Impact of thermal stratification on airborne transmission risk of SARS-CoV-2 in various indoor environments.

There exist various vertical temperature gradients in different-type buildings. A holistic understanding of the impact of different temperature-stratified indoor environments on infection risk is necessary. In this work, the airborne transmission risk of SARS-CoV-2 in different thermally stratified indoor environments is assessed using our previously developed airborne infection risk model. Results show that the vertical temperature gradients in office building, hospital, classroom, etc. are within the range of -0.34 to 3.26 °C/m. In large space such as coach station, airport terminal, and sport hall, the average temperature gradient ranges within 0.13-2.38 °C/m in occupied zone (0-3 m); in ice rink with special requirements of indoor environment, the temperature gradient is higher than those in the above indoor spaces. The existence of temperature gradients causes multi-peaks of the transmission risk of SARS-CoV-2 with distancing, and our results show that in office, hospital ward and classroom, the second peak of the transmission risk is higher than 10-3 in most contact scenarios, while most being lower than 10-6 in large spaces like coach station and airport. The work is expected to provide some guidance on specific intervention policies in relation to the types of indoor environments. Electronic Supplementary Material: the Appendix is available in the online version of this article at 10.1007/s12273-023-1021-5.

Spread of flushing-generated fecal aerosols in a squat toilet cubicle: Implication for infection risk.

Toilet flushing generates and spread fecal aerosols, potentially leading to infection transmission risk. Squat toilets are widely used in public restrooms in some Asian countries including China and India, and remain to be studied. Aerosol dispersion while flushing squat toilet in cubicle was visualized, while the aerosol concentrations were measured on different surfaces by monitoring fluorescence intensity through seeding simulated fluorescence feces. Flushing-generated fecal aerosols could spread to the breathing zone, deposit on floor, and partitions in squat toilet cubicles, and spread even beyond to the restroom lobby. A total of 0.24 % and 0.17 % of seeded fecal waste deposits on the floor and partition (lower than 0.20 m) for each flush. Aerosol concentration decays rapidly, with 86.8 ± 2.2 % reduction in the second minute after a previous flush compared to that in the first minute. Public toilet users are recommended to wait for 2 min after the early flush before entering the cubicle.

Monkeypox virus quadrivalent mRNA vaccine induces immune response and protects against vaccinia virus.

Monkeypox has been declared a public health emergency by the World Health Organization. There is an urgent need for efficient and safe vaccines against the monkeypox virus (MPXV) in response to the rapidly spreading monkeypox epidemic. In the age of COVID-19, mRNA vaccines have been highly successful and emerged as platforms enabling rapid development and large-scale preparation. Here, we develop two MPXV quadrivalent mRNA vaccines, named mRNA-A-LNP and mRNA-B-LNP, based on two intracellular mature virus specific proteins (A29L and M1R) and two extracellular enveloped virus specific proteins (A35R and B6R). By administering mRNA-A-LNP and mRNA-B-LNP intramuscularly twice, mice induce MPXV specific IgG antibodies and potent vaccinia virus (VACV) specific neutralizing antibodies. Further, it elicits efficient MPXV specific Th-1 biased cellular immunity, as well as durable effector memory T and germinal center B cell responses in mice. In addition, two doses of mRNA-A-LNP and mRNA-B-LNP are protective against the VACV challenge in mice. And, the passive transfer of sera from mRNA-A-LNP and mRNA-B-LNP-immunized mice protects nude mice against the VACV challenge. Overall, our results demonstrate that mRNA-A-LNP and mRNA-B-LNP appear to be safe and effective vaccine candidates against monkeypox epidemics, as well as against outbreaks caused by other orthopoxviruses, including the smallpox virus.

[Analysis of chest imaging features of novel coronavirus pneumonia, bacterial pneumonia and viral pneumonia].

