Showing papers by "Shanghai University published in 2020"

On the origin and continuing evolution of SARS-CoV-2

Abstract: The SARS-CoV-2 epidemic started in late December 2019 in Wuhan, China, and has since impacted a large portion of China and raised major global concern. Herein, we investigated the extent of molecular divergence between SARS-CoV-2 and other related coronaviruses. Although we found only 4% variability in genomic nucleotides between SARS-CoV-2 and a bat SARS-related coronavirus (SARSr-CoV; RaTG13), the difference at neutral sites was 17%, suggesting the divergence between the two viruses is much larger than previously estimated. Our results suggest that the development of new variations in functional sites in the receptor-binding domain (RBD) of the spike seen in SARS-CoV-2 and viruses from pangolin SARSr-CoVs are likely caused by natural selection besides recombination. Population genetic analyses of 103 SARS-CoV-2 genomes indicated that these viruses had two major lineages (designated L and S), that are well defined by two different SNPs that show nearly complete linkage across the viral strains sequenced to date. We found that L lineage was more prevalent than the S lineage within the limited patient samples we examined. The implication of these evolutionary changes on disease etiology remains unclear. These findings strongly underscores the urgent need for further comprehensive studies that combine viral genomic data, with epidemiological studies of coronavirus disease 2019 (COVID-19).

Hydroxychloroquine in patients with mainly mild to moderate coronavirus disease 2019: open label, randomised controlled trial.

Abstract: Objective To assess the efficacy and safety of hydroxychloroquine plus standard of care compared with standard of care alone in adults with coronavirus disease 2019 (covid-19). Design Multicentre, open label, randomised controlled trial. Setting 16 government designated covid-19 treatment centres in China, 11 to 29 February 2020. Participants 150 patients admitted to hospital with laboratory confirmed covid-19 were included in the intention to treat analysis (75 patients assigned to hydroxychloroquine plus standard of care, 75 to standard of care alone). Interventions Hydroxychloroquine administrated at a loading dose of 1200 mg daily for three days followed by a maintenance dose of 800 mg daily (total treatment duration: two or three weeks for patients with mild to moderate or severe disease, respectively). Main outcome measure Negative conversion of severe acute respiratory syndrome coronavirus 2 by 28 days, analysed according to the intention to treat principle. Adverse events were analysed in the safety population in which hydroxychloroquine recipients were participants who received at least one dose of hydroxychloroquine and hydroxychloroquine non-recipients were those managed with standard of care alone. Results Of 150 patients, 148 had mild to moderate disease and two had severe disease. The mean duration from symptom onset to randomisation was 16.6 (SD 10.5; range 3-41) days. A total of 109 (73%) patients (56 standard of care; 53 standard of care plus hydroxychloroquine) had negative conversion well before 28 days, and the remaining 41 (27%) patients (19 standard of care; 22 standard of care plus hydroxychloroquine) were censored as they did not reach negative conversion of virus. The probability of negative conversion by 28 days in the standard of care plus hydroxychloroquine group was 85.4% (95% confidence interval 73.8% to 93.8%), similar to that in the standard of care group (81.3%, 71.2% to 89.6%). The difference between groups was 4.1% (95% confidence interval –10.3% to 18.5%). In the safety population, adverse events were recorded in 7/80 (9%) hydroxychloroquine non-recipients and in 21/70 (30%) hydroxychloroquine recipients. The most common adverse event in the hydroxychloroquine recipients was diarrhoea, reported in 7/70 (10%) patients. Two hydroxychloroquine recipients reported serious adverse events. Conclusions Administration of hydroxychloroquine did not result in a significantly higher probability of negative conversion than standard of care alone in patients admitted to hospital with mainly persistent mild to moderate covid-19. Adverse events were higher in hydroxychloroquine recipients than in non-recipients. Trial registration ChiCTR2000029868.

Transplantation of ACE2 - Mesenchymal Stem Cells Improves the Outcome of Patients with COVID-19 Pneumonia.

