public datasets. The Python code will be made publicly available on https://github.com/HUANGLIZI/TFCNs. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

3.
Energy ; 256, 2022.
Article in English | Web of Science | ID: covidwho-2041726

ABSTRACT

The achievement of China's carbon dioxide (CO2) emission reduction target is of great significance in the face of global climate change. Accurate identification of key factors that affect CO2 emissions can provide theoretical support to policymakers when designing related policies. Compared to the traditional method, the generalized Divisia index method (GDIM) can capture the influence of multiple scale factors on carbon emissions, providing new tools for studying the decomposition of carbon emissions. The article proposed a GDIM-based decomposition method to analyze the drivers that influence CO2 emissions in China from 2000 to 2017. The results indicate that investment activity is the primary element in promoting China's carbon emissions, followed by energy use and economic activities. On the contrary, investment carbon intensity is the vital inhibitory factor, followed by GDP carbon intensity. Specifically, the positive driving force of investment and energy use is gradually weakening, while the contribution of economic activities is continuously strengthening. The effectiveness of carbon emission reduction in the Northeast, East, and Southwest is actively promoting China's carbon emission reduction, while the effectiveness of CO2 emission reduction in the Northwest is not performing well. The findings provide support and reference for carbon emission control in China. (C) 2022 Elsevier Ltd. All rights reserved.

4.
Chinese Journal of Evidence-Based Medicine ; 22(8):932-947, 2022.
Article in Chinese | EMBASE | ID: covidwho-2006473

ABSTRACT

Objective To evaluate the evidence of the experience with medical sewage treatment procedures in medical institutions in China. Methods Databases including CNKI, WanFang Data, PubMed, Web of Science, and EBSCO were electronically searched to collect studies on the medical sewage treatment process, flow, and specifications in medical institutions in China. We used the quality evaluation system to classify and grade the experiences based on the principles and methods of evidence-based science and performed a descriptive analysis. Results After the SARS pandemic in 2003, China systematically established and standardized the technical criteria of medical sewage treatment and discharge. Moreover, a prevention system for the epidemic using medical sewage was constructed, which guaranteed that the quality of medical sewage treatment and discharge would meet the criteria and protect the citizens, and the technical specifications of medical sewage treatment would progress and increase strictly. At present, medical sewage treatment in medical institutions in China was based on mechanical and biological methods, and disinfection was mainly performed using chlorine and its compounds, ozone, and ultraviolet light. Conclusion The COVID-19 pandemic requires a higher quality of medical sewage treatment and discharge criteria for medical institutions in China. To meet these criteria, all medical institutions in China should check, replace, and update their old facilities;strengthen personnel training and effectively ensure the quality of medical sewage treatment.

5.
The International journal of pharmacy practice ; 30(Suppl 1):i38-i38, 2022.
Article in English | EuropePMC | ID: covidwho-1999525