OBJECTIVE: To investigate and summarize the chest CT imaging features of patients with novel coronavirus pneumonia (COVID-19), bacterial pneumonia and other viral pneumonia. METHODS: Chest CT data of 102 patients with pulmonary infection due to different etiologies were retrospectively analyzed, including 36 patients with COVID-19 admitted to Hainan Provincial People's Hospital and the Second Affiliated Hospital of Hainan Medical University from December 2019 to March 2020, 16 patients with other viral pneumonia admitted to Hainan Provincial People's Hospital from January 2018 to February 2020, and 50 patients with bacterial pneumonia admitted to Haikou Affiliated Hospital of Central South University Xiangya School of Medicine from April 2018 to May 2020. Two senior radiologists and two senior intensive care physicians were participated to evaluated the extent of lesions involvement and imaging features of the first chest CT after the onset of the disease. RESULTS: Bilateral pulmonary lesions were more common in patients with COVID-19 and other viral pneumonia, and the incidence was significantly higher than that of bacterial pneumonia (91.6%, 75.0% vs. 26.0%, P < 0.05). Compared with other viral pneumonia and COVID-19, bacterial pneumonia was mainly characterized by single-lung and multi-lobed lesion (62.0% vs. 18.8%, 5.6%, P < 0.05), accompanied by pleural effusion and lymph node enlargement. The proportion of ground-glass opacity in the lung tissues of patients with COVID-19 was 97.2%, that of patients with other viral pneumonia was 56.2%, and that of patients with bacterial pneumonia was only 2.0% (P < 0.05). The incidence rate of lung tissue consolidation (25.0%, 12.5%), air bronchial sign (13.9%, 6.2%) and pleural effusion (16.7%, 37.5%) in patients with COVID-19 and other viral pneumonia were significantly lower than those in patients with bacterial pneumonia (62.0%, 32.0%, 60.0%, all P < 0.05), paving stone sign (22.2%, 37.5%), fine mesh sign (38.9%, 31.2%), halo sign (11.1%, 25.0%), ground-glass opacity with interlobular septal thickening (30.6%, 37.5%), bilateral patchy pattern/rope shadow (80.6%, 50.0%) etc. were significantly higher than those of bacterial pneumonia (2.0%, 4.0%, 2.0%, 0%, 22.0%, all P < 0.05). The incidence of local patchy shadow in patients with COVID-19 was only 8.3%, significantly lower than that in patients with other viral pneumonia and bacterial pneumonia (8.3% vs. 68.8%, 50.0%, P < 0.05). There was no significant difference in the incidence of peripheral vascular shadow thickening in patients with COVID-19, other viral pneumonia and bacterial pneumonia (27.8%, 12.5%, 30.0%, P > 0.05). CONCLUSIONS: The probability of ground-glass opacity, paving stone and grid shadow in chest CT of patients with COVID-19 was significantly higher than those of bacterial pneumonia, and it was more common in the lower lungs and lateral dorsal segment. In other patients with viral pneumonia, ground-glass opacity was distributed in both upper and lower lungs. Bacterial pneumonia is usually characterized by single lung consolidation, distributed in lobules or large lobes and accompanied by pleural effusion.

Hijacking the self-replicating machine of bacteriophage for PCR-based cascade signal amplification in detecting SARS-CoV-2 viral marker protein in serum

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Polyvinylidene fluoride multi-scale nanofibrous membrane modified using N-halamine with high filtration efficiency and durable antibacterial properties for air filtration.

HYPOTHESIS: Particulate matter (PM) pollution and the coronavirus (COVID-19) pandemic have increased demand for protective masks. However, typical protective masks only intercept particles and produce peculiar odors if worn for extended periods owing to bacterial growth. Therefore, new protective materials with good filtration and antibacterial capabilities are required. EXPERIMENTS: In this study, we prepared multi-scale polyvinylidene fluoride (PVDF) nanofibrous membranes for efficient filtration and durable antibacterial properties via N-halamine modification. FINDINGS: The N-halamine-modified nanofibrous membrane (PVDF-PAA-TMP-Cl) had sufficient active chlorine content (800 ppm), and the tensile stress and strain were improved compared with the original membrane, from 6.282 to 9.435 MPa and from 51.3 % to 56.4 %, respectively. To further improve the interception efficiency, ultrafine nanofibers (20-35 nm) were spun on PVDF-PAA-TMP-Cl nanofibrous membranes, and multi-scale PVDF-PAA-TMP-Cl nanofibrous membranes were prepared. These membranes exhibited good PM0.3 interception (99.93 %), low air resistance (79 Pa), promising long-term PM2.5 purification ability, and high bactericidal efficiency (>98 %). After ten chlorination cycles, the antibacterial efficiency against Escherichia coli and Staphylococcus aureus exceeded 90 %; hence, the material demonstrated highly efficient filtration and repeatable antibacterial properties. The results of this study have implications for the development of air and water filtration systems and multi-functional protective materials.

