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Dayuanyin (DYY) has been shown to reduce lung inflammation in both coronavirus disease 2019 (COVID-19) and lung injury. This experiment was designed to investigate the efficacy and mechanism of action of DYY against hypoxic pulmonary hypertension (HPH) and to evaluate the effect of DYY on the protection of lung function. Animal welfare and experimental procedures are approved and in accordance with the provision of the Animal Ethics Committee of the Institute of Materia Medica, Chinese Academy of Medical Science. Male C57/BL6J mice were randomly divided into 4 groups: control group, model group, DYY group (800 mg.kg-1), and positive control sildenafil group (100 mg.kg-1). The animals were given control solvents or drugs by gavage three days in advance. On day 4, the animals in the model group, DYY group and sildenafil group were kept in a hypoxic chamber containing 10% +/- 0.5% oxygen, and the animals in the control group were kept in a normal environment, and the control solvent or drugs continued to be given continuously for 14 days. The right ventricular systolic pressure, right ventricular hypertrophy index, organ indices and other metrics were measured in the experimental endpoints. Meantime, the expression levels of the inflammatory factors in mice lung tissues were measured. The potential therapeutic targets of DYY on pulmonary hypertension were predicted using network pharmacology, the expression of nuclear factor kappa B (NF- kappaB) signaling pathway-related proteins were measured by Western blot assay. It was found that DYY significantly reduced the right ventricular systolic pressure, attenuated lung injury and decreased the expression of inflammatory factors in mice. It can also inhibit hypoxia-induced activation of NF- kappaB signaling pathway. DYY has a protective effect on lung function, as demonstrated by DYY has good efficacy in HPH, and preventive administration can slow down the disease progression, and its mechanism may be related to inhibit the activation of NF-kappaB and signal transducer and activator of transcription 3 (STAT3) by DYY.Copyright © 2023, Chinese Pharmaceutical Association. All rights reserved.
ABSTRACT
Dayuanyin (DYY) has been shown to reduce lung inflammation in both coronavirus disease 2019 (COVID-19) and lung injury. This experiment was designed to investigate the efficacy and mechanism of action of DYY against hypoxic pulmonary hypertension (HPH) and to evaluate the effect of DYY on the protection of lung function. Animal welfare and experimental procedures are approved and in accordance with the provision of the Animal Ethics Committee of the Institute of Materia Medica, Chinese Academy of Medical Science. Male C57/BL6J mice were randomly divided into 4 groups: control group, model group, DYY group (800 mg.kg-1), and positive control sildenafil group (100 mg.kg-1). The animals were given control solvents or drugs by gavage three days in advance. On day 4, the animals in the model group, DYY group and sildenafil group were kept in a hypoxic chamber containing 10% +/- 0.5% oxygen, and the animals in the control group were kept in a normal environment, and the control solvent or drugs continued to be given continuously for 14 days. The right ventricular systolic pressure, right ventricular hypertrophy index, organ indices and other metrics were measured in the experimental endpoints. Meantime, the expression levels of the inflammatory factors in mice lung tissues were measured. The potential therapeutic targets of DYY on pulmonary hypertension were predicted using network pharmacology, the expression of nuclear factor kappa B (NF- kappaB) signaling pathway-related proteins were measured by Western blot assay. It was found that DYY significantly reduced the right ventricular systolic pressure, attenuated lung injury and decreased the expression of inflammatory factors in mice. It can also inhibit hypoxia-induced activation of NF- kappaB signaling pathway. DYY has a protective effect on lung function, as demonstrated by DYY has good efficacy in HPH, and preventive administration can slow down the disease progression, and its mechanism may be related to inhibit the activation of NF-kappaB and signal transducer and activator of transcription 3 (STAT3) by DYY.Copyright © 2023, Chinese Pharmaceutical Association. All rights reserved.