ABSTRACT

Introduction Due to propellants, metered dose inhalers (pMDIs) have a higher carbon footprint than low carbon footprint inhalers (LCFIs), such as dry powder or soft mist inhalers (1). Consequently, pMDIs contribute 3.5% of the NHS’s CO2 equivalent emissions (2). Local and national guidelines (NICE, British Thoracic Society) have attempted to increase use of LCFIs, but their effects and factors influencing success are unknown. Aim To investigate temporal and geographical variation in LCFI dispensing in England over five years. Methods Clinical commissioning group (CCG) dispensed items (March 2016-February 2021) were obtained from openprescribing.net for five classes of inhaler where a choice between pMDIs and LCFIs is available: short-acting beta-agonists (SABAs), long-acting beta-agonists (LABAs), inhaled corticosteroids (ICS), ICS plus LABA inhalers (ICS/LABA) and ICS/LABA plus long-acting muscarinic antagonist inhalers (ICS/LABA/LAMA). CCG population age profiles were obtained from the Office for National Statistics. CCG emergency hospital admission and mortality rates were obtained from Public Health England. CCG formularies and guidelines were reviewed to identify where guidance is available to prescribers. To control for total inhaler dispensing, the key measure used is the %LCFI: the number of LCFI items dispensed relative to the total number of pMDI and LCFI items. Multivariate regression models were used to investigate geographical variation. Results The total annual %LCFI increased from 19.5% to 26.3% over the study period. This was driven by the introduction of ICS/LABA/LAMA inhalers in 2018, as %LCFI decreased for SABA, ICS and ICS/LABA inhalers. %LCFI varied between classes. In the final year, it ranged from 6% for both SABA and ICS inhalers, to 41.2% and 43.9% for ICS/LABA and ICS/LABA/LAMA inhalers, respectively. Interestingly, the cost per item for ICS/LABA and ICS/LABA/LAMA inhalers was similar for both pMDIs and LCFIs, but for SABA and ICS inhalers LCFIs were more expensive. %LCFI in the final year varied between CCGs (10.7% to 30.9%). The North West, and Birmingham and London areas had consistently higher %LCFI for all classes. For SABA and ICS inhalers, both the presence of advice on climate change in CCG guidelines or formularies, and greater CCG asthma prevalence, were significantly associated with higher %LCFI (p<0.05). The proportion of CCG population <15 years had a significant negative association with %LCFI for ICS and ICS/LABA inhalers (p<0.05). There were no clinically significant associations between %LCFI and either emergency hospital admission or mortality rates. Conclusion Current initiatives have not been successful in increasing the use of LCFIs, indicating limited implementation of guidelines for unknown reasons. Further action is required to reduce the carbon footprint of inhaler prescribing. Actions to address the financial disincentives to LCFI prescribing, CCG leadership (e.g. guidelines) and the appropriate use of LCFI in young people should be considered. Research into facilitators and barriers to LCFI use would support this. An important limitation is the use of dispensed items data rather than the number of inhalers, although there is no evidence that the number of inhalers per item varies between pMDIs and LCFIs. In addition, the Covid-19 pandemic disrupted prescribing patterns and long-term NHS projects. References (1) Wilkinson AJK, Braggins R, Steinbach I, Smith K. Costs of switching to low global warming potential inhalers. An economic and carbon footprint analysis of NHS prescription data in England. BMJ Open. 2019;9:e028763. (2) Environmental Audit Committee. UK progress on reducing F-Gas emissions inquiry: Fifth report of session 2017-19. London (UK): House of Commons Environmental Audit Committee;25 April 2018. Available from https://publications.parliament.uk/pa/cm201719/cmselect/cmenvaud/469/469.pdf: [Accessed 27 September 2021].

6.
Journal of Xi'an Jiaotong University (Medical Sciences) ; 43(4):483-488, 2022.
Article in Chinese | EMBASE | ID: covidwho-1969734

ABSTRACT

Objective: To analyze the mental health status and influencing factors of China medical team (CMT) members in Africa during COVID-19 pandemic. Methods: From July 2021 to August 2021, 72 members of the 8th CMT in Malawi, the 36th CMT in Sudan and the 22nd CMT in Zambia were tested by 12-item General Health Questionnaire (GHQ-12), Generalized Anxiety Disorder-7 (GAD-7), and Patient Health Questionnaire-9(PHQ-9), general information form and influencing factors form. Results: The results of GHQ-12 were positive for 33.3% (24/72) of the CMT members. 51.4% (37/72) of the CMT members showed different levels of anxiety: 40.3% (29/72) of them had mild anxiety, 8.3% (6/72) of them had moderate anxiety, and 2.8% (2/72) of them had severe anxiety. 52.8% (38/72) of the CMT members had different degrees of depression: 34.7% (25/72) of them had mild depression, 11.1% (8/72) of them had moderate depression, 4.2% (3/72) of them had moderate-severe depression, and 2.8% (2/72) of them had severe depression. The CMT members who contacted with COVID-19 patients got significantly high scores of GHQ-12, GAD-7 and PHQ-9 (P<0.05) compared to those who did not have contact with COVID-19 patients. And CMT members who did not adapt to the local social life got significantly higher scores than those who adapted to the local social life (P<0.05). These factors were the main factors affecting the mental health of the CMT members. Conclusion: During COVID-19, the psychological pressure of CMT members was increased significantly, and both the incidence and severity of anxiety and depression were increased. Paying attention to and improving CMT members' mental health status can ensure the smooth development of medical aid to Africa.

