Epidemiological characteristics of four times of community transmission of COVID-19 in Hebei

Objective To analyze the epidemiological characteristics of community transmission of the coronavirus disease 2019 (COVID-19) caused by four imported cases in Hebei Province, and to provide a scientific basis for the prevention and control of the disease. Methods Descriptive epidemiological methods were used to analyze the epidemiological characteristics of four community-transmitted COVID-19 outbreaks reported in the China Disease Control and Prevention Information System from January 1, 2020 to December 31, 2021 in Hebei Province. Results From January 1, 2020 to December 31, 2021, four community-transmitted COVID-19 outbreaks caused by imported COVID-19 occurred in Hebei Province, respectively related of Hubei (Wuhan) Province, Beijing Xinfadi market, Overseas cases and Ejina banner of Inner Mongolia Autonomous Region. Total of 1 656 cases (1 420 confirmed cases and 236 asymptomatic cases) were reported, including 375 cases in phase A (From January 22 to April 16, 2020), and phase B (from June 14 to June 24, 2020) 27 cases were reported, with 1 116 cases reported in the third phase (Phase C, January 2 to February 14, 2021), and 138 cases reported in the fourth phase (Phase D, October 23 to November 14, 2021). The 1 656 cases were distributed in 104 counties of 11 districts (100.00%), accounting for 60.46% of the total number of counties in the province. There were 743 male cases and 913 female cases, with a male to female ratio of 0.81:1. The minimum age was 13 days, the maximum age was 94 years old, and the average age (median) was 40.3 years old. The incidence was 64.01% between 30 and 70 years old. Farmers and students accounted for 54.41% and 14.73% of the total cases respectively. Of the 1 420 confirmed cases, 312 were mild cases, accounting for 21.97%;Common type 1 095 cases (77.11%);There was 1 severe case and 12 critical cases, accounting for 0.07% and 0.85%, respectively. 7 patients died from 61.0 to 85.7 years old. The mean (median) time from onset to diagnosis was 1.9 days (0-31 days), and the mean (median) time of hospital stay was 15 days (1.5-56 days). Conclusions Four times in Hebei province COVID-19 outbreak in scale, duration, population, epidemic and type of input source, there are some certain difference, but there are some common characteristics, such as the outbreak occurs mainly during the legal holidays or after starting and spreading epidemic area is mainly in rural areas, aggregation epidemic is the main mode of transmission, etc. To this end, special efforts should be made to strengthen the management of people moving around during holidays, and strengthen the implementation of epidemic prevention and control measures in places with high concentration of people. To prevent the spread of the epidemic, we will step up surveillance in rural areas, farmers' markets, medical workers and other key areas and groups, and ensure early detection and timely response.Copyright © 2022 China Tropical Medicine. All rights reserved.

Review of Motion Simulation of Particulate Matter in the Respiratory System and Further CFD Simulations on COVID-19

Respirable particulate matter (RSP) is currently very harmful to the human body, potentially causing pulmonary silicosis, allergic rhinitis, acute bronchitis, and pulmonary heart disease. Therefore, the study of the deposition pattern of RSP in the human respiratory system is key in the prevention, treatment, and research of related diseases, whereby the main methods are computer simulation, in vitro solid models, and theoretical analysis. This paper summarizes and analyzes past deposition of RSP in the respiratory tract and also describes them in specific case studies such as COPD and COVID-19 patients, based on the review of the evidence, direction, and focus of future research focusing on simulation, experimentation, and related applications of RSP deposition in the respiratory tract. © 2023 by the authors.

