DDX3X Is Hijacked by Snakehead Vesiculovirus Phosphoprotein To Facilitate Virus Replication via Stabilization of the Phosphoprotein.

Asp-Glu-Ala-Asp (DEAD) box helicase 3 X-linked (DDX3X) plays important regulatory roles in the replication of many viruses. However, the role of DDX3X in rhabdovirus replication has seldomly been investigated. In this study, snakehead vesiculovirus (SHVV), a kind of fish rhabdovirus, was used to study the role of DDX3X in rhabdovirus replication. DDX3X was identified as an interacting partner of SHVV phosphoprotein (P). The expression level of DDX3X was increased at an early stage of SHVV infection and then decreased to a normal level at a later infection stage. Overexpression of DDX3X promoted, while knockdown of DDX3X using specific small interfering RNAs (siRNAs) suppressed, SHVV replication, indicating that DDX3X was a proviral factor for SHVV replication. The N-terminal and core domains of DDX3X (DDX3X-N and DDX3X-Core) were determined to be the regions responsible for its interaction with SHVV P. Overexpression of DDX3X-Core suppressed SHVV replication by competitively disrupting the interaction between full-length DDX3X and SHVV P, suggesting that full-length DDX3X-P interaction was required for SHVV replication. Mechanistically, DDX3X-mediated promotion of SHVV replication was due not to inhibition of interferon expression but to maintenance of the stability of SHVV P to avoid autophagy-lysosome-dependent degradation. Collectively, our data suggest that DDX3X is hijacked by SHVV P to ensure effective replication of SHVV, which suggests an important anti-SHVV target. This study will help elucidate the role of DDX3X in regulating the replication of rhabdoviruses. IMPORTANCE Growing evidence has suggested that DDX3X plays important roles in virus replication. In one respect, DDX3X inhibits the replication of viruses, including hepatitis B virus, influenza A virus, Newcastle disease virus, duck Tembusu virus, and red-spotted grouper nervous necrosis virus. In another respect, DDX3X is required for the replication of viruses, including hepatitis C virus, Japanese encephalitis virus, West Nile virus, murine norovirus, herpes simplex virus, and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Because DDX3X has rarely been investigated in rhabdovirus replication, this study aimed at investigating the role of DDX3X in rhabdovirus replication by using the fish rhabdovirus SHVV as a model. We found that DDX3X was required for SHVV replication, with the mechanism that DDX3X interacts with and maintains the stability of SHVV phosphoprotein. Our data provide novel insights into the role of DDX3X in virus replication and will facilitate the design of antiviral drugs against rhabdovirus infection.

Integrated bioinformatics to identify potential key biomarkers for COVID-19-related chronic urticaria.

Background: A lot of studies have revealed that chronic urticaria (CU) is closely linked with COVID-19. However, there is a lack of further study at the gene level. This research is aimed to investigate the molecular mechanism of COVID-19-related CU via bioinformatic ways. Methods: The RNA expression profile datasets of CU (GSE72540) and COVID-19 (GSE164805) were used for the training data and GSE57178 for the verification data. After recognizing the shared differently expressed genes (DEGs) of COVID-19 and CU, genes enrichment, WGCNA, PPI network, and immune infiltration analyses were performed. In addition, machine learning LASSO regression was employed to identify key genes from hub genes. Finally, the networks, gene-TF-miRNA-lncRNA, and drug-gene, of key genes were constructed, and RNA expression analysis was utilized for verification. Results: We recognized 322 shared DEGs, and the functional analyses displayed that they mainly participated in immunomodulation of COVID-19-related CU. 9 hub genes (CD86, FCGR3A, AIF1, CD163, CCL4, TNF, CYBB, MMP9, and CCL3) were explored through the WGCNA and PPI network. Moreover, FCGR3A, TNF, and CCL3 were further identified as key genes via LASSO regression analysis, and the ROC curves confirmed the dependability of their diagnostic value. Furthermore, our results showed that the key genes were significantly associated with the primary infiltration cells of CU and COVID-19, such as mast cells and macrophages M0. In addition, the key gene-TF-miRNA-lncRNA network was constructed, which contained 46 regulation axes. And most lncRNAs of the network were proved to be a significant expression in CU. Finally, the key gene-drug interaction network, including 84 possible therapeutical medicines, was developed, and their protein-protein docking might make this prediction more feasible. Conclusions: To sum up, FCGR3A, TNF, and CCL3 might be potential biomarkers for COVID-19-related CU, and the common pathways and related molecules we explored in this study might provide new ideas for further mechanistic research.