7.
14th IEEE International Conference on Computer Research and Development, ICCRD 2022 ; : 12-15, 2022.
Article in English | Scopus | ID: covidwho-1794837

ABSTRACT

During this nearly two-years-long pandemic period, the COVID-19 impacts people's lives dramatically, many people were forced to stay at home by the government's lockdown policy, and they also need to work and study at home. Therefore, there is an equivalent impact on networks as people are more dependent on them. But there are only a limited number of research has been done in this intersection area between the pandemic and networks. So, we want to fill this gap. In this paper, we will study the mobile network data from U.S. Federal Communications Commission (FCC) and COVID-19 cases data from the U.S. centers for disease control and prevention (CDC), then use machine learning to investigate the relationship between mobile network data and COVID-19 cases. We will discuss other related works, which used other methods or investigated this topic in other regions, then we will introduce our machine learning methods, experiments and give the conclusion. © 2022 IEEE.

8.
MEDLINE; 2021.
Preprint in English | MEDLINE | ID: ppcovidwho-329655

ABSTRACT

Recently approved vaccines have already shown remarkable protection in limiting SARS-CoV-2 associated disease. However, immunologic mechanism(s) of protection, as well as how boosting alters immunity to wildtype and newly emerging strains, remain incompletely understood. Here we deeply profiled the humoral immune response in a cohort of non-human primates immunized with a stable recombinant full-length SARS-CoV-2 spike (S) glycoprotein (NVX-CoV2373) at two dose levels, administered as a single or two-dose regimen with a saponin-based adjuvant Matrix-M TM. While antigen dose had some effect on Fc-effector profiles, both antigen dose and boosting significantly altered overall titers, neutralization and Fc-effector profiles, driving unique vaccine-induced antibody fingerprints. Combined differences in antibody effector functions and neutralization were strongly associated with distinct levels of protection in the upper and lower respiratory tract, pointing to the presence of combined, but distinct, compartment-specific neutralization and Fc-mechanisms as key determinants of protective immunity against infection. Moreover, NVX-CoV2373 elicited antibodies functionally target emerging SARS-CoV-2 variants, collectively pointing to the critical collaborative role for Fab and Fc in driving maximal protection against SARS-CoV-2. Collectively, the data presented here suggest that a single dose may prevent disease, but that two doses may be essential to block further transmission of SARS-CoV-2 and emerging variants. Highlights: NVX-CoV2373 subunit vaccine elicits receptor blocking, virus neutralizing antibodies, and Fc-effector functional antibodies. The vaccine protects against respiratory tract infection and virus shedding in non-human primates (NHPs). Both neutralizing and Fc-effector functions contribute to protection, potentially through different mechanisms in the upper and lower respiratory tract. Both macaque and human vaccine-induced antibodies exhibit altered Fc-receptor binding to emerging mutants.

9.
International Symposium on Educational Technology (ISET) ; : 53-57, 2021.
Article in English | Web of Science | ID: covidwho-1700378

ABSTRACT

By the natural parents are the essentials of educating young generations. In China during Covid-19, especially the lock-down period, parents companied children at home and observed their learning behavior. Parental acceptance of online teaming can offer a valuable referencefor thefurther adaptation of online k-12 education. This study used an integrated model of technology acceptance and expected confirmation, demonstrating Parental acceptance by three variables: acceptance, satisfaction, and continuance intention. Moreover, an influential factor model of Parental acceptance was built, which including teacher support, perceive autonomy and interactivity, technology preference and experience. Measurement and structural data models are verified by using partial least squares regression (PLS), which supports all the hypotheses empirically.

10.
International Symposium on Educational Technology (ISET) ; : 96-100, 2021.
Article in English | Web of Science | ID: covidwho-1699098

ABSTRACT

In the beginning of 2020, COVID-19 pandemic emerged in many regions of China, and the spring semester of primary and middle schools was postponed At the call of "Suspension of Classes but not Learning" by MOE, all educational institutes adopted the online learning methods. However, the home-based online learning lacks teacher supervision, peer support, classroom environment constraints. These intensify students' attention difficulty when compared with face-to-face learning in the classroom, which makes students' learning engagement more important to ensure the learning effect. According to online focus group interviews with the education experts and K-12 teachers respectively, the researchers found out some possible influencing factors to K-12 students' online learning engagement: perceived teacher involvement, perceived parental involvement, students' self-discipline, and student emotion. Therefore, this study proposes a prediction model from the above four aspects. By using multivariate linear regression analysis and variance analysis, this study finds: (1) Perceived teacher involvement, perceived parent support, student selfdiscipline and student emotion all have significant positive effects on online learning engagement. (2) There are significant differences in students' online learning engagement for different learning stages and different network environments at home Students' online learning engagement has no significant difference between urban and rural areas.

