Preparation of PLA-based SMS nonwoven composites and its applications in protective apparel

The global COVID-19 pandemic has triggered a huge demand for the protective nonwovens. However, the main raw material of nonwovens comes from petroleum, and the massive consumption of petroleum-based polymers brings great pressure to ecosystem. Therefore, it is significant to develop biodegradable protective barrier products. In this work, a polylactic-based composite (a tri-layer nonwovens composed of spunbond, meltblown and spunbond, SMS) was prepared and applied for protective apparel. The surface morphology and chemical changes of the fibers were characterized and analyzed by scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FTIR) and energy dispersive spectroscopy (EDS). The liquid contact angle and permeability, breathability and moisture permeability, frictional charge and mechanical strength of the samples were evaluated and compared. The samples degradability was also recorded. The results demonstrate that the optimum formula for anti-fouling treatment on SMS is F-30. The treated fabric possesses superior liquid repellency and anti-permeability, with contact angles of water and alcohol at 128° and 115° respectively, while the alcohol repellent grade reaches level 7. The treated sample has less strength loss but exhibits favorable breathability, moisture permeability and anti-static properties, which can meet the requirements of protective apparels. After fluorine resin coating, the composite still provide excellent degradation performance, and the weight loss rate reaches more than 80% after 10 days water degradation. These results provide new insights for the application of PLA-based SMS in biodegradable protective apparel. © 2023 The Textile Institute.

Recommendations for the Diagnosis and Treatment of Maternal SARS-CoV-2 Infection

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has spread worldwide and threatened human's health. With the passing of time, the epidemiology of coronavirus disease 2019 evolves and the knowledge of SARS-CoV-2 infection accumulates. To further improve the scientific and standardized diagnosis and treatment of maternal SARS-CoV-2 infection in China, the Chinese Society of Perinatal Medicine of Chinese Medical Association commissioned leading experts to develop the Recommendations for the Diagnosis and Treatment of Maternal SARS-CoV-2 Infection under the guidance of the Maternal and Child Health Department of the National Health Commission. This recommendations includes the epidemiology, diagnosis, management, maternal care, medication treatment, care of birth and newborns, and psychological support associated with maternal SARS-CoV-2 infection. It is hoped that the recommendations will effectively help the clinical management of maternal SARS-CoV-2 infection.Copyright © Wolters Kluwer Health, Inc. All rights reserved.

Time-frequency connectedness and cross-quantile dependence between carbon emission trading and commodity markets: Evidence from China

This paper aims to investigate the dynamic connectedness and the cross-quantile dependence structure between carbon emission trading and commodity markets in China. We employ both the Baruník and Křehlík (2018) connectedness method and the Baruník and Kley (2019) cross-quantile dependence method to provide time-frequency-quantile evidence. In addition, we use a daily dataset from September 2, 2013, to September 30, 2022, to gauge the macroeconomic effects of the COVID-19 pandemic. We find that Petrochemical is the biggest contributor and recipient in the carbon-commodities system, and the results show that carbon markets are more influenced by other commodity markets than the reverse. Furthermore, the total connectedness is stronger in the short term but can increase over the long term, especially during the onset of COVID-19. The dynamic pair-wise results show that the carbon market can impact other commodity markets, but the effects are diverse and varied. The quantile-varying dependence between the carbon market and commodities is detected, and the cross-quantile dependence gradually strengthens as the trading days increase. This paper concludes with fruitful policy implications for resource decision-makers. © 2023 Elsevier Ltd

Discovery of a novel SARS-CoV-2 main protease inhibitor by a simple and optimized colorimetric screening assay

For rapid discovery of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) main protease (Mpro) inhibitors from a natural product library, a novel colorimetric screening assay was developed. According to the colorimetric principle, the synthetic peptide TSAVLQ-para-nitroanilide (pNA) was used as the Mpro hydrolysis substrate. Subsequently, the working concentration of pNA substrate, Mpro working concentration, hydrolysis time and DMSO tolerance were optimized for the development of a simple and robust colorimetric screening assay. Through these systematic optimizations, we selected 0.4 mumol.L-1 Mpro and 100 mumol.L-1 pNA substrate as the optimal working concentrations in this colorimetric screening assay, and a high Z' factor of 0.9 was achieved. Using this screening assay, natural product ginkgolic acid C13: 0 (GA13: 0) was identified as a novel competitive Mpro inhibitor in vitro. Taken together, we have successfully developed a simple and optimized colorimetric screening assay, which will be vital for the discovery of novel SARS-CoV-2 Mpro inhibitors. Copyright © 2022, Chinese Pharmaceutical Association. All rights reserved.