Abstract: A coronavirus (HCoV-19) has caused the novel coronavirus disease (COVID-19) outbreak in Wuhan, China. Preventing and reversing the cytokine storm may be the key to save the patients with severe COVID-19 pneumonia. Mesenchymal stem cells (MSCs) have been shown to possess a comprehensive powerful immunomodulatory function. This study aims to investigate whether MSC transplantation improves the outcome of 7 enrolled patients with COVID-19 pneumonia in Beijing YouAn Hospital, China, from Jan 23, 2020 to Feb 16, 2020. The clinical outcomes, as well as changes of inflammatory and immune function levels and adverse effects of 7 enrolled patients were assessed for 14 days after MSC injection. MSCs could cure or significantly improve the functional outcomes of seven patients without observed adverse effects. The pulmonary function and symptoms of these seven patients were significantly improved in 2 days after MSC transplantation. Among them, two common and one severe patient were recovered and discharged in 10 days after treatment. After treatment, the peripheral lymphocytes were increased, the C-reactive protein decreased, and the overactivated cytokine-secreting immune cells CXCR3+CD4+ T cells, CXCR3+CD8+ T cells, and CXCR3+ NK cells disappeared in 3-6 days. In addition, a group of CD14+CD11c+CD11bmid regulatory DC cell population dramatically increased. Meanwhile, the level of TNF-α was significantly decreased, while IL-10 increased in MSC treatment group compared to the placebo control group. Furthermore, the gene expression profile showed MSCs were ACE2- and TMPRSS2- which indicated MSCs are free from COVID-19 infection. Thus, the intravenous transplantation of MSCs was safe and effective for treatment in patients with COVID-19 pneumonia, especially for the patients in critically severe condition.

Prevalence of diabetes recorded in mainland China using 2018 diagnostic criteria from the American Diabetes Association: national cross sectional study

Abstract: Objective To assess the prevalence of diabetes and its risk factors. Design Population based, cross sectional study. Setting 31 provinces in mainland China with nationally representative cross sectional data from 2015 to 2017. Participants 75 880 participants aged 18 and older—a nationally representative sample of the mainland Chinese population. Main outcome measures Prevalence of diabetes among adults living in China, and the prevalence by sex, regions, and ethnic groups, estimated by the 2018 American Diabetes Association (ADA) and the World Health Organization diagnostic criteria. Demographic characteristics, lifestyle, and history of disease were recorded by participants on a questionnaire. Anthropometric and clinical assessments were made of serum concentrations of fasting plasma glucose (one measurement), two hour plasma glucose, and glycated haemoglobin (HbA1c). Results The weighted prevalence of total diabetes (n=9772), self-reported diabetes (n=4464), newly diagnosed diabetes (n=5308), and prediabetes (n=27 230) diagnosed by the ADA criteria were 12.8% (95% confidence interval 12.0% to 13.6%), 6.0% (5.4% to 6.7%), 6.8% (6.1% to 7.4%), and 35.2% (33.5% to 37.0%), respectively, among adults living in China. The weighted prevalence of total diabetes was higher among adults aged 50 and older and among men. The prevalence of total diabetes in 31 provinces ranged from 6.2% in Guizhou to 19.9% in Inner Mongolia. Han ethnicity had the highest prevalence of diabetes (12.8%) and Hui ethnicity had the lowest (6.3%) among five investigated ethnicities. The weighted prevalence of total diabetes (n=8385) using the WHO criteria was 11.2% (95% confidence interval 10.5% to 11.9%). Conclusion The prevalence of diabetes has increased slightly from 2007 to 2017 among adults living in China. The findings indicate that diabetes is an important public health problem in China.

Clinical characteristics and therapeutic procedure for four cases with 2019 novel coronavirus pneumonia receiving combined Chinese and Western medicine treatment

Abstract: Pneumonia associated with the 2019 novel coronavirus (2019-nCoV) is continuously and rapidly circulating at present. No effective antiviral treatment has been verified thus far. We report here the clinical characteristics and therapeutic procedure for four patients with mild or severe 2019-nCoV pneumonia admitted to Shanghai Public Health Clinical Center. All the patients were given antiviral treatment including lopinavir/ritonavir (Kaletra®), arbidol, and Shufeng Jiedu Capsule (SFJDC, a traditional Chinese medicine) and other necessary support care. After treatment, three patients gained significant improvement in pneumonia associated symptoms, two of whom were confirmed 2019-nCoV negative and discharged, and one of whom was virus negative at the first test. The remaining patient with severe pneumonia had shown signs of improvement by the cutoff date for data collection. Results obtained in the current study may provide clues for treatment of 2019-nCoV pneumonia. The efficacy of antiviral treatment including lopinavir/ritonavir, arbidol, and SFJDC warrants further verification in future study.