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There is an emerging shift in human-computer interaction (HCI) research from things to events and towards time and temporality as a design material, which is made even more urgent by the unique time of the COVID-19 period. This paper pushes this shift forwards by investigating factors and the way that these shape online media multitasking behaviour over time during COVID-19. We model the factors along the WHAT and HOW dimensions of the HCI-over-Time model (HCIoT) with self-report data from 117 university students and objective behavioural data from 40 university students, who participated in an online course over 2 weeks during COVID-19. The results indicated a pervasiveness of media multitasking behaviour over time in an online course, driven by individual factors and enhanced by their mutual fit. Based on interpretation of our data, we suggest conceptualizing the COVID-19 period as the larger temporal environment in the HCIoT model. The discussion further explains how the broader idea of human-computer-environment fit is significant to understand HCIoT through an interaction lens. We discuss methodological issues related to differentiating between self-report and behavioural measures when applying the HCIoT model. The conclusion supports the feasibility and significance of conceptualizing media multitasking during COVID-19 as temporal HCI and of further developing and operationalizing the HCIoT model by using both behavioural and self-report measures.
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Under the impact of COVID-19, the global economy exhibits obvious slowdown. In such situation, the issues on how to keep balance between supply and demand in SCM (Supply Chain Management) operation have been more apparent than before. For SCM rebuilding, S&OP received extensive attention worldwide. However, there are few examples of successful implementation of S&OP in Japan because Japanese have not been growing accustomed to the phrase S&OP, although the challenges in SCM operations and PSI (Product, Sales, Inventory) management are recognized. Thus, no clear and exact solution is found to guide the operation. In order to further improve the current management level, a new design proposal of data model is rendered to advance the current PSI management that introduces the concepts of S&OP. Especially, we will address the motivation why we need use multidimensional database architecture to design the S&OP process instead of using RDB (Relational Database) which is often used in ERP (Enterprise Resource Planning). © 2022 IEEE.
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Background Taletrectinib is a potent, next-generation, CNS-active, ROS1 tyrosine kinase inhibitor (TKI) with selectivity over TRKB. In previous reports from TRUST-I, taletrectinib showed meaningful clinical efficacy and was well tolerated in pts with ROS1+ NSCLC (n = 109) regardless of crizotinib (CRZ) pretreatment status. We report updated efficacy and safety data with ~1.5 yr follow-up. Methods TRUST-I is a multicenter, open-label, single-arm study with two cohorts: ROS1 TKI-naive and CRZ-pretreated. Pts in both cohorts received taletrectinib 600 mg QD. Key study endpoints included IRC-confirmed ORR (cORR), DoR, disease control rate (DCR), PFS, and safety. A pooled analysis of ORR, PFS, and safety including pts from additional clinical trials was also conducted. Results In the 109 pts from TRUST-I (enrolled prior to Feb 2022) the median follow-up was 18.0 mo in TKI-naive (n = 67) and 16.9 mo in CRZ-pretreated pts (n = 42). cORR was 92.5% in TKI-naive and 52.6% in CRZ-pretreated pts (table). Median DoR (mDoR) and mPFS were not reached. Intracranial-ORR was 91.6%;ORR in pts with G2032R was 80.0%. In a pooled analysis with phase I studies, ORR was 89.5% and 50.0% for TKI-naive and CRZ-pretreated pts, respectively;mPFS was 33.2 mo and 9.8 mo. In 178 pts treated at 600 mg QD, treatment-emergent adverse events (TEAEs) were 92.7%;most (64.0%) were grade 1-2. The most common TEAEs were increased AST (60.7%), increased ALT (55.6%), and diarrhea (55.6%). Neurological TEAEs (dizziness, 18.5%;dysgeusia, 12.4%) and discontinuations due to TEAEs (3.4%) were low. Further updated results will be presented. [Formula presented] Conclusions With additional follow-up, taletrectinib continued to demonstrate meaningful efficacy outcomes including high response rates, prolonged PFS, robust intracranial activity, activity against G2032R, and tolerable safety with low incidence of neurological AEs. Clinical trial identification NCT04395677. Editorial acknowledgement Medical writing and editorial assistance were provided by Arpita Kulshrestha of Peloton Advantage, LLC, an OPEN Health company, and funded by AnHeart Therapeutics, Inc Legal entity responsible for the study AnHeart Therapeutics, Inc. Funding AnHeart Therapeutics, Inc. Disclosure S. He: Financial Interests, Personal, Other, Employment: AnHeart Therapeutics. T. Seto: Financial Interests, Institutional, Research Grant: AbbVie, Chugai Pharmaceutical, Daiichi Sankyo, Eli Lilly Japan, Kissei Pharmaceutical, MSD, Novartis Pharma, Pfizer Japan, Takeda Pharmaceutical;Financial Interests, Personal, Other, Employment: Precision Medicine Asia;Financial Interests, Personal, Speaker's Bureau, Honoraria for lectures: AstraZeneca, Bristol-Myers Squibb, Chugai Pharmaceutical, Covidien Japan, Daiichi Sankyo, Eli Lilly Japan, Kyowa Hakko Kirin, MSD, Mochida Pharmaceutical, Nippon Boehringer Ingelheim, Novartis Pharma, Ono Pharmaceutical, Pfizer Japan, Taiho Pharmaceutical, Takeda Pharmaceutical, Towa Pharmaceutical. C. Zhou: Financial Interests, Personal, Other, Consulting fees: Innovent Biologics Qilu, Hengrui, TopAlliance Biosciences Inc;Financial Interests, Personal, Speaker's Bureau, Payment or honoraria: Eli Lilly China, Sanofi, BI, Roche, MSD, Qilu, Hengrui, Innovent Biologics, C-Stone LUYE Pharma, TopAlliance Biosciences Inc, Amoy Diagnositics, AnHeart. All other authors have declared no conflicts of interest.Copyright © 2023 International Association for the Study of Lung Cancer. Published by Elsevier Inc.
