ABSTRACT
Mental stress has been recognized as an essential risk factor for hypertension. Therefore, experts specializing in cardiology, psychiatry, and Traditional Chinese Medicine organized by the Psycho-cardiology Group, College of Cardiovascular Physicians of Chinese Medical Doctor Association, and Hypertension Group of the Chinese Society of Cardiology proposed the expert consensus on the diagnosis and treatment of adult mental stress-induced hypertension in March 2021, which includes the epidemiology, etiology, diagnosis, and treatment of the mental stress-induced hypertension. This consensus will hopefully facilitate the clinical practice of this disorder. In addition, the COVID-19 pandemic has become one of the primary global sources of psychosocial stressors since the beginning of 2020, and the revision of this expert consensus in 2022 has increased the relevant content. This consensus consists of two parts. The sections of Part A include (I) Background and epidemiological characteristics, (II) Pathogenesis, and (III) Diagnosis. The sections of Part B contain (IV) Treatment recommendations, and (V) Prospects. This article presents Part B of the consensus. © 2022 Heart and Mind ;Published by Wolters Kluwer - Medknow.
ABSTRACT
Mental stress has been recognized as an essential risk factor for hypertension. Therefore, experts specializing in cardiology, psychiatry, and Traditional Chinese Medicine organized by the Psycho-Cardiology Group of College of Cardiovascular Physicians of Chinese Medical Doctor Association and Hypertension Group of Chinese Society of Cardiology proposed the expert consensus on the diagnosis and treatment of adult mental stress-induced hypertension in March 2021, which includes the epidemiology, etiology, diagnosis, and treatment of the mental stress-induced hypertension. This consensus will hopefully facilitate the clinical practice of this disorder. In addition, the COVID-19 pandemic has become one of the primary global sources of psychosocial stressors since the beginning of 2020, and the revision of this expert consensus in 2022 has increased the relevant content. This consensus consists of Part A and Part B. Part A includes (I) Background and epidemiological characteristics, (II) Pathogenesis, and (III) Diagnosis and Part B includes (IV) Treatment recommendations and (V) Prospects. This part presents the content of Part A. © 2022 Heart and Mind ;Published by Wolters Kluwer - Medknow.
ABSTRACT
The COVID-19 pandemic has forced teachers to implement fully online teaching. This study reviewed the popular technologies that are used in online learning, as well as the advantages and difficulties of applying fully online courses for formal education. Based on this research background, this study proposed a nested scaffolding design of an online course for 215 college students in China with the help of six technological tools, which effectively replaced face-to-face interactions and significantly improved the usage of the supporting learning platform. The inner-outer learning cycles supported by the technological tools improved the quality of the scaffolding conversations, reduced the scaffolding time cost that teachers had to expend and enhanced the effectiveness of the individualised scaffolding instructions.Implications for practice or policy:center dot First-year students' learning outcomes can be improved by the scaffolding support from Web 2.0 resource URLs, a small private online course, and EducCoder resources.center dot Course leaders should construct at least 3-5 stage-wise evaluations to deconstruct the big learning process into several observable learning cycles, making the Kolb (1984) cycles controllable.center dot Assessors may need to consider involving various exercises, such as quizzes, online experiments and synthesised tasks to facilitate students' learning.
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In late 2019, the novel coronavirus (COVID-19) became a major health hazard around the world. Recently, the COVID-19 has spread widely in most countries and regions and the number of infected people continues to grow rapidly. Therefore, it is essential to research the development trend of the epidemic. The prediction of the number of infections and deaths is critical and helpful for developing health and epidemic prevention strategies and even curbing the epidemic. In this paper, a one-dimensional convolutional neural network combined with the stacked long-short-term-memory network model (CNN-StackBiLSTM) is proposed for the time-series prediction of cumulative cases and daily new cases. The local feature is extracted by CNN. The stacked BiLSTM captures the deeper characteristics of the time-series data. By combining the two networks, the proposed method simultaneously considers the information of temporal and spatial domains and can achieve accurate prediction results. Examples in Taiwan and Italy demonstrate the effectiveness of the proposed method. The proposed method is compared with LSTM, BiLSTM, and GRU. The mean absolute error, mean square error, R2 score, and root mean square error are calculated to quantificationally measure the different models. The results indicate the proposed method performs well in the prediction of both new daily confirmed cases and cumulative confirmed cases. © 2022 IEEE.
