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Tick-borne viruses (TBVs) have increasingly caused a global public health concern. This study collected Rhipicephalus ticks in Guangdong, southern China to identify RNA viruses. Meta-transcriptome analysis revealed the virome in Rhipicephalus ticks, resulting in the discovery of 10 viruses, including Lihan tick virus, Brown dog tick phlebovirus 1 and 2 in the family Phenuiviridae, Mivirus and Wuhan tick virus 2 in the family Chuviridae, Wuhan tick virus 1 in the family Rhabdoviridae, bovine hepacivirus in the family Flaviviridae, Guangdong tick quaranjavirus (GTQV) in the family Orthomyxoviridae, Guangdong tick orbivirus (GTOV) in the family Reoviridae, and Guangdong tick Manly virus (GTMV) of an unclassified family. Phylogenetic analysis showed that most of these TBVs were genetically related to the strains in countries outside China, and GTQV, GTOV, and GTMV may represent novel viral species. These findings provided evidence of the long-distance spread of these TBVs in Guangdong, southern China, suggesting the necessity and importance of TBV surveillance. [ABSTRACT FROM AUTHOR]

During its 6,300-km course from the Tibetan Plateau to the ocean, the Yangtze River is joined by two large lakes: Dongting Lake and Poyang Lake. We explain why these lakes exist. Deglaciation forced the ocean adjacent to the Yangtze mouth to rise ∼120 m. This forced a wave of rising water surface elevation and concomitant bed aggradation upstream. While aggradation attenuated upstream, the low bed slope of the Middle-Lower Yangtze River (∼2 × 10-5 near Wuhan) made it susceptible to sea level rise. The main stem, sourced at 5,054 m above sea level, had a substantial sediment load to “fight” against water surface level rise by means of bed aggradation. The tributaries of the Middle-Lower Yangtze have reliefs of approximately hundreds of meters, and did not have enough sediment supply to fill the tributary accommodation space created by main-stem aggradation. We show that the resulting tributary blockage likely gave rise to the lakes. We justify this using field data and numerical modeling, and derive a dimensionless number capturing the critical rate of water surface rise for blockage versus nonblockage. [ABSTRACT FROM AUTHOR]

In order to investigate the pollution status and sedimentary records of polycyclic aromatic hydrocarbons (PAHs) in the sediments of Houguan Lake in Wuhan, this study collected 7 surface sediment samples and 1 sedimentary column sample in September 2020. The sedimentary column chronological sequence of the Lake was constructed using a combined 210Pb and 137Cs dating method. The content of 16 optimized PAHs was analyzed using gas chromatography-mass spectrometry (GC-MS), and the source of PAHs was analyzed using characteristic ratio method. The results showed that the average concentration of PAHs in the surface sediment was (247.90±32.01) ng/g, belonging to a moderate pollution level, with 3 and 4 ring PAHs being the main pollutants, and there was no significant difference in spatial distribution. The sedimentation rate of the sedimentary column is 0.73 cm/a, and the collected sedimentary column can reflect the sedimentation process in the past 160 years. The average content of 16 PAHs in the sedimentary column is 56.84 ng/g, indicating a low pollution level. According to the composition characteristics of PAHs, the sedimentation process is divided into four stages. The composition characteristics of PAHs in different stages differ significantly, reflecting the transformation of energy structure in different historical periods. Before the 21st century, there was a significant positive correlation between the content of PAHs and socio-economic indicators such as GDP and permanent population. In recent years, the content of PAHs have been mainly affected by meteorological conditions such as evaporation and temperature, indicating that with China' s emphasis on ecological civilization construction, Wuhan has achieved certain results in ecological environment protection. [ABSTRACT FROM AUTHOR]

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High resolution satellite images are becoming increasingly available for urban multi-temporal semantic understanding. However, few datasets can be used for land-use/land-cover (LULC) classification, binary change detection (BCD) and semantic change detection (SCD) simultaneously because classification datasets always have one time phase and BCD datasets focus only on the changed location, ignoring the changed classes. Public SCD datasets are rare but much needed. To solve the above problems, a tri-temporal SCD dataset made up of Gaofen-2 (GF-2) remote sensing imagery (with 11 LULC classes and 60 change directions) was built in this study, namely, the Wuhan Urban Semantic Understanding (WUSU) dataset. Popular deep learning based methods for LULC classification, BCD and SCD are tested to verify the reliability of WUSU. A Siamese-based multi-task joint framework with a multi-task joint loss (MJ loss) named ChangeMJ is proposed to restore the object boundaries and obtains the best results in LULC classification, BCD and SCD, compared to the state-of-the-art (SOTA) methods. Finally, a large spatial-scale mapping for Wuhan central urban area is carried out to verify that the WUSU dataset and the ChangeMJ framework have good application values. [ABSTRACT FROM AUTHOR]

