Maternal and Perinatal Outcomes of SARS-CoV-2 and Variants in Pregnancy

Pregnancy is a physiological state that predisposes women to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, a disease that can cause adverse maternal and perinatal outcomes. The severity of coronavirus disease 2019 (COVID-19) disease is known to vary by viral strain;however, evidence for the effects of this virus in pregnant women has yet to be fully elucidated. In this review, we describe maternal and perinatal outcomes, vaccination, and vertical transmission, among pregnant women infected with the different SARS-CoV-2 variants identified to date. We also summarize existing evidence for maternal and perinatal outcomes in pregnant women with specific information relating to SARS-CoV-2 variants. Our analysis showed that Omicron infection was associated with fewer severe maternal and perinatal adverse outcomes while the Delta variant was associated with worse pregnancy outcomes. Maternal deaths arising from COVID-19 were found to be rare (<1.0%), irrespective of whether the virus was a wild-Type strain or a variant. Severe maternal morbidity was more frequent for the Delta variant (10.3%), followed by the Alpha (4.7%), wild-Type (4.5%), and Omicron (2.9%) variants. The rates of stillbirth were 0.8%, 4.1%, 3.1%, and 2.3%, respectively, in pregnancies infected with the wild-Type strain, Alpha, Delta, and Omicron variants, respectively. Preterm birth and admission to neonatal intensive care units were more common for cases with the Delta infection (19.0% and 18.62%, respectively), while risks were similar for those infected with the wild-Type (14.7% and 11.2%, respectively), Alpha (14.9% and 13.1%), and Omicron variants (13.2% and 13.8%, respectively). As COVID-19 remains a global pandemic, and new SARS-CoV-2 variants continue to emerge, research relating to the specific impact of new variants on pregnant women needs to be expanded.Copyright © Wolters Kluwer Health, Inc. All rights reserved.

The COVID-19 pandemic and life expectancy among older adults in Asian countries

Millions of lives in Asia were lost in the ongoing COVID-19 pandemic, causing a reduction of 1.66 years in life expectancy at birth (e0) in 2019–2021 and a reduction of 1.41 years in life expectancy at age 60 (e60). Using the World Population Prospects 2022, we decomposed mortality changes at older ages (ages 60+) that contributed to Asia's reduction in e0 and e60. Overall, changes in mortality at older ages contributed to more than 70 per cent of reduction in e0 for all its subregions, except Eastern Asia (<37 per cent), and changes in mortality at oldest-old ages (80+) led to a reduction in e60 by 25 per cent. The sex difference in reduction of e60 varied across Asian countries, despite a similar pattern across subregions. These findings helped us understand the impacts of the COVID-19 pandemic on human mortality and the large variations across subregions and countries, which could have important policy implications. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

Overall management strategies for colorectal cancer patients during the COVID-19 outbreak.

The Corona Virus Disease 2019 (COVID-19) since December, 2019 has a wide range of infection due to the strong infectious characteristics. Both medical staff and patients are at increased risk of infection. It is an urgent clinical problem for specialist doctors to work with diagnosis and treatment of cancer patients during the epidemic situation. Based on the colorectal cancer diagnosis and treatment guidelines (2019 CSCO guideline), combined with their own experience, the authors propose the overall management strategies for colorectal cancer patients. This strategies cover the key diagnosis and treatment of colorectal cancer, and provide targeted clinical practice. These work will be helpful for colorectal cancer specialists to carry out the diagnosis and treatment of colorectal cancer effectively under the epidemic of COVID-19.Copyright © 2020 by the Chinese Medical Association.

Altered infective competence of the human gut microbiome in COVID-19.

BACKGROUND: Infections with SARS-CoV-2 have a pronounced impact on the gastrointestinal tract and its resident microbiome. Clear differences between severe cases of infection and healthy individuals have been reported, including the loss of commensal taxa. We aimed to understand if microbiome alterations including functional shifts are unique to severe cases or a common effect of COVID-19. We used high-resolution systematic multi-omic analyses to profile the gut microbiome in asymptomatic-to-moderate COVID-19 individuals compared to a control group. RESULTS: We found a striking increase in the overall abundance and expression of both virulence factors and antimicrobial resistance genes in COVID-19. Importantly, these genes are encoded and expressed by commensal taxa from families such as Acidaminococcaceae and Erysipelatoclostridiaceae, which we found to be enriched in COVID-19-positive individuals. We also found an enrichment in the expression of a betaherpesvirus and rotavirus C genes in COVID-19-positive individuals compared to healthy controls. CONCLUSIONS: Our analyses identified an altered and increased infective competence of the gut microbiome in COVID-19 patients. Video Abstract.

