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1.
Sustainability ; 14(3):1092, 2022.
Article in English | MDPI | ID: covidwho-1625045

ABSTRACT

Good health and well-being are key to achieving the main goals of the UN Sustainable Development Goals (SDGs), especially after the outbreak of the COVID-19 epidemic. What is a concern for both government and society is how to understand the spatial match of hierarchical healthcare facilities and residential areas in terms of quantity and capacity, to meet the challenges of various diseases and build a healthy life. Using hierarchical healthcare data and cellphone signaling data in Beijing, China, we used the kernel density estimation, a bivariate spatial autocorrelation model, and a coupling index to explore the spatial relationships between hierarchical healthcare facilities and residential areas. We found large numbers of both healthcare facilities and residential areas in the urban center, and small numbers of both at the urban edge. The hospitals and designated retail pharmacies in the densely populated areas do not have enough capacity to meet the need of the population. In addition, the capacity of primary healthcare institutions can meet people’s needs. Our findings would serve as a reference for urban planning, optimization of hierarchical healthcare facilities, and research on similar themes.

3.
Emerging Markets Review ; : 100878, 2022.
Article in English | ScienceDirect | ID: covidwho-1611714

ABSTRACT

The early-warning system (EWS) is recognized in the literature as a method of detecting crises prior to events and to reduce false alarms of possible crises. This study constructs an EWS for BRICS (Brazil, Russia, India, China, and South Africa) countries to examine the risk of an external liquidity shock. The EWS index incorporates the sources, channels, and effects of shock in order to capture the key aspects of shock within the past 18 years. The findings show that the index peaks during financial crises. We then assess the predictive power of the EWS using an ARMA-GARCH model, which shows that Brazil, India, and South Africa are at great risk of shocks whereas China and Russia have relatively moderate risk in the coming years. The overall results highlight the importance of establishment of an EWS for countries such as Brazil, India, South Africa and other developing countries that have been struggling to cope up with the Covid 19 pandemic.

4.
Front Cell Dev Biol ; 9: 772965, 2021.
Article in English | MEDLINE | ID: covidwho-1606148

ABSTRACT

Autophagy is a conservative lysosomal catabolic pathway commonly seen in eukaryotic cells. It breaks down proteins and organelles by forming a two-layer membrane structure of autophagosomes and circulating substances and maintaining homeostasis. Autophagy can play a dual role in viral infection and serve either as a pro-viral factor or an antiviral defense element dependent on the virus replication cycle. Recent studies have suggested the complicated and multidirectional role of autophagy in the process of virus infection. On the one hand, autophagy can orchestrate immunity to curtail infection. On the other hand, some viruses have evolved strategies to evade autophagy degradation, facilitating their replication. In this review, we summarize recent progress of the interaction between autophagy and viral infection. Furthermore, we highlight the link between autophagy and SARS-CoV-2, which is expected to guide the development of effective antiviral treatments against infectious diseases.

5.
BMC Psychiatry ; 21(1): 530, 2021 10 27.
Article in English | MEDLINE | ID: covidwho-1594206

ABSTRACT

BACKGROUND: An increasing number of undergraduate students in China have been reported to have psychological problems. In response to the COVID-19 pandemic, a series of preventive and control measures were implemented, which undoubtedly worsened their psychological health. Coping style and social support were probably important factors that affected the psychological well-being of undergraduate students during the pandemic. This study aimed to explore the effects of coping style and perceived social support on the psychological well-being of college students and relevant risk factors. METHODS: This cross-sectional study was performed in February and March of 2020 by distributing an online questionnaire among undergraduate students from seven geographical regions across China. The questionnaire included sociodemographic information; the 21-item Depression, Anxiety and Stress Scale (DASS-21); the Perceived Social Support Scale (PSSS); and the Simplified Coping Style Questionnaire (SCSQ). For the analyses, t-tests, one-way analysis of variance (ANOVA), the Kruskal-Wallis test and multiple linear regression were utilized. The level of significance was set at P < 0.05. RESULTS: Among 3113 college students, the rates of anxiety, depression and stress symptoms were 13.3, 15.4 and 6.8%, respectively. Increased rates of current smoking and drinking (5.5 and 25.2%, respectively) among undergraduates were identified. The results indicated that the PSSS subscales and SCSQ subscales were significantly associated with DASS-21 scores (P < 0.001). Multiple linear regression analysis showed that active coping style and family support were protective factors while passive coping style could aggravate psychological problems among participants (P < 0.001). CONCLUSIONS: A remarkable number of college students adopted passive coping strategies to cope with negative feelings, such as smoking and drinking, which were detrimental to their mental health. In contrast, active coping strategies helped improve their psychological well-being. Moreover, family support was particularly important for maintaining their mental health and ameliorating mental health challenges in this major health crisis. Consequently, suitable psychointervention, routine screening for risk behaviors, and provision of further social support are needed for undergraduate students in the COVID-19 pandemic or other emergency public health events.


