Paediatricians' awareness of Canadian screen time guidelines, perception of screen time use, and counselling during the COVID-19 pandemic

Objectives Paediatricians are essential in guiding families on screen time use as digital media becomes increasingly prevalent. While this has been highlighted through the COVID-19 pandemic there is no literature on paediatricians' awareness of Canadian screen time guidelines, or perception of these guidelines during this time. The aim of this study was to assess pediatricians' knowledge, attitudes, and comfort with the Canadian Paediatric Society's (CPS) screen time guidelines, specifically during the COVID-19 pandemic. Methods Our survey was developed by a paediatric resident and paediatric endocrinologist, reviewed by local experts, and sent electronically to members of the CPS Community and Developmental Paediatrics sections. Results All 53 respondents were aware of current CPS screen time guidelines, and the majority self-reported fair to excellent knowledge of guidelines for both age groups (<5 years and school-aged children/adolescents). Over 80% noticed increased screen use during the pandemic, and 98% were somewhat or very concerned about screen use and their patients' health and well-being. Pediatricians reported concerns about associations between increased screen time with worsening behaviour, mental health concerns, obesity, and sedentary lifestyle. The greatest barrier to reducing screen time was perceived insufficient motivation or support from caregivers/families. Conclusions Responding Canadian paediatricians are knowledgeable and comfortable with current screen time guidelines in Canada. Despite this, there is increasing concern with health outcomes associated with screen use. These results highlight paediatricians' important role in counselling patients and may encourage further local advocacy and public education around screen use and associated health risks in children.

Structural Racism through Sundown Towns and its relationship to COVID-19 local risk and diversity.

"Sundown towns" across the US prevented racial and ethnic minorities from living and working within their borders as they forced minorities to leave these towns after sunset. The objective of this study was to explore the relationship between historic sundown town status, COVID-19 local risk index and racial/ethnic city-level diversity. We used a multi-level hierarchical model was used to examine the effect of historic sundown town status on the COVID-19 local risk index and city-level diversity. Over 2,400 Sundown towns were cataloged across the United States, with the greatest density in the Midwest. Sundown towns, which historically excluded racial/ethnic minorities, had significantly less racial/ethnic diversity as measured and lower COVID-19 local risk index compared to non-Sundown towns. Findings show that residual segregation enforced by historic Sundown towns continues to impact current inequities among racial/ethnic minorities related to risk for COVID-19 at the neighborhood level. We recommend that public health officials for pandemic preparedness should devote greater resources to these historically segregated racial/ethnic minority areas because of the higher risk these areas possess because of structural racism brought on my historical segregation policies.

Olfactory Performance in Post Mild-to-Moderate Acute Covid-19 across 2 Years

Background: Previous longitudinal studies (n=6) of objective olfaction performance post-acute COVID-19 have a maximum follow-up of 6-month and do not often test biomarkers. Although olfactory dysfunction appears to improve within two months of symptom onset, 4/6 longitudinal studies show persistent olfactory impairment. Method(s): PCR-confirmed COVID-19 patients in the prospective ADAPT cohort (Sydney, Australia) were assessed across 18 acute symptoms and hospitalization status: 40% mild, 50% moderate, 10% severe/hospitalised - none deceased). Blood samples were taken 2 (N=179), 4 (N=148) and 12-month (N=118) post-diagnosis. The NIH Odor Identification Test (OIT) and the Cogstate brief cognitive battery were performed. 58 also had an olfaction test at 24-month. The OIT raw data were transformed into demographically-corrected T-scores. OIT's attrition was completely random and only initial age (40+/-15 versus 47+/-15) differed between patients lost to follow-up and those in the study at 24-month. We tested peripheral neurobiomarkers (NFL, GFAP, S100B, GM-CSF) and immune markers (Interleukin-IL panel: 1-beta, 1Ralpha, 4, 5, 6, 8, 10, 12p40, 12p70, 13, and MCP-1, TNF-alpha and INF-gamma), analyzed as Log transformed and elevated/normal range using published references. Our previous analyses had shown no relationship with the kynurenine pathway, but an association of impaired olfaction and impaired cognition at 2-month only. Linear mixed effect regressions with time effect (months) tested olfaction trajectories (random subject effect) and their association with the biomarkers (main and time interaction). Result(s): At 2 months post-diagnosis 30% had impaired olfaction and those who had acute severe disease were more likely to be impaired (54% versus 26%, p=.009). 21%, 31% and 37% had impaired olfaction at 4, 12 and 24-months. Olfactory performance declined over time (p< .0001), which was dependent on the initial performance (Fig 1). Neurobiomarkers were within the normal range. IFN-gamma, IL-1Ralpha, IL-13 and TNF-alpha increased across time, p< .03-p< .0005. TNF-alpha and IFN-gamma showed a time covariance with poorer olfaction performance. Conclusion(s): Post-acute mild to moderate COVID-19 is associated with a declining olfactory performance up to 2-yr post-diagnosis, especially when initially impaired with the provisio of attrition although random. Olfactory performance decline may be mediated by upregulated immune parameters which are distinct from those driving cognitive changes. (Figure Presented).

