Showing papers by "Xi'an Jiaotong University published in 2021"

Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)

Abstract: In 2008, we published the first set of guidelines for standardizing research in autophagy. Since then, this topic has received increasing attention, and many scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Thus, it is important to formulate on a regular basis updated guidelines for monitoring autophagy in different organisms. Despite numerous reviews, there continues to be confusion regarding acceptable methods to evaluate autophagy, especially in multicellular eukaryotes. Here, we present a set of guidelines for investigators to select and interpret methods to examine autophagy and related processes, and for reviewers to provide realistic and reasonable critiques of reports that are focused on these processes. These guidelines are not meant to be a dogmatic set of rules, because the appropriateness of any assay largely depends on the question being asked and the system being used. Moreover, no individual assay is perfect for every situation, calling for the use of multiple techniques to properly monitor autophagy in each experimental setting. Finally, several core components of the autophagy machinery have been implicated in distinct autophagic processes (canonical and noncanonical autophagy), implying that genetic approaches to block autophagy should rely on targeting two or more autophagy-related genes that ideally participate in distinct steps of the pathway. Along similar lines, because multiple proteins involved in autophagy also regulate other cellular pathways including apoptosis, not all of them can be used as a specific marker for bona fide autophagic responses. Here, we critically discuss current methods of assessing autophagy and the information they can, or cannot, provide. Our ultimate goal is to encourage intellectual and technical innovation in the field.

Functional Hydrogels as Wound Dressing to Enhance Wound Healing.

Abstract: Hydrogels, due to their excellent biochemical and mechnical property, have shown attractive advantages in the field of wound dressings. However, a comprehensive review of the functional hydrogel as a wound dressing is still lacking. This work first summarizes the skin wound healing process and relates evaluation parameters and then reviews the advanced functions of hydrogel dressings such as antimicrobial property, adhesion and hemostasis, anti-inflammatory and anti-oxidation, substance delivery, self-healing, stimulus response, conductivity, and the recently emerged wound monitoring feature, and the strategies adopted to achieve these functions are all classified and discussed. Furthermore, applications of hydrogel wound dressing for the treatment of different types of wounds such as incisional wound and the excisional wound are summarized. Chronic wounds are also mentioned, and the focus of attention on infected wounds, burn wounds, and diabetic wounds is discussed. Finally, the future directions of hydrogel wound dressings for wound healing are further proposed.

Boron-doped nitrogen-deficient carbon nitride-based Z-scheme heterostructures for photocatalytic overall water splitting

Abstract: Photocatalytic overall water splitting can be achieved using Z-scheme systems that mimic natural photosynthesis by combining dissimilar semiconductors in series. However, coupling well-suited H2- and O2-evolving components remains challenging. Here, we fabricate a Z-scheme system for photocatalytic overall water splitting based on boron-doped, nitrogen-deficient carbon nitride two-dimensional (2D) nanosheets. We prepare ultrathin carbon nitride nanosheets with varying levels of boron dopants and nitrogen defects, which leads to nanosheets that can act as either H2- or O2-evolving photocatalysts. Using an electrostatic self-assembly strategy, the nanosheets are coupled to obtain a 2D/2D polymeric heterostructure. Owing to their ultrathin nanostructures, strong interfacial interaction and staggered band alignment, a Z-scheme route for efficient charge-carrier separation and transfer is realized. The obtained heterostructure achieves stoichiometric H2 and O2 evolution in the presence of Pt and Co(OH)2 co-catalysts, and the solar-to-hydrogen efficiency reaches 1.16% under one-sun illumination. Splitting water using suspensions of particulate carbon nitride-based photocatalysts may be a cheap way to produce hydrogen, but efficiencies have remained low. Now, Shen and colleagues use doped carbon nitride-based Z-scheme heterostructures to split water with a solar-to-hydrogen efficiency of 1.1% in the presence of metal-based co-catalysts.

