Efficacy and safety of triazavirin therapy for coronavirus disease 2019 : A pilot randomized controlled trial

Acknowledgements: We are deeply grateful to the front-line clinicians who participated in the study while directly fighting the epidemic. This study was supported by the Chinese Academy of Engineering Projects for COVID-19 (2020-KYGG-01-04) and Heilongjiang Province Urgent Project-6 for COVID-19. Data and safety monitoring board members of this trial included Kang Li, Yong Zhang, Songjiang Liu, and Yaohui Shi.Peer reviewedPublisher PD

Network Pharmacology Based Research on the Combination Mechanism Between Escin and Low Dose Glucocorticoids in Anti-rheumatoid Arthritis

Rheumatoid arthritis (RA) is characterized by chronic progressive symmetrical synovitis and destruction of multiple joints. Glucocorticoids (GCs) are widely used in the treatment of RA. However, their adverse effects can be serious. Escin, which is isolated from Aesculus hippocastanum L., has been reported to have anti-inflammatory effects. We investigated the anti-RA effect of Escin combined with low dose GCs (dexamethasone, Dex) and the underlying mechanism. Adjuvant-induced RA rats and lipopolysaccharides (LPS)-injured RAW264.7 cells were used to investigate the anti-RA effects of Escin combined with low dose Dex in vivo and in vitro. The results showed that Escin combined with low-dose Dex significantly decreased arthritic index, serum IL-6 and TNF-α levels, reduced paw swelling, and ameliorated the joint pathology and immune organ pathology. Gene chip results revealed that Nr3c1 (GR) expression was significantly altered, and that GR was activated by Escin and low dose Dex in vivo and in vitro. Additionally, Escin combined with low dose Dex also significantly increased GR mRNA expression. However, when GR expression was suppressed by its specific inhibitor, the anti-RA effect of Escin combined with low-dose Dex was abolished. The data in this study demonstrated that Escin combined with Dex reduced the dose of Dex, and exerted significant anti-RA effects, which could also reduce the adverse effects of Dex. This combination might result from GR activation. This study might provide a new combination of drugs for the treatment of RA

Multiple Magnetic Foreign Bodies Causing Severe Digestive Tract Injuries in a Child

Foreign body (FB) ingestion is a common emergency as well as a major cause of accidental injury and represents a severe public health problem in childhood, especially in infants. Most cases of FB ingestion reported in children aged between 6 months and 3 years depend primarily on the fact that young children are more likely to explore objects using their mouth and are not able to distinguish edible objects from nonedible ones, their teeth are physiologically lacking, and they have poor swallowing coordination. Although, sometimes it can cause serious complications, FB ingestion generally has a low mortality rate. However, accidental ingestion of magnetic toys, as a rare kind of FB mostly encountered in children, has now become more common due to the increased availability of objects and toys with magnetic elements. The majority of magnetic FB traverse the gastrointestinal (GI) system spontaneously without complication, but in rare cases may cause severe damages to the GI tract due to its special pathogenesis [Kay and Wyllie: Curr Gastroenterol Rep 2005;7: 212–218]. Ingestion of multiple magnets may be related to increased morbidity resulting in a delay of recognition of FB injury that can lead to serious complications and require surgical resolution

Resource Allocation for Tethered UAVs Aided NOMA Networks: A Location-Aware Air-Ground Collaborative Perspective

The research of the mutli-UAV assisted NOMA networks has received a lot of attention because of its superior ability to improve spectrum efficiency and high maneuverability simultaneously. In this research, we take into account downlink NOMA networks with multiple tethered UAV assistance, and investigate the joint UAVs location, user scheduling, user pairing and power distribution problem. The design aims to maximize the sum-rate that can be achieved with a minimum rate restriction, as a complex problem involving mixed-integer programming. First, we determine the best user pairing and power distribution methods for established UAVs positions, which gives the closed-form solution for parameters. Afterwards, we formulate the UAV position optimization problem as a local altruistic game from the viewpoint of air-ground cooperation on the bias of interference graphs. It has been shown to be an exact potential game that permits more than one pure approach Nash equilibrium (PNE). A centralized-distributed iterative learning method is proposed to reach the ideal PNE as rapidly as possible, maximizing the specified network utility measure. The proposed algorithm performs better than the current techniques, according to simulation findings, and greatly boosts network utility. Simulation results show that, nearly 5% and 26% networks utility can be enhanced by the proposed method compared with “head-pairs-tail” and random schemes respectively

A Novel Segmentation Recognition Algorithm of <i>Agaricus bisporus</i> Based on Morphology and Iterative Marker-Controlled Watershed Transform

Accurate recognition of Agaricus bisporus is a prerequisite for precise automatic harvesting in a factory environment. Aimed at segmenting mushrooms adhering together from the complex background, this paper proposes a watershed-based segmentation recognition algorithm for A. bisporus. First, the foreground of A. bisporus is extracted via Otsu threshold segmentation and morphological operations. Then, a preliminary segmentation algorithm and a novel iterative marker generation method are proposed to prepare watershed markers. On this basis, a marker-controlled watershed algorithm is adopted to segment and recognize A. bisporus individuals. All the algorithms are implemented based on OpenCV (Open Source Computer Vision) libraries. Tests on images of A. bisporus collected at the cultivation bed show that the average correct recognition rate of the proposed algorithm is 95.7%, the average diameter measurement error is 1.15%, and the average coordinate deviation rate is 1.43%. The average processing time is 705.7 ms per single image, satisfying the real-time constraints based on 1 image/s. The proposed algorithm performed better than the current Circle Hough Transform (OpenCV’s implementation). It is convenient and easy to operate, providing a sound basis for subsequent research on mechanized harvesting equipment for A. bisporus