Chemical characteristics and sources of PM2.5 in Hohhot, a semi-arid city in northern China: insight from the COVID-19 lockdown

A knowledge gap exists concerning how chemical composition and sources respond to implemented policy control measures for aerosols, particularly in a semi-arid region. To address this, a single year's offline measurement was conducted in Hohhot, a semi-arid city in northern China, to reveal the driving factors of severe air pollution in a semi-arid region and assess the impact of the COVID-19 lockdown measures on chemical characteristics and sources of PM2.5. Organic matter, mineral dust, sulfate and nitrate accounted for 31.5 %, 14.2 %, 13.4 % and 12.3 % of the total PM2.5 mass, respectively. Coal combustion, vehicular emission, crustal source and secondary inorganic aerosols were the main sources of PM2.5 in Hohhot, at 38.3 %, 35.0 %, 13.5 %, and 11.4 %, respectively. Due to the coupling effect of emission reduction and improved atmospheric conditions, the concentration of secondary inorganic components, organic matter and elemental carbon declined substantially from the pre-lockdown (pre-LD) period to the lockdown (LD) and post-lockdown (post-LD) periods. The source contribution of secondary inorganic aerosols increased (from 21.1 % to 37.8 %), whereas the contribution of vehicular emission reduced (from 35.5 % to 4.4 %) due to lockdown measures. The rapid generation of secondary inorganic components caused by unfavorable meteorological conditions during lockdown led to serious pollution. This study elucidates the complex relationship between air quality and environmental policy.

Increased utilization of teledermatology among Medicare Part B beneficiaries during the COVID-19 pandemic.

Enhanced telehealth flexibilities in response to the COVID-19 pandemic have prompted heightened use across many physician specialties; yet, national trends have not been assessed within dermatology, specifically. In this longitudinal review of 2017 to 2020 Medicare billing data, we identified a 210-fold increase in teledermatology evaluation and management (E&M) visits between 2019 and 2020, which helped to slightly offset the substantial 20.1% decline in in-person E&M visits. Teledermatology comprised an overall greater proportion of E&M visits in states with the largest declines in in-person visits. Teledermatology E&M visits were primarily comprised by established patient video visits (74.3%); yet, the relatively more substantial role of telephone-only visits in certain rural states may reflect limitations in technologic access in these areas. Asynchronous teledermatology (including store-and-forward dermatology) also increased by 34-fold in 2020, supporting its utility for evaluation of a changing lesion or for triage purposes. The findings underscore the growing role of telehealth in dermatologic care and are important given that certain telehealth flexibilities are set to expire at the end of the public health emergency without additional congressional intervention.

Dynamic Behavior Investigation of a Novel Epidemic Model Based on COVID-19 Risk Area Categorization

This study establishes a compartment model for the categorized COVID-19 risk area. In this model, the compartments represent administrative regions at different transmission risk levels instead of individuals in traditional epidemic models. The county-level regions are partitioned into High-risk (H), Medium-risk (M), and Low-risk (L) areas dynamically according to the current number of confirmed cases. These risk areas are communicable by the movement of individuals. An LMH model is established with ordinary differential equations (ODEs). The basic reproduction number R0 is derived for the transmission of risk areas to determine whether the pandemic is controlled. The stability of this LHM model is investigated by a Lyapunov function and Poincare–Bendixson theorem. We prove that the disease-free equilibrium (R0 < 1) is globally asymptotically stable and the disease will die out. The endemic equilibrium (R0 > 1) is locally and globally asymptotically stable, and the disease will become endemic. The numerical simulation and data analysis support the previous theoretical proofs. For the first time, the compartment model is applied to investigate the dynamics of the transmission of the COVID-19 risk area. This work should be of great value in the development of precision region-specific containment strategies.

Why Controlling the Asymptomatic Infection Is Important: A Modelling Study with Stability and Sensitivity Analysis

The large proportion of asymptomatic patients is the major cause leading to the COVID-19 pandemic which is still a significant threat to the whole world. A six-dimensional ODE system (SEIAQR epidemical model) is established to study the dynamics of COVID-19 spreading considering infection by exposed, infected, and asymptomatic cases. The basic reproduction number derived from the model is more comprehensive including the contribution from the exposed, infected, and asymptomatic patients. For this more complex six-dimensional ODE system, we investigate the global and local stability of disease-free equilibrium, as well as the endemic equilibrium, whereas most studies overlooked asymptomatic infection or some other virus transmission features. In the sensitivity analysis, the parameters related to the asymptomatic play a significant role not only in the basic reproduction number R0. It is also found that the asymptomatic infection greatly affected the endemic equilibrium. Either in completely eradicating the disease or achieving a more realistic goal to reduce the COVID-19 cases in an endemic equilibrium, the importance of controlling the asymptomatic infection should be emphasized. The three-dimensional phase diagrams demonstrate the convergence point of the COVID-19 spreading under different initial conditions. In particular, massive infections will occur as shown in the phase diagram quantitatively in the case R0>1. Moreover, two four-dimensional contour maps of Rt are given varying with different parameters, which can offer better intuitive instructions on the control of the pandemic by adjusting policy-related parameters.