Networked control systems: a survey of trends and techniques

Abstract: Networked control systems are spatially distributed systems in which the communication between sensors, actuators, and controllers occurs through a shared band-limited digital communication network. Several advantages of the network architectures include reduced system wiring, plug and play devices, increased system agility, and ease of system diagnosis and maintenance. Consequently, networked control is the current trend for industrial automation and has ever-increasing applications in a wide range of areas, such as smart grids, manufacturing systems, process control, automobiles, automated highway systems, and unmanned aerial vehicles. The modelling, analysis, and control of networked control systems have received considerable attention in the last two decades. The ‘ control over networks ’ is one of the key research directions for networked control systems. This paper aims at presenting a survey of trends and techniques in networked control systems from the perspective of ‘ control over networks ’ , providing a snapshot of five control issues: sampled-data control, quantization control, networked control, event-triggered control, and security control. Some challenging issues are suggested to direct the future research.

Functional Supramolecular Polymeric Networks: The Marriage of Covalent Polymers and Macrocycle-Based Host-Guest Interactions

Abstract: Covalent polymers connected by non-covalent interactions constitute a fascinating set of materials known as supramolecular polymer networks (SPNs). A key feature of SPNs is that the underlying covalent polymers endow the resulting self-assembled materials with features, such as structural and mechanical integrity, good processability, recyclability, stimuli-responsiveness, self-healing, and shape memory, that are not recapitulated in the case of classic covalent polymer systems. The unique nature of SPNs derives from the controlled marriage of traditional covalent polymers and macrocycle-based host-guest interactions. As a consequence, supramolecular polymeric networks have played important roles in a number of diverse fields, including polymer science, supramolecular chemistry, materials science, biomedical materials, and information storage technology. In this Review, we summarize advances made in the area of functional SPNs, with a focus on original literature reports appearing in the past five years. The treatment is organized according to the key macrocycle-based host-guest interactions used to produce various SPNs. The role of the underlying polymer backbones is also discussed.

Organ-on-a-chip: recent breakthroughs and future prospects

Abstract: The organ-on-a-chip (OOAC) is in the list of top 10 emerging technologies and refers to a physiological organ biomimetic system built on a microfluidic chip. Through a combination of cell biology, engineering, and biomaterial technology, the microenvironment of the chip simulates that of the organ in terms of tissue interfaces and mechanical stimulation. This reflects the structural and functional characteristics of human tissue and can predict response to an array of stimuli including drug responses and environmental effects. OOAC has broad applications in precision medicine and biological defense strategies. Here, we introduce the concepts of OOAC and review its application to the construction of physiological models, drug development, and toxicology from the perspective of different organs. We further discuss existing challenges and provide future perspectives for its application.

Dynamic Event-Triggered Distributed Coordination Control and its Applications: A Survey of Trends and Techniques

Abstract: Distributed coordination control is the current trend in networked systems and finds prosperous applications across a variety of fields, such as smart grids and intelligent transportation systems. One fundamental issue in coordinating and controlling a large group of distributed and networked agents is the influence of intermittent interagent interactions caused by constrained communication resources. Event-triggered communication scheduling stands out as a promising enabler to strike a balance between the desired control performance and the satisfactory resource efficiency. What distinguishes dynamic event-triggered scheduling from traditional static event-triggered scheduling is that the triggering mechanism can be dynamically adjusted over time in accordance with both available system information and additional dynamic variables. This article provides an up-to-date overview of dynamic event-triggered distributed coordination control. The motivation of dynamic event-triggered scheduling is first introduced in the context of distributed coordination control. Then some techniques of dynamic event-triggered distributed coordination control are discussed in detail. Implementation and design issues are well addressed. Furthermore, this article exemplifies two applications of dynamic event-triggered distributed coordination control in the fields of microgrids and automated vehicles. Several challenges are suggested to direct the future research.