APOE interacts with ACE2 inhibiting SARS-CoV-2 cellular entry and inflammation in COVID-19 patients.

Apolipoprotein E (APOE) plays a pivotal role in lipid including cholesterol metabolism. The APOE ε4 (APOE4) allele is a major genetic risk factor for Alzheimer's and cardiovascular diseases. Although APOE has recently been associated with increased susceptibility to infections of several viruses, whether and how APOE and its isoforms affect SARS-CoV-2 infection remains unclear. Here, we show that serum concentrations of APOE correlate inversely with levels of cytokine/chemokine in 73 COVID-19 patients. Utilizing multiple protein interaction assays, we demonstrate that APOE3 and APOE4 interact with the SARS-CoV-2 receptor ACE2; and APOE/ACE2 interactions require zinc metallopeptidase domain of ACE2, a key docking site for SARS-CoV-2 Spike protein. In addition, immuno-imaging assays using confocal, super-resolution, and transmission electron microscopies reveal that both APOE3 and APOE4 reduce ACE2/Spike-mediated viral entry into cells. Interestingly, while having a comparable binding affinity to ACE2, APOE4 inhibits viral entry to a lesser extent compared to APOE3, which is likely due to APOE4's more compact structure and smaller spatial obstacle to compete against Spike binding to ACE2. Furthermore, APOE ε4 carriers clinically correlate with increased SARS-CoV-2 infection and elevated serum inflammatory factors in 142 COVID-19 patients assessed. Our study suggests a regulatory mechanism underlying SARS-CoV-2 infection through APOE interactions with ACE2, which may explain in part increased COVID-19 infection and disease severity in APOE ε4 carriers.

Let AI Perform Better Next Time—A Systematic Review of Medical Imaging-Based Automated Diagnosis of COVID-19: 2020–2022

The pandemic of COVID-19 has caused millions of infections, which has led to a great loss all over the world, socially and economically. Due to the false-negative rate and the time-consuming characteristic of the Reverse Transcription Polymerase Chain Reaction (RT-PCR) tests, diagnosing based on X-ray images and Computed Tomography (CT) images has been widely adopted to confirm positive COVID-19 RT-PCR tests. Since the very beginning of the pandemic, researchers in the artificial intelligence area have proposed a large number of automatic diagnosing models, hoping to assist radiologists and improve the diagnosing accuracy. However, after two years of development, there are still few models that can actually be applied in real-world scenarios. Numerous problems have emerged in the research of the automated diagnosis of COVID-19. In this paper, we present a systematic review of these diagnosing models. A total of 179 proposed models are involved. First, we compare the medical image modalities (CT or X-ray) for COVID-19 diagnosis from both the clinical perspective and the artificial intelligence perspective. Then, we classify existing methods into two types—image-level diagnosis (i.e., classification-based methods) and pixel-level diagnosis (i.e., segmentation-based models). For both types of methods, we define universal model pipelines and analyze the techniques that have been applied in each step of the pipeline in detail. In addition, we also review some commonly adopted public COVID-19 datasets. More importantly, we present an in-depth discussion of the existing automated diagnosis models and note a total of three significant problems: biased model performance evaluation;inappropriate implementation details;and a low reproducibility, reliability and explainability. For each point, we give corresponding recommendations on how we can avoid making the same mistakes and let AI perform better in the next pandemic.

Uncertainty analysis of facemasks in mitigating SARS-CoV-2 transmission.