Altered infective competence of the human gut microbiome in COVID-19 (preprint)

Objectives: Infections with SARS-CoV-2 have a pronounced impact on the gastrointestinal tract and its resident microbiome. Clear differences between severe cases of infection and healthy individuals have been reported, including the loss of commensal taxa. We aimed to understand if microbiome alterations including functional shifts are unique to severe cases or a common effect of COVID-19. Design: We used high-resolution systematic multi-omic analyses to profile the gut microbiome in asymptomatic-to-moderate COVID-19 individuals compared to a control group. Results: We found a striking increase in the overall abundance and expression of both virulence factors and antimicrobial resistance genes in COVID-19. Importantly, these genes are encoded and expressed by commensal taxa from families such as Acidaminococcaceae and Erysipelatoclostridiaceae, which we found to be enriched in COVID-19 positive individuals. We also found an enrichment in the expression of a betaherpesvirus and rotavirus C genes in COVID-19 positive individuals compared to healthy controls. Conclusion: Our analyses identified an altered and increased infective competence of the gut microbiome in COVID-19 patients.

Research on the Feedback Mechanism of Mobile and Digitized English Teaching in College during COVID-19

Object: this research aims to organize, evaluate, improve and supervise college students' comprehensive English ability and learning autonomy through mobile and digital learning activities and management. Method: this research applied Task-based English Teaching and Itest System to improve students' learning autonomy and English ability by launching exercise tasks of 4 different English skills every weekday, such as writing, translation, reading and listening. Various learning data was recorded by Itest System everyday as an accordance for guiding and supervising students learning activity, and a means of the mobilization and digitization of the task, feedback and incentive mechanisms. Result:the pass rate of the exercises launched by Itest system is high at the beginning and ending of a semester and every Monday, while it's pretty low in the mid-term of a semester and every Friday. Moreover, the improvement effect of the 4 different English skills is different, and the progress of the 952 students' listening and translation is more obvious. Conclusion: the educational mechanism in this research is effective in improving the English translation and listening skills of the freshmen in college. Digitized management can clarify blind areas in students' learning activities, and locate students' problems and problematic students. Mobile English teaching can minimize close contact, but its disciplinary constriction to a few students needs the assistance of college counselor. Students' learning autonomy is low at the mid-term of a semester and on every Friday, which requires more management force. © 2022 ACM.

Combinatorial analysis reveals highly coordinated early-stage immune reactions that predict later antiviral immunity in mild COVID-19 patients.

While immunopathology has been widely studied in patients with severe COVID-19, immune responses in non-hospitalized patients have remained largely elusive. We systematically analyze 484 peripheral cellular or soluble immune features in a longitudinal cohort of 63 mild and 15 hospitalized patients versus 14 asymptomatic and 26 household controls. We observe a transient increase of IP10/CXCL10 and interferon-ß levels, coordinated responses of dominant SARS-CoV-2-specific CD4 and fewer CD8 T cells, and various antigen-presenting and antibody-secreting cells in mild patients within 3 days of PCR diagnosis. The frequency of key innate immune cells and their functional marker expression are impaired in hospitalized patients at day 1 of inclusion. T cell and dendritic cell responses at day 1 are highly predictive for SARS-CoV-2-specific antibody responses after 3 weeks in mild but not hospitalized patients. Our systematic analysis reveals a combinatorial picture and trajectory of various arms of the highly coordinated early-stage immune responses in mild COVID-19 patients.