Graph Convolutional Networks for Hyperspectral Image Classification

Abstract: Convolutional neural networks (CNNs) have been attracting increasing attention in hyperspectral (HS) image classification due to their ability to capture spatial–spectral feature representations. Nevertheless, their ability in modeling relations between the samples remains limited. Beyond the limitations of grid sampling, graph convolutional networks (GCNs) have been recently proposed and successfully applied in irregular (or nongrid) data representation and analysis. In this article, we thoroughly investigate CNNs and GCNs (qualitatively and quantitatively) in terms of HS image classification. Due to the construction of the adjacency matrix on all the data, traditional GCNs usually suffer from a huge computational cost, particularly in large-scale remote sensing (RS) problems. To this end, we develop a new minibatch GCN (called miniGCN hereinafter), which allows to train large-scale GCNs in a minibatch fashion. More significantly, our miniGCN is capable of inferring out-of-sample data without retraining networks and improving classification performance. Furthermore, as CNNs and GCNs can extract different types of HS features, an intuitive solution to break the performance bottleneck of a single model is to fuse them. Since miniGCNs can perform batchwise network training (enabling the combination of CNNs and GCNs), we explore three fusion strategies: additive fusion, elementwise multiplicative fusion, and concatenation fusion to measure the obtained performance gain. Extensive experiments, conducted on three HS data sets, demonstrate the advantages of miniGCNs over GCNs and the superiority of the tested fusion strategies with regard to the single CNN or GCN models. The codes of this work will be available at https://github.com/danfenghong/IEEE_TGRS_GCN for the sake of reproducibility.

A deep learning algorithm using CT images to screen for Corona virus disease (COVID-19).

Abstract: The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-COV-2) has caused more than 26 million cases of Corona virus disease (COVID-19) in the world so far. To control the spread of the disease, screening large numbers of suspected cases for appropriate quarantine and treatment are a priority. Pathogenic laboratory testing is typically the gold standard, but it bears the burden of significant false negativity, adding to the urgent need of alternative diagnostic methods to combat the disease. Based on COVID-19 radiographic changes in CT images, this study hypothesized that artificial intelligence methods might be able to extract specific graphical features of COVID-19 and provide a clinical diagnosis ahead of the pathogenic test, thus saving critical time for disease control. We collected 1065 CT images of pathogen-confirmed COVID-19 cases along with those previously diagnosed with typical viral pneumonia. We modified the inception transfer-learning model to establish the algorithm, followed by internal and external validation. The internal validation achieved a total accuracy of 89.5% with a specificity of 0.88 and sensitivity of 0.87. The external testing dataset showed a total accuracy of 79.3% with a specificity of 0.83 and sensitivity of 0.67. In addition, in 54 COVID-19 images, the first two nucleic acid test results were negative, and 46 were predicted as COVID-19 positive by the algorithm, with an accuracy of 85.2%. These results demonstrate the proof-of-principle for using artificial intelligence to extract radiological features for timely and accurate COVID-19 diagnosis. • The study evaluated the diagnostic performance of a deep learning algorithm using CT images to screen for COVID-19 during the influenza season. • As a screening method, our model achieved a relatively high sensitivity on internal and external CT image datasets. • The model was used to distinguish between COVID-19 and other typical viral pneumonia, both of which have quite similar radiologic characteristics.

Dual-Dynamic-Bond Cross-Linked Antibacterial Adhesive Hydrogel Sealants with On-Demand Removability for Post-Wound-Closure and Infected Wound Healing.

Abstract: The design and development of a smart bioadhesive hydrogel sealant with self-healing and excellent antibacterial activity to achieve high wound closure effectiveness and post-wound-closure care is highly desirable in clinical applications. In this work, a series of adhesive antioxidant antibacterial self-healing hydrogels with promising traits were designed through dual-dynamic-bond cross-linking among ferric iron (Fe), protocatechualdehyde (PA) containing catechol and aldehyde groups and quaternized chitosan (QCS) to enable the closure of skin incisions and promotion of methicillin-resistant Staphylococcus aureus (MRSA)-infected wound healing. The dual-dynamic-bond cross-linking of a pH-sensitive coordinate bond (catechol-Fe) and dynamic Schiff base bonds with reversible breakage and re-formation equips the hydrogel with excellent autonomous healing and on-demand dissolution or removal properties. Additionally, the hydrogel presents injectability, good biocompatibility and antibacterial activity, multifunctional adhesiveness, and hemostasis as well as NIR responsiveness. The in vivo evaluation in a rat skin incision model and infected full-thickness skin wound model revealed the high wound closure effectiveness and post-wound-closure care of the smart hydrogels, demonstrating its great potential in dealing with skin incisions and infected full-thickness skin wounds.