Full-color fluorescent carbon quantum dots

Abstract: Quantum dots have innate advantages as the key component of optoelectronic devices. For white light-emitting diodes (WLEDs), the modulation of the spectrum and color of the device often involves various quantum dots of different emission wavelengths. Here, we fabricate a series of carbon quantum dots (CQDs) through a scalable acid reagent engineering strategy. The growing electron-withdrawing groups on the surface of CQDs that originated from acid reagents boost their photoluminescence wavelength red shift and raise their particle sizes, elucidating the quantum size effect. These CQDs emit bright and remarkably stable full-color fluorescence ranging from blue to red light and even white light. Full-color emissive polymer films and all types of high-color rendering index WLEDs are synthesized by mixing multiple kinds of CQDs in appropriate ratios. The universal electron-donating/withdrawing group engineering approach for synthesizing tunable emissive CQDs will facilitate the progress of carbon-based luminescent materials for manufacturing forward-looking films and devices.

Review of Artificial Intelligence Techniques in Imaging Data Acquisition, Segmentation and Diagnosis for COVID-19

Abstract: (This paper was submitted as an invited paper to IEEE Reviews in Biomedical Engineering on April 6, 2020.) The pandemic of coronavirus disease 2019 (COVID-19) is spreading all over the world. Medical imaging such as X-ray and computed tomography (CT) plays an essential role in the global fight against COVID-19, whereas the recently emerging artificial intelligence (AI) technologies further strengthen the power of the imaging tools and help medical specialists. We hereby review the rapid responses in the community of medical imaging (empowered by AI) toward COVID-19. For example, AI-empowered image acquisition can significantly help automate the scanning procedure and also reshape the workflow with minimal contact to patients, providing the best protection to the imaging technicians. Also, AI can improve work efficiency by accurate delination of infections in X-ray and CT images, facilitating subsequent quantification. Moreover, the computer-aided platforms help radiologists make clinical decisions, i.e., for disease diagnosis, tracking, and prognosis. In this review paper, we thus cover the entire pipeline of medical imaging and analysis techniques involved with COVID-19, including image acquisition, segmentation, diagnosis, and follow-up. We particularly focus on the integration of AI with X-ray and CT, both of which are widely used in the frontline hospitals, in order to depict the latest progress of medical imaging and radiology fighting against COVID-19.

Triboelectric nanogenerator sensors for soft robotics aiming at digital twin applications

Abstract: Designing efficient sensors for soft robotics aiming at human machine interaction remains a challenge. Here, we report a smart soft-robotic gripper system based on triboelectric nanogenerator sensors to capture the continuous motion and tactile information for soft gripper. With the special distributed electrodes, the tactile sensor can perceive the contact position and area of external stimuli. The gear-based length sensor with a stretchable strip allows the continuous detection of elongation via the sequential contact of each tooth. The triboelectric sensory information collected during the operation of soft gripper is further trained by support vector machine algorithm to identify diverse objects with an accuracy of 98.1%. Demonstration of digital twin applications, which show the object identification and duplicate robotic manipulation in virtual environment according to the real-time operation of the soft-robotic gripper system, is successfully created for virtual assembly lines and unmanned warehouse applications. Designing efficient sensors for human machine interaction remains a challenge. Here, the authors present a soft robotic fingers system based on a triboelectric nanogenerator (L-TENG) sensor to capture the continuous motion of soft gripper and a soft tactile (T-TENG) sensor for tactile sensing, that can achieve an object recognition accuracy of 98.1%.