Revision ideas and implementation suggestions on technical specifications for disinfection centralized treatment engineering of medical waste

Three technical specifications for centralized treatment engineering of medical waste, which were issued in 2006, have played significant roles in guiding and standardizing the construction and operation of centralized treatment engineering of medical waste in over ten years period. However, with development of industry and upgrading of technologies, especially after the coronavirus disease 2019 (COVID-19) epidemic, the medical waste disposal industry faces new opportunities and challenges, and the construction and operation of the centralized treatment engineering of medical waste needs some adjustments. Under such circumstances, revised three technical specifications were issued and implemented in April 2021. Based on the review of the implementation situations of the technical specifications and the development status of the industry, this study analyzed the necessity of the revision of the technical specifications, and explained the revision ideas of the three technical specifications in terms of construction scale, disinfection treatment technical requirements, pollution control technical requirements and disinfection effect detection frequency. Moreover, to promote the implementation of the revised specifications, suggestions were put forward on clarifying the application scenarios, the technical positioning and the legal effect of the specifications. This study can provide a reference for the construction and operation of medical waste disinfection centralized treatment project in the new era. © 2022, Science Press. All right reserved.

College Teachers' Attitudes Towards Online Teaching and the Influencing Factors: Lessons from China

To examine the online teaching attitudes of university teachers and the influencing factors during the Covid-19 pandemic, this study conducted a large-scale survey (N=1090) on university teachers in 16 provinces in China. A series of Kruskal-Wallis nonparametric tests were performed to determine the impact of teacher demographic characteristics on their online teaching attitudes. The results revealed that most teachers had positive opinions of online instruction with several perceived benefits, but also recognized the challenges and disadvantages to teach online. The differences in age, educational background, professional titles and prior online teaching experience significantly affected teachers' attitudes towards online teaching. The study concluded with several implication for preparing university teachers for online instruction in the post-pandemic world. © 2021 IEEE.

Exploring COVID-19 in mainland China during the lockdown of Wuhan via functional data analysis

In this paper, we analyze the time series data of the case and death counts of COVID-19 that broke out in China in December, 2019. The study period is during the lockdown of Wuhan. We exploit functional data analysis methods to analyze the collected time series data. The analysis is divided into three parts. First, the functional principal component analysis is conducted to investigate the modes of variation. Second, we carry out the functional canonical correlation analysis to explore the relationship between confirmed and death cases. Finally, we utilize a clustering method based on the Expectation-Maximization (EM) algorithm to run the cluster analysis on the counts of confirmed cases, where the number of clusters is determined via a cross-validation approach. Besides, we compare the clustering results with some migration data available to the public.

What Drives College Teachers' Behavioral Intention to Teach Online? A Structural Equation Modelling Approach

Using technology acceptance model (TAM) as a theoretical framework, the study explored the potential factors that influence college teachers' behavioral intention to teach online based on the results of a national survey (N=1090) administered during the Covid-19 pandemic. A structural equation modelling (SEM) was proposed by introducing new constructs such as subjective norm, facilitating conditions, affective and cognitive attitude into the TAM model. Meanwhile, the individual differences of college teachers were examined as moderating variables. The results suggested that cognitive attitude had much large impact on teachers' behavioral intention to teach online, and perceived use- fulness of online learning platforms had greater influence on teachers' online teaching attitude than perceived ease of use, particularly on cognitive attitude. Additionally, the moderating effect of teachers' individual differences were also found to be insignificant. The study results supported the revised TAM as a theoretical model to understand college teachers' online teaching behavioral intention, and can inform the policies to sustain teachers' motivation for continual online teaching practice during the post-pandemic world. © 2021 IEEE.

Deep immune profiling reveals early-stage and highly coordinated immune responses in mild COVID-19 patients (preprint)

While immunopathology has been widely studied in severe COVID-19 patients, immunoprotective factors in non-hospitalized patients have remained largely elusive. We systematically analyzed 484 peripheral immune cell signatures, various serological parameters and TCR repertoire in a longitudinal cohort of 63 mild and 15 hospitalized patients versus 14 asymptomatic and 26 control individuals. Within three days following PCR diagnosis, we observed coordinated responses of CD4 and CD8 T cells, various antigen presenting cells and antibody-secreting cells in mild, but not hospitalized COVID-19 patients. This early-stage SARS-CoV-2-specific response was predominantly characterized by substantially expanded clonotypes of CD4 and less of CD8 T cells. The early-stage responses of T cells and dendritic cells were highly predictive for later seroconversion and protective antibody levels after three weeks in mild non-hospitalized, but not in hospitalized patients. Our systemic analysis provides the first full picture and early-stage trajectory of highly coordinated immune responses in mild COVID-19 patients.