The normalized difference vegetation index (NDVI) is the most widely used vegetation index for monitoring vegetation vigor and cover. As NDVI time series are usually derived at coarse or medium spatial resolutions, pixel size often represents a mixture of vegetated and non-vegetated surfaces. In heterogeneous urban areas, mixed pixels impede the accurate estimation of gross primary productivity (GPP). To address the mixed pixel effect on NDVI time series and GPP estimation, we proposed a framework to extract subpixel vegetation NDVI (NDVIvege) from Landsat OLI images in urban areas, using endmember fractions, mixed NDVI (NDVImix), and NDVI of non-vegetation endmembers. Results demonstrated that the NDVIvege extracted by this framework agreed well with the true NDVIvege cross seasons and vegetation fractions, with R2 ranging from 0.74 to 0.82 and RMSE ranging from 0.03 to 0.04. The NDVIvege time series was applied to evaluate vegetation GPP in Wuhan, China. The total annual GPP estimated with NDVIvege was 28-35% higher than the total annual GPP estimated with NDVImix, implying uncertainty in the GPP estimations caused by mixed pixels. This study showed the potential of the proposed framework to resolve NDVIvege for characterizing vegetation dynamics in heterogeneous areas. [ABSTRACT FROM AUTHOR]

Regional submicron particles (PM1) compositions, sources, and interaction are still not clear as the desynchrony in observation. This study focused on PM1 at five sites synchronously in North China Plain and Central China during January 2018. The average PM1 mass concentrations decreased from north to south, with higher values in Luohe (125 ± 59.4 μg m−3), followed by borderline cities (54.1–93.3 μg m−3) and a south site of Wuhan (63.6 ± 21.5 μg m−3). Organic matter (41.8%–51.0%) and secondary inorganic aerosols (SIAs; 28.2%–33.2%) occupied the high fractions for all the five sites. Coal combustion and industrial processes mainly raised the differences in PM1 chemical compositions between regions. The changes of NO3−/SO42− between sites were different as a function of relatively humidity and temperature, reflecting the differences of secondary formation mechanism. For a short intraregional transport case from south to north, PM1 increased from 102 to 185 μg m−3 as the accumulation and aerosol‐planet boundary layer interaction under a stable meteorological condition. For a long‐range transport case from north to south with a high wind speed (5.5 m s−1) and boundary layer height (529 m), PM1 decreased by only 0.9 μg m−3 (−1.3%) as the enhanced formation of SIA by 12.6% under increased relative humidity (by 7.2%) and enhanced industrial emission (by 19.1%) at the south site. The results provide a useful data set for modeling PM1 chemical compositions and their impacts and are helpful for regional‐joint control of atmospheric particles and precursor gases. Plain Language Summary: Studies have shown that PM1 has a significant impact on health, climate, and economy, but its chemical compositions, sources, and transport between North China Plain (NCP) and Central China (CC) are still poorly characterized. This study focused on the comprehensive characterization of PM1 species at five sites in NCP and CC during January 2018. The mass concentration of PM1 showed a decreasing trend from north (125 ± 59.4 μg m−3) to south (54.1 ± 20.5 μg m−3). The organic matter and secondary inorganic aerosols (SIAs) are the two most important species of PM1 which contributed 41.8%–51.0% and 28.2%–33.2%, respectively. Coal combustion and industrial processes mainly raised the differences in chemical compositions between regions. Differences in the transformation of secondary aerosols between the regions indicated the control precursor pollutants should be emphasized. The PM1 increased sharply from 102 to 185 μg m−3 with the influences of vehicle emission (38.6%) when the transport direction was from south to north. The PM1 decreased slightly (−1.3%) as the enhanced formation of SIA (+12.6%) and emission of industry (+19.1%) when the transport direction changed from north to south. The results are helpful for further understanding the differences between regions and regional‐joint control. Key Points: Organic matter and secondary inorganic aerosol are the dominant species in PM1The chemical species and sources of PM1 varied in North and South ChinaTwo transport cases explain the aerosol accumulation and interplay between north and south [ABSTRACT FROM AUTHOR]