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This research is considered as the transformation of cognitive immersion based on the theory by Liu et al. (2021), to describe the possibilities of immersive learning by distance teaching tools. It provides insights among the importance of distance learning for design education, especially under specific situations such as COVID-19 pandemic. The tools to support distance learning are categorized and discussed, degrees of immersion are compared among formal learning, informal learning and social learning courseware. The methods rely on an extensive secondary research and literature review, aims to transform the theoretical framework of cognitive immersive learning by online-based tools, also provide new thoughts for innovatively teaching design in the future. As the output, we establish a theoretical model based on online tools, also a design framework to help with course design or idea visualization for instructors. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Background. T cells are central to the early identification and clearance of viral infections and support antibody generation by B cells, making them desirable for assessing the immune response to SARS-CoV-2 infection and vaccines. We combined 2 high-throughput immune profiling methods to create a quantitative picture of the SARS-CoV-2 T-cell response that is highly sensitive, durable, diagnostic, and discriminatory between natural infection and vaccination. Methods. We deeply characterized 116 convalescent COVID-19 subjects by experimentally mapping CD8 and CD4 T-cell responses via antigen stimulation to 545 Human Leukocyte Antigen (HLA) class I and 284 class II viral peptides. We also performed T-cell receptor (TCR) repertoire sequencing on 1815 samples from 1521 PCR-confirmed SARS-CoV-2 cases and 3500 controls to identify shared public TCRs from SARS-CoV-2-associated CD8 and CD4 T cells. Combining these approaches with additional samples from vaccinated individuals, we characterized the response to natural infection as well as vaccination by separating responses to spike protein from other viral targets. Results. We find that T-cell responses are often driven by a few immunodominant, HLA-restricted epitopes. As expected, the SARS-CoV-2 T-cell response peaks about 1-2 weeks after infection and is detectable at least several months after recovery. Applying these data, we trained a classifier to diagnose past SARS-CoV-2 infection based solely on TCR sequencing from blood samples and observed, at 99.8% specificity, high sensitivity soon after diagnosis (Day 3-7 = 85.1%;Day 8-14 = 94.8%) that persists after recovery (Day 29+/convalescent = 95.4%). Finally, by evaluating TCRs binding epitopes targeting all non-spike SARS-CoV-2 proteins, we were able to separate natural infection from vaccination with > 99% specificity. Conclusion. TCR repertoire sequencing from whole blood reliably measures the adaptive immune response to SARS-CoV-2 soon after viral antigenic exposure (before antibodies are typically detectable) as well as at later time points, and distinguishes post-infection vs. vaccine immune responses with high specificity. This approach to characterizing the cellular immune response has applications in clinical diagnostics as well as vaccine development and monitoring.
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Background. Approximately 10-20% of patients with critical COVID-19 harbor neutralizing autoantibodies (auto-Abs) that target type I interferons (IFN), a family of cytokines that induce critical innate immune defense mechanisms upon viral infection. Studies to date indicate that these auto-Abs are mostly detected in men over age 65. Methods. We screened for type I IFN serum auto-Abs in sera collected < 21 days post-symptom onset in a subset of 103 COVID-19 inpatients and 24 outpatients drawn from a large prospective cohort study of SARS-CoV-2 infected patients enrolled across U.S. Military Treatment Facilities. The mean age of this n = 127 subset of study participants was 55.2 years (SD = 15.2 years, range 7.7 - 86.2 years), and 86/127 (67.7%) were male. Results. Among those hospitalized 49/103 (47.6%) had severe COVID-19 (required at least high flow oxygen), and nine subjects died. We detected neutralizing auto-Abs against IFN-α, IFN-ω, or both, in four inpatients (3.9%, 8.2% of severe cases), with no auto-Abs detected in outpatients. Three of these patients were white males over the age of 62, all with multiple comorbidities;two of whom died and the third requiring high flow oxygen therapy. The fourth patient was a 36-year-old Hispanic female with a history of obesity who required mechanical ventilation during her admission for COVID-19. Conclusion. These findings support the association between type I IFN auto-antibody production and life-threatening COVID-19. With further validation, reliable high-throughput screening for type I IFN auto-Abs may inform diagnosis, pathogenesis and treatment strategies for COVID-19, particularly in older males. Our finding of type I IFN auto-Ab production in a younger female prompts further study of this autoimmune phenotype in a broader population.