Memory-Based Event-Triggering H ∞ Load Frequency Control for Power Systems Under Deception Attacks

Abstract: This article proposes a memory-based event-triggering $H_{\infty }$ load frequency control (LFC) method for power systems through a bandwidth-constrained open network. To overcome the bandwidth constraint, a memory-based event-triggered scheme (METS) is first proposed to reduce the number of transmitted packets. Compared with the existing memoryless event-triggered schemes, the proposed METS has the advantage to utilize series of the latest released signals. To deal with the random deception attacks induced by open networks, a networked power system model is well established, which couples the effects of METS and random deception attacks in a unified framework. Then, a sufficient stabilization criterion is derived to obtain the memory $H_{\infty }$ LFC controller gains and event-triggered parameters simultaneously. Compared with existing memoryless LFC, the control performance is greatly improved since the latest released dynamic information is well utilized. Finally, an illustrative example is used to show the effectiveness of the proposed method.

A high performance wearable strain sensor with advanced thermal management for motion monitoring.

Abstract: Resistance change under mechanical stimuli arouses mass operational heat, damaging the performance, lifetime, and reliability of stretchable electronic devices, therefore rapid thermal heat dissipating is necessary. Here we report a stretchable strain sensor with outstanding thermal management. Besides a high stretchability and sensitivity testified by human motion monitoring, as well as long-term durability, an enhanced thermal conductivity from the casted thermoplastic polyurethane-boron nitride nanosheets layer helps rapid heat transmission to the environments, while the porous electrospun fibrous thermoplastic polyurethane membrane leads to thermal insulation. A 32% drop of the real time saturated temperature is achieved. For the first time we in-situ investigated the dynamic operational temperature fluctuation of stretchable electronics under repeating stretching-releasing processes. Finally, cytotoxicity test confirms that the nanofillers are tightly restricted in the nanocomposites, making it harmless to human health. All the results prove it an excellent candidate for the next-generation of wearable devices. Though stretchable strain sensors are attractive for next-generation applications due to their high sensitivity, heat generated in these devices limits their reliability. Here, the authors report boron nitride nanosheet-based stretchable strain sensors with enhanced thermal management.

PCL: Proposal Cluster Learning for Weakly Supervised Object Detection

Abstract: Weakly Supervised Object Detection (WSOD), using only image-level annotations to train object detectors, is of growing importance in object recognition. In this paper, we propose a novel deep network for WSOD. Unlike previous networks that transfer the object detection problem to an image classification problem using Multiple Instance Learning (MIL), our strategy generates proposal clusters to learn refined instance classifiers by an iterative process. The proposals in the same cluster are spatially adjacent and associated with the same object. This prevents the network from concentrating too much on parts of objects instead of whole objects. We first show that instances can be assigned object or background labels directly based on proposal clusters for instance classifier refinement, and then show that treating each cluster as a small new bag yields fewer ambiguities than the directly assigning label method. The iterative instance classifier refinement is implemented online using multiple streams in convolutional neural networks, where the first is an MIL network and the others are for instance classifier refinement supervised by the preceding one. Experiments are conducted on the PASCAL VOC, ImageNet detection, and MS-COCO benchmarks for WSOD. Results show that our method outperforms the previous state of the art significantly.

BeCome: Blockchain-Enabled Computation Offloading for IoT in Mobile Edge Computing

Abstract: Benefiting from the real-time processing ability of edge computing, computing tasks requested by smart devices in the Internet of Things are offloaded to edge computing devices (ECDs) for implementation. However, ECDs are often overloaded or underloaded with disproportionate resource requests. In addition, during the process of task offloading, the transmitted information is vulnerable, which can result in data incompleteness. In view of this challenge, a blockchain-enabled computation offloading method, named BeCome, is proposed in this article. Blockchain technology is employed in edge computing to ensure data integrity. Then, the nondominated sorting genetic algorithm III is adopted to generate strategies for balanced resource allocation. Furthermore, simple additive weighting and multicriteria decision making are utilized to identify the optimal offloading strategy. Finally, performance evaluations of BeCome are given through simulation experiments.

Xiaozhang Tie Improves Intestinal Motility in Rats With Cirrhotic Ascites by Regulating the Stem Cell Factor/c-kit Pathway in Interstitial Cells of Cajal.