Objective: Lung cancer is responsible for millions of deaths yearly, and its burden is severe worldwide. This study aimed to investigate the burden of lung cancer in the population of Wuhan based on the surveillance data from 2010 to 2019. Methods: Data of this study was obtained from the Mortality Register System established by the Wuhan Center for Disease Control and Prevention. The study systematically analyzed the burden of lung cancer deaths in the population of Wuhan and its 13 administrative regions from 2010 to 2019 via the Joinpoint regression models, Age-Period-Cohort (APC) models, and decomposition analysis. Results: This study found the upward and downward trends in the agestandardized mortality rates (ASMRs) and age-standardized years of life lost rates (ASYLLRs) of lung cancer from 2010 to 2019. In Joinpoint regression models, the corresponding estimated annual percentage change (EAPC) were 1.00% and -1.90%, 0.60%, and -3.00%, respectively. In APC models, lung cancer mortality tended to increase with age for both sexes in Wuhan, peaking at the 85-89 age group; The period effects for different populations have started to gradually decline in recent years. In addition, the cohort effects indicated that the risk of lung cancer death was highest among those born in the 1950s-1955s, at 1.08 (males) and 1.01 (females). Among all administrative districts in Wuhan, the ASMR of lung cancer in the Xinzhou District has remained the highest over the study period. In decomposition analysis, both population aging (P<0.01) and population growth (P<0.01) aggravated (Z>0) lung cancer deaths in the Wuhan population. Conclusions: The burden of lung cancer death in the Wuhan population has shown a gradual decline in recent years, but the impact of aging and population growth on lung cancer mortality should not be ignored. Therefore, lung cancer surveillance must be strengthened to reduce the burden of lung cancer in Wuhan. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) pandemic began in January 2020 in Wuhan, China, with a new coronavirus designated SARS-CoV-2. The principal cause of death from COVID-19 disease quickly emerged as acute respiratory distress syndrome (ARDS). A key ARDS pathogenic mechanism is the "Cytokine Storm", which is a dramatic increase in inflammatory cytokines in the blood. In the last two years of the pandemic, a new pathology has emerged in some COVID-19 survivors, in which a variety of long-term symptoms occur, a condition called post-acute sequelae of COVID-19 (PASC) or "Long COVID". Therefore, there is an urgent need to better understand the mechanisms of the virus. The spike protein on the surface of the virus is composed of joined S1–S2 subunits. Upon S1 binding to the ACE2 receptor on human cells, the S1 subunit is cleaved and the S2 subunit mediates the entry of the virus. The S1 protein is then released into the blood, which might be one of the pivotal triggers for the initiation and/or perpetuation of the cytokine storm. In this study, we tested the hypothesis that the S1 spike protein is sufficient to activate inflammatory signaling and cytokine production, independent of the virus. Our data support a possible role for the S1 spike protein in the activation of inflammatory signaling and cytokine production in human lung and intestinal epithelial cells in culture. These data support a potential role for the SARS-CoV-2 S1 spike protein in COVID-19 pathogenesis and PASC. [ABSTRACT FROM AUTHOR]

Background: Existing clinical studies supported the potential efficacy of mesenchymal stromal cells as well as derived exosomes in the treatment of COVID-19. We aimed to explore the safety and efficiency of aerosol inhalation of the exosomes derived from human adipose-derived MSCs (haMSC-Exos) in patients with COVID-19. Methods: The MEXCOVID trial is a phase 2a single-arm, open-labelled, interventional trial and patients were enrolled in Jinyintan Hospital, Wuhan, China. Eligible 7 patients were assigned to receive the daily dose of haMSCs-Exos (2.0 × 108 nano vesicles) for consecutively 5 days. The primary outcomes included the incidence of prespecified inhalation-associated events and serious adverse events. We also observed the demographic data, clinical characteristics, laboratory results including lymphocyte count, levels of D-dimer and IL-6 as well as chest imaging. Results: Seven severe COVID-19 related pneumonia patients (4 males and 3 females) were enrolled and received nebulized haMSC-Exos. The median age was 57 year (interquartile range (IQR), 43 year to 70 year). The median time from onset of symptoms to hospital admission and administration of nebulized haMSC-Exos was 30 days (IQR, 15 days to 40 days) and 54 d (IQR, 34 d to 69 d), respectively. All COVID-19 patients tolerated the haMSC-Exos nebulization well, with no evidence of prespecified adverse events or clinical instability during the nebulization or during the immediate post-nebulization period. All patients presented a slight increase of serum lymphocyte counts (median as 1.61 × 109/L vs. 1.78 × 109/L). Different degrees of resolution of pulmonary lesions after aerosol inhalation of haMSC-Exos were observed among all patients, more obviously in 4 of 7 patients. Conclusions: Our trial shows that a consecutive 5 days inhalation dose of clinical grade haMSC-Exos up to a total amount of 2.0 × 109 nano vesicles was feasible and well tolerated in seven COVID-19 patients, with no evidence of prespecified adverse events, immediate clinical instability, or dose-relevant toxicity at any of the doses tested. This safety profile is seemingly followed by CT imaging improvement within 7 days. Further trials will have to confirm the long-term safety or efficacy in larger population. Trial Registration: MEXCOVID, NCT04276987. [ABSTRACT FROM AUTHOR]