Electroceramics for High-Energy Density Capacitors: Current Status and Future Perspectives

Abstract: Materials exhibiting high energy/power density are currently needed to meet the growing demand of portable electronics, electric vehicles and large-scale energy storage devices. The highest energy densities are achieved for fuel cells, batteries, and supercapacitors, but conventional dielectric capacitors are receiving increased attention for pulsed power applications due to their high power density and their fast charge-discharge speed. The key to high energy density in dielectric capacitors is a large maximum but small remanent (zero in the case of linear dielectrics) polarization and a high electric breakdown strength. Polymer dielectric capacitors offer high power/energy density for applications at room temperature, but above 100 °C they are unreliable and suffer from dielectric breakdown. For high-temperature applications, therefore, dielectric ceramics are the only feasible alternative. Lead-based ceramics such as La-doped lead zirconate titanate exhibit good energy storage properties, but their toxicity raises concern over their use in consumer applications, where capacitors are exclusively lead free. Lead-free compositions with superior power density are thus required. In this paper, we introduce the fundamental principles of energy storage in dielectrics. We discuss key factors to improve energy storage properties such as the control of local structure, phase assemblage, dielectric layer thickness, microstructure, conductivity, and electrical homogeneity through the choice of base systems, dopants, and alloying additions, followed by a comprehensive review of the state-of-the-art. Finally, we comment on the future requirements for new materials in high power/energy density capacitor applications.

High-entropy ceramics: Present status, challenges, and a look forward

Abstract: High-entropy ceramics (HECs) are solid solutions of inorganic compounds with one or more Wyckoff sites shared by equal or near-equal atomic ratios of multi-principal elements. Although in the infant stage, the emerging of this new family of materials has brought new opportunities for material design and property tailoring. Distinct from metals, the diversity in crystal structure and electronic structure of ceramics provides huge space for properties tuning through band structure engineering and phonon engineering. Aside from strengthening, hardening, and low thermal conductivity that have already been found in high-entropy alloys, new properties like colossal dielectric constant, super ionic conductivity, severe anisotropic thermal expansion coefficient, strong electromagnetic wave absorption, etc., have been discovered in HECs. As a response to the rapid development in this nascent field, this article gives a comprehensive review on the structure features, theoretical methods for stability and property prediction, processing routes, novel properties, and prospective applications of HECs. The challenges on processing, characterization, and property predictions are also emphasized. Finally, future directions for new material exploration, novel processing, fundamental understanding, in-depth characterization, and database assessments are given.

Encapsulated Metal Nanoparticles for Catalysis.

Abstract: Metal nanoparticles have drawn great attention in heterogeneous catalysis One challenge is that they are easily deactivated by migration-coalescence during the catalysis process because of their high surface energy With the rapid development of nanoscience, encapsulating metal nanoparticles in nanoshells or nanopores becomes one of the most promising strategies to overcome the stability issue of the metal nanoparticles Besides, the activity and selectivity could be simultaneously enhanced by taking advantage of the synergy between the metal nanoparticles and the encapsulating materials as well as the molecular sieving property of the encapsulating materials In this review, we provide a comprehensive summary of the recent progress in the synthesis and catalytic properties of the encapsulated metal nanoparticles This review begins with an introduction to the synthetic strategies for encapsulating metal nanoparticles with different architectures developed to date, including their encapsulation in nanoshells of inorganic oxides and carbon, porous materials (zeolites, metal-organic frameworks, and covalent organic frameworks), and organic capsules (dendrimers and organic cages) The advantages of the encapsulated metal nanoparticles are then discussed, such as enhanced stability and recyclability, improved selectivity, strong metal-support interactions, and the capability of enabling tandem catalysis, followed by the introduction of some representative applications of the encapsulated metal nanoparticles in thermo-, photo-, and electrocatalysis At the end of this review, we discuss the remaining challenges associated with the encapsulated metal nanoparticles and provide our perspectives on the future development of the field

Sintilimab plus a bevacizumab biosimilar (IBI305) versus sorafenib in unresectable hepatocellular carcinoma (ORIENT-32): a randomised, open-label, phase 2-3 study.