Integrated smart analytics of nucleic acid amplification tests via paper microfluidics and deep learning in cloud computing

Pandemics such as COVID-19 have exposed global inequalities in essential health care. Here, we proposed a novel analytics of nucleic acid amplification tests (NAATs) by combining paper microfluidics with deep learning and cloud computing. Real-time amplifications of synthesized SARS-CoV-2 RNA templates were performed in paper devices. Information pertained to on-chip reactions in time-series format were transmitted to cloud server on which deep learning (DL) models were preloaded for data analysis. DL models enable prediction of NAAT results using partly gathered real-time fluorescence data. Using information provided by the G-channel, accurate prediction can be made as early as 9 min, a 78% reduction from the conventional 40 min mark. Reaction dynamics hidden in amplification curves were effectively leveraged. Positive and negative samples can be unbiasedly and automatically distinguished. Practical utility of the approach was validated by cross-platform study using clinical datasets. Predicted clinical accuracy, sensitivity and specificity were 98.6%, 97.6% and 99.1%. Not only the approach reduced the need for the use of bulky apparatus, but also provided intelligent, distributable and robotic insights for NAAT analysis. It set a novel paradigm for analyzing NAATs, and can be combined with the most cutting-edge technologies in fields of biosensor, artificial intelligence and cloud computing to facilitate fundamental and clinical research.Copyright © 2023 Elsevier Ltd

Simulation and theoretical study of AlGaN-based deep-ultraviolet light-emitting diodes with a stepped electron barrier layer

Owing to the COVID-19 outbreak, sterilization of deep-ultraviolet light-emitting diodes (DUV LEDs) has attracted increasing attention. Effectively improving the radiative recombination efficiency and mitigating the efficiency degradation, mainly caused by electron leakage and nonradiative recombination, have also emerged as two of the main issues to be addressed. In this study, a DUV LED epitaxial structure with a novel electron-blocking layer (EBL) is proposed. The DUV LED with a luminescence wavelength of similar to 297 nm was formed by the stepwise variation of the Al component. Through the simulation and analysis of its performance parameters, we found that, compared to the conventional EBL structure, this new EBL structure not only reduces the electron leakage to the p-region effectively but also increases the hole injection into the active region, resulting in an increase in carrier concentration in the active region, a two-to-three-fold increase in the radiative recombination rate, and a 58% increase in the internal quantum efficiency, thus alleviating the efficiency droop and achieving a more efficient operation at high current densities. (C) 2022 Author(s).

Epidemiological characteristics of four times of community transmission of COVID-19 in Hebei

Objective To analyze the epidemiological characteristics of community transmission of the coronavirus disease 2019 (COVID-19) caused by four imported cases in Hebei Province, and to provide a scientific basis for the prevention and control of the disease. Methods Descriptive epidemiological methods were used to analyze the epidemiological characteristics of four community-transmitted COVID-19 outbreaks reported in the China Disease Control and Prevention Information System from January 1, 2020 to December 31, 2021 in Hebei Province. Results From January 1, 2020 to December 31, 2021, four community-transmitted COVID-19 outbreaks caused by imported COVID-19 occurred in Hebei Province, respectively related of Hubei (Wuhan) Province, Beijing Xinfadi market, Overseas cases and Ejina banner of Inner Mongolia Autonomous Region. Total of 1 656 cases (1 420 confirmed cases and 236 asymptomatic cases) were reported, including 375 cases in phase A (From January 22 to April 16, 2020), and phase B (from June 14 to June 24, 2020) 27 cases were reported, with 1 116 cases reported in the third phase (Phase C, January 2 to February 14, 2021), and 138 cases reported in the fourth phase (Phase D, October 23 to November 14, 2021). The 1 656 cases were distributed in 104 counties of 11 districts (100.00%), accounting for 60.46% of the total number of counties in the province. There were 743 male cases and 913 female cases, with a male to female ratio of 0.81∶1. The minimum age was 13 days, the maximum age was 94 years old, and the average age (median) was 40.3 years old. The incidence was 64.01% between 30 and 70 years old. Farmers and students accounted for 54.41% and 14.73% of the total cases respectively. Of the 1 420 confirmed cases, 312 were mild cases, accounting for 21.97%;Common type 1 095 cases (77.11%);There was 1 severe case and 12 critical cases, accounting for 0.07% and 0.85%, respectively. 7 patients died from 61.0 to 85.7 years old. The mean (median) time from onset to diagnosis was 1.9 days (0-31 days), and the mean (median) time of hospital stay was 15 days (1.5-56 days). Conclusions Four times in Hebei province COVID-19 outbreak in scale, duration, population, epidemic and type of input source, there are some certain difference, but there are some common characteristics, such as the outbreak occurs mainly during the legal holidays or after starting and spreading epidemic area is mainly in rural areas, aggregation epidemic is the main mode of transmission, etc. To this end, special efforts should be made to strengthen the management of people moving around during holidays, and strengthen the implementation of epidemic prevention and control measures in places with high concentration of people. To prevent the spread of the epidemic, we will step up surveillance in rural areas, farmers′ markets, medical workers and other key areas and groups, and ensure early detection and timely response. © 2022 China Tropical Medicine. All rights reserved.