Subject(s)
COVID-19 , Pandemics , Adaptation, Psychological , Anxiety/epidemiology , China/epidemiology , Cross-Sectional Studies , Depression/epidemiology , Humans , Mental Health , SARS-CoV-2 , Social Support , Students , Surveys and Questionnaires
6.
Infect Dis Model ; 7(1): 212-230, 2022 Mar.
Article in English | MEDLINE | ID: covidwho-1593254

ABSTRACT

Classical epidemiological models assume mass action. However, this assumption is violated when interactions are not random. With the recent COVID-19 pandemic, and resulting shelter in place social distancing directives, mass action models must be modified to account for limited social interactions. In this paper we apply a pairwise network model with moment closure to study the early transmission of COVID-19 in New York and San Francisco and to investigate the factors determining the severity and duration of outbreak in these two cities. In particular, we consider the role of population density, transmission rates and social distancing on the disease dynamics and outcomes. Sensitivity analysis shows that there is a strongly negative correlation between the clustering coefficient in the pairwise model and the basic reproduction number and the effective reproduction number. The shelter in place policy makes the clustering coefficient increase thereby reducing the basic reproduction number and the effective reproduction number. By switching population densities in New York and San Francisco we demonstrate how the outbreak would progress if New York had the same density as San Francisco and vice-versa. The results underscore the crucial role that population density has in the epidemic outcomes. We also show that under the assumption of no further changes in policy or transmission dynamics not lifting the shelter in place policy would have little effect on final outbreak size in New York, but would reduce the final size in San Francisco by 97%.

7.
PLoS One ; 16(12): e0261424, 2021.
Article in English | MEDLINE | ID: covidwho-1599330

ABSTRACT

The COVID-19 outbreak has caused two waves and spread to more than 90% of Canada's provinces since it was first reported more than a year ago. During the COVID-19 epidemic, Canadian provinces have implemented many Non-Pharmaceutical Interventions (NPIs). However, the spread of the COVID-19 epidemic continues due to the complex dynamics of human mobility. We develop a meta-population network model to study the transmission dynamics of COVID-19. The model takes into account the heterogeneity of mitigation strategies in different provinces of Canada, such as the timing of implementing NPIs, the human mobility in retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residences due to work and recreation. To determine which activity is most closely related to the dynamics of COVID-19, we use the cross-correlation analysis to find that the positive correlation is the highest between the mobility data of parks and the weekly number of confirmed COVID-19 from February 15 to December 13, 2020. The average effective reproduction numbers in nine Canadian provinces are all greater than one during the time period, and NPIs have little impact on the dynamics of COVID-19 epidemics in Ontario and Saskatchewan. After November 20, 2020, the average infection probability in Alberta became the highest since the start of the COVID-19 epidemic in Canada. We also observe that human activities around residences do not contribute much to the spread of the COVID-19 epidemic. The simulation results indicate that social distancing and constricting human mobility is effective in mitigating COVID-19 transmission in Canada. Our findings can provide guidance for public health authorities in projecting the effectiveness of future NPIs.