In the context of global spread of coronavirus disease 2019 (COVID-19) caused by a novel coronavirus (SARS-CoV-2), there is a controversial issue on whether the use of facemasks is promising to control or mitigate the COVID-19 transmission. This study modeled the SARS-CoV-2 transmission process and analyzed the ability of surgical mask and N95 in reducing the infection risk with Sobol's analysis. Two documented outbreaks of COVID-19 with no involvers wearing face masks were reviewed in a restaurant in Guangzhou (China) and a choir rehearsal in Mount Vernon (USA), suggesting that the proposed model can be well validated when airborne transmission is assumed to dominate the virus transmission indoors. Subsequently, the uncertainty analysis of the protection efficiency of N95 and surgical mask were conducted with Monte Carlo simulations, with three main findings: (1) the uncertainty in infection risk is primarily apportioned by respiratory activities, virus dynamics, environment factors and individual exposures; (2) wearing masks can effectively reduce the SARS-CoV-2 infection risk to an acceptable level (< 10-3) by at least two orders of magnitude; (3) faceseal leakage can reduce protection efficiency by approximately 4% when the infector is speaking or coughing, and by approximately 28% when the infector is sneezing. This work indicates the effectiveness of non-pharmaceutical interventions during the pandemic, and implies the importance of the synergistic studies of medicine, environment, social policies and strategies, etc., on reducing hazards and risks of the pandemic.

Exposure Risk to Medical Staff in a Nasopharyngeal Swab Sampling Cabin under Four Different Ventilation Strategies

Medical staff working in a nasopharyngeal swab sampling cabin are exposed to a higher exposure risk of COVID-19. In this study, computational fluid dynamics (CFD) are used to evaluate the exposure risk to medical staff in a nasopharyngeal swab sampling cabin of Chinese customs under four different ventilation strategies, i.e., multiple supply fans ventilation (MSFV), multiple exhaust fans ventilation (MEFV), single exhaust fan and outer windows closed ventilation (SEFV), and single exhaust fan and outer windows opened ventilation (SEFV-W). The impact of physical partitions on exposure risk is also discussed. The results show that MSFV performed best in reducing exposure risk. No significant difference was found between MEFV and SEFV. SEFV-W performed better than SEFV with a ventilation rate of 10–50 L/(s∙Person), while it performed worse with a ventilation rate of 50–90 L/(s∙Person). The exposure risk to medical staff did not decrease linearly with the increase in the ventilation flow rate under the four ventilation strategies. For MSFV, the installation of partitions is conducive to the reduction in the exposure risk. This study is expected to provide some guidance for ventilation designs in sampling cabins.

A Regional Industrial Economic Forecasting Model Based on a Deep Convolutional Neural Network and Big Data

To accurately predict the economic development of each industry in different types of regions, a deep convolutional neural network model was designed for predicting the annual GDP;GDP growth index;and primary, secondary and tertiary industry growth values of each. In the model, raw industrial data are preprocessed by a normalization operation and subsequently transformed by the BoxCox method to approach the normal distribution. Panel data of consecutive years are constructed and used as input to the deep convolutional neural network, and industrial data of year t + 1 are used as the output of the network. Simulation experiments were conducted to analyze 23 years of industrial economic data from 31 provinces, municipalities, and autonomous regions in China. The experimental results show that R-squared value is larger than 0.91 for all 31 provinces and root mean squared log errors (RMSLE) of all regions are less than 0.1, which demonstrate that the proposed method achieves high prediction accuracy with generalization capability and can accurately predict the economic growth trends of different types of regions.

Biodegradable and high-performance multiscale structured nanofiber membrane as mask filter media via poly(lactic acid) electrospinning.