Background: Since the outbreak of coronavirus disease (COVID-19) in December 2019 in Wuhan, it has spread rapidly worldwide. We aimed to establish and validate a nomogram that predicts the probability of coronavirus-associated acute respiratory distress syndrome (CARDS). Methods: In this single-centre, retrospective study, 261 patients with COVID-19 were recruited using positive reverse transcription–polymerase chain reaction tests for severe acute respiratory syndrome coronavirus 2 in Tongji Hospital at Huazhong University of Science and Technology (Wuhan, China). These patients were randomly distributed into the training cohort (75%) and the validation cohort (25%). The factors included in the nomogram were determined using univariate and multivariate logistic regression analyses based on the training cohort. The area under the receiver operating characteristic curve (AUC), consistency index (C-index), calibration curve, and decision curve analysis (DCA) were used to evaluate the efficiency of the nomogram in the training and validation cohorts. Results: Independent predictive factors, including fasting plasma glucose, platelet, D-dimer, and cTnI, were determined using the nomogram. In the training cohort, the AUC and concordance index were 0.93. Similarly, in the validation cohort, the nomogram still showed great distinction (AUC: 0.92) and better calibration. The calibration plot also showed a high degree of agreement between the predicted and actual probabilities of CARDS. In addition, the DCA proved that the nomogram was clinically beneficial. Conclusion: Based on the results of laboratory tests, we established a predictive model for acute respiratory distress syndrome in patients with COVID-19. This model shows good performance and can be used clinically to identify CARDS early. Trial Registration: Ethics committee of Ruijin Hospital, Shanghai Jiao Tong University School of Medicine (No.:(2020) Linlun-34th). [ABSTRACT FROM AUTHOR]

The novel coronavirus disease 2019 (COVID-19) emerged in Wuhan, China, and has spread rapidly to nearly every part of the world. Unfortunately, no drug or vaccine has been accepted for the treatment of this pandemic. Researchers have established the efficacy of some existing antiviral drugs to control COVID-19 in vitro. Some of them are remdesivir (GS-5734), chloroquine, hydroxychloroquine, theaflavin. Topological indices are mathematical interpretations of a molecule generated by an algorithm implemented to a given molecular representation. Topological indices are used to model different physicochemical properties and biological activities of chemical compounds. In this work, some degree-based and neighborhood degree sum-based topological indices are investigated for the aforesaid antiviral drugs using polynomial approach. The results obtained can aid in the design of new medicine for the treatment of COVID-19. [ABSTRACT FROM AUTHOR]

The road map is a fundamental part of a spatial data infrastructure (SDI), and is widely applied in navigation, smart transportation, and mobile location services. Recently, with the ubiquity of positioning devices, crowdsourced trajectories have become a significant data resource for road map construction and updating. However, existing trajectory‐based methods mainly place emphasis on extracting road geometry features and may ignore continuous updating of road semantic information. Hence, we propose a divide‐and‐conquer method to construct a spatial‐semantic road map by incorporating multiple data sources (e.g., crowdsourced trajectories and geo‐tagged data). The proposed method divides road map construction into two sub‐tasks, road structure reconstruction and road attributes inference. The road structure reconstruction process starts to partition raw trajectory data into different cliques of roadways and road intersections, and then extracts various targeted road structures by analyzing the turning modes in different trajectory cliques. The road attributes inference process aims to infer three pieces of crucial semantic information about road speeds, turning rules, and road names from crowdsourced trajectories and geo‐tagged data. The case studies in Wuhan were examined to illustrate that the proposed method can construct a routable road map with enhanced geometric structures and rich semantic information, providing a beneficial data solution for car navigation and SDI update. [ABSTRACT FROM AUTHOR]