Is Outdoor Recreation Associated with Greater Climate Change Concern in the United States?

There has been extensive research on the association between environmental attitudes and outdoor recreation (or nature-based leisure activities) since the 1970s. There is now considerable evidence to support the claim that spending time in nature leads to greater connectedness to nature and thereby greater pro-environmental attitudes and behavior. However, there is an absence of research focused specifically on the association between outdoor recreation and concern for climate change, which is arguably the most pressing environmental problem facing the world today. We build on previous research by using the 2021 General Social Survey and structural equation modeling to analyze the association between frequency of engaging in outdoor recreation and concern for climate change among adults in the United States, with special attention to the role of enjoying being in nature. Controlling for other factors, we find that frequency of outdoor recreation has a positive, significant effect on climate change concern, but only indirectly via enjoyment of nature. Individuals who more frequently engage in outdoor recreation activities tend to report a greater sense of enjoyment of being outside in nature, and this enjoyment of nature is associated with a higher level of concern for climate change.

Pathogenesis and Treatment of Cytokine Storm Induced by Infectious Diseases.

Cytokine storm is a phenomenon characterized by strong elevated circulating cytokines that most often occur after an overreactive immune system is activated by an acute systemic infection. A variety of cells participate in cytokine storm induction and progression, with profiles of cytokines released during cytokine storm varying from disease to disease. This review focuses on pathophysiological mechanisms underlying cytokine storm induction and progression induced by pathogenic invasive infectious diseases. Strategies for targeted treatment of various types of infection-induced cytokine storms are described from both host and pathogen perspectives. In summary, current studies indicate that cytokine storm-targeted therapies can effectively alleviate tissue damage while promoting the clearance of invading pathogens. Based on this premise, "multi-omics" immune system profiling should facilitate the development of more effective therapeutic strategies to alleviate cytokine storms caused by various diseases.

Crop yield forecasting and associated optimum lead time analysis based on multi-source environmental data across China

• Develop a within-growing season yield forecast system with random forest model. • Random forest model performs well in predicting grain yield in China. • We identified the most important stage-specific predictors determining crop yield. • The most important variable influencing yields varied with crop types. Accurate and timely crop yield forecasts can provide essential information to make conclusive agricultural policies and to conduct investments. Recent studies have used different machine learning techniques to develop such yield forecast systems for single crops at regional scales. However, no study has used multiple sources of environmental predictors (climate, soil, and vegetation) to forecast yields for three major crops in China. In this study, we adopted 7-year observed crop yield data (2013–2019) for three major grain crops (wheat, maize, and rice) across China, and three major data sets including climate, vegetation indices, and soil properties were used to develop a dynamic yield forecasting system based on the random forest (RF) model. The RF model showed good performance for estimating yields of all three crops with correlation coefficient (r) higher than 0.75 and normalized root means square errors (nRMSE) lower than 18.0%. Our results also showed that crop yields can be satisfactorily forecasted at one to three months prior to harvest. The optimum lead time for yield forecasting depended on crop types. In addition, we found the major predictors influencing crop yield varied between crops. In general, solar radiation and vegetation indices (especially during jointing to milk development stages) were identified as the main predictor for winter wheat;vegetation indices (throughout the growing season) and drought (especially during emergence to tasseling stages) were the most important predictors for spring maize;soil moisture (throughout the growing season) was the dominant predictor for summer maize, late rice, and mid rice;precipitation (especially during booting to heading stages) was the main predictor for early rice. Our study provides insights into practical crop yield forecasting and the understanding of yield response to environmental conditions at a large scale across China. The methods undertaken in this research can be easily implemented in other countries with available information on climate, soil, and vegetation conditions. [ABSTRACT FROM AUTHOR] Copyright of Agricultural & Forest Meteorology is the property of Elsevier B.V. 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.)