11.
Journal of Vascular Access ; 22(6):10NP-11NP, 2021.
Article in English | EMBASE | ID: covidwho-1582630

ABSTRACT

Background: The coronavirus disease 2019 (COVID-19) struck China from late 2019 before its rapid spread across the country. Tianjin, as one of the largest cites in the north of China, reported a number of confirmed COVID-19 cases shortly after its outbreak in Wuhan province. After the pandemic was brought under control in May, strict control measures were put in place as routine to prevent cross-infection, which contributed to the change in vascular access practice. Therefore, a retrospective study was conducted to evaluate the impact of COVID-19 on vascular access in non-hot-spot region, north China. Methods: In this multicenter cross-sectional study, vascular access data was collected from the hemodialysis patients treated at 52 hospitals in Tianjin from 1 January to 14 Decmeber 2020. The practice of vascular access was estimated during the outbreak of Covid-19 since late 2019. Results: Among the 6885 hemodialysis patients included, 4719 arteriovenous fistulas were identified as the main type of vascular access, accounting for 68.54%. While 2114 patients (30.7%) had tunneled cuffed catheter. The proportion of arteriovenous graft reached as low as 1%. Overall, 1819 vascular access sites were placed in the patients newly diagnosed with uremia, of whom 990 (54.5%) underwent catheter insertion, 811 (44.6%) underwent AVF creation, and only 18 AVGs were created. In addition, the proportion of vascular access sites performed in general hospitals was 88.6%. During the period, tempt catheter insertion was carried out for 1371 (75%) incident hemodialysis patients. Due to stenosis of AVF, percutaneous transluminal angioplasty was conducted for 83 patients. However, no patient got diagnosed with Covid-19. Conclusions: Catheter was the primary vascular access type during the pandemic and the rate of catheter use for incident patients was high. Most of vascular access creation was carried out in general hospitals while the numbers of AVG and PTA were relatively low.

12.
2021 International Symposium on Educational Technology, ISET 2021 ; : 122-126, 2021.
Article in English | Scopus | ID: covidwho-1470350

ABSTRACT

In recent years, online teaching has become a hot topic in K-12 education reform. Based on the expectation confirmation model of information systems continuance (ECM-IS), four individual characteristic factors of self-efficacy, innovation, perceived risk and information literacy as well as two external environmental factors of subjective norms and facilitating conditions were introduced to build a theoretical model of factors affecting teachers' continuance intention of online teaching from the perspective of technology-individual-environment. This study tested model encompassing nine variables through empirical research. Data were collected on a sample of 59156 K-12 teachers who have had an online teaching experience during COVID-19 using an online questionnaire. Data were modelled using the partial least squares-structural equation model (PLS-SEM) to test the hypotheses. Results indicated that perceived usefulness and satisfaction in the ECM-IS model have significant effect on teachers' continuance intention while self-efficacy, information literacy, innovation and subjective norms were found to significantly affect teachers' continuance intention. However, perceived risk and facilitating conditions have no effect on continuance intention. According to the results, there are some suggestions for better online teaching effects: improving hardware facilities and software resources, innovating teacher training and research methods, and optimizing online teaching service supply. © 2021 IEEE.

13.
2021 International Symposium on Educational Technology, ISET 2021 ; : 117-121, 2021.
Article in English | Scopus | ID: covidwho-1470349

ABSTRACT

College students are the online learning subjects in the Covid-19 pandemic and their preferences towards online learning have certain reference value for the subsequent improvement of online learning platforms and the optimization of online teaching and learning. The study combined information literacy with Uses and Gratifications Theory, characterized students' online learning preferences with usage, gratifications, and acceptance, and introduced online interaction to construct an influencing factor model for university students' preferences towards online learning. The partial least squares method was used to verify the measurement model and structural model. All the research hypotheses are supported by the empirical research. © 2021 IEEE.