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Background. Corynebacterium striatum (CS), a common human commensal colonizing the skin and nasopharynx, has been associated with nosocomial infections in immunocompromised and chronically ill patients. During the winter 2020-2021 COVID-19 surge, a 420-bed California hospital reported a marked increase in CS respiratory cultures among ventilated COVID-19 patients. We conducted a public health investigation to assess and mitigate nosocomial transmission and contributing infection prevention and control (IPC) practices. Methods. A case was defined as a patient with CS in respiratory cultures from January 1, 2020 - February 28, 2021. We reviewed clinical characteristics on a subset of cases in 2021 and IPC practices in affected hospital locations. CS respiratory isolates collected on different dates and locations were assessed for relatedness by whole genome sequencing (WGS) on MiSeq. Results. Eighty-three cases were identified, including 75 among COVID-19 patients (Figure 1). Among 62 patients identified in 2021, all were ventilated;58 also had COVID-19, including 4 cases identified on point prevalence survey (PPS). The median time from admission to CS culture was 19 days (range, 0-60). Patients were critically ill;often it was unclear whether CS cultures represented colonization or infection. During the COVID-19 surge, two hospital wings (7W and 7S) were converted to negative-pressure COVID-19 units. Staff donned and doffed personal protective equipment in anterooms outside the units;extended use of gowns was practiced, and lapses in glove changes and hand hygiene (HH) between patients likely occurred. In response to the CS outbreak, patients were placed in Contact precautions and cohorted. Staff were re-educated on IPC for COVID-19 patients. Gowns were changed between CS patients. Subsequent PPS were negative. Two CS clusters were identified by WGS: cluster 1 (5 cases) in unit 7W, and cluster 2 (2 cases) in unit 7S (Figure 2). Conclusion. A surge in patients, extended use of gowns and lapses in core IPC practices including HH and environmental cleaning and disinfection during the winter 2020-2021 COVID-19 surge likely contributed to this CS outbreak. WGS provides supportive evidence for nosocomial CS transmission among critically ill COVID-19 patients.
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Emotion, as an essential element in communication, is becoming increasingly important and influential in the era of social media. The expression of social media users also has more and more emotional characteristics. Based on the framework of emotional expression, this study encodes the collected 49 microblogs published by China's official media accounts and their comments during COVID-19, and discusses the relationship between account types, text forms, discussion intensity and emotional expression tendency. It is found that account types and discussion intensity have a correlation with the emotional expression of Weibo users, while the correlation between text forms and emotional expression is not obvious. This study analyzes the emotional expression of social media and reflects on how to correctly understand the phenomenon of emotional expression and avoid the occurrence of 'post-truth' events. © 2021 IEEE.
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Objective To explore the epidemic characteristics of COVID-19 in Lu’an city, so as to provide scientific basis for the prevention and control of COVID-19 in this area. Methods All the confirmed cases of COVID-19 were selected from the Infectious Disease Reporting System from the onset of disease to 24:00 on February 18th, 2020 in Lu’an City. The general demographic, onset and medical information, and epidemiological characteristics of confirmed cases were collected to describe the feature of patients. The spatial and temporal distribution of disease transmission was analyzed by SaTScan 9.6.0.0 software, and Excel 2010 software was used to draw the epidemic curves of all cases. Results A total of 69 confirmed cases were reported in Lu’an City by February 18th, 2020. There were more male cases (44) than female (25), and cases mainly aged 36-45 years old (37.68%). The proportion of workers was the highest (24.64%). The first symptom of conformed cases was fever (50, 72.46%), cough (25, 36.23%) and fatigue (12, 17.40%). The epidemic was more serious in Jinzhai County (23), Huoshan County (17) and Huoqiu County (13). The number of cases in Lu’an showed that the first epidemic peak occurred between January 25th and January 28th, and the largest number of cases occurred on January 27th, then showed a downward trend. A total of 45 aggregate cases were found. Conclusion The COVID-19 epidemic in Lu’an City is generally preventable and controllable. It will be alert to the risk of family clustering, spread of asymptomatic infections and imported cases. Future work should focus on the investigation of close contacts. © 2021, Publication Centre of Anhui Medical University. All rights reserved.