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The Global Justice Index is a multiyear research project based at Fudan Institute for Advanced Study in Social Sciences that assesses the contributions made by each country to achieving greater global justice. We have published results from 2010 to 2019 in Global Justice Index Report, Global Justice Index Report 2020, Global Justice Index Report 2021, and we are now presenting our fourth-year results for 2020 in Global Justice Index Report 2022, which is an updated version of previous years' reports. This year, we take into account changes to global justice influenced by the COVID-19 pandemic. The report consists of four sections: introduction, findings, main results, and conclusion. In the introduction, we discuss the development of the conceptual framework and evaluative principles to justify our selection of the dimensions and indicators for measurement. Next, in the findings section, we report the data, indicators, and our results for each country for each of the 10 issues we identify, and provide regional comparisons for Asia, Europe, North America, Latin America, Africa, and Oceania. In the following section, we present the main results for the global justice indices, and report the ranking of each country's contribution to achieving greater global justice. In the final section, we discuss the applications and limitations of the index and potential further research trajectories. © 2023, The Author(s).
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Introduction: The respiratory tract infections (RTIs), including pneumonia, influenza and Coronavirus Disease 2019 (COVID-19), are the leading cause of hospitalization and mortality worldwide, contributing to elevated healthcare and societal costs. There is conflicting evidences about the effects of angiotensin converting enzyme inhibitor (ACEIs) or angiotensin II receptor blockers (ARBs) on the susceptibility of RTIs. Method(s): Systematic review of interventional and observational studies that reported use of ACEI or/and ARB on incidence of pneumonia or influenza or COVID-19. Searching was conducted in the databases of PubMed, Excerpta Medica Database (Embase), Web of Science, Cochrane Central Register of Controlled Trials (CENTRAL), including the Cochrane Library until April 2022, and references of retrieved relevant articles. We assessed the quality of included studies by using Cochrane Collaboration Risk of Bias tool for Randomized Controlled Trials and Newcastle-Ottawa Scale for observational studies. DerSimonian Laird random-effects meta-analysis was conducted to pool effects for the incidence of pneumonia, influenza and COVID-19. Subgroup analyses were carried according to baseline morbidities (hypertension or cardiovascular diseases, cerebrovascular diseases, chronic kidney disease (CKD) and other non-communicable diseases). Pooled estimates of odds ratios (OR) and corresponding 95% confidence intervals (95% CI) were computed, and heterogeneity among studies was assessed using Cochran's Q test and the I2 metrics, with two tailed P values. Result(s): 73 studies met the inclusion criteria, of which 38 studies assessed the odds of pneumonia, 32 studies assessed Covid-19 and 3 studies assessed influenza. The quality of included studies was moderate. Use of ACEIs was associated with a significantly reduced odds of pneumonia (23 studies: OR 0.74, 95% CI 0.64 to 0.85;I2=76.8%), of COVID-19 (24 studies: OR 0.87, 95% CI 0.82 to 0.92;I2=81.9%) and influenza (3 studies: OR 0.75, 95% CI 0.57 to 0.98, I2=97.7%), compared with control treatment. Use of ARBs was also associated with reduced odds of COVID-19 (25 studies: OR 0.90, 95% CI 0.83 to 0.97;I2=91.9%), but not with odds of pneumonia or influenza. These findings remain consistent in the community population, patients with history of cerebrovascular diseases or cardiovascular diseases, but not in those with CKD, diabetes and chronic obstructive pulmonary diseases. Conclusion(s): The current evidence favours a putative protective role of ACEIs, not ARB in odds of pneumonia, COVID-19 and influenza. Patient populations that may benefit most are those within the community, history of cerebrovascular diseases and cardiovascular diseases. No conflict of interestCopyright © 2023