AI-aided on-chip nucleic acid assay for smart diagnosis of infectious disease

Global pandemics such as COVID-19 have resulted in significant global social and economic disruption. Although polymerase chain reaction (PCR) is recommended as the standard test for identifying the SARS-CoV-2, conventional assays are time-consuming. In parallel, although artificial intelligence (AI) has been employed to contain the disease, the implementation of AI in PCR analytics, which may enhance the cognition of diagnostics, is quite rare. The information that the amplification curve reveals can reflect the dynamics of reactions. Here, we present a novel AI-aided on-chip approach by integrating deep learning with microfluidic paper-based analytical devices (mu PADs) to detect synthetic RNA templates of the SARS-CoV-2 ORFlab gene. The mu PADs feature a multilayer structure by which the devices are compatible with conventional PCR instruments. During analysis, real-time PCR data were synchronously fed to three unsupervised learning models with deep neural networks, including RNN, LSTM, and GRU. Of these, the GRU is found to be most effective and accurate. Based on the experimentally obtained datasets, qualitative forecasting can be made as early as 13 cycles, which significantly enhances the efficiency of the PCR tests by 67.5% (similar to 40 min). Also, an accurate prediction of the end-point value of PCR curves can be obtained by GRU around 20 cycles. To further improve PCR testing efficiency, we also propose AI-aided dynamic evaluation criteria for determining critical cycle numbers, which enables real-time quantitative analysis of PCR tests. The presented approach is the first to integrate AI for on-chip PCR data analysis. It is capable of forecasting the final output and the trend of qPCR in addition to the conventional end-point Cq calculation. It is also capable of fully exploring the dynamics and intrinsic features of each reaction. This work leverages methodologies from diverse disciplines to provide perspectives and insights beyond the scope of a single scientific field. It is universally applicable and can be extended to multiple areas of fundamental research.

The safety and efficacy of surufatinib for the treatment of advanced neuroendocrine tumors: A prospective, multicenter, real-world study

Background: Surufatinib (a small-molecule inhibitor of VEGFR1-3, FGFR1, and CSF-1R) has exhibited encouraging antitumor activity for the treatment of advanced neuroendocrine tumors (including NEN and NEC) in multiple registration studies. Here, we report the preliminary results of advanced neuroendocrine tumors of an ongoing, multicenter, real-world study of surufatinib + MDT (ChiCTR2100049999). Challenges in tumor clinical trials management in the face of the COVID-19 resurgence period in Shanghai. Methods: In this multicenter, single-arm real-world study, adults (18-80) with advanced neuroendocrine tumors (including NEN and NEC) were eligible and received surufatinib (300mg orally, QD) with MDT（multidisciplinary collaborative diagnosis and treatment). The primary endpoint was progression-free survival (PFS) per RECIST 1.1. We minimized the interruptions caused by the pandemic using telemedicine platforms for all patients. This included online consultations, follow-up drug distributions, and health management services. Results: Twenty-three pts were enrolled, with 20 NEN and 3 NEC. At the data cutoff date (April 10, 2022), 15 pts had at least one post-baseline tumor assessment;of them, the confirmed ORR (95%CI) was 20% (4.3-48.1), and DCR (95%CI) was 93.33% (68.1-99.8). Median PFS (mPFS) (95%CI): 10.640 mo (3.796-17.484);median OS: not reached and median duration of follow up was 6.870 mo (6.797-6.943). A pNET patient (NO. 010007) was interrupted by asymptomatic COVID-19 infection 9 mo after enrollment. There are no interruptions caused by COVID-19 for other patients. An NEC patient treated with single agent had a 5.85 mo PFS, evaluated as NE, in whom target lesion resected after baseline. In overall pts (n=23), most commonly (≥3 pts) with hemorrhage, anemia, hypertension, proteinuria, and abdominal pain. Three pts had TRAEs that led to treatment discontinuation. Conclusions: Surufatinib + MDT exhibited promising efficacy and manageable toxicity in pts with advanced neuroendocrine tumors. Now and in the future, it is necessary to design regulatory changes in telehealth adoption for clinical trial design in the pandemic era. Clinical trial identification: ChiCTR2100049999. Legal entity responsible for the study: The authors. Funding: Hutchison MediPharma Limited. Disclosure: All authors have declared no conflicts of interest.