The usage of single-use face masks (SFMs) has increased since the outbreak of the coronavirus pandemic. However, non-degradability and mismanagement of SFMs have raised serious environmental concerns. Moreover, both melt-blown and nanofiber-based mask filters inevitably suffer from poor filtration performance, like a continuous decrease in the removal efficiency for particulate matter (PM) and weak breathability. Herein, we report a new method to create biodegradable and reusable fibrous mask filters. The filter consists of a true nanoscale bio-based poly(lactic acid) (PLA) fiber (an average size of 37 ± 4 nm) that is fabricated via electrospinning of an extremely dilute solution. Furthermore, we designed a multiscale structure with integrated features, such as low basis weight (0.91 g m-2), small pore size (0.73 µm), and high porosity (91.72%), formed by electrospinning deposition of true nanoscale fibers on large pore of 3D scaffold nanofiber membranes. The resultant mask filter exhibited a high filtration efficiency (PM0.3-99.996%) and low pressure drop (104 Pa) superior to the commercial N95 filter. Importantly, this filter has a durable filtering efficiency for PM and natural biodegradability based on PLA. Therefore, this study offers an innovative strategy for the preparation of PLA nanofibers and provides a new design for high-performance nanofiber filters.

Extended short-range airborne transmission of respiratory infections.

Debate and scientific inquiries regarding airborne transmission of respiratory infections such as COVID-19 and influenza continue. Health authorities including the WHO and the US CDC have recognized the airborne transmission of COVID-19 in specific settings, although the ventilation requirements remain to be determined. In this work we consider the long-range airborne transmission as an extended short-range airborne route, which reconciles the link between short- and long-range airborne routes. The effective short-range distance is defined as the distance in short range at which long-range route has the same volumetric exposure value as that due to short-range route. Our data show that a decrease in ventilation rate or room volume per person, or an increase in the ratio of the number of infected to susceptible people reduces the effective short-range distance. In a normal breathing scenario with one out of five people infected and a room volume of 12 m3 per person to ensure an effective short-range distance of 1.5 m, a ventilation rate of 10 L/s per person is needed for a duration of 2 h. Our results suggest that effective environmental prevention strategies for respiratory infections require appropriate increases in the ventilation rate while maintaining a sufficiently low occupancy. PRACTICAL IMPLICATIONS: Demonstration of the long-range airborne route as an extended short-range airborne route suggests the significant role played by building ventilation in respiratory infection exposure. The reconciliation of short- and long-range airborne transmission suggests that the commonly observed dominance of close-contact transmission is a probable evidence of short-range airborne transmission, following a separate earlier study that revealed the relative insignificance of large droplet transmission in comparison with the short-range airborne-route. Existing ventilation standards do not account for respiratory infection control, and this study presents a possible approach to account for infection under new ventilation standards.

PAN/FPU Composite Nanofiber Membrane with Superhydrophobic and Superoleophobic Surface as a Filter Element for High‐Efficiency Protective Masks

Recently, because of the outbreak of COVID‐19, the demand for various types of filter elements in protective materials has increased globally. Furthermore, new requirements for the filtration performance of PM2.5 liquid (oil) particles have been put forward. In this work, Superhydrophobic and superoleophobic composite nanofibers with excellent filtration capacity for oil and salt particles are developed through the modification of polyacrylonitrile (PAN) by fluoro‐polyurethane (FPU) doping. The results show that the PAN/FPU composite nanofibers doped with 9 wt% FPU has a uniform fiber morphology with a diameter of 240 ± 30 nm. Compared to the pure PAN nanofibers, the water‐based contact angle of PAN/FPU increases from 90 ± 5° to 151 ± 5°, and the oil‐based contact angle increases from 58 ± 2° to 152 ± 3°. Importantly, at a high flow rate of 95 L min−1, the filtration efficiency of the PAN/FPU nanofiber membrane for 0.3 µm oil particles increases from 92 ± 1% to 99.2 ± 0.1%. After cyclic loading, the filtration efficiency of 0.3 µm oil particles remains above 98%. Meanwhile, the filtration efficiency for 0.3 µm salt particles remains at 98.23 ± 0.1%. The PAN/FPU nanofiber membrane developed in this work is effective in applications and has good market prospects as a protective filtration material. [ABSTRACT FROM AUTHOR] Copyright of Macromolecular Materials & Engineering is the property of John Wiley & Sons, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Revisiting physical distancing threshold in indoor environment using infection-risk-based modeling.