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Depression is one of the leading factors in global disability and a top driver for suicides. Studies have shown that depression has an effect on language usage. In recent years, especially during the COVID pandemic, social media platforms have become the de facto platform for many individuals to self-disclose or discuss mental health issues like depression. This trend presents a unique opportunity for researchers and healthcare professionals to detect potential mental illnesses for early intervention or treatment by taking advantage of the recent advances in machine learning approaches. Existing depression detection methods on social media, however, suffer from two major limitations. First, these solutions heavily rely on the amount, quality, and type of user-posted content. Second, the overlooked social circle impact should be leveraged to enhance the prediction capabilities. In this paper, we propose a depression detection framework, MentalNet, based on heterogeneous graph convolution by capturing users' interactions (replies, mentions, and quotetiveets) with their friends on social media and differentiating the intimacy of users' social circles (e.g., family, friends, or acquaintances). Specifically, we formulate the problem of depression detection on social media as a graph classification problem by representing users' social circles in the format of heterogeneous graphs. MentalNet embraces three modules, (1) extraction of ego-network node features, (2) construction of user interaction graphs, and (3) depression detection based on heterogeneous graph classification. The extensive experiments on Twitter data demonstrate that MentalNet consistently and significantly outperforms the state-of-the-art methods in terms of all the effectiveness metrics. Compared to the baseline methods, MentalNet is able to effectively predict early depression in Twitter users with up to 24% improvement on F1 score. © 2022 IEEE.
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Background: COVID-19 vaccines are important for patients with heart failure (HF) to prevent severe outcomes but the safety concerns could lead to vaccine hesitancy. This study aimed to investigate the safety of two COVID-19 vaccines, BNT162b2 and CoronaVac, in patients with HF. Methods: We conducted a self-controlled case series analysis using the data from the Hong Kong Hospital Authority and the Department of Health. The primary outcome was hospitalization for HF and the secondary outcomes were major adverse cardiovascular events (MACE) and all hospitalization. We identified patients with a history of HF before February 23, 2021 and developed the outcome event between February 23, 2021 and March 31, 2022 in Hong Kong. Incidence rate ratios (IRR) were estimated using conditional Poisson regression to evaluate the risks following the first three doses of BNT162b2 or CoronaVac. Findings: We identified 32,490 patients with HF, of which 3035 were vaccinated and had a hospitalization for HF during the observation period (BNT162b2 = 755;CoronaVac = 2280). There were no increased risks during the 0–13 days (IRR 0.64 [95% confidence interval 0.33–1.26];0.94 [0.50–1.78];0.82 [0.17–3.98]) and 14–27 days (0.73 [0.35–1.52];0.95 [0.49–1.84];0.60 [0.06–5.76]) after the first, second and third doses of BNT162b2. No increased risks were observed for CoronaVac during the 0–13 days (IRR 0.60 [0.41–0.88];0.71 [0.45–1.12];1.64 [0.40–6.77]) and 14–27 days (0.91 [0.63–1.32];0.79 [0.46–1.35];1.71 [0.44–6.62]) after the first, second and third doses. We also found no increased risk of MACE or all hospitalization after vaccination. Interpretation: Our results showed no increased risk of hospitalization for HF, MACE or all hospitalization after receiving BNT162b2 or CoronaVac vaccines in patients with HF. Funding: The project was funded by a Research Grant from the Food and Health Bureau, The Government of the Hong Kong Special Administrative Region (Ref. No. COVID19F01). F.T.T.L. (Francisco T.T. Lai) and I.C.K.W. (Ian C.K. Wong)'s posts were partly funded by the D24H;hence this work was partly supported by AIR@InnoHK administered by Innovation and Technology Commission. © 2022 The Authors