Prevalence of psychological symptoms and associated risk factors among nurses in 30 provinces during the COVID-19 pandemic in China

Background With the outbreak of the coronavirus disease 2019 (COVID-19), nurses have won well-deserved recog-nition for their indispensable roles in providing humane and professional healthcare for patients. However, by the nature of their role working at the forefront of patient care, nurses are prone to experiencing mental health conse-quences. Therefore, we pay attention to measuring the magnitude of psychological symptoms and identifying associ-ated factors among nurses in China.Methods We launched a nationwide, cross-sectional survey of nurses who worked in secondary or tertiary hospitals and public or private hospitals from 30 provinces in China. The prevalence and severity of symptoms of burnout, depression, and anxiety were investigated, respectively. Multivariable logistic regression analyses were performed to identify factors associated with each psychological symptom.Findings A total of 138 279 respondents who worked in 243 hospitals completed this survey. A substantial propor-tion of nurses reported symptoms of burnout (34%), depression (55.5%), and anxiety (41.8%). In line with the dispro-portionality of economic development, we noted that the middle or western region was an independent risk factor for depression and anxiety. Compared with those working in the secondary hospital, nurses who worked in tertiary hospitals were associated with a higher likelihood of burnout and depression.Interpretation Nurses are experiencing emotional, physical, and mental exhaustion during the COVID-19 epidemic. Governments and health policymakers need to draw attention to reinforcing prevention and ameliorating counter-measures to safeguard nurses' health.Funding The strategic consulting project of the Chinese Academy of Engineering [2021-32-5]. Advanced Institute of Infomation Technology, Peking University, Zhejiang Province [2020-Z-17]Copyright (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Improved SEIR Model Based on Recovery Rate Optimization to Predict COVID-19

When using the traditional SEIR infectious disease model to predict the trend of novel coronavirus pneumonia epidemic, numerous initial parameters need to be tuned, and the parameters cannot change over time during the prediction process, which reduces the accuracy of the model. Firstly, thesis used a logistic model to preprocess the SEIR model parameters and proposed a SEIR model based on time series recovery rate optimization with a new parameter of effective immunity rate. Secondly, the model was trained with epidemic data from domestic and foreign provinces and cities, and the usability of the model was demonstrated experimentally, and the mean absolute percentage error (MAPE) and goodness of fit (R2) were used to compare with other models, which proved the superiority of the model prediction and indicated further research directions. © 2022 IEEE.

mHealth and social mediation: Mobile support among stigmatized people living with HIV and substance use disorder

The social mediation role of mobile technology is typified by mHealth apps designed to connect individuals to others and support substance use disorder (SUD) recovery. In this study, we examined the use and utility of one such app designed to support people living with HIV (PLWH) and SUD. Drawing on Ling's emphasis on reciprocity and micro-coordination in mobile telephony as a social mediation technology, we gathered digital trace data from app logs to construct two metrics, initiation (i.e. whether a particular feature is engaged on a given day) and intensity (i.e. degree of involvement in the activity when engaged on that day), at three levels of communication—networked (one-to-many), dyadic (one-to-one), and intraindividual (self-to-self). We consider these affordances alongside use of information resources, games and relaxation links, a meeting and events calendar, and support tools to address use urges. We found few differences in patterns of use by race, sex, and age, though African Americans were less likely to engage in intraindividual expression, whereas women and older users were more likely to make use of this affordance. The initiation and intensity of network and dyadic reception, as well as the intensity of network expression, predicts recovery outcomes as measured on a weekly "check-in” survey, suggesting the utility of mobile log data for digital phenotyping in mHealth. By implementing this app during the COVID-19 pandemic, the study also found the disruption caused by national lockdown was negatively related to the app use. © The Author(s) 2023.