Characterization, Contributing Factors, And Outcomes Of Bleeding Complication In Extracorporeal Membrane Oxygenation for SARS-CoV-2 Pneumonia: A Single-Institution Experience

Background: SARS-CoV-2 (i.e., COVID-19) has brought extracorporeal membrane oxygenation (ECMO) into the forefront of critical care. Its unique pathophysiology has added a level of complexity to ECMO therapy, particularly, the hematologic manifestations. Here we detail the spectrum and outcomes of bleeding complications in ECMO for COVID-19 and identify potential contributing factors. Methods: All patients who received ECMO for SARS-CoV-2 pneumonia severe acute respiratory distress syndrome at our institution between March 1, 2020 and April 12, 2021 were reviewed. Patient characteristics, laboratory results, and overall outcomes were recorded. Bleeding events were reviewed with regard to the type/location and intervention required. Severity was graded according to the degree of intervention for treatment (1 [conservative or minor] - 3 [major, life-threatening, or operative]). Laboratory results and patient characteristics were compared between patients with bleeding events and those without to identify factors associated with bleeding risk. Results: Fifty-four patients (mean age 53.2 years, 61.1% female, 51.9% Caucasian) underwent ECMO cannulation for SARSCoV-2 pneumonia at our institution. Thirty-eight (70.4%) received veno-pulmonary artery ECMO. The mean duration of support was 33.2 days with an in-hospital mortality of 42.6%. 68.5% of patients experienced at least one bleeding event during their ECMO course with 92 bleeding events (n=23 [grade 1], n=31 [grade 2], n=38 [grade 3]) over 1804 cannulation days. The most common types of bleeding types were nasal/oropharyngeal (n=30, 32.6%), pulmonary (n=18, 19.6%), and gastrointestinal (n=11, 12.0%). Eight (16.0%) patients required operative intervention and 11 (20.3%) died as a result of a bleeding event, mainly due to intracranial hemorrhages (n=5, 9.3%). There was no difference in the mean cumulative function for bleeding events between different ECMO support modalities (p=0.85) which demonstrated a linear pattern over time. Factors that increased the risk of bleeding included patient cumulative volume balance (OR 1.22 per 1000 mL increase from admission, p<0.001) while higher platelet count (OR 0.83 per 50x103/uL increase, p=0.03) was protective. Conclusion: ECMO for SARS-CoV-2 pneumonia is associated with a diverse and unique profile of bleeding complications. The incidence of bleeding complications is linearly related to cannulation duration. Certain patient factors may affect the risk of bleeding while on ECMO.

Recent advances in nanozymes for combating bacterial infection

Bacterial infection is a major threat to public health around the world. Currently, antibiotics remain the most extensive mode of medical treatment for bacterial infection. However, the overuse and misuse of antibiotics have exacerbated the emergence of antibiotic-resistant strains, especially during the COVID-19 pandemic. In addition, the improper and excessive use of biocides and disinfectants has a catastrophic impact on antibiotic management plans worldwide. Therefore, there is an urgent need for alternative antibacterial treatments to alleviate this crisis. In recent years, nanozymes have become promising new antibacterial agents because of their broad-spectrum antibacterial activity, less drug resistance, and high stability. This review focuses on the classification of nanozymes and research progress of nanozymes as antibacterial agents, as well as perspectives for future research in this field.