Background: We aimed to understand how glycaemic levels among COVID-19 patients impact their disease progression and clinical complications. Methods: We enrolled 2,366 COVID-19 patients from Huoshenshan hospital in Wuhan. We stratified the COVID-19 patients into four subgroups by current fasting blood glucose (FBG) levels and their awareness of prior diabetic status, including patients with FBG<6.1mmol/L with no history of diabetes (group 1), patients with FBG<6.1mmol/L with a history of diabetes diagnosed (group 2), patients with FBG≥6.1mmol/L with no history of diabetes (group 3) and patients with FBG≥6.1mmol/L with a history of diabetes diagnosed (group 4). A multivariate cause-specific Cox proportional hazard model was used to assess the associations between FBG levels or prior diabetic status and clinical adversities in COVID-19 patients. Results: COVID-19 patients with higher FBG and unknown diabetes in the past (group 3) are more likely to progress to the severe or critical stage than patients in other groups (severe: 38.46% vs 23.46%-30.70%; critical 7.69% vs 0.61%-3.96%). These patients also have the highest abnormal level of inflammatory parameters, complications, and clinical adversities among all four groups (all p<0.05). On day 21 of hospitalisation, group 3 had a significantly higher risk of ICU admission [14.1% (9.6%-18.6%)] than group 4 [7.0% (3.7%-10.3%)], group 2 [4.0% (0.2%-7.8%)] and group 1 [2.1% (1.4%-2.8%)], (P<0.001). Compared with group 1 who had low FBG, group 3 demonstrated 5 times higher risk of ICU admission events during hospitalisation (HR=5.38, 3.46-8.35, P<0.001), while group 4, where the patients had high FBG and prior diabetes diagnosed, also showed a significantly higher risk (HR=1.99, 1.12-3.52, P=0.019), but to a much lesser extent than in group 3. Conclusion: Our study shows that COVID-19 patients with current high FBG levels but unaware of pre-existing diabetes, or possibly new onset diabetes as a result of COVID-19 infection, have a higher risk of more severe adverse outcomes than those aware of prior diagnosis of diabetes and those with low current FBG levels. [ABSTRACT FROM AUTHOR]

At the end of December 2019, the COVID-19 pandemic began in Wuhan of China. COVID-19 affects different people with a wide spectrum of clinical manifestations, ranging from asymptomatic with recovery without hospitalization up to a severe acute respiratory syndrome (SARS). The innate and adaptive immunity appears responsible for the defense against the virus and recovery from the disease. The innate immune system, as the first line of defense, is essential for the detection of virus and subsequent activation of acquired immunity. The innate immune response is carried out by sentinel cells such as monocytes/macrophages and dendritic cells and by receptors known as pattern recognition receptors (PRR). These receptors can recognize various components of the virus, which lead to intracellular signaling and subsequently the synthesis of various cytokines. These cytokines then recruit other immune cells, activate adaptive immune responses, and inhibit viral spreading. The most common receptors include Toll-like receptors, C-type lectin receptors, and RIG-I like receptors. This review describes the current knowledge about the interplay between innate immune responses and SARS-CoV-2 with a focus on the innate immune cells and the role of their receptors in viral RNA recognition, as well as their mechanisms for recognizing SARS-CoV-2. [ABSTRACT FROM AUTHOR]

Summary: Coronavirus disease 2019 (COVID‐19) pandemic has caused high number of infections and deaths of healthcare workers globally. Distribution and possible transmission route of SARS‐CoV‐2 in hospital environment should be clarified. We herein collected 431 environmental (391 surface and 40 air) samples in the intensive care unit (ICU) and general wards (GWs) of three hospitals in Wuhan, China from February 21 to March 4, 2020, and detected SARS‐CoV‐2 RNA by real‐time quantitative PCR. The viral positive rate in the contaminated areas was 17.8% (28/157), whereas there was no virus detected in the clean areas. Higher positive rate (22/59, 37.3%) was found in ICU than that in GWs (3/63, 4.8%). The surfaces of computer keyboards and mouse in the ICU were the most contaminated (8/10, 80.0%), followed by the ground (6/9, 66.7%) and outer glove (2/5, 40.0%). From 17 air samples in the contaminated areas, only one sample collected at a distance of around 30 cm from the patient was positive. Enhanced surface disinfection and hand hygiene effectively decontaminated the virus from the environment. This finding might help understand the transmission route and contamination risk of SARS‐CoV‐2 and evaluate the effectiveness of infection prevention and control measures in healthcare facilities. [ABSTRACT FROM AUTHOR]

