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1.
Brief Bioinform ; 22(6)2021 11 05.
Article in English | MEDLINE | ID: covidwho-1348051

ABSTRACT

The identification of protein-ligand interaction plays a key role in biochemical research and drug discovery. Although deep learning has recently shown great promise in discovering new drugs, there remains a gap between deep learning-based and experimental approaches. Here, we propose a novel framework, named AIMEE, integrating AI model and enzymological experiments, to identify inhibitors against 3CL protease of SARS-CoV-2 (Severe acute respiratory syndrome coronavirus 2), which has taken a significant toll on people across the globe. From a bioactive chemical library, we have conducted two rounds of experiments and identified six novel inhibitors with a hit rate of 29.41%, and four of them showed an IC50 value <3 µM. Moreover, we explored the interpretability of the central model in AIMEE, mapping the deep learning extracted features to the domain knowledge of chemical properties. Based on this knowledge, a commercially available compound was selected and was proven to be an activity-based probe of 3CLpro. This work highlights the great potential of combining deep learning models and biochemical experiments for intelligent iteration and for expanding the boundaries of drug discovery. The code and data are available at https://github.com/SIAT-code/AIMEE.


Subject(s)
COVID-19/drug therapy , Protease Inhibitors/chemistry , SARS-CoV-2/chemistry , Small Molecule Libraries/chemistry , Antiviral Agents/chemistry , Antiviral Agents/therapeutic use , Artificial Intelligence , COVID-19/genetics , COVID-19/virology , Drug Discovery , Humans , Ligands , Protease Inhibitors/therapeutic use , SARS-CoV-2/drug effects , SARS-CoV-2/pathogenicity , Small Molecule Libraries/therapeutic use
2.
J Affect Disord ; 294: 128-136, 2021 Nov 01.
Article in English | MEDLINE | ID: covidwho-1317696

ABSTRACT

BACKGROUND: We aimed to explore the risk profiles attributable to psychosocial and behavioural problems during the coronavirus disease 2019 pandemic. To this end, we created a risk-prediction nomogram model. METHODS: A national multicentre study was conducted through an online questionnaire involving 12,186 children (6-11 years old) and adolescents (12-16 years old). Respondents' psychosocial and behavioural functioning were assessed using the Achenbach Child Behaviour Checklist (CBCL). Data were analysed using STATA software and R-language. RESULTS: The positive detection rate of psychological problems within Wuhan was greater than that outside Wuhan for schizoid (P = 0.005), and depression (P = 0.030) in children, and for somatic complaints (P = 0.048), immaturity (P = 0.023), and delinquent behaviour (P = 0.046) in adolescents. After graded multivariable adjustment, seven factors associated with psychological problems in children and adolescents outside Wuhan were parent-child conflict (odds ratio (OR): 4.94, 95% confidence interval (95% CI): 4.27-5.72), sleep problems (OR: 4.05, 95% CI: 3.77-4.36), online study time (OR: 0.41, 95% CI: 0.37-0.47), physical activity time (OR: 0.510, 95% CI: 0.44-0.59), number of close friends (OR: 0.51, 95% CI: 0.44-0.6), time spent playing videogames (OR: 2.26, 95% CI: 1.90-2.69) and eating disorders (OR: 2.71, 95% CI: 2.35-3.11) (all P < 0.001). Contrastingly, within Wuhan, only the first four factors, namely, parent-child conflict (5.95, 2.82-12.57), sleep problems (4.47, 3.06-6.54), online study time (0.37, 0.22-0.64), and physical activity time (0.42, 0.22-0.80) were identified (all P < 0.01). Accordingly, nomogram models were created with significant attributes and had decent prediction performance with C-indexes over 80%. LIMITATION: A cross-sectional study and self-reported measures. CONCLUSIONS: Besides the four significant risk factors within and outside Wuhan, the three additional factors outside Wuhan deserve special attention. The prediction nomogram models constructed in this study have important clinical and public health implications for psychosocial and behavioural assessment.