Abstract: Summary Background China has a high burden of hepatocellular carcinoma, and hepatitis B virus (HBV) infection is the main causative factor. Patients with hepatocellular carcinoma have a poor prognosis and a substantial unmet clinical need. The phase 2–3 ORIENT-32 study aimed to assess sintilimab (a PD-1 inhibitor) plus IBI305, a bevacizumab biosimilar, versus sorafenib as a first-line treatment for unresectable HBV-associated hepatocellular carcinoma. Methods This randomised, open-label, phase 2–3 study was done at 50 clinical sites in China. Patients aged 18 years or older with histologically or cytologically diagnosed or clinically confirmed unresectable or metastatic hepatocellular carcinoma, no previous systemic treatment, and a baseline Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1 were eligible for inclusion. In the phase 2 part of the study, patients received intravenous sintilimab (200 mg every 3 weeks) plus intravenous IBI305 (15 mg/kg every 3 weeks). In the phase 3 part, patients were randomly assigned (2:1) to receive either sintilimab plus IBI305 (sintilimab–bevacizumab biosimilar group) or sorafenib (400 mg orally twice daily; sorafenib group), until disease progression or unacceptable toxicity. Randomisation was done using permuted block randomisation, with a block size of six, via an interactive web response system, and stratified by macrovascular invasion or extrahepatic metastasis, baseline α-fetoprotein, and ECOG performance status. The primary endpoint of the phase 2 part of the study was safety, assessed in all patients who received at least one dose of study drug. The co-primary endpoints of the phase 3 part of the study were overall survival and independent radiological review committee (IRRC)-assessed progression-free survival according to Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 in the intention-to-treat population. The study is registered with ClinicalTrials.gov , NCT03794440 . The study is closed to new participants and follow-up is ongoing for long-term outcomes. Findings Between Feb 11, 2019 and Jan 15, 2020, we enrolled 595 patients: 24 were enrolled directly into the phase 2 safety run-in and 571 were randomly assigned to sintilimab–bevacizumab biosimilar (n=380) or sorafenib (n=191). In the phase 2 part of the trial, 24 patients received at least one dose of the study drug, with an objective response rate of 25·0% (95% CI 9·8–46·7). Based on the preliminary safety and activity data of the phase 2 part, in which grade 3 or worse treatment-related adverse events occurred in seven (29%) of 24 patients, the randomised phase 3 part was started. At data cutoff (Aug 15, 2020), the median follow-up was 10·0 months (IQR 8·5–11·7) in the sintilimab–bevacizumab biosimilar group and 10·0 months (8·4–11·7) in the sorafenib group. Patients in the sintilimab–bevacizumab biosimilar group had a significantly longer IRRC-assessed median progression-free survival (4·6 months [95% CI 4·1–5·7]) than did patients in the sorafenib group (2·8 months [2·7–3·2]; stratified hazard ratio [HR] 0·56, 95% CI 0·46–0·70; p Interpretation Sintilimab plus IBI305 showed a significant overall survival and progression-free survival benefit versus sorafenib in the first-line setting for Chinese patients with unresectable, HBV-associated hepatocellular carcinoma, with an acceptable safety profile. This combination regimen could provide a novel treatment option for such patients. Funding Innovent Biologics. Translation For the Chinese translation of the abstract see Supplementary Materials section.