COVID-19, recovery policies and the resilience of EU ETS

COVID-19 pandemic and its recovery bring opportunities and threats for global climate governance and further challenge climate related assets. In this study, we analyze the efficiency of government response policies and fiscal policies on green recovery by observing the variation characteristics of carbon allowance prices in the EU emission trading system (EU ETS). Using the OLS and threshold methods in the original time scales, we find that: (1) The EUA prices had an inverted U-shaped relationship with the number of new confirmed cases and deaths. (2) Government response policies had a better effect than fiscal policies when mitigating the negative impact of the pandemic. After decomposing and reconstructing the time series, the multiscale analysis indicates that: (3) The carbon price fluctuated in the short term with the increasing number of newly confirmed cases (or deaths) but gradually recovered due to the recovery policies. (4) Government response policies had a "stop-loss" effect in the short term, and then working alongside fiscal policies, sustained and promoted the development of the EU ETS and green recovery. In the post-COVID-19 era, we suggest the combination of various policies to convert the current health crisis into opportunities for climate change mitigation.

[Epidemiological characteristics of three local epidemics of COVID-19 in Guangzhou].

Objective: To understand the epidemiological characteristics of three local COVID-19 epidemics in Guangzhou and provide reference for optimizing strategies and measures of COVID-19 prevention and control. Methods: The data of local COVID-19 cases in Guangzhou reported as of June 18, 2021 were collected from National Notifiable Disease Report System of China. The software Excel 2019 and SPSS 22.0 were applied for data cleaning and statistical analysis. Results: A total of 726 COVID-19 cases were reported in the three local epidemics in Guangzhou. In the epidemic associated with the outbreak of COVID-19 in Hubei province, 366 cases were reported. Most cases were female (51.6%, 189/366), aged 18-65 years (81.4%, 298/366), jobless/unemployed (32.2%, 118/366) and retired persons (20.2%,74/366). The initial symptoms of most cases were fever (71.6%, 250/349) and cough (60.7%, 212/349). In the epidemic associated with the imported COVID-19 cases from Africa, 207 cases were reported. Most cases were aged 18-40 years (72.9%, 151/207), male (69.6%, 144/207), and engaged in commercial services (62.3%,129/207). The initial symptoms of most cases were no obvious discomfort (55.6%, 15/27) and cough (37.0%, 10/27). In the epidemic associated with Delta variant of SARS-CoV-2, 153 cases were reported, in which women accounted for 58.8% (90/153), most cases were over 41 years old (64.7%,99/153), and retired persons accounted for the highest proportion (32.0%,49/153). The initial symptoms of most cases were cough (32.9%, 48/146) and no obvious discomfort (28.1%, 41/146). The household secondary attack rates of the three local epidemics were 11.2%, 5.7% and 11.5%, respectively. The median (P25, P75) of incubation periods were 6.5 (4.0,10.8) d, 4.0 (2.5, 6.0) d and 4.0 (3.0,5.0) d. The serial intervals median (P25, P75) were 4.0 (3.0, 8.0) d, 4.0 (2.5, 6.0) d and 3.0 (2.0,5.0) d. There were significant differences in gender, age, occupation, initial symptoms, household secondary attack rate and incubation period among the three local COVID-19 epidemics (all P<0.05). In the proportion of the case finding way, passive detection in patient treatment were mainly 44.3%(162/366) in the epidemic associated with the outbreak of COVID-19 in Hubei province,but active community case screening [58.5% (121/207) and 27.5% (24/153)] and close contact management in imported case were mostly [33.3% (69/207) and 67.3% (103/153)] in the epidemic associated with the imported COVID-19 cases from Africa and with Delta variant of SARS-CoV-2, respectively. Conclusions: Due to the different sources of infection, strain types and prevention and control strategies, the epidemiological characteristics of the three local COVID-19 epidemics in Guangzhou differed in demographics, clinical symptoms, transmission routes and case finding, which suggested that it is necessary to improve the key population and common symptom monitoring in the routine prevention and control of COVID-19 to prevent the reemerge of the epidemic.

Immune signatures underlying post-acute COVID-19 lung sequelae.