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The wide spread of the coronavirus (COVID-19) has significantly impacted the global human activities. Compared to numerous studies on conventional air pollutants, atmospheric mercury that has matched sources from both anthropogenic and natural emissions is rarely investigated. At a regional site in eastern China, an intensive measurement was performed, showing obvious decreases in gaseous elemental mercury (GEM) during the COVID-19 lockdown, while it was not as significant as most of the other measured air pollutants. Before the lockdown, when anthropogenic emissions dominated, GEM showed no correlation with temperature and negative correlations with wind speed and the height of the boundary layer. In contrast, GEM showed significant correlation with temperature, while the relationship between GEM and the wind speed/boundary layer disappeared during the lockdown, suggesting the enhanced natural emissions of mercury. By applying a machine learning model and the SHAP (SHapley Additive exPlanations) approach, it was found that the mercury pollution episodes before the lockdown were driven by anthropogenic sources, while they were mainly driven by natural sources during and after the lockdown. Source apportionment results showed that the absolute contribution of natural surface emissions to GEM unexpectedly increased (44 %) during the lockdown. Throughout the whole study period, a significant negative correlation was observed between the absolute contribution of natural and anthropogenic sources to GEM. We conclude that the natural release of mercury could be stimulated to compensate for the significantly reduced anthropogenic GEM via the surface-air exchange in the balance of mercury.
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SARS-CoV-2 has caused a global pandemic unseen for nearly a century. To date hundreds of millions of people have been diagnosed and millions more have died from COVID-19 disease;many of which are in groups with comorbidities. Obesity is associated with a 3.07 times higher risk of hospitalization and a 1.42 times higher risk of severe illness. However, our understanding of obesityaccelerated severity of COVID-19 is limited. To model the increased disease severity of obese individuals with COVID-19, we used a humanized ACE2 (hACE2) transgenic mouse model, in which hACE2 is under the cytokeratin-18 promoter (K18). Modeling the effects of obesity on COVID-19 in K18-hACE2 mice will help us better understand the mechanisms underlying obesity-accelerated severity of COVID-19 disease and inflammation. We have developed a study in which K18 hACE2 mice infected with SARS-CoV-2 were fed both a normal standard diet as well as a western high fat and carbohydrate diet that causes them to gain excess weight and become obese over a period of 3 months. K18-hACE2 obese mice lose a signifyingly more percentage body weight over both a 7 (acute) 14 day (long-term) period than normal diet fed mice do after infection with SARS-CoV-2. H&E staining analysis of lung histological changes indicated a dramatic increase in inflammation in our K18 hACE2 obese mice infected with SARS-CoV-2 . Subgenomic qPCR and IHC staining was used to quantify virus (viral titer) which indicated that in both of our diet groups after infection did not have a significantly different SARS-CoV-2 viral load. No significant difference in the SARS-CoV-2 viral load was detected at either 7 or 14 dpi with SARS-CoV-2 . We further measured adipokines with an ELISA on two of the most notable adipokines: leptin and adiponectin. Levels of leptin were significantly higher in our obese K18-hACE2 mice but not in our normal mice after infection. There was no difference however in the levels of adiponectin. Obese K18-hACE2 mice show a more severe COVID 19 phenotype than normal diet mice after infection and can be used to further study the underlying mechanism of how SARS-CoV-2 infection in obese individuals causes a more severe disease phenotype.
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The COVID-19 outbreak has drawn attention to viral infectious diseases once again, and the development of antiviral drugs for both known and potentially emerging viruses is of great significance. In recent years, peptides and protein drugs are becoming a hot spot in the field of antiviral drug research and development. Phage display technology, as a powerful tool for screening peptides and protein drugs, has been increasingly concerned in the academic and industrial fields. The present review introduced the basic principle of phage display technology, summarized phage display libraries often used in antiviral drug discovery and their applications, discussed the challenges and future direction of antiviral drug research and development based on phage display technology.