Subject(s)
COVID-19/prevention & control , COVID-19/transmission , Epidemics/prevention & control , SARS-CoV-2 , Travel/statistics & numerical data , Basic Reproduction Number/statistics & numerical data , COVID-19/epidemiology , Canada/epidemiology , Humans , Incidence , Models, Statistical , Physical Distancing , Quarantine/methods
8.
Infect Dis Ther ; 2021 Dec 27.
Article in English | MEDLINE | ID: covidwho-1588666

ABSTRACT

INTRODUCTION: Seasonal influenza poses a major public health burden worldwide. Influenza vaccines, updated yearly to match circulating strains based on World Health Organization (WHO) recommendations, are the cornerstone of prevention and require regular monitoring. The COVID-19 pandemic is expected to cause logistical, site access and medical staff constraints and could affect the safety profile of influenza vaccines. METHODS: Following European Medicines Agency guidance, an enhanced safety surveillance (ESS) study assessed the frequency and severity of predefined and other adverse events (AEs) occurring within 7 days of receiving GSK's inactivated quadrivalent seasonal influenza vaccine (IIV4), in Belgium, Germany and Spain in 2020/21, using adverse drug reaction (ADR) cards. RESULTS: During the 2020/21 influenza season, 1054 participants vaccinated with GSK's IIV4 were enrolled (all adults in Belgium and Germany, 30% adults/70% children in Spain); 96 eligible children received a second dose. Overall, 1042 participants completed the study. After doses 1 and 2, 98.9% and 100% of participants, respectively, returned their completed ADR card. After doses 1 and 2, 37.8% (398/1054) and 13.5% (13/96) of participants, respectively, reported at least one AE. The most frequently reported categories of AEs were "general disorders and administration site conditions" (e.g. injection site pain) and "nervous system disorders" (e.g. headache). There were no deaths or serious AEs deemed related to GSK's IIV4. CONCLUSION: This ESS study assessed AEs in near real time. The COVID-19 pandemic did not alter the safety profile of GSK's IIV4. No safety signals were detected during the study, which confirms the excellent safety profile of GSK's IIV4.

9.
Preprint in English | EuropePMC | ID: ppcovidwho-296285

ABSTRACT

The abrupt outbreak of the COVID-19 pandemic was the most significant event in 2020, which had profound and lasting impacts across the world. Studies on energy markets observed a decline in energy demand and changes in energy consumption behaviors during COVID-19. However, as an essential part of system operation, how the load forecasting performs amid COVID-19 is not well understood. This paper aims to bridge the research gap by systematically evaluating models and features that can be used to improve the load forecasting performance amid COVID-19. Using real-world data from the New York Independent System Operator, our analysis employs three deep learning models and adopts both novel COVID-related features as well as classical weather-related features. We also propose simulating the stay-at-home situation with pre-stay-at-home weekend data and demonstrate its effectiveness in improving load forecasting accuracy during COVID-19.

10.
Front Psychol ; 12: 773134, 2021.
Article in English | MEDLINE | ID: covidwho-1551539

ABSTRACT

Background: Most studies on mental health problems caused by COVID-19 crisis in children were limited to the period of home quarantine. It remained unclear what adverse impact of the psychosocial stressors caused by school reopening, as well as the transitions in daily activities and social interactions had on mental health in children. Methods: A total of 6400 students in primary schools were enrolled in a cross-sectional study conducted in East China, between June 26 and July 6, 2020, when schools reopened. Children's mental health status was assessed by the parent version of Strengths and Difficulties Questionnaire (SDQ). Ultimately, data on a total of 6017 children with completed information on mental health, psychosocial stressors, daily activities, and social interactions were eligible for analysis. The associations of mental health with psychosocial stressors, daily activities, and social interactions were determined by ordinal logistic regression models. Stratified analyses were conducted according to grade, gender, school level, area, and caregiver-child relationship to further observe the effects of stressors on mental status. Results: The prevalence of borderline, moderately abnormal, and prominently abnormal scores were 7.16, 3.34, and 1.96% for total difficulties, and 13.83, 13.45, and 17.85% for prosocial behavior, respectively. Children with psychological stressors had a significantly higher risk of being in a worse category of mental health status, with the maximum adjusted OR of 7.90 (95% CI 3.33-18.75) in those definitely afraid of inadaptation to study and life styles. Time used in home work and computer games was positively related to mental health problems, while physical exercises and frequency of communication with others was negatively related. The effects of psychological stressors on total difficulties were more evident in middle-high grade students (OR = 7.52, 95% CI 4.16-8.61), boys (OR = 6.95, 95% CI 4.83-8.55), those who lived in Taizhou (OR = 7.62, 95% CI 4.72-8.61) and with poor caregiver-child relationship (OR = 7.79, 95% CI 2.26-8.65). Conclusion: Emotional and behavioral difficulties, especially less prosocial behavior, were prevalent in primary school children after schools reopened. The Chinese government, communities, schools, and families need to provide more effective support for students' transition back into the school building and address emotional and behavioral problems for children with difficulties.