Severe coronavirus disease 2019 (COVID-19) pneumonia survivors often exhibit long-term pulmonary sequelae, but the underlying mechanisms or associated local and systemic immune correlates are not known. Here, we have performed high-dimensional characterization of the pathophysiological and immune traits of aged COVID-19 convalescents, and correlated the local and systemic immune profiles with pulmonary function and lung imaging. We found that chronic lung impairment was accompanied by persistent respiratory immune alterations. We showed that functional severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)­specific memory T and B cells were enriched at the site of infection compared with those of blood. Detailed evaluation of the lung immune compartment revealed that dysregulated respiratory CD8+ T cell responses were associated with the impaired lung function after acute COVID-19. Single-cell transcriptomic analysis identified the potential pathogenic subsets of respiratory CD8+ T cells contributing to persistent tissue conditions after COVID-19. Our results have revealed pathophysiological and immune traits that may support the development of lung sequelae after SARS-CoV-2 pneumonia in older individuals, with implications for the treatment of chronic COVID-19 symptoms.

Spreading Dynamics Analysis for Railway Networks

The 2019 Coronavirus Disease (COVID-19), with the characteristics of rapid onset, strong infectivity, fast transmission and wide susceptibility, has quickly swept China since its appearance in Wuhan, Hubei province. COVID-19 spreads among people mainly by movement and close contact. Railway plays an important role in transport people national-wide as its essential role in public transportation, which conduced to the spreading of COVID-19 from Hubei province to other provinces in some sense. Inspired by this, this paper collected the data of Trains with Infectors (TwI) reported by the national health commission of the People’s Republic of China. Then the spreading of COVID-19 via railway network with the concept of complex network is analyzed. Results show that nodes with higher centrality tends to provide more TwI, and the closure of Wuhan railway station significantly prevents the spreading of COVID-19. © 2021, Springer Nature Singapore Pte Ltd.

Research on the Development of Online Education in the Age of AI and 5G

Online education is a new educational pattern relying on netwok, Which adds flexibility and availability, regards of time, place, or pace of learning. Best of all, with online education, we can stick to our jobs and at the same time study and absorb the latest knowledge. AI, big data and 5G are the scinetific technology which lead the online education industry to decelop into a richer ecosystem and make Online education promote its advantages. In the second half of 2020, the COVID-19 pandemic in China has been under control, and China's online education will face both opportunities and challenges. This paper mainly adopts the method of questionnaire survey analysis, SPSS 20.0 statistical software and PLS to analyze the influencing factors of China's online education in the post-epidemic era. Finding that the education level, income level, education level and the purpose of the education have positive effect on online education, the education cost of online education has the reverse effect, the lower the price of online education, the larger the quantity of online education that will be demanded. At the same time, this paper finds that when students spend more time in online classes and the fewer exams they pass, the more students spend on online education platforms. According to the results, some countermeasures and suggestions are put forward. © 2021 IEEE.

Open design and 3D printing of face shields: The case study of a UK-China initiative

At the start of the COVID-19 outbreak, many countries lacked personal protective equipment (PPE) to protect healthcare workers. To address this problem, open design and 3D printing technologies were adopted to provide much-in-need PPEs for key workers. This paper reports an initiative by designers and engineers in the UK and China. The case study approach and content analysis method were used to study the stakeholders, the design process, and other relevant issues such as regulation. Good practice and lessons were summarised, and suggestions for using distributed 3D printing to supply PPEs were made. It concludes that 3D printing has played an important role in producing PPEs when there was a shortage of supply, and distributed manufacturing has the potential to quickly respond to local small-bench production needs. In the future, clearer specification, better match of demands and supply, and quicker evaluation against relevant regulations will provide efficiency and quality assurance for 3D printed PPE supplies. © 2020 Universidade do Vale do Rio dos Sinos. All rights reserved.

Enabling rapid COVID-19 small molecule drug design through scalable deep learning of generative models

We improved the quality and reduced the time to produce machine learned models for use in small molecule antiviral design. Our globally asynchronous multi-level parallel training approach strong scales to all of Sierra with up to 97.7% efficiency. We trained a novel, character-based Wasserstein autoencoder that produces a higher quality model trained on 1.613 billion compounds in 23 minutes while the previous state of the art takes a day on 1 million compounds. Reducing training time from a day to minutes shifts the model creation bottleneck from computer job turnaround time to human innovation time. Our implementation achieves 318 PFLOPs for 17.1% of half-precision peak. We will incorporate this model into our molecular design loop enabling the generation of more diverse compounds;searching for novel, candidate antiviral drugs improves and reduces the time to synthesize compounds to be tested in the lab.