SARS-CoV-2 SNV Genotyping Test Technology

The global pandemic of the COVID-19 has had a major impact on the entire human society, and human beings are facing challenges such as fiscal stimulus, financial stress, and debt restructuring. Before the emergence of specific therapeutic drugs and methods, large-scale population screening and isolation has become the most effective method for epidemic management. However, the new strain of coronavirus this time has shown a very high genetic variability, with a statistical mutation rate of more than 2. 3%c as of March 31st, 2022. So far, new highly infectious virus strains have been emerging, and the number of mutant strains officially warned by the World Health Organization has reached 7. Therefore, in the next virus prevention and control and research, we not only need to detect SARS-CoV-2, but also need to explore accurate and practical single nucleotide variation (SNV) genotyping techniques, especially for large-scale population screening. It is not only necessary to obtain information on the SRAS-CoV-2, but also to accurately and quickly distinguish variant strains with higher infectivity and virulence. This paper briefly introduces the infection and mutation mechanism of the virus, and focuses on the classification and review of the existing main SARS-CoV-2 SNV genotyping techniques, hoping to provide insight into the development of new detection technolooies. © 2022, China Biotechnology Press. All rights reserved.

Quantitative analysis of the impact of anthropogenic emissions and meteorological factors on air quality: Cases during the epidemic in Xingtai City

Meteorological and human factors during the specific epidemic are critical for effectively evaluating the causes of air quality changes in different areas. This study selected Xingtai City, Hebei Province as the research object, took 2020 epidemic situation as an experimental scenario of extreme emission reduction under the extreme control measures, and 2021 epidemic situation as an experimental analysis scenario of future normalized epidemic prevention and control. Compared with the period prior to the epidemic, the ozone concentration during the two epidemics increased, and the particle concentration during the 2021 epidemic also increased. The concentration of other pollutants during the 2020 epidemic decreased to varying degrees. Compared with the same period in 2019, the ozone concentration during the two epidemics also increased. In addition, the pollutant concentration during the 2021 epidemic declined more. Using LSTM algorithm and WRF-CMAQ model to quantify impacts of meteorological factors on the changes in pollutant concentration during the two epidemic periods. The human-induced changes in different pollutant concentrations were deduced as indicated by the results from the air quality simulation. The simulation of LSTM algorithm during the two outbreaks shows that human being had a negative impact on pollutants (reducing their concentration) and accounted for a high proportion in the total change, while the influence of meteorological factors simulated with CMAQ model was much higher than that with LSTM algorithm. Anthropogenic influences dominated during the 2020 epidemic period, while compared to that during the 2020 epidemic period, the impact of anthropogenic activities on pollutants (except NO2) was positive (promoting an increase in pollutant concentration) during the 2021 epidemic period. © 2022 Chinese Society for Environmental Sciences. All rights reserved.

A commentary of Messenger RNA vaccines in MIT Technology Review 2021

One hundred years after the 1918 influenza pandemic, the world has seen another major outbreak on a global scale. This one is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), an enveloped positive-sense single-stranded RNA virus. According to the World Health Organization, as of June 17, 2021, there have been 176,693,988 confirmed cases of human coronavirus disease 2019 (COVID-19), resulting in 3,830,304 deaths. Vaccines are the most effective way to prevent viral infection. During this pandemic, the speed at which the vaccine progressed from research and development to application was unprecedented. As of June 15, 2021, a total of 2,377,780,590 doses of various vaccines against SARS-CoV-2 have been administered worldwide. These vaccines included the messenger RNA (mRNA) vaccine, which became famous upon their debut application in the real world and was listed as one of the '10 Breakthrough Technologies of 2021' by MIT Technology Review. (1).