Abstract: We previously discovered that Xiaozhang Tie (XZT) was helpful for cirrhotic ascites, with obvious abdominal distention relief, suggesting that it may improve gastrointestinal (GI) motility. However, the underlying mechanisms of GI motility in cirrhotic ascites are unclear. Here, we aimed to discover explored the effect of XZT on GI motility in animal cirrhotic ascites and probed the action mechanism affecting GI motility by regulating the SCF/c-kit pathway in ICCs and GI hormones. First, rat models of cirrhotic ascites were developed and then divided randomly into the following three subgroups: model control, XZT group, and mosapride group. The efficacy of XZT on treating cirrhotic ascites was evaluated on the basis of ascites weight and volume, 24 h urine volume, and feces water content. GI motility, intestine propulsion and gartric residue were detected using the migration distance of ink in vivo, and the frequency of contraction and tension of isolated gastric and jejunal muscle strips were measured after incubation with XZT extracts. Serum GI hormone content, including motilin (MTL), substance P (SP), somatostain (SS), and vasoactive intestinal polypeptide were assayed. Subsequently, ICCs were isolated from jejunum, and primarily cultured ICCs were incubated with and without XZT and SCF. The cell vitality of the ICCs was measured. A whole-cell patch recording technique was used to record the current of K+ and Na+ channels in the ICC membrane. Expressions of c-kit/p-c-kit, p-Akt, p-Stat3, and p-Erk1/2 were detected in vivo and in vitro. The results revealed that XZT significantly reduced ascites weight and increased urine volume and fecal water content in model rats. XZT promoted intestinal motility and increased MTL level but reduced SP and SS levels. It enhanced the current of Na+ and K+ in ICCs and improved c-kit expression and signaling mediator phosphorylation in SCF/c-kit, which was inhibited by imatinib in vitro and downregulated in model rats in vivo. Our study concluded that XZT reduced the amount of ascites and improved intestinal motility in cirrhotic rats, which may be associated with its effect on ascites and was involved in the mechanisms regulating the SCF/c-Kit signaling pathway in ICCs and improving gastrointestinal hormone secretion.

Switching-Like Event-Triggered Control for Networked Control Systems Under Malicious Denial of Service Attacks

Abstract: This article investigates the switching-like event-triggered control for networked control systems (NCSs) under the malicious denial of service (DoS) attacks. First, by dividing the DoS attacks into S-interval (DoS-free case) and D-interval (DoS case), a switching-like event-triggered communication scheme (SETC) is well designed to deal with intermittent DoS attacks to improve communication efficiency while keeping the desired control performance. Second, by considering the SETC and NCSs into a unified framework, the studied system is transferred into a time-delay system. Then, under the constraint of the number of maximum allowable data dropouts induced by DoS attacks, a stability criterion and a stabilization criterion are derived, which can be used to estimate the event-triggered communication parameters and obtain the security controller gain simultaneously. Moreover, the derived stabilization criterion can also provide a tradeoff to balance communication efficiency and $H_{\infty }$ control performance. At last, a networked invert pendulum on a cart is conducted to show the effectiveness of the proposed method.

Crowdsourcing Based Description of Urban Emergency Events Using Social Media Big Data

Abstract: Crowdsourcing is a process of acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces, such as sensors, devices, vehicles, buildings, and human. Especially, nowadays, no countries, no communities, and no person are immune to urban emergency events. Detection about urban emergency events, e.g., fires, storms, traffic jams is of great importance to protect the security of humans. Recently, social media feeds are rapidly emerging as a novel platform for providing and dissemination of information that is often geographic. The content from social media usually includes references to urban emergency events occurring at, or affecting specific locations. In this paper, in order to detect and describe the real time urban emergency event, the 5W (What, Where, When, Who, and Why) model is proposed. Firstly, users of social media are set as the target of crowd sourcing. Secondly, the spatial and temporal information from the social media are extracted to detect the real time event. Thirdly, a GIS based annotation of the detected urban emergency event is shown. The proposed method is evaluated with extensive case studies based on real urban emergency events. The results show the accuracy and efficiency of the proposed method.