Reliability and validity of the Chinese version of fear of coronavirus disease 2019 scale

Objective To translate the English version of fear of coronavirus disease 2019 (COVID-19) scale (FCV-19S) into Chinese and assess its reliability and validity. Methods FCV-19S was translated and culture-adapted to form a Chinese version of fear of COVID-19 scale (FCV-19S-C). A total of 334 questionnaires were sent out online, including FCV-19S-C, Chinese version of depression, anxiety and stress scale (DASS-C21), impact of event scale-revised (IES-R) and public stigma scale. The reliability and validity of FCV-19S-C and the influencing factors of COVID-19 fear were analyzed with the survey data. Results FCV-19S-C contained 7 items. One common factor was extracted by exploratory factor analysis, reflecting that all items in the scale belonged to the common factor, which could explain 69.5% of total variation. The load of item factors ranged from 0.780 to 0.873, showing good construct validity. The total score of FCV-19S-C was positively correlated with the total scores of DASS-C21 and IES-R (r＝0.403 and 0.471, both P＜0.01), indicating that the scale had good concurrent validity. The Cronbach’s α coefficient of FCV-19S-C was 0.924, showing good reliability. Linear regression analysis showed that the influences of COVID-19 on the psychological level and family income could predict the total score of FCV-19S-C (β＝0.62 and 0.20, both P＜0.01). The total score of FCV-19S-C could predict the total score of the public stigma scale (β＝0.37, P＜0.01). Conclusion FCV-19S-C has good reliability and validity, and can be used as a tool to understand the public fear of COVID-19 in China. The fear of COVID-19 is related to the loss of family income and the public stigma of COVID-19 patients.

Emergency disposal and management of medical waste during the COVID-19 outbreak in China

At the beginning of 2020, COVID-19 began to explode on a large scale around the world, with medical and health institutions around the world are facing great pressure. During this period, medical institutions that treat patients with COVID-19 will also generate a large amount of medical waste. If not handled properly, infectious viruses will enter the environment and cause secondary pollution and new epidemic. Wuhan was the first city to have a large-scale outbreak during the outbreak. In the early stage of the outbreak, the relevant competent departments of medical and health institutions and medical waste disposal agencies in China quickly and timely issued a series of technical guidelines and Management measures to control secondary pollution of medical waste during COVID-19. This article analysed the medical waste disposal capacity in Wuhan city, Hubei Province and China at 2020, which also introduce the medical waste treatment measures taken in China during the outbreak, hoping to provide technical reference for other countries.

Current status of drug candidates against SARS-CoV-2

By April 19, 2021, the ongoing coronavirus disease 2019 (COVID-2019), which is caused by severe acute respiratory syndrome-coronavirus 2 (SARS-CoV-2) has infected more than one hundred and fourty million individuals across more than 200 countries or territories and killed more than three million twenty-six thousand individuals worldwide. There are currently no specific drugs available for patients with COVID-19 infection, but a number of potential drug targets have been identified with the further understanding of the virological characteristics and pathogenesis of SARS-CoV-2. Some candidate drugs have shown good antiviral activity against SARS-CoV-2 in preclinical or clinical trials. This paper summarizes the current status of potential therapeutic drugs for COVID-19 in order to provide references for future COVID-19 therapy.

View Identification Assisted Fully Convolutional Network for Lung Field Segmentation of Frontal and Lateral Chest Radiographs

Locating lung field is a critical and fundamental processing stage in the automated analysis of chest radiographs (CXRs) for pulmonary disorders. During the routine examination of CXRs, using both frontal and lateral CXRs can benefit clinical diagnosis of cardiothoracic and lung diseases. However, the accurate segmentation of lung fields on both frontal and lateral CXRs is still challenging due to the blurry boundary of the lung field on lateral CXRs and the poor generalization ability of the models. Existing deep learning-based methods focused on lung field segmentation on frontal CXRs, and the generalization ability of these methods on the different type of CXRs (e.g., pediatric CXRs) and new lung diseases (e.g., COVID-19) has not been tested. In this paper, a view identification assisted fully convolutional network (VI-FCN) is proposed for the segmentation of lung fields on frontal and lateral CXRs simultaneously. The VI-FCN consists of an FCN branch for lung field segmentation and a view identification branch for identification of the frontal and lateral CXRs and for enhancing the lung field segmentation. To improve the generalization ability of VI-FCN, six public datasets and our frontal and lateral CXRs (over 2000 CXRs) were collected for training. The segmentation of lung fields on the Japanese Society of Radiological Technology (JSRT) dataset yields mean dice similarity coefficient (DSC) of 0.979 ±0.008, mean Jaccard index (Ω) of 0.959 ±0.016, and mean boundary distance (MBD) of 1.023 ±0.487mm. Besides, the VI-FCN achieves mean DSC of 0.973 ±0.010, mean Ωof 0.947 ±0.018, and mean MBD of 1.923 ±0.755mm for the segmentation of lung fields on our lateral CXRs. The experiments demonstrate the superior performance of the proposed VI-FCN over most of existing state-of-the-art methods. Moreover, the proposed VI-FCN achieves promising results on untrained pediatric CXRs and COVID-19 datasets. CCBYNCND

