Environmental impact assessment for the use of an orally aerosolised adenovirus type-5 vector-based COVID-19 vaccine in randomised clinical trials.

BACKGROUND: An orally aerosolised adenovirus type-5 vector-based COVID-19 vaccine (Ad5-nCoV) has recently been authorized for boosting immunization in China. Our study aims to assess the environmental impact of the use of aerosolised Ad5-nCoV. METHODS: We collected air samples from rooms, swabs from the setting desks of the vaccine nebuliser, mask samples from participants and blood samples of nurses who administered the inoculation in the clinical trials. The viral load of adenovirus type-5 vector in the samples and the antibody levels against the wild-type SARS-CoV-2 strain in serum were detected. RESULTS: Only one (4.00%) air samples collected before the initiation of vaccination was positive, which were almost positive during and after the vaccination (97.96%, 100%, respectively). All nurses in the trial A showed at least four-fold increase of the neutralizing antibody against the SARS-CoV-2 after the initiation of the study. In trial B, the positive proportion of the mask samples was 72.97% at 30 minutes after vaccination, 8.11% at day 1, and 0% at days 3, 5, and 7, respectively. CONCLUSION: The vaccination with the orally aerosolised Ad5-nCoV could have some spillage of the vaccine vector viral particles in the environment and cause human exposure.

Comprehensive Oncogenic Features of Coronavirus Receptors in Glioblastoma Multiforme.

The COVID-19 pandemic caused by SARS-CoV-2 infection has placed health systems under excessive pressure and especially elderly people with cancer. Glioblastoma multiforme (GBM) is a malignant brain tumor with an increasing incidence in elderly individuals, and thereby GBM patients are a vulnerable population during the COVID-19 outbreak. Accumulating studies have implied that SARS-CoV-2 might invade the brain directly via coronavirus receptors. However, little is known about SARS-CoV-2 infection in the clinical development of GBM. Here, we explored the oncogenic roles of six coronavirus receptors (ACE2, DPP4, ANPEP, AXL, TMPRSS2, and ENPEP) in GBM using bioinformatics and experimental approaches. We found that ANPEP and ENPEP were significantly increased at both the mRNA and protein levels in GBM compared with normal brain tissue. Kaplan-Meier survival curves and Cox regression analysis demonstrated that high expressions of ANPEP and ENPEP are associated with poor prognosis and survival. Moreover, all receptors are positively correlated with the immune infiltration levels of monocyte. Furthermore, we identified 245 genes between COVID-19 and coronavirus receptors-correlated genes in GBM and performed a thorough analysis of their protein-protein interaction network, functional signaling pathway and molecular process. Our work explores for the first time the association of coronavirus receptors with GBM and suggests ANPEP and ENPEP as potential therapeutic targets of GBM irrespective of COVID-19.

Effects of angiotensin receptor blockers and angiotensin-converting enzyme inhibitors on COVID-19.

BACKGROUND: The World Health Organization reported that 28637952 people worldwide had been infected with severe acute respiratory syndrome coronavirus 2, the causative agent of coronavirus disease 2019 (COVID-19), by September 13. AIM: The aim was to investigate whether long-term use of renin-angiotensin-aldosterone system (RAAS) inhibitors for the treatment of hypertension aggravates the performance of COVID-19 patients with hypertension. METHODS: This was a retrospective analysis of lung computed tomography (CT) data and laboratory values of COVID-19 patients with hypertension who were admitted to Huoshenshan Hospital, Wuhan, Hubei Province, between February 18 and March 31, 2020. Patients were divided into two groups. Group A included 19 people who were long-term users of RAAS inhibitors for hypertension; and group B included 28 people who were randomly selected from the database and matched with group A by age, sex, basic diseases, and long-term use of other antihypertensive drugs. All patients underwent a series of CT and laboratory tests. We compared the most severe CT images of the two groups and the laboratory examination results within 2 d of the corresponding CT images. RESULTS: The time until the most severe CT images from the onset of COVID-19 was 30.37 ± 14.25 d group A and 26.50 ± 11.97 d in group B. The difference between the two groups was not significant (t = 1.01, P = 0.32). There were no significant differences in blood laboratory values, C-reactive protein, markers of cardiac injury, liver function, or kidney function between the two groups. There was no significant difference in the appearance of the CT images between the two groups. The semiquantitative scores of each involved lobe were 11.84 ± 5.88 in group A and 10.36 ± 6.04 group B. The difference was not significantly different (t = 0.84, P = 0.41). CONCLUSION: Chest CT is an important imaging tool to monitor the characteristics of COVID-19 and the degree of lung injury. Chronic use of RAAS inhibitors is not related to the severity of COVID-19, and it does not worsen the clinical process.

Progressive liver injury and increased mortality risk in COVID-19 patients: A retrospective cohort study in China.