Oral exams for large-enrollment engineering courses to promote academic integrity and student engagement during remote instruction

This work-in-progress paper presents an innovative practice of using oral exams to maintain academic integrity and promote student engagement in large-enrollment engineering courses during remote instruction. With the abrupt and widespread transition to distance learning and assessment brought on by the COVID-19 pandemic, there has been a registered upsurge in academic integrity violations globally. To address the challenge of compromised integrity, in the winter quarter of 2021 we have implemented oral exams across six mostly high-enrollment mechanical and electrical engineering undergraduate courses. We present our oral exam design parameters in each of the courses and discuss how oral exams relate to academic integrity, student engagement, stress, and implicit bias. We also address the challenge of scalability, as most of our oral exams were implemented in large classes, where academic integrity and student-instructor disconnection have generally gotten disproportionately worse during remote learning. Our survey results indicate that oral exams have positively contributed to academic integrity in our courses. Based on our preliminary study and experiences, we expect oral exams can be effectively leveraged to hinder cheating and foster academic honesty in students, even when in-person instruction and assessment resumes.

Evaluating Oral Exams in Large Undergraduate Engineering Courses

While studies have shown that oral exams are a valuable method of assessment, their use has been limited due to concerns about scalability, examiner bias and student anxiety. This paper presents preliminary results on incorporating oral exams into two large undergraduate engineering courses, examining the potential viability of these assessment strategies. This work was done when the courses were offered remotely due to COVID-19, but the results offer valuable insights that could carry over to in-person instruction as well. © 2021 IEEE.

Study on calibration of mask protective effect detector based on precise photometer

With the outbreak of COVID-19 masks as the most important personal protective equipment, its necessity and importance becomes evident. Particle protective performance, as the key index of masks, the accuracy of its test result is very important. In this study, based on the high-precision photometer, the calibration method of particle protective performance testers for mask is studied. The protective performance is evaluated by the percentage of particle concentration reduction of before and after the mask. Photometric method is a relatively mature technology of particle concentration measurement, with advantages of portability and quick response. In our study, two photometers are used in the calibration. In order to ensure the accuracy, it is necessary to calibrate the two photometers first. Aerosol with concentrations about 1, 10, 20 and 30 mg/m3 is generated in the test chamber, respectively. The filter weight method is used to measure the concentration in the test chamber as the standard values. Within the weighing time, the concentration test results measured by the two photometers are recorded and calibrated with the concentration results measured by the weight method. For the two calibrated photometers, one is used to measure the particle concentration in the test chamber, the other is used to measure the particle concentration in the mask which is attached to the head mold. In this way, the particle protective performance value measured by the instrument can be calibrated. In our experiment, the extended uncertainty of the calibration results are lower than 3%. © 2021 SPIE.

Tuberous Sclerosis Complex Secondary to the Presence of Fetal Cardiac Rhabdomyoma: A Case Report and Literature Review

Fetal cardiac rhabdomyoma is associated with tuberous sclerosis complex (TSC) which is an autosomal dominant hereditary neurocutaneous disease with an incidence of approximately 1 in 5 000 to 10 000 live birth. It is caused by mutations in the TSC1 or TSC2 gene, de novo mutations accounting for approximately 80% of TSC cases, which can involve multiple organs and systems such as the heart, brain, kidney, lung, skin, and so on. Cardiac rhabdomyoma is the most common fetal heart tumor, accounting for about 60% of cases. It is closely related to TSC and may be the only manifestation of TSC which occurs during pregnancy. This study retrospectively analyzed the clinical data of a neonate with TSC diagnosed with fetal cardiac rhabdomyomas and confirmed by amniocentesis prenatal diagnosis as gene testing TSC1 gene positively. The parents had no such mutation. However, due to the influence of the sudden coronavirus disease 2019 (COVID-19) epidemic, the TSC genetic test report was not obtained until 38 weeks of pregnancy. Multiple hypo-pigmented spots (diameter >5 mm) were found immediately after birth. The characteristic cardiac feature of TSC is a rhabdomyoma and the diagnosis of TSC is based upon genetic testing and multiple ultrasound examinations or magnetic resonance imaging. Most patients with TSC have epilepsy, and one-half or more have cognitive deficits and learning disabilities. So rigorous follow-up will continue for the case we reported.