11.
Data Brief ; 38: 107381, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1531176

ABSTRACT

One year after identifying the first case of the 2019 coronavirus disease (COVID-19) in Canada, federal and provincial governments are still struggling to manage the pandemic. Provincial governments across Canada have experimented with widely varying policies in order to limit the burden of COVID-19. However, to date, the effectiveness of these policies has been difficult to ascertain. This is partly due to the lack of a publicly available, high-quality dataset on COVID-19 interventions and outcomes for Canada. The present paper provides a dataset containing important, Canadian-specific data that is known to affect COVID-19 outcomes, including sociodemographic, climatic, mobility and health system related information for all 10 Canadian provinces and their health regions. This dataset also includes longitudinal data on the daily number of COVID-19 cases, deaths, and the constantly changing intervention policies that have been implemented by each province in an attempt to control the pandemic.

12.
Data Brief ; 38: 107360, 2021 Oct.
Article in English | MEDLINE | ID: covidwho-1531175

ABSTRACT

This dataset provides information related to the outbreak of COVID-19 disease in the United States, including data from each of 3142 US counties from the beginning of the outbreak (January 2020) until June 2021. This data is collected from many public online databases and includes the daily number of COVID-19 confirmed cases and deaths, as well as 46 features that may be relevant to the pandemic dynamics: demographic, geographic, climatic, traffic, public-health, social-distancing-policy adherence, and political characteristics of each county. We anticipate many researchers will use this dataset to train models that can predict the spread of COVID-19 and to identify the key driving factors.

13.
IEEE Access ; 8: 155987-156000, 2020.
Article in English | MEDLINE | ID: covidwho-1528284

ABSTRACT

Deep Learning-based chest Computed Tomography (CT) analysis has been proven to be effective and efficient for COVID-19 diagnosis. Existing deep learning approaches heavily rely on large labeled data sets, which are difficult to acquire in this pandemic situation. Therefore, weakly-supervised approaches are in demand. In this paper, we propose an end-to-end weakly-supervised COVID-19 detection approach, ResNext+, that only requires volume level data labels and can provide slice level prediction. The proposed approach incorporates a lung segmentation mask as well as spatial and channel attention to extract spatial features. Besides, Long Short Term Memory (LSTM) is utilized to acquire the axial dependency of the slices. Moreover, a slice attention module is applied before the final fully connected layer to generate the slice level prediction without additional supervision. An ablation study is conducted to show the efficiency of the attention blocks and the segmentation mask block. Experimental results, obtained from publicly available datasets, show a precision of 81.9% and F1 score of 81.4%. The closest state-of-the-art gives 76.7% precision and 78.8% F1 score. The 5% improvement in precision and 3% in the F1 score demonstrate the effectiveness of the proposed method. It is worth noticing that, applying image enhancement approaches do not improve the performance of the proposed method, sometimes even harm the scores, although the enhanced images have better perceptual quality.