Physical distancing has been an important policy to mitigate the spread of the novel coronavirus disease 2019 (COVID-19) in public settings. However, the current 1-2 m physical distancing rule is based on the physics of droplet transport and could not directly translate into infection risk. We therefore revisit the 2-m physical distancing rule by developing an infection-risk-based model for human speaking. The key modeling framework components include viral load, droplets dispersion and evaporation, deposition efficiency, viral dose-response rate and infection risk. The results suggest that the one-size-fits-all 2-m physical distancing rule derived from the pure droplet-physics-based model is not applicable under some realistic indoor settings, and may rather increase transmission probability of diseases. Especially, in thermally stratified environments, the infection risk could exhibit multiple peaks for a long distance beyond 2 m. With Sobol's sensitivity analysis, most variance of the risk is found to be significantly attributable to the variability in temperature gradient, exposure time and breathing height difference. Our study suggests there is no such magic 2 m physical distancing rule for all environments, but it needs to be used alongside other strategies, such as using face cover, reducing exposure time, and controlling the thermal stratification of indoor environment.

Evidence for CAT gene being functionally involved in the susceptibility of COVID-19.

Novel coronary pneumonia (COVID-19) is a respiratory distress syndrome caused by a new type of coronavirus. Understanding the genetic basis of susceptibility and prognosis to COVID-19 is of great significance to disease prevention, molecular typing, prognosis, and treatment. However, so far, there have been only two genome-wide association studies (GWASs) on the susceptibility of COVID-19. Starting with these reported DNA variants, we found the genes regulated by these variants through cis-eQTL and cis-meQTL acting. We further did a series of bioinformatics analysis on these potential risk genes. The analysis shows that the genetic variants on EHF regulate the expression of its neighbor CAT gene via cis-eQTL. There was significant evidence that CAT and the SARS-CoV-2-related S protein binding protein ACE2 interact with each other. Intracellular localization results showed that CAT and ACE2 proteins both exists in the cell membrane and extracellular area and their interaction could have an impact on the cell invasion ability of S protein. In addition, the expression of these three genes showed a significant positive correlation in the lungs. Based on these results, we propose that CAT plays a crucial intermediary role in binding effectiveness of ACE2, thereby affecting the susceptibility to COVID-19.

Are You Tired of Working amid the Pandemic? The Role of Professional Identity and Job Satisfaction against Job Burnout.

With the outbreak of novel coronavirus in 2019, most universities changed from traditional offline teaching to online teaching, which brought about a large amount of problems, including teachers' physical and mental problems. Because of teaching on the computer screen for a long period of time, the teacher lacks communication and can act casually. With long-term accumulation, the problem of teachers' job burnout has become increasingly serious. The main purpose of this study was to examine the influence of professional identity on job burnout during the period of the novel coronavirus. At the same time, this study also discussed the moderating effect of job satisfaction on professional identity and job burnout, and its relationship between job satisfaction and job burnout. During the peak period of the COVID-19 epidemic, we conducted an online survey-483 Chinese university teachers with online teaching experience completed the Teacher Professional Identity Scale, Job Satisfaction Scale, and Job Burnout Scale. The results of this study found professional identity and job satisfaction of university teachers to be significantly negative predictors of job burnout, with job satisfaction playing a moderating role between professional identity and job burnout. This study also confirmed that professional identity and job satisfaction are important factors affecting job burnout of university teachers. Therefore, this study proposed that schools should adopt more effective strategies to improve university teachers' professional identity and job satisfaction in order to reduce the practical problems of job burnout, ensure the effectiveness of online teaching, and maintain the sustainable development during the epidemic.

COVID-19 and cardiovascular diseases.

The coronavirus disease 2019 (COVID-19) remains a global public health emergency. Despite being caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), besides the lung, this infectious disease also has severe implications in the cardiovascular system. In this review, we summarize diverse clinical complications of the heart and vascular system, as well as the relevant high mortality, in COVID-19 patients. Systemic inflammation and angiotensin-converting enzyme 2-involved signaling networking in SARS-CoV-2 infection and the cardiovascular system may contribute to the manifestations of cardiovascular diseases. Therefore, integration of clinical observations and experimental findings can promote our understanding of the underlying mechanisms, which would aid in identifying and treating cardiovascular injury in patients with COVID-19 appropriately.