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This paper uses Python, R language, Gephi and other software to crawl and classify the comment content of Weibo hot search events. Using word cloud, co-occurrence social network graphs, LDA topic classification visualization methods, this paper regularizes and integrates public opinions of hot events. Through this research, we can get the influence of public opinion mediators, public opinion objects, and government forces on the network public opinion and put forward corresponding improvement suggestions. We hope to contribute to the government's governance and prevention of online public opinion during the spread of COVID-19 and other public hot events.
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The unintentional emission reductions caused by the COVID-19 pandemic provides an opportunity to investigate the impact of energy, industry, and transportation activities on air pollutants and CO2 emissions and their synergy. Here, we constructed an approach to estimate city-level high resolution dynamic emissions of both anthropogenic air pollutants and CO2 by introducing dynamic temporal allocation coefficients based on real-time multisource activity data. We first apply this approach to estimate the spatiotemporal evolution of sectoral emissions in eastern China, focusing on the period around the COVID-19 lockdown. Comparisons with observational data show that our approach can well capture the spatiotemporal changes of both short-lived precursors (NOx and NMVOCs) and CO2 emissions. Our results show that air pollutants (SO2, NOx, and NMVOCs) were reduced by up to 31%-53% during the lockdown period accompanied by simultaneous changes of 40% CO2 emissions. The declines in power and heavy industry sectors dominated regional SO2 and CO2 reductions. NOx reductions were mainly attributed to mobile sources, while NMVOCs emission reductions were mainly from light industry sectors. Our findings suggest that differentiated emission control strategies should be implemented for different source categories to achieve coordinated reduction goals. © 2021 American Chemical Society.
Subject(s)
COVID-19 , Infertility , Insurance, Health , Pandemics , Reproductive Health Services , Adult , Female , Humans , Middle Aged , Reproductive Techniques, Assisted , Socioeconomic Factors , United States , Young AdultABSTRACT
The outbreak of COVID-19 has accelerated the construction of educational informationization and strengthened the integration and application of education and digitalization. Educators have increased demands for smart education to guarantee the quality of online teaching during the epidemic. As a key factor of smart education, smart classroom is expected to produce an important effect on education and teaching. However, at the present stage, there are some problems with smart classroom, such as complex equipment environment and inadequate combination with professional knowledge. Exercise Physiology is a course with strong practicality. For the traditional teaching mode, it is hard for students to gain a deep understanding of related knowledge. In view of this, this paper attempts to introduce a research-based teaching mode based on the smart classroom environment, make it run through three parts of the class, i.e., pre-class, in-class and post-class, make use of all kinds of equipment and functions in the smart classroom to form an interactive teaching mode that integrates pre-class, in-class and post-class. To be specific, the process includes storing in the cloud, pushing smartly, asking questions, creating scenarios, forming an individual learning mode, combining online teaching method with collaborative learning mode, giving quantitative results according to the status of collaborative learning and finally performing feedback evaluation and expanding after-class knowledge. Through the practical teaching of Exercise Physiology, the teaching mode established in this study can achieve a good teaching effect and teaching quality. In particular, it is of great significance for promoting students' classroom satisfaction and ability to analyze problems and developing good learning habits in them. © 2021. All Rights Reserved.
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The ability of patients with hematologic malignancies (HM) to develop an effective humoral immune response after COVID-19 is unknown. A prospective study was performed to monitor the immune response to SARS-CoV-2 of patients with follicular lymphoma (FL), diffuse large B-cell lymphoma (DLBCL), chronic lymphoproliferative disorders (CLD), multiple myeloma (MM), or myelodysplastic/myeloproliferative syndromes (MDS/MPN). Antibody (Ab) levels to the SARS-CoV-2 nucleocapsid (N) and spike (S) protein were measured at +1, +3, +6 months after nasal swabs became PCR-negative. Forty-five patients (9 FL, 8 DLBCL, 8 CLD, 10 MM, 10 MDS/MPS) and 18 controls were studied. Mean anti-N and anti-S-Ab levels were similar between HM patients and controls, and shared the same behavior, with anti-N Ab levels declining at +6 months and anti-S-Ab remaining stable. Seroconversion rates were lower in HM patients than in controls. In lymphoma patients mean Ab levels and seroconversion rates were lower than in other HM patients, primarily because all nine patients who had received rituximab within 6 months before COVID-19 failed to produce anti-N and anti-S-Ab. Only one patient requiring hematological treatment after COVID-19 lost seropositivity after 6 months. No reinfections were observed. These results may inform vaccination policies and clinical management of HM patients.