Potassium-ion batteries: outlook on present and future technologies

Abstract: The limited resources and uneven distribution of lithium stimulate strong motivation to develop new rechargeable batteries that use alternative charge carriers. Potassium-ion batteries (PIBs) are at the top of the list of alternatives because of the abundant raw materials and relatively high energy density, fast ion transport kinetics in the electrolyte, and low cost. However, several challenges still hinder the development of PIBs, such as low reversible capacity, poor rate performance, and inferior cycling stability. Research on the cathode is currently focused on developing materials with high energy density and cycling stability, mainly including layered transition metal oxides, polyanion compounds, organic compounds, etc. Anodes based on intercalation reactions, conversion reactions, and alloying with potassium are currently under development, and promising results have been published. This review comprehensively summarizes the research effort to date on the electrode material optimization (e.g., crystals, morphology, reaction mechanisms, and interface control), the synthesis methods, and the full cell fabrication for PIBs to enhance the electrochemical potassium storage and provide a platform for further development in this battery system.

Haplotype-resolved diverse human genomes and integrated analysis of structural variation.

Abstract: Long-read and strand-specific sequencing technologies together facilitate the de novo assembly of high-quality haplotype-resolved human genomes without parent-child trio data. We present 64 assembled haplotypes from 32 diverse human genomes. These highly contiguous haplotype assemblies (average minimum contig length needed to cover 50% of the genome: 26 million base pairs) integrate all forms of genetic variation, even across complex loci. We identified 107,590 structural variants (SVs), of which 68% were not discovered with short-read sequencing, and 278 SV hotspots (spanning megabases of gene-rich sequence). We characterized 130 of the most active mobile element source elements and found that 63% of all SVs arise through homology-mediated mechanisms. This resource enables reliable graph-based genotyping from short reads of up to 50,340 SVs, resulting in the identification of 1526 expression quantitative trait loci as well as SV candidates for adaptive selection within the human population.

Camrelizumab in Combination with Apatinib in Patients with Advanced Hepatocellular Carcinoma (RESCUE): A Nonrandomized, Open-label, Phase II Trial.

Abstract: Purpose: We assessed the efficacy and safety of camrelizumab [an anti-programmed death (PD-1) mAb] plus apatinib (a VEGFR-2 tyrosine kinase inhibitor) in patients with advanced hepatocellular carcinoma (HCC). Patients and Methods: This nonrandomized, open-label, multicenter, phase II study enrolled patients with advanced HCC who were treatment-naive or refractory/intolerant to first-line targeted therapy. Patients received intravenous camrelizumab 200 mg (for bodyweight ≥50 kg) or 3 mg/kg (for bodyweight Results: Seventy patients in the first-line setting and 120 patients in the second-line setting were enrolled. As of January 10, 2020, the ORR was 34.3% [24/70; 95% confidence interval (CI), 23.3–46.6] in the first-line and 22.5% (27/120; 95% CI, 15.4–31.0) in the second-line cohort per IRC. Median progression-free survival in both cohorts was 5.7 months (95% CI, 5.4–7.4) and 5.5 months (95% CI, 3.7–5.6), respectively. The 12-month survival rate was 74.7% (95% CI, 62.5–83.5) and 68.2% (95% CI, 59.0–75.7), respectively. Grade ≥3 treatment-related adverse events (TRAE) were reported in 147 (77.4%) of 190 patients, with the most common being hypertension (34.2%). Serious TRAEs occurred in 55 (28.9%) patients. Two (1.1%) treatment-related deaths occurred. Conclusions: Camrelizumab combined with apatinib showed promising efficacy and manageable safety in patients with advanced HCC in both the first-line and second-line setting. It might represent a novel treatment option for these patients. See related commentary by Pinato et al., p. 908

Recent research and development status of laser cladding: A review

Abstract: In industries such as aerospace, petrochemistry and automobile, many parts of different machines are under environment which shows high temperature and high pressure, and have their proneness to wear and corrosion. Therefore, the wear resistibility and stability under high temperature need to be further improved. Nowadays, Laser cladding (LC) is widely used in machine parts repairing and functional coating due to its advantages such as lower dilution rate, small heat-affected zone and good metallurgical bonding between coating and substrate. In this paper, LC is introduced in detail from aspects of process simulation, monitoring and parameter optimization. At the same time, the paper gives a comprehensive review over LC material system as high entropy alloys (HEAs), amorphous alloy and single crystal alloy have been gradually showing their advantages over traditional metal materials in LC. In addition, the applications of LC in functional coatings and in maintenance of machine parts are also outlined. Also, the existing problems and the development trend of LC is discussed then.