14.
Chem Biol Interact ; 351: 109744, 2021 Nov 11.
Article in English | MEDLINE | ID: covidwho-1509623

ABSTRACT

Remdesivir, an intravenous nucleotide prodrug, has been approved for treating COVID-19 in hospitalized adults and pediatric patients. Upon administration, remdesivir can be readily hydrolyzed to form its active form GS-441524, while the cleavage of the carboxylic ester into GS-704277 is the first step for remdesivir activation. This study aims to assign the key enzymes responsible for remdesivir hydrolysis in humans, as well as to investigate the kinetics of remdesivir hydrolysis in various enzyme sources. The results showed that remdesivir could be hydrolyzed to form GS-704277 in human plasma and the microsomes from human liver (HLMs), lung (HLuMs) and kidney (HKMs), while the hydrolytic rate of remdesivir in HLMs was the fastest. Chemical inhibition and reaction phenotyping assays suggested that human carboxylesterase 1 (hCES1A) played a predominant role in remdesivir hydrolysis, while cathepsin A (CTSA), acetylcholinesterase (AchE) and butyrylcholinesterase (BchE) contributed to a lesser extent. Enzymatic kinetic analyses demonstrated that remdesivir hydrolysis in hCES1A (SHUTCM) and HLMs showed similar kinetic plots and much closed Km values to each other. Meanwhile, GS-704277 formation rates were strongly correlated with the CES1A activities in HLM samples from different individual donors. Further investigation revealed that simvastatin (a therapeutic agent for adjuvant treating COVID-19) strongly inhibited remdesivir hydrolysis in both recombinant hCES1A and HLMs. Collectively, our findings reveal that hCES1A plays a predominant role in remdesivir hydrolysis in humans, which are very helpful for predicting inter-individual variability in response to remdesivir and for guiding the rational use of this anti-COVID-19 agent in clinical settings.

15.
Front Psychol ; 12: 712529, 2021.
Article in English | MEDLINE | ID: covidwho-1497130

ABSTRACT

To investigate the prevalence of emotional and behavioral problems (EBPs) among children during the COVID-19 post-pandemic in China; examine associations between COVID-19-related knowledge and precautions and problems in children, and explore the potential explanatory value of the mental health status of caregivers on any associations observed. Based on a cross-sectional design, caregivers of 6,017 children from 12 primary schools in Shanghai and Taizhou, China, were invited to complete an online survey from June 26 to July 6, 2020. EBPs of the children were assessed using the Strengths and Difficulties Questionnaire (SDQ), while the emotional problems of caregivers were assessed using the Depression Anxiety Stress Scales-21 (DASS-21). Structural equation modeling was employed to estimate the direct and indirect associations (explained by the emotional problems of caregivers) between COVID-19-related knowledge and precautions and the EBPs among children. The overall prevalence of EBPs in the sample was 12.5%, and 5.3% of them had a high or very high SDQ total difficulties score during the COVID-19 post-pandemic. After adjustment for covariates, higher COVID-19-related knowledge (ß = -0.83; P < 0.001) and precautions (ß = -0.80; P < 0.001) were significantly associated with lower SDQ total difficulties score among children. There was an explanatory effect of emotional problems of caregivers on the aforementioned associations, which explained 31% and 41% of the total effect, respectively. Higher levels of knowledge and precautions of COVID-19 were associated with lower EBPs among children, and the relationship was partially explained by the emotional problems in caregivers. It may be beneficial to improve pandemic-related prevention education and adopt psychological interventions toward the emotional status of caregivers for the psychological health of children.

16.
Int J Environ Res Public Health ; 18(20)2021 10 14.
Article in English | MEDLINE | ID: covidwho-1480725

ABSTRACT

Outsourcing remanufacturing is an important way to achieve resource recycling, green manufacturing and carbon neutrality goals. To analyze the impact of carbon trade on manufacturing/remanufacturing under outsourcing remanufacturing, this article builds a game model between an original equipment manufacturer (OEM) and a remanufacturer under the carbon trade policy. In the outsourcing remanufacturing model, this article compares the impact of the carbon trade policy on the unit retail price, sales volume, revenue, environmental impact, and consumer surplus of new and remanufactured products. The research mainly draws the following conclusions: (1) Carbon trade increases the prices of both new and remanufactured products and the cost of outsourcing. Only when certain conditions are met can increased carbon trade prices increase revenue. (2) The carbon trade policy helps reduce the adverse impact on the environment, but only when the carbon trade price is greater than a certain threshold can it increase consumer surplus. (3) Consumer preferences and carbon emissions of the unit product affect manufacturers' profits. Increased consumer preference for remanufactured products and reduced carbon emissions of remanufactured products contribute to increased sales and revenues.