The effect of Pickering emulsion adjuvants on the immune efficacy of the COVID-19 polypeptide vaccine

Pickering emulsions were prepared by phacoemulsification in an ice water bath with squalene as the oil phase and an aluminum adjuvant as the particle stabilizer. The effects of formulation and process conditions on the size and distribution of the Pickering emulsions were investigated. Pickering emulsions prepared under the optimal prescription and process conditions were mixed with a peptide antigen to obtain a peptide vaccine. The optimal prescription and process condition of the Pickering emulsion is as follows: squalene as the oil phase, ultra-pure water as the water phase with 5 mg/ml aluminum adjuvant, and an ultrasonication time of 4 min at 200 W power. BALB/c mice were immunized with the peptide vaccine, and the ability of the Pickering emulsion as an immunological adjuvant to improve the efficacy of the peptide vaccine was evaluated. Under optimal conditions, a Pickering emulsion with a small particle size (430.8 nm), uniform distribution (polydispersion index of 16.9%), and zeta potential of 31.5 mV, was obtained. Immunological results showed that the serum specific antibody level in the vaccinated group reached 1×104 after three immunizations. The proportion of CD4+T cells and CD4/CD8 cells was significantly higher (P < 0.05) in the vaccinated groups than the blank control group. Further, cytokine (TNF-α) secretion decreased in the aluminum adjuvant and Pickering emulsion groups but increased in the Freund's adjuvant group. All three vaccinated groups of mice exhibited low but detectable levels of IFN-γ secretion. © 2023

Typical es of COVID-19 Pneumonia in Adult

Medical History and Clinical Manifestation © Henan Science and Technology Press 2020.

Surface Subsidence Characteristics and Causes in Beijing (China) before and after COVID-19 by Sentinel-1A TS-InSAR

Surface subsidence is a serious threat to human life, buildings and traffic in Beijing. Surface subsidence is closely related to human activities, and human activities in Beijing area showed a decreasing trend during the Corona Virus Disease 2019 (COVID-19). To study surface subsidence in Beijing before and after the COVID-19 outbreak and its causes, a total of 51 Sentinel-1A SAR images covering Beijing from January 2018 to April 2022 were selected to derive subsidence information by Time Series Interferometry Synthetic Aperture Radar (TS-InSAR). The results of surface subsidence in Beijing demonstrate that Changping, Chaoyang, Tongzhou and Daxing Districts exhibited the most serious subsidence phenomenon before the COVID-19 outbreak. The four main subsidence areas form an anti-Beijing Bay that surrounds other important urban areas. The maximum subsidence rate reached −57.0 mm/year. After the COVID-19 outbreak, the main subsidence area was separated into three giant subsidence funnels and several small subsidence funnels. During this period, the maximum subsidence rate was reduced to −43.0 mm/year. Human activity decrease with the COVID-19 outbreak. This study effectively analysed the influence of natural factors on surface subsidence after excluding most of the human factors. The following conclusions are obtained from the analysis: (1) Groundwater level changes, Beijing's geological structure and infrastructure construction are the main reasons for surface subsidence in Beijing. (2) Seasonal changes in rainfall and temperature indirectly affect groundwater level changes, thereby affecting surface subsidence in the area. (3) The COVID-19 outbreak in early 2020 reduced the payload of Beijing's transportation facilities. It also slowed down the progress of various infrastructure construction projects in Beijing. These scenarios affected the pressure on the soft land base in Beijing and reduced the surface subsidence trend to some extent. © 2023 by the authors.

The impact of COVID-19 on the tourism and hospitality Industry: Evidence from international stock markets

COVID-19 seriously affects the tourism and hospitality industry. In this study, we investigate the behavior of 40 tourism and hospitality stock market indices worldwide from two perspectives. First, empowered by the Granger causality test and network analysis, we test the spillover effects among these stock markets and find that the dynamics of interconnectedness network structures differ significantly in the pre-pandemic and in-pandemic periods. Second, we employ econometric models to explore how the influence of COVID-19 on these stock markets varies by considering the interconnectedness structure, the government response stringency index, and other country-level characteristics. We find that the interconnectedness structure significantly and robustly affects stock returns in the tourism and hospitality markets. Our investigation provides a better understanding of the impact of COVID-19 on tourism and hospitality industry. © 2022 Elsevier Inc.