Hydroxychloroquine in patients mainly with mild to moderate COVID–19: an open–label, randomized, controlled trial

Abstract: Objectives To assess the efficacy and safety of hydroxychloroquine (HCQ) plus standard-of-care (SOC) compared with SOC alone in adult patients with COVID-19. Design Multicenter, open-label, randomized controlled trial. Setting 16 government-designated COVID-19 treatment centers in China through 11 to 29 in February 2020. Participants 150 patients hospitalized with COVID-19. 75 patients were assigned to HCQ plus SOC and 75 were assigned to SOC alone (control group). Interventions HCQ was administrated with a loading dose of 1, 200 mg daily for three days followed by a maintained dose of 800 mg daily for the remaining days (total treatment duration: 2 or 3 weeks for mild/moderate or severe patients, respectively). Main outcome measures The primary endpoint was the 28-day negative conversion rate of SARS-CoV-2. The assessed secondary endpoints were negative conversion rate at day 4, 7, 10, 14 or 21, the improvement rate of clinical symptoms within 28-day, normalization of C-reactive protein and blood lymphocyte count within 28-day. Primary and secondary analysis was by intention to treat. Adverse events were assessed in the safety population. Results The overall 28-day negative conversion rate was not different between SOC plus HCQ and SOC group (Kaplan-Meier estimates 85.4% versus 81.3%, P=0.341). Negative conversion rate at day 4, 7, 10, 14 or 21 was also similar between the two groups. No different 28-day symptoms alleviation rate was observed between the two groups. A significant efficacy of HCQ on alleviating symptoms was observed when the confounding effects of anti-viral agents were removed in the post-hoc analysis (Hazard ratio, 8.83, 95%CI, 1.09 to 71.3). This was further supported by a significantly greater reduction of CRP (6.986 in SOC plus HCQ versus 2.723 in SOC, milligram/liter, P=0.045) conferred by the addition of HCQ, which also led to more rapid recovery of lymphopenia, albeit no statistical significance. Adverse events were found in 8.8% of SOC and 30% of HCQ recipients with two serious adverse events. The most common adverse event in the HCQ recipients was diarrhea (10%). Conclusions The administration of HCQ did not result in a higher negative conversion rate but more alleviation of clinical symptoms than SOC alone in patients hospitalized with COVID-19 without receiving antiviral treatment, possibly through anti-inflammatory effects. Adverse events were significantly increased in HCQ recipients but no apparently increase of serious adverse events. Trial registration ChiCTR2000029868.

Photonic microwave generation in the X- and K-band using integrated soliton microcombs

Abstract: Microwave photonic technologies, which upshift the carrier into the optical domain, have facilitated the generation and processing of ultra-wideband electronic signals at vastly reduced fractional bandwidths. For microwave photonic applications such as radars, optical communications and low-noise microwave generation, optical frequency combs are useful building blocks. By virtue of soliton microcombs, frequency combs can now be built using CMOS-compatible photonic integrated circuits. Yet, currently developed integrated soliton microcombs all operate with repetition rates significantly beyond those that conventional electronics can detect, preventing their use in microwave photonics. Access to this regime is challenging due to the required ultra-low waveguide loss and large dimensions of the nanophotonic resonators. Here, we demonstrate soliton microcombs operating in two widely employed microwave bands, the X-band (~10 GHz, for radar) and the K-band (~20 GHz, for 5G). Driven by a low-noise fibre laser, these devices produce more than 300 frequency lines within the 3 dB bandwidth, and generate microwave signals featuring phase noise levels comparable to modern electronic microwave oscillators. Our results establish integrated microcombs as viable low-noise microwave generators. Furthermore, the low soliton repetition rates are critical for future dense wavelength-division multiplexing channel generation schemes and could significantly reduce the system complexity of soliton-based integrated frequency synthesizers and atomic clocks. Nanophotonic microwave synthesizers in the X-band (10 GHz, for radar) and K-band (20 GHz, for 5G), based on integrated soliton microcombs driven by a low-noise fibre laser, link the fields of microwave photonics and integrated microcombs.