Boosted binary Harris hawks optimizer and feature selection

Abstract: Feature selection is a required preprocess stage in most of the data mining tasks. This paper presents an improved Harris hawks optimization (HHO) to find high-quality solutions for global optimization and feature selection tasks. This method is an efficient optimizer inspired by the behaviors of Harris' hawks, which try to catch the rabbits. In some cases, the original version tends to stagnate to the local optimum solutions. Hence, a novel HHO called IHHO is proposed by embedding the salp swarm algorithm (SSA) into the original HHO to improve the search ability of the optimizer and expand the application fields. The update stage in the HHO optimizer, which is performed to update each hawk, is divided into three phases: adjusting population based on SSA to generate SSA-based population, generating hybrid individuals according to SSA-based individual and HHO-based individual, and updating search agent in the light of greedy selection and HHO’s mechanisms. A large group of experiments on many functions is carried out to investigate the efficacy of the proposed optimizer. Based on the overall results, the proposed IHHO can provide a faster convergence speed and maintain a better balance between exploration and exploitation. Moreover, according to the proposed continuous IHHO, a more stable binary IHHO is also constructed as a wrapper-based feature selection (FS) approach. We compare the resulting binary IHHO with other FS methods using well-known benchmark datasets provided by UCI. The experimental results reveal that the proposed IHHO has better accuracy rates over other compared wrapper FS methods. Overall research and analysis confirm the improvement in IHHO because of the suitable exploration capability of SSA.

Direct observation of chemical short-range order in a medium-entropy alloy

Abstract: Complex concentrated solutions of multiple principal elements are being widely investigated as high- or medium-entropy alloys (HEAs or MEAs)1–11, often assuming that these materials have the high configurational entropy of an ideal solution. However, enthalpic interactions among constituent elements are also expected at normal temperatures, resulting in various degrees of local chemical order12–22. Of the local chemical orders that can develop, chemical short-range order (CSRO) is arguably the most difficult to decipher and firm evidence of CSRO in these materials has been missing thus far16,22. Here we discover that, using an appropriate zone axis, micro/nanobeam diffraction, together with atomic-resolution imaging and chemical mapping via transmission electron microscopy, can explicitly reveal CSRO in a face-centred-cubic VCoNi concentrated solution. Our complementary suite of tools provides concrete information about the degree/extent of CSRO, atomic packing configuration and preferential occupancy of neighbouring lattice planes/sites by chemical species. Modelling of the CSRO order parameters and pair correlations over the nearest atomic shells indicates that the CSRO originates from the nearest-neighbour preference towards unlike (V−Co and V−Ni) pairs and avoidance of V−V pairs. Our findings offer a way of identifying CSRO in concentrated solution alloys. We also use atomic strain mapping to demonstrate the dislocation interactions enhanced by the CSROs, clarifying the effects of these CSROs on plasticity mechanisms and mechanical properties upon deformation. Direct experimental evidence of chemical short-range atomic-scale ordering (CSRO) in a VCoNi medium-entropy alloy is provided via diffraction and electron microscopy, analysed from specific crystallographic directions.

Haemostatic materials for wound healing applications

Abstract: Wounds are one of the most common health issues, and the cost of wound care and healing has continued to increase over the past decade. The first step in wound healing is haemostasis, and the development of haemostatic materials that aid wound healing has accelerated in the past 5 years. Numerous haemostatic materials have been fabricated, composed of different active components (including natural polymers, synthetic polymers, silicon-based materials and metal-containing materials) and in various forms (including sponges, hydrogels, nanofibres and particles). In this Review, we provide an overview of haemostatic materials in wound healing, focusing on their chemical design and operation. We describe the physiological process of haemostasis to elucidate the principles that underpin the design of haemostatic wound dressings. We also highlight the advantages and limitations of the different active components and forms of haemostatic materials. The main challenges and future directions in the development of haemostatic materials for wound healing are proposed. Uncontrolled bleeding is a major cause of death, incentivizing the development of biomaterials that aid haemostasis and wound healing. This Review highlights the active components and forms of haemostatic materials, with a focus on their chemical design, and considers future trends in their development.