Objectives: This study aimed to identify the independent factors associated with depression in community-dwelling older adults in Wuhan, China. Methods: Four hundred and seventy older adults (aged ≥65 years) from four communities dwelling on Junshan Street in Wuhan, China were included in this study. Participants completed a questionnaire that asked questions pertaining to age, gender, educational level, income, living situation, care situation, social support, and social engagement. The 30-item Geriatric Depression Scale (GDS-30), the Fried frailty phenotype scale, the activities of daily living (ADL) scale, the mini nutritional assessment scale-short form (MNA-SF), and the Mini-cog scale were used to assess depression, frailty, self-care ability, malnutritional risk, and cognitive dysfunction, respectively. Differences in age, gender, educational level, income, living situation, care situation, social support, social engagement, ADL score, risk of malnutrition, frailty, and cognitive dysfunction between the non-depression (GDS-30 score <10 points) and depression groups (GDS-30 score ≥10 points) were compared using a chi-square test. Moreover, correlations between factors and depression were analyzed using Pearson's correlation. Then, significant variables (p < 0.05) from the chi-square test were included in a multivariable logistic regression model to identify the independent factors associated with depression. Results: The incidence of depression among the participants was 14.04%. Age (p < 0.001), educational level (p < 0.001), living situation (p < 0.001), social support (p = 0.001), ADL score (p = 0.023), frailty (p < 0.001), and cognitive dysfunction (p < 0.001) were all significantly associated with depression, in which age, poor social support, frailty, and cognitive dysfunction were identified as independent factors. Conclusion: Improving social support and effective interventions for frailty and cognitive dysfunction may help relieve depression in community-dwelling older adults. [ABSTRACT FROM AUTHOR]

Heavy metals are released into the water system through various natural processes and anthropogenic activities, thus indirectly or directly endangering human health. The distribution, source, water quality and health risk assessment of dissolved heavy metals (V, Mn, Fe, Co, Ni, Zn, As, Mo, Sb) in major rivers in Wuhan were analyzed by correlation analysis (CA), principal component analysis (PCA), heavy metal pollution index (HPI), hazard index (HI) and carcinogenic risk (CR). The results showed that the spatial variability of heavy metal contents was pronounced. PCA and CA results indicated that natural sources controlled Mn, Fe, Co, Ni and Mo, and industrial emissions were the dominant factor for V, Zn and Sb, while As was mainly from the mixed input of urban and agricultural activities. According to the heavy metal pollution index (HPI, ranging from 23.74 to 184.0) analysis, it should be noted that As and Sb contribute most of the HPI values. The health risk assessment using HI and CR showed that V and Sb might have a potential non-carcinogenic risk and As might have a potential carcinogenic risk to adults and children in the study area (CR value exceeded target risk 10−4). At the same time, it was worth noting that As might have a potential non-carcinogenic risk for children around QLR (HI value exceeded the threshold value 1). The secular variation of As and Sb should be monitor in high-risk areas. The results of this study can provide important data for improving water resources management efficiency and heavy metal pollution prevention in Wuhan. [ABSTRACT FROM AUTHOR]

At the beginning of the coronavirus disease 2019 (COVID-19) outbreak, college students returning home from Wuhan, Hubei Province, experienced various degrees of discrimination. This study first investigates perceived discrimination among college students returning home from Wuhan. Then, an experimental method is used to investigate the effectiveness of an intervention designed to reduce the perceived discrimination among those who returned to towns outside of Hubei Province. A total of 63 college students participated in the experiment. In the experimental group (N = 31), a wise intervention based on reading and writing was adopted to intervene in perceived discrimination among the participants. The results showed that the perceived discrimination among students returning from Wuhan to towns outside of Hubei Province was significantly higher than that among students returning to towns within Hubei Province. The wise intervention reduced the perceived discrimination in the experimental group but not in the control group. Further analysis found that perceived social support fully mediated the relationship between the intervention and perceived discrimination. These results provide insights on how the content of intervention (perceived social support) and the form of intervention (wise intervention) can prevent the occurrence of psychological problems in epidemic situations. [ABSTRACT FROM AUTHOR]

The hot spots of people's activities are an important part of urban spatial structure research, and the analysis of the driving forces of urban hot spots can provide a scientific basis for urban planning. The determination of urban hot spots is affected by the heterogeneity of the analysis data, resulting in differences in the hot spot driving factors. To analyze the spatial distributions of urban hot spots, this article conducted a series of exploratory spatial analyses on spatiotemporal travel data and further applied a binary logistic regression (BLR) model to analyze the driving factors affecting the distribution of urban hot spots to accurately characterize the distribution pattern of urban hot spots. First, a spatial autocorrelation test was performed on the trajectory data. Based on the test results, the Getis–Ord Gi∗ statistical method was used to calculate the distribution area of urban hot spots. Second, considering the internal and external factors that affect the distribution of urban hot spots, 10 driving factors in the categories of terrain, socioeconomics, and road and transportation facility accessibility were selected as the independent variables in the regression model of the hot spot distribution. Third, a BLR model was used to establish a driving force model that altered the distribution of hot spots in cities to explore the influencing factors and the degree of the hot spot distribution. Finally, the accuracy of the hot spot driving force model was evaluated according to the receiver operating characteristic (ROC) curve. Taking Wuhan as an example, the results show that the area under the ROC curve of the hot spot model established in this article reaches 0.918, and the model has a good fit. The formation of urban hot spots is a combination of internal driving factors such as terrain and socioeconomics as well as external driving factors such as the accessibility of roads and transportation facilities. Among these factors, transportation facility accessibility contributes most to the hot spot distribution. [ABSTRACT FROM AUTHOR]