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The Sustainable Development Goals call for taking urgent action to combat climate change and reduce inequalities. However, the related actions have not been effective. Global CO2 emissions in 2021 are projected to rebound to approaching the 2018–2019 peak, and wealth inequality has been increasing at the very top of the distribution resulting from the COVID-19 pandemic. To test whether a trade-off exists between social and environmental benefits, this study calculates county-level wealth inequality with the Gini coefficient and consumption-based household carbon emissions with the emissions coefficient method and input–output modeling. Data are collected from the China Family Panel Studies, the Visible Infrared Imaging Radiometer Suite, the Chinese National Bureau of Statistics and Carbon Emission Account and Datasets in 2014, 2016 and 2018. In addition, a high-dimensional fixed-effects model, an instrumental variable model and causal mediation analysis are adopted to empirically test how wealth inequality influences household carbon emissions and explore the underlying mechanisms. The results show that county-level wealth inequality has a positive impact on household carbon emissions per capita. This means that policies designed to narrow the wealth gap can help reduce carbon emissions, making progress toward multiple SDGs. Moreover, the study reveals that the social norms of the Veblen effect and short-termism play an important role in mediating the relationship between wealth inequality and consumption-based household carbon emissions. This finding provides a new perspective to understand the mechanism behind wealth inequality and household carbon emissions related to climate change. Copyright © 2022 Qin, Wu, Zhang and Wang.
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The Covid pandemic had turned the world upside down, but not much is known about how people’s empathy toward others in difficult situations might be affected by the pandemic. Based on a nationally representative sample (N = 943) from China, this study first let participants read three real scenarios and then measured: (1) how empathy toward others might be influenced by the perceived social support people obtained by using social media (i.e., WeChat);and (2) how different demographics such as age and gender as well as lockdown situations may affect preserving empathetic during the Covid outbreak. Results show that perceived social support via WeChat not only positively impacted empathy but also interacted with anxiety in influencing the degree to which participants could maintain empathy toward others. Those living in cities or towns with higher incomes were more empathetic to others. While anxiety does not necessarily decrease empathy, those who reported gaining more social support on social media showed more empathy toward others despite their elevated levels of anxiety. Age negatively predicted empathy, but gender and lockdown conditions did not impact empathy. This study contributes to the literature by identifying the critical role empathy plays in people’s affective response to others during a public health crisis. © The Author(s) 2022.
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With the outbreak of the novel coronavirus pneumonia (COVID-19), urban traffic control is an important measure to block the spread and control the development of the epidemic. In this study, to elucidate the blocking effects of different traffic control measures on the transmission of COVID-19 within city territories, the four administrative cities of Jingzhou, Xiaogan, Jingmen, and Shijiazhuang were selected as the study areas. The situation of the epidemic before and after the implementation of three typical traffic control measures-road closure, passenger traffic stoppage, and community population flow control-was analyzed. Based on the classical dynamics theory of infectious diseases, an optimized epidemic transmission susceptible, infectious, removed, exposed (SEIR) model was established, considering the infectivity of the exposed, population migration, and population flow in urban communities. Thereafter, the model was used to study the blocking effects based on whether traffic control measures were implemented in each city and the various traffic control measures on the development of the epidemic. The results indicate that the daily incidence rate of each city is related to the immigration index of approximately 14 days ago;the traffic control measures adopted by each city are also highly effective in blocking the spread of the epidemic. Compared with no traffic control measures, the peak numbers of infected persons in Jingzhou, Xiaogan, Jingmen, and Shijiazhuang decreased by 61.29%, 53.71%, 66.16%, and 66.33%, respectively. The blocking effects of the three control measures exhibit a few differences. The blocking effect of road closure measures is the most prominent;the numbers of latent and infected persons can be reduced by 40.54%-70.88% and 49.11%-64.34%, respectively, using different implementation nodes. Furthermore, a timely and comprehensive implementation of the three traffic control measures can effectively block the spread of the epidemic and control the development of the epidemic in cities. This improved SEIR model, which considers the characteristics of the incubation period, can accurately predict the development trends of the epidemic, thus serving as a technical reference for the formulation of urban traffic control plans over the duration of the epidemic. © 2022, Editorial Department of China Journal of Highway and Transport. All right reserved.