SUPER-RESOLUTION AND INFECTION EDGE DETECTION CO-GUIDED LEARNING FOR COVID-19 CT SEGMENTATION

In this paper, we propose a novel super-resolution and infection edge detection co-guided learning network for COVID-19 CT segmentation (CogSeg). Our CogSeg is a coherent framework consisting of two branches. Specifically, we use image super-resolution (SR) as an auxiliary task, which assist segmentation to recover high-resolution representations. Moreover, we propose an infection edge detection guided region mutual information (RMI) loss, which uses the edge detection results of segmentation to explicitly maintain the high order consistency between segmentation prediction and ground truth around infection edge pixels. Our CogSeg network can effectively maintain high-resolution representation and leverages edge details to improve the segmentation performance. When evaluated on two publicly available COVID-19 CT datasets, our CogSeg improves 10.63 and 13.02 points than the established baseline method (i.e. U-Net) w.t.r mIoU. Moreover, our CogSeg achieves more appealing results both quantitatively and qualitatively than the state-of-the-art methods.

[Preparation and identification of rat polyclonal antibody against SARS-CoV-2 main protease (Mpro)]

Objective To investigate the immunological functions of SARS-CoV-2 main protease (Mpro) in coronavirus disease 2019 (COVID-19), polyclonal antibody against Mpro was developed. Methods A codon-optimized SARS-CoV-2 Mpro gene was synthesized and ligated into a pET-28a vector for construction of a recombinant plasmid named by pET-28a-Mpro. Subsequently, this plasmid was transformed into E.coli Rosetta (DE3) competent cells for Mpro expression in an optimized condition, and then Mpro was purified using a HisTrap chelating column. The purified Mpro was used as immunogen to inoculate rats and the serum was collected after third immunization cycle. The titer, selectivity and sensitivity of polyclonal antibody against Mpro were analyzed using the ELISA and Western blot analysis. Results An optimized expression condition in E.coli cells for Mpro was determined, and the recombinant Mpro was purified by a HisTrap chelating column. The ELISA and Western blot analysis demonstrated that the highly sensitive polyclonal antibody against Mpro specially recognized the recombinant Mpro, and the titer reached 1:256 000. Conclusion The highly specific polyclonal antibody against SARS-CoV-2 Mpro is successfully prepared, which lays an experimental foundation for investigating the immunological function of Mpro in COVID-19.

Analysis of characteristics and meteorological causes of surface ozone pollution in Chengdu during the COVID-19 epidemic

Affected by the COVID-19 epidemic, a series of lockdown control measures adopted by various regions have reduced the emission intensity of air pollutants. Taking Chengdu as an example, this study analyzed the meteorological conditions and pollution concentration characteristics in the first half of 2020 and focused on a detailed analysis of variations in ozone (O3) concentration. The results showed that: ①Compared with 2019, except for O3, all five pollutants in Chengdu showed a decreased trend, and the concentrations of NO2, CO, SO2, PM10 and PM2.5 decreased by 13.60%, 8.96%, 6.30%, 4.56%, 1.80%, respectively. On the contrary, O3 concentration increased abnormally, with the largest increase in February (35.1%) and May (36.1%). ②During the first half of 2020, the high O3 concentration level appeared earlier than in previous years (2015-2019). Meteorological conditions were more supportive to the generation of O3 also. The geopotential heights of 100 hPa and 500 hPa showed positive anomalies, the temperature and sunshine duration was higher than in previous years, and the relative humidity as well as precipitation were lower with a quiet breeze. ③The O3 formation process lasted a long time from April 25th to May 6th, mainly due to the increased emissions of O3 precursors during this period and the relatively stable weather situation, which kept the Chengdu area exposed to unfavorable weather conditions of high temperature (average temperature>30℃), low humidity (40%~60%), and quiet breeze (1.3 m•s-1) for a long time. The backward trajectories and potential sources of air pollution showed that the air quality was affected by the short-distance transportation of high-polluted air masses from the East of Chengdu and southern Sichuan. © 2021, Science Press. All right reserved.