ICNet: Information Conversion Network for RGB-D Based Salient Object Detection

Abstract: RGB-D based salient object detection (SOD) methods leverage the depth map as a valuable complementary information for better SOD performance. Previous methods mainly resort to exploit the correlation between RGB image and depth map in three fusion domains: input images, extracted features, and output results. However, these fusion strategies cannot fully capture the complex correlation between the RGB image and depth map. Besides, these methods do not fully explore the cross-modal complementarity and the cross-level continuity of information, and treat information from different sources without discrimination. In this paper, to address these problems, we propose a novel Information Conversion Network (ICNet) for RGB-D based SOD by employing the siamese structure with encoder-decoder architecture. To fuse high-level RGB and depth features in an interactive and adaptive way, we propose a novel Information Conversion Module (ICM), which contains concatenation operations and correlation layers. Furthermore, we design a Cross-modal Depth-weighted Combination (CDC) block to discriminate the cross-modal features from different sources and to enhance RGB features with depth features at each level. Extensive experiments on five commonly tested datasets demonstrate the superiority of our ICNet over 15 state-of-the-art RGB-D based SOD methods, and validate the effectiveness of the proposed ICM and CDC block.

Incipient winding fault detection and diagnosis for squirrel-cage induction motors equipped on CRH trains.

Abstract: Stator/rotor winding faults are the common faults in squirrel-cage induction motor systems, which motivates the study of incipient fault detection and isolation (IFDI) to improve the safety and reliability of CRH (China Railway High-speed) trains. In this paper, a dynamic model for squirrel caged induction motor in d-q coordinate system is established firstly, further, the models and characteristics of incipient broken-rotor-bar fault and turn-to-turn short fault are analyzed. After that, a novel robust diagnosis design is proposed for the possible incipient stator/rotor winding faults. Experimental analyses show that the detection and isolation scheme designed in this paper provides high sensitivity and accurate isolation to incipient winding faults.

Combinative treatment of β-elemene and cetuximab is sensitive to KRAS mutant colorectal cancer cells by inducing ferroptosis and inhibiting epithelial-mesenchymal transformation.

Abstract: Background and Purpose: RAS mutations limit the effectiveness of anti-epidermal growth factor receptor (EGFR) monoclonal antibodies in combination with chemotherapy for metastatic colorectal cancer (mCRC) patients. Therefore, new cell death forms have focused on identifying indirect targets to inhibit Ras-induced oncogenesis. Recently, emerging evidence has shown the potential of triggering ferroptosis for cancer therapy, particularly for eradicating aggressive malignancies that are resistant to traditional therapies. Methods: KRAS mutant CRC cell HCT116 and Lovo were treated with cetuximab and β-elemene, a bioactive compound isolated from Chinese herb Curcumae Rhizoma. Ferroptosis and epithelial-mesenchymal transformation (EMT) were detected in vitro and in vivo. Orthotopic CRC animal model were established and the tumor growth was monitored by IVIS bioluminescence imaging. Tumor tissues were collected to determine ferroptosis effect and the expression of EMT markers after the treatment. Results: CCK-8 assay showed that synergetic effect was obtained when 125 µg/ml β-elemene was combined with 25 µg/ml cetuximab in KRAS mutant CRC cells. AV/PI staining suggested a non-apoptotic mode of cell death after the treatment with β-elemene and cetuximab. In vitro, β-elemene in combination with cetuximab was shown to induce iron-dependent reactive oxygen species (ROS) accumulation, glutathione (GSH) depletion, lipid peroxidation, upregulation of HO-1 and transferrin, and downregulation of negative regulatory proteins for ferroptosis (GPX4, SLC7A11, FTH1, glutaminase, and SLC40A1) in KRAS mutant CRC cells. Meanwhile, combinative treatment of β-elemene and cetuximab inhibited cell migration and decreased the expression of mesenchymal markers (Vimentin, N-cadherin, Slug, Snail and MMP-9), but promoted the expression of epithelial marker E-cadherin. Moreover, ferroptosis inhibitors but not other cell death suppressors abrogated the effect of β-elemene in combination with cetuximab on KRAS mutant CRC cells. In vivo, co-treatment with β-elemene and cetuximab inhibited KRAS mutant tumor growth and lymph nodes metastases. Conclusions: Our data for the first time suggest that the natural product β-elemene is a new ferroptosis inducer and combinative treatment of β-elemene and cetuximab is sensitive to KRAS mutant CRC cells by inducing ferroptosis and inhibiting EMT, which will hopefully provide a prospective strategy for CRC patients with RAS mutations.