The coronavirus disease 2019 (COVID-19) has caused a global pandemic, resulting in considerable morbidity and mortality. Tocilizumab, an inhibitor of IL-6, has been widely repurposed as a treatment of severely ill patients without robust evidence supporting its use. In this study, we aimed to systematically describe the effectiveness of treatment and prevention of the cytokine storms in COVID-19 patients with tocilizumab. In this multicentered retrospective and observational cohort study, 65 patients with COVID-19 receiving tocilizumab and 130 not receiving tocilizumab were propensity score matched at a ratio of 2:1 based on age, sex, and comorbidities from January 20, 2020 to March 18, 2020 in Wuhan, China. After adjusting for confounding, the detected risk for in-hospital death was lower in the tocilizumab group versus nontocilizumab group (hazard ratio = 0.47; 95% confidence interval = 0.25-0.90; p = 0.023). Moreover, use of tocilizumab was associated with a lower risk of acute respiratory distress syndrome (odds ratio = 0.23; 95% confidence interval = 0.11-0.45; p < 0.0001). Furthermore, patients had heightened inflammation and more dysregulated immune cells before treatment, which might aggravate disease progression. After tocilizumab administration, abnormally elevated IL-6, C-reactive protein, fibrinogen, and activated partial thromboplastin time decreased. Tocilizumab may be of value in prolonging survival in patients with severe COVID-19, which provided a novel strategy for COVID-19-induced cytokine release syndrome. Our findings could inform bedside decisions until data from randomized, controlled clinical trials become available. [ABSTRACT FROM AUTHOR]

COVID‐19 has a significant impact on public health and poses a challenge to medical staffs, especially to front‐line medical staffs who are exposed to and in direct contact with patients. To understand the psychological stress status of medical staffs during the outbreak of COVID‐19, random sample questionnaire survey was conducted among 2110 medical staffs and 2158 college students in all provinces of China through a questionnaire, which was compiled and completed through the Questionnaire Star platform relying on Wechat, QQ, and other social software. The differences in psychological stress status of different groups were compared through the analysis of the questionnaire. Results revealed that in all provinces of China, medical staffs scored significantly higher on all items of psychological stress than college students (P <.001). In Wuhan, medical staffs scored significantly higher than college students in all items of psychological stress (P <.001). While among medical staffs, the group in Wuhan area scored significantly higher than the group outside Wuhan on the following items: "Thought of being in danger," "The possibility of self‐illness," "Worrying about family infection" (P <.05), "Poor sleep quality," "Needing psychological guidance," and "Worrying about being infected" (P <.01) in the Psychological Stress Questionnaire, but on the item "Confidence in the victory of the epidemic," the group in Wuhan area scored significantly lower than the group outside Wuhan (P <.05). The emotion, cognition, physical, and mental response of front‐line medical staff showed obvious "exposure effect", which calls for a psychological crisis intervention strategy that can be helpful. Highlights: The emotion, cognition, physical, and mental response of front‐line medical staff showed obvious "exposure effect," which calls for a psychological crisis intervention strategy that can be helpful. [ABSTRACT FROM AUTHOR]