Subject(s)
COVID-19 , Problem Behavior , Adolescent , Child , Cross-Sectional Studies , Humans , Nomograms , Pandemics , Risk Factors , SARS-CoV-2
3.
Transl Psychiatry ; 11(1): 342, 2021 06 03.
Article in English | MEDLINE | ID: covidwho-1258580

ABSTRACT

This study aims to explore the psychosocial and behavioral problems of children and adolescents in the early stage of reopening schools. In this national cross-sectional study, a total of 11072 students from China were naturally divided into two groups based on their schooling status: reopened schools (RS) and home schooling (HS) group. The psychosocial and behavioral functioning were measured by Achenbach Child Behaviour Checklist (CBCL) and compared in these two groups. Multivariable logistic regression analyses were conducted to explore the independent predictors associated with the psychosocial and behavioral problems. Our results showed that the students in the RS group had more adverse behaviors than that of HS group. The RS group had the higher rates of parent-offspring conflict, prolonged homework time, increased sedentary time and sleep problems (all p < 0.001). When separate analyses were conducted in boys and girls, the RS group had the higher scores for (1) overall behavioral problems (p = 0.02 and p = 0.01), internalizing (p = 0.02 and p = 0.02) and externalizing (p = 0.02 and p = 0.004) behaviors in the 6-11 age group; (2) externalizing (p = 0.049 and p = 0.006) behaviors in the 12-16 age group. Multivariable regression showed parent-offspring conflict and increased sedentary time were the most common risk factors, while physical activity and number of close friends were protective factors for behavior problems in RS students (p < 0.01 or 0.05). The present study revealed that students' psychosocial and behavioral problems increased in the early stage of schools reopened unexpectedly. These findings suggest that close attention must be paid and holistic strategies employed in the school reopening process of post-COVID-19 period.


Subject(s)
COVID-19 , Problem Behavior , Adolescent , Child , China/epidemiology , Cross-Sectional Studies , Female , Humans , Male , Pandemics , SARS-CoV-2 , Schools
4.
Complexity ; 2021, 2021.
Article in English | ProQuest Central | ID: covidwho-1177605

ABSTRACT

To survive in a competitive environment, small and medium enterprises (SMEs) have had to adapt to the digital environment in order to adjust to customer needs globally, particularly in the post-COVID-19 world. The advantages of cloud computing (e.g., flexibility, scalability, and low entry cost) provide opportunities for SMEs with a restricted budget and limited resources. To understand how SMEs adopt cloud computing in a complex digital environment, this study examines how antecedents combine with each other to explain the high adoption of cloud computing. From the perspectives of holism and set theory, we draw on complexity and configuration theories, present a conceptual model including seven antecedents based on the technology-organization-environment framework, and conduct an asymmetric fuzzy-set qualitative comparative analysis. Through an empirical study with 123 Chinese companies, we identify nine combinations (configurations) of determinant antecedents that lead to the high adoption of cloud computing. The results show that none of the factors are indispensable to explain a high adoption on their own;instead, they are insufficient but necessary parts of the causal combinations that explain a high adoption. This study contributes to the literature on cloud computing adoption by extending current knowledge on how antecedents combine to increase the adoption and identify specific patterns of SMEs for whom these factors are essential and greatly influence their adoption.

5.
Am. Rev. Public Adm. ; 2020.
Article in English | ELSEVIER | ID: covidwho-1067054

ABSTRACT

The COVID-19 pandemic has put pressure on essential public services. While much of the economy has been shut down, essential public services have continued. Using professional experience, publicly available information, and interviews with two municipal utility managers, we evaluate the challenges presented to municipal utility services by the COVID-19 pandemic and explore some of the responses by utilities to the pandemic. Specifically, we focus on the strategies utilities have used to keep employees safe from the virus and plans for workforce shortages. One important strategy we identify is reliance on mutual aid agreements, where utilities agree to send staff and equipment to other utilities in times of crisis. We also explore the role of a municipal utility association in coordinating response. The case of utility response to COVID-19 carries important potential implications for both public administration practice and research.

6.
Am. Rev. Public Adm. ; 2020.
Article in English | ELSEVIER | ID: covidwho-639721

ABSTRACT

The COVID-19 pandemic has put pressure on essential public services. While much of the economy has been shut down, essential public services have continued. Using professional experience, publicly available information, and interviews with two municipal utility managers, we evaluate the challenges presented to municipal utility services by the COVID-19 pandemic and explore some of the responses by utilities to the pandemic. Specifically, we focus on the strategies utilities have used to keep employees safe from the virus and plans for workforce shortages. One important strategy we identify is reliance on mutual aid agreements, where utilities agree to send staff and equipment to other utilities in times of crisis. We also explore the role of a municipal utility association in coordinating response. The case of utility response to COVID-19 carries important potential implications for both public administration practice and research.

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