The Connectedness of the Coronavirus Disease Pandemic in the World: A Study Based on Complex Network Analysis

Since the coronavirus disease (COVID-19) pandemic started at the beginning of 2020, it has seriously affected various countries’ economic and social development and accelerated the economic recession worldwide. Therefore, the connectedness of the global COVID-19 network across countries is studied in this article. Based on COVID-19 correlations in 122 countries, we construct a complex network of COVID-19 from January 19, 2020, to August 15, 2020. We then deconstruct the overall global network connectedness and analyze the connectedness characteristics. Moreover, we empirically investigate the network connectedness influencing factors by using various countries’ macroeconomic and social data. We find that the global COVID-19 pandemic network has some prominent complex network properties, such as low path length, high clustering, and good community structure. Furthermore, population density, economic size, trade, government spending, and quality of medical treatment are significant macrofactors affecting COVID-19 connectedness in different countries. © Copyright © 2021 Zhu, Kou, Lai, Feng and Du.

Overall management strategies for colorectal cancer patients during the COVID-19 outbreak

The Corona Virus Disease 2019 (COVID-19) since December, 2019 has a wide range of infection due to the strong infectious characteristics. Both medical staff and patients are at increased risk of infection. It is an urgent clinical problem for specialist doctors to work with diagnosis and treatment of cancer patients during the epidemic situation. Based on the colorectal cancer diagnosis and treatment guidelines (2019 CSCO guideline), combined with their own experience, the authors propose the overall management strategies for colorectal cancer patients. This strategies cover the key diagnosis and treatment of colorectal cancer, and provide targeted clinical practice. These work will be helpful for colorectal cancer specialists to carry out the diagnosis and treatment of colorectal cancer effectively under the epidemic of COVID-19. Copyright © 2020 by the Chinese Medical Association.

Oropharyngeal Secretion as Alternative for SARS-CoV-2 Detection.

This study aimed to determine if sampling of oropharyngeal secretions (OSs) helps improves detection of SARS-CoV-2 RNA by nucleic acid amplification testing of potential patients with COVID-19. The first prospective study consisted of 75 patients with COVID-19 who were ready for discharge and who had 2 consecutive negative results per nucleic acid amplification testing (NAAT) of viral samples retrieved with nasopharyngeal swabs (NPSs). Because of detection of potential false negatives in that cohort, the NAAT results of paired OS and NPS samples from 50 additional recruits with COVID-19 during their recovery stage were used in a second prospective study to compare the diagnostic values of the 2 viral RNA sampling methods. For identification of the frequency of inconsistency between the sampling methods, the McNemar's test was used for difference analysis and the kappa statistic for consistency analysis. OSs obtained from 2 of the 75 participants in the first study yielded positive results for SARS-CoV-2 nucleic acid. Both were male and aged >60 y. Subsequent chemiluminescence enzyme immunoassays indicated that they were positive for the SARS-CoV-2 IgM and IgG antibodies. For parallel NAAT of OS and NPS samples in the second study, McNemar's test indicated that the difference between the frequencies of inconsistent parts of OS and NPS was statistically significant (P = 0.021). Cohen's kappa coefficient for OS and NPS was 0.244, which is indicative of fair consistency. The NPS test has a risk of sending home more patients (59%) who still have the infection, while the OS test will make such an error in fewer patients (14%). Although OS sampling improves the accuracy of SARS-CoV-2 nucleic acid testing, it has to be emphasized that this conclusion is based on a very small sample size. Detection of viral RNA from a patient's secretions is not confirmative of viral infectivity.