14.
2021 International Symposium on Educational Technology, ISET 2021 ; : 96-100, 2021.
Article in English | Scopus | ID: covidwho-1470345

ABSTRACT

In the beginning of2020, COVID-19 pandemic emerged in many regions of China, and the spring semester of primary and middle schools was postponed. At the call of Suspension of Classes but not Learning by MOE, all educational institutes adopted the online learning methods. However, the home-based online learning lacks teacher supervision, peer support, classroom environment constraints. These intensify students' attention difficulty when compared -with face-to-face learning in the classroom, which makes students' learning engagement more important to ensure the learning effect. According to online focus group interviews with the education experts and K-12 teachers respectively, the researchers found out some possible influencing factors to K-12 students' online learning engagement: perceived teacher involvement, perceived parental involvement, students' self-discipline, and student emotion. Therefore, this study proposes a prediction model from the above four aspects. By using multivariate linear regression analysis and variance analysis, this study finds: (1) Perceived teacher involvement, perceived parent support, student self-discipline and student emotion all have significant positive effects on online learning engagement. (2) There are significant differences in students' online learning engagement for different learning stages and different network environments at home Students' online learning engagement has no significant difference between urban and rural areas. © 2021 IEEE.

15.
2021 International Symposium on Educational Technology, ISET 2021 ; : 53-57, 2021.
Article in English | Scopus | ID: covidwho-1470339

ABSTRACT

By the natural parents are the essentials of educating young generations. In China during Covid-19, especially the lock-down period, parents companied children at home and observed their learning behavior. Parental acceptance of online learning can offer a valuable reference for the further adaptation of online k-12 education. This study used an integrated model of technology acceptance and expected confirmation, demonstrating Parental acceptance by three variables: Acceptance, satisfaction, and continuance intention. Moreover, an influential, factor model of Parental acceptance was built, which including teacher support, perceive autonomy and interactivity, technology preference and experience. Measurement and structural data models are verified by using partial least squares regression (PLS), which supports all the hypotheses empirically. © 2021 IEEE.

16.
Environmental Science and Technology Letters ; 2021.
Article in English | Scopus | ID: covidwho-1469945

ABSTRACT

The unintentional emission reductions caused by the COVID-19 pandemic provides an opportunity to investigate the impact of energy, industry, and transportation activities on air pollutants and CO2 emissions and their synergy. Here, we constructed an approach to estimate city-level high resolution dynamic emissions of both anthropogenic air pollutants and CO2 by introducing dynamic temporal allocation coefficients based on real-time multisource activity data. We first apply this approach to estimate the spatiotemporal evolution of sectoral emissions in eastern China, focusing on the period around the COVID-19 lockdown. Comparisons with observational data show that our approach can well capture the spatiotemporal changes of both short-lived precursors (NOx and NMVOCs) and CO2 emissions. Our results show that air pollutants (SO2, NOx, and NMVOCs) were reduced by up to 31%-53% during the lockdown period accompanied by simultaneous changes of 40% CO2 emissions. The declines in power and heavy industry sectors dominated regional SO2 and CO2 reductions. NOx reductions were mainly attributed to mobile sources, while NMVOCs emission reductions were mainly from light industry sectors. Our findings suggest that differentiated emission control strategies should be implemented for different source categories to achieve coordinated reduction goals. © 2021 American Chemical Society.

17.
Geophysical Research Letters ; 48(13):12, 2021.
Article in English | Web of Science | ID: covidwho-1434071

ABSTRACT

The impacts of anthropogenic emissions on the reduction of source-specific equivalent black carbon (eBC) aerosols and their direct radiative effects (DREs) were investigated during the lockdown of the coronavirus outbreak in a megacity of China in 2020. Five eBC sources were identified using a hybrid environmental receptor model. Results showed that biomass burning, traffic-related emissions, and coal combustion were the dominant contributors to eBC. The generalized additive model indicated that the reduction of traffic-related eBC during the lockdown was entirely attributed to the decrease of emissions. Decreased biomass-burning activities and favorable meteorological factors are both important drivers for the biomass-burning eBC reduction during the lockdown. A radiative transfer model showed that the DRE efficiency of eBC from biomass burning was the strongest, followed by coal combustion and traffic-related emissions. This study highlights that aggressive reduction in the consumption of residential solid fuels would be effective in achieving climate change mitigation.