Frontline Science: COVID-19 infection induces readily detectable morphologic and inflammation-related phenotypic changes in peripheral blood monocytes

Abstract: Excessive monocyte/macrophage activation with the development of a cytokine storm and subsequent acute lung injury, leading to acute respiratory distress syndrome (ARDS), is a feared consequence of infection with COVID-19. The ability to recognize and potentially intervene early in those patients at greatest risk of developing this complication could be of great clinical utility. In this study, we performed flow cytometric analysis of peripheral blood samples from 34 COVID-19 patients in early 2020 in an attempt to identify factors that could help predict the severity of disease and patient outcome. Although we did not detect significant differences in the number of monocytes between patients with COVID-19 and normal healthy individuals, we did identify significant morphologic and functional differences, which are more pronounced in patients requiring prolonged hospitalization and intensive care unit (ICU) admission. Patients with COVID-19 have larger than normal monocytes, easily identified on forward scatter (FSC), side scatter analysis by routine flow cytometry, with the presence of a distinct population of monocytes with high FSC (FSC-high). On more detailed analysis, these CD14+ CD16+ , FSC-high monocytes show features of mixed M1/M2 macrophage polarization with higher expression of CD80+ and CD206+ compared with the residual FSC-low monocytes and secretion of higher levels of IL-6, IL-10, and TNF-α, when compared with the normal controls. In conclusion, the detection and serial monitoring of this subset of inflammatory monocytes using flow cytometry could be of great help in guiding the prognostication and treatment of patients with COVID-19 and merits further evaluation.

Conductive Biomaterials as Bioactive Wound Dressing for Wound Healing and Skin Tissue Engineering.

Abstract: Conductive biomaterials based on conductive polymers, carbon nanomaterials, or conductive inorganic nanomaterials demonstrate great potential in wound healing and skin tissue engineering, owing to the similar conductivity to human skin, good antioxidant and antibacterial activities, electrically controlled drug delivery, and photothermal effect. However, a review highlights the design and application of conductive biomaterials for wound healing and skin tissue engineering is lacking. In this review, the design and fabrication methods of conductive biomaterials with various structural forms including film, nanofiber, membrane, hydrogel, sponge, foam, and acellular dermal matrix for applications in wound healing and skin tissue engineering and the corresponding mechanism in promoting the healing process were summarized. The approaches that conductive biomaterials realize their great value in healing wounds via three main strategies (electrotherapy, wound dressing, and wound assessment) were reviewed. The application of conductive biomaterials as wound dressing when facing different wounds including acute wound and chronic wound (infected wound and diabetic wound) and for wound monitoring is discussed in detail. The challenges and perspectives in designing and developing multifunctional conductive biomaterials are proposed as well. Highlights: 1 The design and application of conductive biomaterials for wound healing are comprehensively reviewed, including versatile conductive agents, the various forms of conductive wound dressings, and different in vivo applications.2 Three main strategies of which conductive biomaterials realizing their applications in wound healing and skin tissue engineering are discussed.3 The challenges and perspectives in designing multifunctional conductive biomaterials and further clinical translation are proposed.

Machine Remaining Useful Life Prediction via an Attention-Based Deep Learning Approach

Abstract: For prognostics and health management of mechanical systems, a core task is to predict the machine remaining useful life (RUL). Currently, deep structures with automatic feature learning, such as long short-term memory (LSTM), have achieved great performances for the RUL prediction. However, the conventional LSTM network only uses the learned features at last time step for regression or classification, which is not efficient. Besides, some handcrafted features with domain knowledge may convey additional information for the prediction of RUL. It is thus highly motivated to integrate both those handcrafted features and automatically learned features for the RUL prediction. In this article, we propose an attention-based deep learning framework for machine's RUL prediction. The LSTM network is employed to learn sequential features from raw sensory data. Meanwhile, the proposed attention mechanism is able to learn the importance of features and time steps, and assign larger weights to more important ones. Moreover, a feature fusion framework is developed to combine the handcrafted features with automatically learned features to boost the performance of the RUL prediction. Extensive experiments have been conducted on two real datasets and experimental results demonstrate that our proposed approach outperforms the state-of-the-arts.