Public Opinion Analysis on Novel Coronavirus Pneumonia and Interaction With Event Evolution in Real World

During the novel coronavirus pneumonia, the underlying comments and news of the epidemic had bombed on the Internet media and social networks, reflecting the views and attitudes of the governments, society, and individuals to the epidemic situation. Those comments are closely related to people's lives and blend with each other. Novel coronavirus pneumonia affects people's lives, and they publish comments on social networks and media, and the underlying information from social networks and Internet media in turn affects people's attitude to the epidemic and the measures, and strategies taken to fight coronavirus in life. We collect the comments from various social network platforms and network media such as Weibo, WeChat, Chinanews, Sina News, NetEase News, Sohu News, and analyze the overall situation of public opinion on the novel coronavirus pneumonia. We explore the interaction between online public opinion and real life using a variety of algorithms in different stages of the epidemic. We can obtain public attention and key nodes in the dissemination of public opinion by detecting hot events and calculating user's influence. The analysis of information dissemination path is conducive to the rapid propagation of healthy comments, curbing the spread of bad information. Event-specific details and topics are mined from large amounts of comments by thematic clustering and association relationship detecting, which helps to provide technical support for government response measures. The emotional analysis of Internet users' groups helps to guide the direction of public opinion. The situation analysis shows the deep blending and mutual influence between the online public opinion and the real world.

[A special on epidemic prevention and control:screening for novel coronavirus related conjunctivitis among the patients with coronavirus disease 2019].

This article was published ahead of print on the official website of Chinese Journal of Ophthalmology on April 16,2020. Objective: To screen for novel coronavirus related conjunctivitis among patients with coronavirus disease 2019. Methods: Prospective series case study. Eighty-one patients diagnosed as coronavirus disease 2019 in Guangxi Zhuang Autonomous Region People's Hospital were enrolled with ophthalmological consultation and screening for novel coronavirus related conjunctivitis, including the inquiring of eye symptoms and checking for conjunctivitis-related signs. Novel coronavirus nucleic acid testing of conjunctival swabs was performed on patients with clinical manifestations of conjunctivitis. Results: Only 3 of the 81 patients (3.70%) complained of eye discomfort, which appeared on day 16.67±9.29 after the diagnosis of coronavirus disease 2019. The eye signs were not typical of viral conjunctivitis. Novel coronavirus nucleic acid tests of conjunctival swabs were negative in both eyes. There was no evidence to support the diagnosis of novel coronavirus related conjunctivitis. The remaining 78 patients showed no clinical symptoms or signs of conjunctivitis. Conclusions: The occurrence of novel coronavirus related conjunctivitis may be low in patients with coronavirus disease 2019.(Chin J Ophthalmol, 2020, 56: 433-437).

Prenatal anxiety and obstetric decisions among pregnant women in Wuhan and Chongqing during the COVID-19 outbreak: a cross-sectional study.

OBJECTIVES: To investigate the mental status of pregnant women and to determine their obstetric decisions during the COVID-19 outbreak. DESIGN: Cross-sectional study. SETTING: Two cities in China--Wuhan (epicentre) and Chongqing (a less affected city). POPULATION: A total of 1947 pregnant women. METHODS: We collected demographic, pregnancy and epidemic information from our pregnant subjects, along with their attitudes towards COVID-19 (using a self-constructed five-point scale). The Self-Rating Anxiety Scale (SAS) was used to assess anxiety status. Obstetric decision-making was also evaluated. The differences between cities in all of the above factors were compared and the factors that influenced anxiety levels were identified by multivariable analysis. MAIN OUTCOME MEASURES: Anxiety status and its influencing factors. Obstetric decision-making. RESULTS: Differences were observed between cities in some background characteristics and women's attitudes towards COVID-19 in Wuhan were more extreme. More women in Wuhan felt anxious (24.5 versus 10.4%). Factors that influenced anxiety also included household income, subjective symptom and attitudes. Overall, obstetric decisions also revealed city-based differences; these decisions mainly concerned hospital preference, time of prenatal care or delivery, mode of delivery and infant feeding. CONCLUSIONS: The outbreak aggravated prenatal anxiety and the associated factors could be targets for psychological care. In parallel, key obstetric decision-making changed, emphasising the need for pertinent professional advice. Special support is essential for pregnant mothers during epidemics. TWEETABLE ABSTRACT: The COVID-19 outbreak increased pregnant women's anxiety and affected their decision-making.