BACKGROUND: Liver injury is common and also can be fatal, particularly in severe or critical patients with coronavirus disease 2019 (COVID-19). AIM: To conduct an in-depth investigation into the risk factors for liver injury and into the effective measures to prevent subsequent mortality risk. METHODS: A retrospective cohort study was performed on 440 consecutive patients with relatively severe COVID-19 between January 28 and March 9, 2020 at Tongji Hospital, Wuhan, China. Data on clinical features, laboratory parameters, medications, and prognosis were collected. RESULTS: COVID-19-associated liver injury more frequently occurred in patients aged ≥ 65 years, female patients, or those with other comorbidities, decreased lymphocyte count, or elevated D-dimer or serum ferritin (P < 0.05). The disease severity of COVID-19 was an independent risk factor for liver injury (severe patients: Odds ratio [OR] = 2.86, 95% confidence interval [CI]: 1.78-4.59; critical patients: OR = 13.44, 95%CI: 7.21-25.97). The elevated levels of on-admission aspartate aminotransferase and total bilirubin indicated an increased mortality risk (P < 0.001). Using intravenous nutrition or antibiotics increased the risk of COVID-19-associated liver injury. Hepatoprotective drugs tended to be of assistance to treat the liver injury and improve the prognosis of patients with COVID-19-associated liver injury. CONCLUSION: More intensive monitoring of aspartate aminotransferase or total bilirubin is recommended for COVID-19 patients, especially patients aged ≥ 65 years, female patients, or those with other comorbidities. Drug hepatotoxicity of antibiotics and intravenous nutrition should be alert for COVID-19 patients.

Application of feature extraction method based on support vector machine in Internet of things

Although much less fatal than the Ebola and previous SARS virus epidemics, the current coronavirus outbreak (COVID-19) has spread to more people in more countries in a much shorter time frame. With the rapid development of the Internet of things, it has played an important role to track/monitor transmission movements throughout the population. The technology infrastructure between mobile devices, wearable devices and sensors, smart home device makes it possible to readily deploy solutions to monitor and collect data and perform analysis to ensure policy make intelligent, rapid decisions. This research combines AOL and Support Vector Machine to form the Internet of things cycle through smart home. The parameters of Support Vector Machine model are optimized by ALO algorithm, which shortens the learning time and improves the performance of classifier. Then, the algorithm of ALO is used to optimize the Support Vector Machine intrusion detection method and agent technology, and the intrusion detection model is established. Experimental results show that the combination of these two can effectively reduce the false alarm rate of network intrusion. [ABSTRACT FROM AUTHOR] Copyright of Journal of Intelligent & Fuzzy Systems is the property of IOS Press 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.)

Pattern recognition of wood structure design parameters under external interference based on artificial neural network with BIM environment

Under the influence of novel corona virus pneumonia, the staff are controlled. Therefore, it is a difficult problem to measure the parameters of wood structure building on site. The measurement error of traditional wood structure parameters in complex environment is large, so an efficient and accurate measurement and recognition method is needed. In this paper, a method combining random decrement method and ITD method is proposed to measure the frequency, damping ratio and other structural dynamic parameters of ancient building timber structure under crowd random load excitation. In this paper, the frequency and damping ratio of the typical ancient building timber structure are predicted by using the artificial neural network model trained by the known data. The experimental results show that the population density has a great influence on the measurement of the dynamic parameters of the wooden structure of ancient buildings. Using this method, combined with the long-term monitoring data of temperature and humidity, the influence of various environmental factors on the dynamic characteristics of the structure can be analyzed. This provides data support for structural damage identification and health monitoring. [ABSTRACT FROM AUTHOR] Copyright of Journal of Intelligent & Fuzzy Systems is the property of IOS Press 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.)

Clinical characteristics of cardiac injury in patients with COVID-19

Objective: To analyze the clinical characteristics, cardiac injury characteristics and early warning indexes of severe type in patients with COVID-19, so as to provide data for the evaluation, clinical treatment and prognosis of COVID-19 patients.

Prevalence of Kidney Injury and Associations with Critical Illness and Death in Patients with COVID-19.

BACKGROUND AND OBJECTIVES: Coronavirus disease 2019 is spreading rapidly across the world. This study aimed to assess the characteristics of kidney injury and its association with disease progression and death of patients with coronavirus disease 2019. DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS: This is a retrospective study. Two representative cohorts were included. Cohort 1 involved severe and critical patients with coronavirus disease 2019 from Wuhan, China. Cohort 2 was all patients with coronavirus disease 2019 in Shenzhen city (Guangdong province, China). Any kidney injury was defined as the presence of any of the following: hematuria, proteinuria, in-hospital AKI, or prehospital AKI. AKI was defined according to the Kidney Disease Improving Global Outcomes (KDIGO) creatinine criteria. The primary outcome was death at the end of follow-up. The secondary outcome was progression to critical illness during the study period. RESULTS: A total of 555 patients were enrolled; 42% of the cases (229 of 549) were detected with any kidney injury, 33% of the cases (174 of 520) were detected with proteinuria, 22% of the cases (112 of 520) were detected with hematuria, and 6% of the cases (29 of 520) were detected with AKI. Of the 29 patients with AKI, 21 cases were recognized as in-hospital AKI, and eight were recognized as prehospital AKI. Altogether, 27 (5%) patients died at the end of follow-up. The death rate was 11% (20 of 174) in patients with proteinuria, 16% (18 of 112) in patients with hematuria, and 41% (12 of 29) in the AKI settings. Multivariable Cox regression analysis showed that proteinuria (hazard ratio, 4.42; 95% confidence interval, 1.22 to 15.94), hematuria (hazard ratio, 4.71; 95% confidence interval, 1.61 to 13.81), and in-hospital AKI (hazard ratio, 6.84; 95% confidence interval, 2.42 to 19.31) were associated with death. Among the 520 patients with noncritical illness at admission, proteinuria (hazard ratio, 2.61; 95% confidence interval, 1.22 to 5.56) and hematuria (hazard ratio, 2.50; 95% confidence interval, 1.23 to 5.08) were found to be associated with progression to critical illness during the study period. CONCLUSIONS: Kidney injury is common in coronavirus disease 2019, and it is associated with poor clinical outcomes. PODCAST: This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2020_09_18_CJN04780420.mp3.