Global patterns of breast cancer incidence and mortality: A population-based cancer registry data analysis from 2000 to 2020

Abstract: Background Breast cancer is the most commonly diagnosed cancer and leading cause of cancer death among women worldwide but has patterns and trends which vary in different countries. This study aimed to evaluate the global patterns of breast cancer incidence and mortality and analyze its temporal trends for breast cancer prevention and control. Methods Breast cancer incidence and mortality data in 2020 were obtained from the GLOBOCAN online database. Continued data from the Cancer Incidence in Five Continents Time Trends, the International Agency for Research on cancer mortality and China National Central Cancer Registry were used to analyze the time trends from 2000 to 2015 through Joinpoint regression, and annual average percent changes of breast cancer incidence and mortality were calculated. Association between Human Development Index and breast cancer incidence and mortality were estimated by linear regression. Results There were approximately 2.3 million new breast cancer cases and 685,000 breast cancer deaths worldwide in 2020. Its incidence and mortality varied among countries, with the age-standardized incidence ranging from the highest of 112.3 per 100,000 population in Belgium to the lowest of 35.8 per 100,000 population in Iran, and the age-standardized mortality from the highest of 41.0 per 100,000 population in Fiji to the lowest of 6.4 per 100,000 population in South Korea. The peak age of breast cancer in some Asian and African countries were over 10 years earlier than in European or American countries. As for the trends of breast cancer, the age-standardized incidence rates significantly increased in China and South Korea but decreased in the United States of America (USA) during 2000-2012. Meanwhile, the age-standardized mortality rates significantly increased in China and South Korea but decreased in the United Kingdom, the USA, and Australia during 2000 and 2015. Conclusions The global burden of breast cancer is rising fast and varies greatly among countries. The incidence and mortality rates of breast cancer increased rapidly in China and South Korea but decreased in the USA. Increased health awareness, effective prevention strategies, and improved access to medical treatment are extremely important to curb the snowballing breast cancer burden, especially in the most affected countries.

Fracture, fatigue, and friction of polymers in which entanglements greatly outnumber cross-links.

Abstract: In gels and elastomers, the role of entanglements on deformation has been studied, but their effects on fracture, fatigue, and friction are less well understood. In this study, we synthesized polym...

High-performance lead-free bulk ceramics for electrical energy storage applications: design strategies and challenges

Abstract: Compared with fuel cells and electrochemical capacitors, dielectric capacitors are regarded as promising devices to store electrical energy for pulsed power systems due to their fast charge/discharge rates and ultrahigh power density. Dielectric materials are core components of dielectric capacitors and directly determine their performance. Over the past decade, extensive efforts have been devoted to develop high-performance dielectric materials for electrical energy storage applications and great progress has been achieved. Here, we present an overview on the current state-of-the-art lead-free bulk ceramics for electrical energy storage applications, including SrTiO3, CaTiO3, BaTiO3, (Bi0.5Na0.5)TiO3, (K0.5Na0.5)NbO3, BiFeO3, AgNbO3 and NaNbO3-based ceramics. This review starts with a brief introduction of the research background, the development history and the basic fundamentals of dielectric materials for energy storage applications as well as the universal strategies to optimize their energy storage performance. Emphases are placed on the design strategies for each type of dielectric ceramic based on their special physical properties with a summary of their respective advantages and disadvantages. Challenges along with future prospects are presented at the end of this review. This review will not only accelerate the exploration of higher performance lead-free dielectric materials, but also provides a deeper understanding of the relationship among chemical composition, physical properties and energy storage performance.