High capacity and reversible hydrogen storage on two dimensional C2N monolayer membrane

Searching advanced materials with high capacity and efficient reversibility for hydrogen storage is a key issue for the development of hydrogen as a clean energy. Here, we have explored the potential application of C2N monolayer using as a promising material for hydrogen storage through a comprehensive density functional theory (DFT) investigation. Our calculational results indicate that hydrogen molecule can only form weak interaction on neutral C2N monolayer with the adsorption energy of 0.06 eV. However, if extra charges (5 e−) are introduced to the system, the adsorption energy of hydrogen molecule on C2N will be dramatically enhanced to 0.27 eV. Moreover, once the extra charges are moved from the system, the adsorbed hydrogen molecule will be spontaneously released from C2N monolayer without any barrier. Interestingly, the average adsorption energy for each of the 48 absorbed H2 molecules is 0.28 eV with the charge injection (8 e−). This adsorption energy meets the criterion of the Department of Energy (DOE) for hydrogen storage (0.2–0.6 eV). Moreover, C2N has a high hydrogen storage capacity of 10.5 wt %. Overall, this investigation demonstrates that the new fabricated C2N can be used as an efficient material for hydrogen storage with high capacity and reversibility by modifying the charges that it carried. The narrow band gap (1.70 eV) of C2N also ensures the electrochemical methods can be easily realized in experiment

Psychometric Properties of the Abbreviated Version of the Dual School Climate and School Identification Measure&ndash;Student (SCASIM-St15) among Adolescents in China

School climate and school identification are two distinct yet closely interrelated components of school environment; both are associated with adolescents&rsquo; multiple health behavioral changes. The 15-item Abbreviated version of the Dual School Climate and School Identification Measure&ndash;Student (SCASIM-St15) and its 5-factor model simultaneously and separately assess these two constructs. This study validated the Chinese version of SCASIM-St15 among 1108 students from junior middle schools, senior middle schools, and vocational high schools in Taizhou city, Zhejiang, China, via an anonymous, self-administered cross-sectional survey. Confirmatory factor analysis supports the 5-factor model of the original SCASIM-St15 with a satisfactory model fit. Its four factors (i.e., student&ndash;student relations, staff&ndash;student relations, academic emphasis, and shared values and approach) assess school climate; its fifth factor assesses school identification. The subscales of the SCASIM-St15 demonstrate good psychometric properties, including measurement invariance (across sex and school type), good internal consistency, an absence of floor effect, and good external validity with four external variables (depression, peer victimization, classmate support, and teacher&ndash;student relationship). However, some substantial ceiling effects were observed. The five subscales differ significantly across the school types but not between males and females. The validated SCASIM-St15 can be applied to simultaneously understand school climate/school identification among Chinese adolescents, which may greatly facilitate future related observational and intervention research

Constructing disease-specific gene networks using pair-wise relevance metric: Application to colon cancer identifies interleukin 8, desmin and enolase 1 as the central elements

<p>Abstract</p> <p>Background</p> <p>With the advance of large-scale omics technologies, it is now feasible to reversely engineer the underlying genetic networks that describe the complex interplays of molecular elements that lead to complex diseases. Current networking approaches are mainly focusing on building genetic networks at large without probing the interaction mechanisms specific to a physiological or disease condition. The aim of this study was thus to develop such a novel networking approach based on the relevance concept, which is ideal to reveal integrative effects of multiple genes in the underlying genetic circuit for complex diseases.</p> <p>Results</p> <p>The approach started with identification of multiple disease pathways, called a gene forest, in which the genes extracted from the decision forest constructed by supervised learning of the genome-wide transcriptional profiles for patients and normal samples. Based on the newly identified disease mechanisms, a novel pair-wise relevance metric, adjusted frequency value, was used to define the degree of genetic relationship between two molecular determinants. We applied the proposed method to analyze a publicly available microarray dataset for colon cancer. The results demonstrated that the colon cancer-specific gene network captured the most important genetic interactions in several cellular processes, such as proliferation, apoptosis, differentiation, mitogenesis and immunity, which are known to be pivotal for tumourigenesis. Further analysis of the topological architecture of the network identified three known hub cancer genes [interleukin 8 (IL8) (<it>p </it>≈ 0), desmin (DES) (<it>p </it>= 2.71 × 10^-6) and enolase 1 (ENO1) (<it>p </it>= 4.19 × 10^-5)], while two novel hub genes [RNA binding motif protein 9 (RBM9) (<it>p </it>= 1.50 × 10^-4) and ribosomal protein L30 (RPL30) (<it>p </it>= 1.50 × 10^-4)] may define new central elements in the gene network specific to colon cancer. Gene Ontology (GO) based analysis of the colon cancer-specific gene network and the sub-network that consisted of three-way gene interactions suggested that tumourigenesis in colon cancer resulted from dysfunction in protein biosynthesis and categories associated with ribonucleoprotein complex which are well supported by multiple lines of experimental evidence.</p> <p>Conclusion</p> <p>This study demonstrated that IL8, DES and ENO1 act as the central elements in colon cancer susceptibility, and protein biosynthesis and the ribosome-associated function categories largely account for the colon cancer tumuorigenesis. Thus, the newly developed relevancy-based networking approach offers a powerful means to reverse-engineer the disease-specific network, a promising tool for systematic dissection of complex diseases.</p