Recommendations for obstetric anesthesia during coronavirus disease 2019 epidemic

Obstetric anesthesia is an important part of clinical anesthesia during the coronavirus disease 2019(COVID-19 )epidemic. Obstetric anesthesia management faces challenges such as difficulty in evaluation, in managing patients with emergent or fluctuating conditions, and in taking care of both the mother and the fetus/newborn.Obstetric anesthesia should focus on the following aspects.First, detailed evaluation of COVID-19 should be carried out.Except for epidemic-related evaluation, the effect of physiologic changes during pregnancy and complex condition of the parturient and critical condition on COVID-19 evaluation should be considered.The possible effects of maternal lung conditions on the fetus should be paid attention to simultaneously to determine the optimal timing for delivery, delivery mode and degree of protection.Second, tight infection control of the environment, staff and devices is necessary.Delivery of the suspected or diagnosed cases of novel coronavirus infection should be performed in an isolation delivery room or in a negative pressure operating room.Anesthetic personnel should be minimized, and skilled anesthetists should be arranged in priority.Medical staff should wear personal protective equipment according to standards.Third, the keypoint of optimizing anesthesia management is to maintain sufficient oxygenation and stable circulation.For neuraxial anesthesia, coughing and hypotension should be minimized.For general anesthesia, protection from infection during airway management is essential.Fourth, humanistic care should be implemented, and psychological health education and psychological crisis intervention should be conducted for parturients.Fifth, though no evidence supported the vertical transmission yet, the newborn of the suspected or diagnosed mother of novel coronavirus infection should be isolated, and breastfeeding is not permitted until the mother recover.To minimize the risk of infection and optimize clinical safety, multi-discipline-based teamwork by the obstetricians, anesthetists, neonatologists, infect-control experts and intensive care unit staff on infection control and maternal-fetal management is important. © 2020 Chinese Medical Association

A paper-based device for integrated high-throughput COVID-19 diagnostic tests

Novel microfluidic paper-based analytical devices (μPADs) were developed for qualitatively detecting biological pathogens. 32 reaction units for parallelized nucleic acid analysis were built on a single device. Also, an integrated system including modules of on-chip heating, temperature control, ultraviolet illumination and nucleic acid detection were designed and constructed. We first demonstrated the performance of the devices by detecting synthesized templates using Eiken loop-mediated isothermal amplification (LAMP) kit. Furthermore, the utility of the devices, system and protocols were verified by clinical tests. Multiple samples from COVID-19 cases were concurrently identified within 15 minutes using TianDZ RT-LAMP kit. © 2020 CBMS-0001

Current status and bottlenecks of global pharmaceutical developments against COVID-19

The outbreaks of severe acute respiratory syndrome (SARS) in February 2003 in Guangdong, China, middle east respiratory syndrome (MERS) in September2012 in Kingdom of Saudi Arabia, and the current COVID-19 pandemics in December 2019 in Wuhan, China, are all caused by coronaviruses, and patients primarily died of acute respiratory distress syndrome (ARDS). Compared with more than 5 years of wreaking havoc from MERS-CoV and Ebor, China successfully contains the SARS-CoV within one year, which shows her advantages in political governance controlling such pandemics. Many coronaviruses have been separated and their molecular structures analyzed. However, there is no specific anti-coronavirus drug developed in the world since the outbreaks. The problems come from not only pharmaceutical technology per se that must treat both coronaviruses and their life-threatening ARDS, but also the small size of patients who could immune against the coronaviruses after infections resulting in pharmaceutical reluctance to invest in the area. Facing both the pharmaceutical and social-economic bottlenecks, here, we summarized the current development of anti-coronavirus drugs, and proposed the strategies of repurposing existing drugs and preparing their pharmacological combinations to fight the viruses including COVID-19 based on a well-understanding of how the coronaviruses enter the host and damage our respiratory system.