18.
Nano Biomedicine and Engineering ; 13(3):225-228, 2021.
Article in English | EMBASE | ID: covidwho-1403981

ABSTRACT

The novel coronavirus pneumonia, a global pandemic disease named as coronavirus disease 2019, has caused enormous losses on the health and economies of people all over the world, while there is still a lack of quick and sensitive diagnostic method and effective therapy. Developing rapid diagnostic method for coronavirus disease 2019 has become exceptional urgent. Herein we report a rapid diagnostic method for the novel coronavirus through monitoring the volatile biomarkers in human exhaled breath. The breath volatile biomarkers are derived from the metabolism of novel coronavirus, including acetoin, 2,4,6-trimethylpyridine, 3-methyl tridecane, tetradecane, isooctyl alcohol, pentadecane, hexadecane, 1-methylene-1H-indene. By comparing the types and concentrations of the volatile biomarkers in human exhaled breath combined with SERS sensor, we could distinguish between the healthy person and the patients with coronavirus disease 2019. This work confirms that various volatile organic compounds metabolized by novel coronavirus can be employed for rapidly screening of patients with coronavirus disease 2019, and has broad application prospects in the prevention and control of the epidemic.

19.
Investigative Ophthalmology and Visual Science ; 62(8), 2021.
Article in English | EMBASE | ID: covidwho-1378835

ABSTRACT

Purpose : Coronavirus disease 2019 (COVID-19) has impacted individuals seeking preventative, follow-up, and emergent ophthalmic care. In this retrospective study, we assessed the impact of COVID-19 on inpatient and emergency department (ED) ophthalmology care at a large tertiary academic hospital in the United States. Methods : We analyzed 570 ED and inpatient ophthalmology consults from March 13 to May 15 in 2020 and over the same period in 2019. Our primary endpoints were the number of consults and the percentage of consults that were 'vision-threatening' between the time periods. Our secondary endpoints were the demographics of the patients, relation to trauma, relation to an exacerbation of a chronic ocular condition, if the consult required surgical intervention, and time to surgery. Results : The total number of ED and inpatient consults decreased by 35.2% in 2020 compared to 2019. The total number of visually threatening diagnoses decreased, 97 in 2019 to 83 in 2020. The proportion of presentations with visually threatening diagnosis increased from 28.0% to 37.1% (p=0.0237). In 2020, there were a higher proportion of consults related to trauma (31.7% compared to 23.4%, p=0.0289), and consults requiring surgical intervention (19.6% compared to 12.4%, p=0.0192). The time to surgery was similar between time periods studied (p=0.902). There was not a significant difference in proportion of consults resulting from exacerbations of chronic ocular conditions (p=0.554). Conclusions : The volume of ophthalmic consults to our tertiary eye center and ED declined during the COVID-19 pandemic. There was an increase in the proportion of visually threatening diseases indicating a higher overall acuity seen by the consulting service. There was a total decrease in visually threatening diseases (despite an increase in numbers of consults from trauma), suggesting that some patients may have avoided urgent ophthalmic care due to fear of COVID-19 and the lockdown. Further research is needed to characterize the effect of COVID-19 and the regional stay-at-home order on emergent ophthalmic care delivery so we can better prepare for later stages of the pandemic and also for future pandemics.

20.
Electrochimica Acta ; 387:8, 2021.
Article in English | Web of Science | ID: covidwho-1291914

ABSTRACT

The development of COVID-19 detection strategies with high sensitivity and selectivity are urgent for early diagnosis. Herein, we constructed an electrochemical dual-aptamer biosensor based on the metal organic frameworks MIL-53(Al) decorated with Au@Pt nanoparticles and enzymes to determine SARSCoV-2 nucleocapsid protein (2019-nCoV-NP) via co-catalysis of the nanomaterials, horseradish peroxidase (HRP) and G-quadruplex DNAzyme. First, the two thiol-modified aptamers (N48 and N61), as recognition elements, were immobilized on the surface of gold electrode (GE) to capture the biomarker 2019nCoV-NP. Then, the nanomaterial composites Au@Pt/MIL-53 (Al) were decorated by HRP and hemin/Gquadruplex DNAzyme as signal nanoprobe. The designed nanoprobe was applied to amplifying the aptasensor signal via co-catalyzing the oxidation of hydroquinone in the presence of hydrogen peroxide. Finally, the aptamer-protein-nanoprobe sandwich electrochemical detection system was fabricated on the GE surface. The results demonstrated that this aptasensor had a wide linear range from 0.025 to 50 ng mL -1 and the detection limit was 8.33 pg mL -1 for 2019-nCoV-NP. This aptasensor has great potential in the early diagnosis of COVID-19 with high sensitivity, selectivity and reliability. (c) 2021 Elsevier Ltd. All rights reserved.

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