Functional zones are basic spatial units of urban management and urban planning and they provide the basic space where human activities occur. The concept of urban functional zones is closely related to two basic factors: urban landscape environment and human activities. The former provides the basic space for human activity and influences urban land use at a coarse scale, and the latter indicates the differentiation of functions in local urban areas. In previous studies, the hierarchical correspondence and interaction between urban landscape and human activities have not been given full consideration in the cognition of urban functional zones, which would influence the accuracy and interpretability of the results. Therefore, a hierarchical fusion method considering urban landscape and human activity patterns based on multi‐source data is proposed in this article. We introduce a new cognition framework. First, a land use classification based on urban landscape features from remote sensing images is extracted and used as the fundamental results of urban land uses. Then, fine‐grained functional semantics of local urban areas are recognized based on human activity patterns extracted from crowdsourced data (i.e., points of interest and taxi trajectories). Finally, the above results at different scales are fused with hierarchical constraints, which means that the information from both urban landscape and human activities can be fully utilized to obtain a refined and fine‐grained map of urban functional zones. Wuhan, China was chosen as an example to evaluate the performance of the proposed method. Results show that the overall accuracy of the proposed method is 82.51% (accuracies of the mixed functional zones and single functional zones are 77.93 and 87.96%, respectively) and compared with state‐of‐the‐art methods, the proposed method performed better for the recognition of mixed functional zones. [ABSTRACT FROM AUTHOR]

Much effort has been applied to the study of land use multi‐objective optimization. However, most of these studies have focused on the final land use scenarios in the projected year, without considering how to reach the final optimized land use scenario. To fill this gap, a spatio‐temporal land use multi‐objective optimization (STLU‐MOO) model is innovatively proposed in this research to determine possible spatial land use solutions over time. The STLU‐MOO is an extension of a genetic land use multi‐objective optimization model (LU‐MOO) in which the LU‐MOO is generally carried out in different years, and the solutions at year T will affect the solutions at year T + 1. We used the Wuhan agglomeration (WHA) as our case study area. The STLU‐MOO model was employed separately for the nine cities in the WHA, and social, economic, and environmental objectives have been considered. The success of the experiments in the case study demonstrated the value and novelty of our proposed STLU‐MOO model. In addition, the results also indicated that the objectives considered in the case study were in conflict. According to the results, the optimal land use plan in 2050 can be traced back to 2040, 2030, and 2020, providing a series of Pareto solutions over the years which can provide spatio‐temporal land use multi‐objective optimization solutions to support the land use planning process. [ABSTRACT FROM AUTHOR]

A total of 16% (11/68) of the patients in the death group had secondary infections, and 1% (1/82) of the patients in the discharge group had secondary infections ( I p i = 0.0018). Among the 68 fatal cases, 36 patients (53%) died of respiratory failure, five patients (7%) with myocardial damage died of circulatory failure, 22 patients (33%) died of both, and five remaining died of an unknown cause (Fig. [Extracted from the article]

Background: To investigate deep vein thrombosis (DVT) in hospitalized patients with coronavirus disease 2019 (COVID-19), we performed a single institutional study to evaluate its prevalence, risk factors, prognosis, and potential thromboprophylaxis strategies in a large referral and treatment center.Methods: We studied a total of 143 patients with COVID-19 from January 29, 2020 to February 29, 2020. Demographic and clinical data, laboratory data, including ultrasound scans of the lower extremities, and outcome variables were obtained, and comparisons were made between groups with and without DVT.Results: Of the 143 patients hospitalized with COVID-19 (age 63±14 years, 74 [51.7%] men), 66 patients developed lower extremity DVT (46.1%: 23 [34.8%] with proximal DVT and 43 [65.2%] with distal DVT). Compared with patients who did not have DVT, patients with DVT were older and had a lower oxygenation index, a higher rate of cardiac injury, and worse prognosis, including an increased proportion of deaths (23 [34.8%] versus 9 [11.7%]; P=0.001) and a decreased proportion of patients discharged (32 [48.5%] versus 60 [77.9%]; P<0.001). Multivariant analysis showed an association only between CURB-65 (confusion status, urea, respiratory rate, and blood pressure) score 3 to 5 (odds ratio, 6.122; P=0.031), Padua prediction score ≥4 (odds ratio, 4.016; P=0.04), D-dimer >1.0 μg/mL (odds ratio, 5.818; P<0.014), and DVT in this cohort, respectively. The combination of a CURB-65 score 3 to 5, a Padua prediction score ≥4, and D-dimer >1.0 μg/mL has a sensitivity of 88.52% and a specificity of 61.43% for screening for DVT. In the subgroup of patients with a Padua prediction score ≥4 and whose ultrasound scans were performed >72 hours after admission, DVT was present in 18 (34.0%) patients in the subgroup receiving venous thromboembolism prophylaxis versus 35 (66.0%) patients in the nonprophylaxis group (P=0.010).Conclusions: The prevalence of DVT is high and is associated with adverse outcomes in hospitalized patients with COVID-19. Prophylaxis for venous thromboembolism may be protective in patients with a Padua protection score ≥4 after admission. Our data seem to suggest that COVID-19 is probably an additional risk factor for DVT in hospitalized patients. [ABSTRACT FROM AUTHOR]