Integration of a hybrid scan approach and in-house high-resolution MS2 spectral database for charactering the multicomponents of Xuebijing Injection

Xuebijing (XBJ) Injection is a reputable patent Chinese medicine widely used to cure sepsis, among the Chinese ″Three Medicines and Three Prescriptions″ solution to fight against COVID-19. We were aimed to achieve the comprehensive multicomponent characterization from the single drugs to traditional Chinese medicine (TCM) formula, by integrating powerful data acquisition and the in-house MS2 spectral database searching. By ultra-high performance liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (UHPLC/IM-QTOF-MS), a hybrid scan approach (HDMSE-HDDDA) was developed, while the HDMSE data for five component drugs and 56 reference compounds were acquired and processed to establish an in-house MS2 spectral database of XBJ. Good resolution of the XBJ components was accomplished on a Zorbax Eclipse Plus C18 column within 24 min, while a fit-for-purpose HDMSE-HDDDA approach was elaborated in two ionization modes for enhanced MS2 data acquisition. XBJ MS2 spectral library was thus established on the UNIFITM platform involving rich structure-related information for the chemicals from five component drugs. We could identify or tentatively characterize 294 components from XBJ, involving 81 flavonoids, 51 terpenoids, 42 phthalides, 40 organic acids, 13 phenylpropanoids, seven phenanthrenequinones, six alkaloids, and 54 others. In contrast to the application of conventional MS1 library, this newly established strategy could demonstrate superiority in the accuracy of identification results and the characterization of isomers, due to the more restricted filtering/matching criteria. Conclusively, the integration of the HDMSE-HDDDA hybrid scan approach and the in-house MS2 spectral database can favor the efficient and more reliable multicomponent characterization from single drugs to the TCM formula. © 2022 The Author(s)

FingerDTA: A Fingerprint-Embedding Framework for Drug-Target Binding Affinity Prediction

Many efforts have been exerted toward screening potential drugs for targets, and conducting wet experiments remains a laborious and time-consuming approach. Artificial intelligence methods, such as Convolutional Neural Network (CNN), are widely used to facilitate new drug discovery. Owing to the structural limitations of CNN, features extracted from this method are local patterns that lack global information. However, global information extracted from the whole sequence and local patterns extracted from the special domain can influence the drugtarget affinity. A fusion of global information and local patterns can construct neural network calculations closer to actual biological processes. This paper proposes a Fingerprint-embedding framework for Drug-Target binding Affinity prediction (FingerDTA), which uses CNN to extract local patterns and utilize fingerprints to characterize global information. These fingerprints are generated on the basis of the whole sequence of drugs or targets. Furthermore, FingerDTA achieves comparable performance on Davis and KIBA data sets. In the case study of screening potential drugs for the spike protein of the coronavirus disease 2019 (COVID-19), 7 of the top 10 drugs have been confirmed potential by literature. Ultimately, the docking experiment demonstrates that FingerDTA can find novel drug candidates for targets. All codes are available at http://lanproxy.biodwhu.cn:9099/mszjaas/FingerDTA.git. © 2018 Tsinghua University Press.

Prevalence of psychological symptoms and associated risk factors among nurses in 30 provinces during the COVID-19 pandemic in China: Prevalence of psychological symptoms among Chinese nurses

Background: With the outbreak of the coronavirus disease 2019 (COVID-19), nurses have won well-deserved recognition for their indispensable roles in providing humane and professional healthcare for patients. However, by the nature of their role working at the forefront of patient care, nurses are prone to experiencing mental health consequences. Therefore, we pay attention to measuring the magnitude of psychological symptoms and identifying associated factors among nurses in China. Methods: We launched a nationwide, cross-sectional survey of nurses who worked in secondary or tertiary hospitals and public or private hospitals from 30 provinces in China. The prevalence and severity of symptoms of burnout, depression, and anxiety were investigated, respectively. Multivariable logistic regression analyses were performed to identify factors associated with each psychological symptom. Findings: A total of 138 279 respondents who worked in 243 hospitals completed this survey. A substantial proportion of nurses reported symptoms of burnout (34%), depression (55·5%), and anxiety (41·8%). In line with the disproportionality of economic development, we noted that the middle or western region was an independent risk factor for depression and anxiety. Compared with those working in the secondary hospital, nurses who worked in tertiary hospitals were associated with a higher likelihood of burnout and depression. Interpretation: Nurses are experiencing emotional, physical, and mental exhaustion during the COVID-19 epidemic. Governments and health policymakers need to draw attention to reinforcing prevention and ameliorating countermeasures to safeguard nurses' health. Funding: The strategic consulting project of the Chinese Academy of Engineering [2021-32-5]. Advanced Institute of Infomation Technology, Peking University, Zhejiang Province [2020-Z-17] © 2022 The Author(s)