Subject(s)
Carbon , Outsourced Services , Commerce , Policy , Recycling
17.
Front Chem ; 9: 746134, 2021.
Article in English | MEDLINE | ID: covidwho-1477804

ABSTRACT

Asymptomatic COVID-19 has become one of the biggest challenges for controlling the spread of the SARS-CoV-2. Diagnosis of asymptomatic COVID-19 mainly depends on quantitative reverse transcription PCR (qRT-PCR), which is typically time-consuming and requires expensive reagents. The application is limited in countries that lack sufficient resources to handle large-scale assay during the COVID-19 outbreak. Here, we demonstrated a new approach to detect the asymptomatic SARS-CoV-2 infection using serum metabolic patterns combined with ensemble learning. The direct patterns of metabolites and lipids were extracted by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) within 1 s with simple sample preparation. A new ensemble learning model was developed using stacking strategy with a new voting algorithm. This approach was validated in a large cohort of 274 samples (92 asymptomatic COVID-19 and 182 healthy control), and provided the high accuracy of 93.4%, with only 5% false negative and 7% false positive rates. We also identified a biomarker panel of ten metabolites and lipids, as well as the altered metabolic pathways during asymptomatic SARS-CoV-2 Infection. The proposed rapid and low-cost approach holds promise to apply in the large-scale asymptomatic COVID-19 screening.

18.
Int J Biol Macromol ; 187: 976-987, 2021 Sep 30.
Article in English | MEDLINE | ID: covidwho-1474606

ABSTRACT

Coronavirus 3C-like protease (3CLpro) is a crucial target for treating coronavirus diseases including COVID-19. Our preliminary screening showed that Ampelopsis grossedentata extract (AGE) displayed potent SARS-CoV-2-3CLpro inhibitory activity, but the key constituents with SARS-CoV-2-3CLpro inhibitory effect and their mechanisms were unrevealed. Herein, a practical strategy via integrating bioactivity-guided fractionation and purification, mass spectrometry-based peptide profiling and time-dependent biochemical assay, was applied to identify the crucial constituents in AGE and to uncover their inhibitory mechanisms. The results demonstrated that the flavonoid-rich fractions (10-17.5 min) displayed strong SARS-CoV-2-3CLpro inhibitory activities, while the constituents in these fractions were isolated and their SARS-CoV-2-3CLpro inhibitory activities were investigated. Among all isolated flavonoids, dihydromyricetin, isodihydromyricetin and myricetin strongly inhibited SARS-CoV-2 3CLpro in a time-dependent manner. Further investigations demonstrated that myricetin could covalently bind on SARS-CoV-2 3CLpro at Cys300 and Cys44, while dihydromyricetin and isodihydromyricetin covalently bound at Cys300. Covalent docking coupling with molecular dynamics simulations showed the detailed interactions between the orthoquinone form of myricetin and two covalent binding sites (surrounding Cys300 and Cys44) of SARS-CoV-2 3CLpro. Collectively, the flavonoids in AGE strongly and time-dependently inhibit SARS-CoV-2 3CLpro, while the newly identified SARS-CoV-2 3CLpro inhibitors in AGE offer promising lead compounds for developing novel antiviral agents.


Subject(s)
3C Viral Proteases/chemistry , 3C Viral Proteases/metabolism , Ampelopsis/chemistry , Antiviral Agents/pharmacology , Flavonoids/pharmacology , SARS-CoV-2/enzymology , Antiviral Agents/chemistry , Binding Sites/drug effects , Cysteine/metabolism , Flavonoids/chemistry , Flavonols/chemistry , Flavonols/pharmacology , Mass Spectrometry , Models, Molecular , Molecular Docking Simulation , Molecular Dynamics Simulation , Plant Extracts/chemistry , Plant Extracts/pharmacology , Protease Inhibitors/chemistry , Protease Inhibitors/pharmacology , Protein Binding/drug effects , Protein Conformation/drug effects , SARS-CoV-2/drug effects
20.
Mol Cell Probes ; 60: 101771, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1432043

ABSTRACT

The emergence of the influenza A(H1N1)pdm09 virus with the NA-H275Y mutation, which confers oseltamivir resistance, must be monitored, especially in patients undergoing neuraminidase inhibitor treatment. In this study, we developed a reverse transcription recombinase-aided amplification assay that has high sensitivity (detection limit: 1.0 × 101 copies/µL) and specificity for detecting the oseltamivir-resistant H275Y mutation; the assay is performed within 30 min at a constant temperature of 39° Celsius using an isothermal device. This method is suitable for the clinical application of targeted testing, thereby providing technical support for precision medicine in individual drug applications for patients with severe infection or immunosuppression.

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