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Background: The impact of the Coronavirus Disease 2019 (COVID-19) pandemic on people's mental health has been gradually revealed. Emotional responses under this pandemic have been a focus. This study aimed to observe the time map and predictors of transient daily emotions (on-spot emotional responses) during the COVID-19 outbreak in Chinese people. Methods: A total of 133,027 Chinese people from all cities and areas of China took part in this 25-day online investigation from January 27 to February 20, 2020. Hierarchical regression was carried out. Results: Chinese people reported mild positive and negative emotions during COVID-19, and the trend was that negative emotions declined and happy emotion increased in a curvilinear style. Females reported stronger on-spot negative emotions. Young and unmarried people, and individuals with lower risk perception reported lower negative emotions and higher happiness, while people with postgraduate or higher education, medical staff and patients, and individuals coming from areas with more confirmed cases, experienced stronger positive and negative emotions. In the regression model, risk predictors of negative emotions were being female, being older in age, having postgraduate or higher education, living in a city with more confirmed cases, being a patient or medical staff, and having higher risk perception, while protective predictors of negative emotions were being unmarried, having high-school or college education, and later investigating date. Notably, been married was negative predictor of happiness. Conclusions: This large sample, 25-day successive online investigation is among the first to reveal the time map of on-spot emotions in Chinese people under the COVID-19 pandemic. The risk and protective predictors of on-spot negative emotions help to recognize vulnerable people under pandemic conditions and further develop more targeted early interventions for future crises. © 2021 The Authors
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Objective To summarize the clinical characteristics of patients with coronavirus disease 2019 (COVID-19) infected with Delta variant, so as to provide further references for clinical diagnosis and treatment. Methods A real-world study was conducted to analyze the characteristics of 166 COVID-19 patients infected with Delta variant at Guangzhou Eighth People’s Hospital, Guangzhou Medical University. Results The study enrolled 5 asymptomatic cases, 123 non-severe cases (mild and moderate type), and 38 severe cases (severe and critical type). Among these patients, 69 (41.6%) were male and 97 (58.4%) were female, with a mean age of 47.0±23.5 years. Thirty-nine cases (23.5%) had received 1 or 2 doses of inactivated vaccine. The incidence of severe COVID-19 cases was 7.7% in 2-doses vaccinated patients, which was lower than that of 11.5% in 1-dose and 26.8% in unvaccinated patients. The proportion of severe cases in 2 dose-vaccinated patients was 7.7%, which was lower than that of 11.5% in 1-dose vaccinated patients and 26.8% in unvaccinated patients, but the difference was not significant (P>0.05). The most common clinical symptom was fever (134 cases, 83.2%), and 39.1% of cases presented with high-grade fever (≥ 39 °C);other symptoms were cough, sputum, fatigue, and xerostomia. The proportion of fever in severe cases was significantly higher than that of non-severe cases (97.4% vs. 76.4%, P<0.01). Similarly, the proportion of severe cases with high peak temperature (≥ 39 ℃) () was also higher than that of non-severe cases (65.8% vs. 30.9%, P<0.01). The median minimal Cycle threshold (Ct) values of viral nucleic acid N gene and ORFlab gene were 20.3 and 21.5, respectively, and the minimum Ct values were 11.9 and 13.5, respectively. Within 48 h of admission, 9.0% of cases presented with decreased white blood cell counts, and 52.4% with decreased lymphocyte counts. The proportions of increased C-reactive protein, serum amyloid A, interleukin 6, and interleukin 10 were 32.5%, 57.4%, 65.3%, and 35.7%, respectively. The proportions of elevated C-reactive protein, serum amyloid A and interleukin-6 in severe cases were significantly higher than those in non-severe cases (P<0.01). Logistic regression analysis showed that older age and higher peak temperature were associated with a higher likelihood of severe cases (OR>3, 95% CI: 2-7, P<0.01). In terms of treatment, traditional Chinese medicine (TCM) was used in 97.6% of non-severe cases and 100% in severe cases. Other treatments included respiratory and nutritional support, immunotherapy (such as neutralizing antibodies and plasma of recovered patients). The median times from admission to progression to severe cases, of fever clearance, and of nucleic acid conversion were 5 days, 6 days and 19 days, respectively. No deaths were reported within 28 days. Conclusions The symptoms of Delta variant infection in Guangzhou are characterized by a high proportion of fever, high peak temperature, long duration of fever, high viral load, a long time to nucleic acid conversion, and a high incidence of severe cases. The severe cases exhibit a higher percentage of elderly patients, a longer duration of fever and have a higher fever rate and a higher hyperthermia rate than non-severe cases. Age and hyperthermia are independent risk factors for progression to severe disease. The combination of TCM and Western medicine can control the progression of the disease effectively. © 2021 Chinese Medical Association. All rights reserved.