Important scoring systems for assessing the severity of COVID-19 based on COVID-19-related deaths in Wuhan, China

Background: This study aimed to investigate the clinical characteristics of 21 deaths and evaluate potential factors affecting disease severity and mortality risk in patients with coronavirus disease (COVID-19). Methods: This retrospective analysis assessed clinical data of 21 patients who died owing to COVID-19. Disease severity and mortality risk were assessed using Acute Physiology and Chronic Health Evaluation II (APACHE II);Sepsis-related Organ Failure Assessment (SOFA);multilobular infiltration, hypo-lymphocytosis, bacterial coinfection, smoking history, hypertension and age (MuLBSTA);and pneumonia severity index (PSI) scores. Results: The mean age of the patients was 66 ± 14 years and 15 (71.4%) patients were men. Sixteen (76.2%) patients had chronic medical illnesses. Twelve (57.1%) patients were overweight. Decreased lymphocyte proportions were observed in 17 (81.0%) patients on admission. Elevated D-dimer levels were observed in 11 (52.4%) patients, and the levels significantly increased when pneumonia deteriorated. The initial APACHE II and SOFA scores demonstrated that 18 (85.7%) and 13 (61.9%) patients, respectively, were in the middle-risk level. MuLBSTA and PSI scores after admission were associated with higher risks of mortality in 13 (61.9%) patients. Most patients developed organ failure and subsequently died. Conclusions: Older, overweight, male patients with a history of chronic illnesses and continuously decreased lymphocyte proportions and increased D-dimer levels might have higher risks of death owing to COVID-19. The combination of general scoring (SOFA) and pneumonia-specific scoring (MuLBSTA and PSI) systems after admission might be sensitive in assessing the mortality risk of patients with COVID-19 who are in critical condition. Copyright © 2021 Shandong University, published by Wolters Kluwer, Inc.

Post-hospitalisation respiratory and physical functions in patients with SARS-CoV-2 delta.

BACKGROUND Despite growing concern regarding the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) delta variant of concern (VOC), the respiratory and physical functions of patients with delta VOC post-discharge have not been investigated compared to those of patients with ancestral SARS-CoV-2.METHODS Sixty-three discharged patients with coronavirus disease (COVID-19) were included. Patients were divided into delta VOC and ancestral SARS-CoV-2 groups. On Day 14 post-discharge, differences in chest computed tomography, modified Medical Research Council and Borg Dyspnoea Scale scores, and Manual Muscle Test scores were compared. Prognoses of respiratory and physical function were compared between patients who recovered from moderate and severe COVID-19.RESULTS Of the 63 patients, respectively 28 and 35 were in the delta VOC and ancestral SARS-CoV-2 groups. On Day 14 post-discharge, 35 patients (56.5%) had abnormalities on imaging. Visual semi-quantitative scores of both lungs were significantly higher in the severe group. However, there was no difference in this or any other score ratings between the groups.CONCLUSION At 14 days post-discharge, ground glass opacities and pleural thickening were the most common residual findings; no difference in respiratory and physical functions during the convalescence period were noted in patients with SARS-CoV-2 delta VOC and ancestral SARS-CoV-2.

The impact of some economic and financial variables on the employment change during Covid-19 in China

This chapter examines the impact of some economic and financial variables on the employment change covering the period of Covid-19 in China. We apply the annual data of China during the period of 1989-2019 by building a long-term model and find that industrial upgrading and economically active population cause economic development, along with the increase of unemployment population. The results show a reverse change in variables of GDP and registered unemployed persons in urban areas. We then apply the quarterly data of 2019-2020 by constructing a short-term model and find that GDP and unemployment conditions still show a reverse change. Because of the lag effect, the increase in national financial expenditure is not associated with a slowdown in the employment market;a rise in GDP or business prosperity is consistent with a fall in unemployment. The Vector Autoregression Model thus provides an empirical prediction of recovery in labour markets of China. © 2022 World Scientific Publishing Company.