Constructing a plasma-based Schottky heterojunction for near-infrared-driven photothermal synergistic water disinfection: synergetic effects and antibacterial mechanisms

Developing green and highly efficient water disinfection technique is of great importance to public health. Herein, a near-infrared (NIR) light-triggerable thermo-sensitive defective molybdenum oxide-nitrogen doped carbon (MoO3-x/NCNs) composite was fabricated and applied to water disinfection. With the synergy of photodynamic and photothermal effects, the MoO3-x/NCNs achieve a rapid and effective inactivation of Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) as compared to photocatalytic treatment or thermal catalytic alone. Particularly, MONC-3 with optimal ratio can completely inactivate 7.6 log of E. coli and S. aureus within 60 min and 100 min, respectively. The MONC-3 hybrid exhibits efficient charge separation and migration ability due to the formation of Schottky heterojunction, resulting in the highly enhanced ·O2– (11.34×10-10 M) generation activity. Meanwhile, excellent NIR light absorption and photothermal conversion efficiency (52.6%) of MONC-3 can generate local high temperature to promote photocatalytic reaction rate and destruct the bacterial integrity. The monitoring of cell damage process confirmed the irreversible death of bacteria. Based on density functional theory (DFT) calculation, the antibacterial mechanism and Schottky effect were clarified. This work provides new insights for constructing a water disinfection strategy based on plasma-induced photothermal synergy catalysis.

Pea Protein Nanoemulsion Effectively Stabilizes Vitamin D in Food Products: A Potential Supplementation during the COVID-19 Pandemic.

Vitamin D deficiency is a global issue which has been exacerbated by the COVID-19 pandemic-related lockdowns. Fortification of food staples with vitamin D provides a solution to alleviate this problem. This research explored the use of pea protein nanoemulsion (PPN) to improve the stability of vitamin D in various food products. PPN was created using a pH-shifting and ultrasonication combined method. The physicochemical properties were studied, including particle size, foaming ability, water holding capacity, antioxidant activity, and total phenolic contents. The fortification of several food formulations (non-fat cow milk, canned orange juice, orange juice powder, banana milk, and infant formula) with vitamin D-PPN was investigated and compared to raw untreated pea protein (UPP) regarding their color, viscosity, moisture content, chemical composition, vitamin D stability, antioxidant activity, and morphology. Finally, a sensory evaluation (quantitative descriptive analysis, and consumer testing) was conducted. The results show that PPN with a size of 21.8 nm protected the vitamin D in all tested products. PPN may serve as a potential carrier and stabilizer of vitamin D in food products with minimum effects on the taste and color. Hence, PPN may serve as a green and safe method for food fortification during the COVID-19 pandemic.

The impact of COVID-19 on small and medium-sized enterprises (SMEs): Evidence from two-wave phone surveys in China.

This paper examines the short-term and mid-term impact of COVID-19 restrictions on SMEs, based on two waves of phone interviews with a previously surveyed large SME sample in China. The outbreak of COVID-19 and the resultant lockdowns took a heavy toll on SMEs. Afflicted by problems of logistics blocks, labor shortages, and drops in demand, 80% of SMEs were temporarily closed at the time of the first wave of interviews in February 2020. After reining in COVID-19, authorities largely eased lockdown restrictions in April. Consequently, most SMEs had reopened by the time of the second round of surveys in May. However, many firms, particularly export firms, were running at partial capacity, primarily due to inadequate demand. Moreover, around 19% of incorporated enterprises and 25% of self-employed businesses had permanently closed between the two waves of surveys.

Effects of the COVID-19 Pandemic on Anti-vascular Endothelial Growth Factor Treatment in China.

We evaluated the impact of the COVID-19 pandemic on anti-VEGF treatment in ophthalmology patients in a single hospital in northern China. A total of 93 anti-VEGF injections were administered to 85 eyes of 72 patients at The China Medical University First Hospital Department of Ophthalmology during the COVID-19 pandemic. Compared to the same period in 2019, the number of injections decreased by 70%. Fifty-nine eyes of 46 patients were receiving 3+PRN anti-VEGF treatment prior to the outbreak of the COVID-19 pandemic; all of these patients experienced treatment interruptions due to COVID-19-associated reasons. Anatomic and functional outcomes suggest that patients with anti-VEGF treatment interruptions are at risk for severe adverse visual sequelae. Moreover, deferred anti-VEGF treatment due to patient-related or department-related reasons during the COVID-19 pandemic may result in poor visual outcomes for new patients. Our results suggest that COVID-19 has had a significant negative effect on anti-VEGF treatment in ophthalmology patients. Detailed guidance from global experts in ophthalmology is highly sought after in these challenging circumstances.