Showing papers by "Southwest University published in 2020"

Targeting cancer stem cell pathways for cancer therapy

Abstract: Since cancer stem cells (CSCs) were first identified in leukemia in 1994, they have been considered promising therapeutic targets for cancer therapy. These cells have self-renewal capacity and differentiation potential and contribute to multiple tumor malignancies, such as recurrence, metastasis, heterogeneity, multidrug resistance, and radiation resistance. The biological activities of CSCs are regulated by several pluripotent transcription factors, such as OCT4, Sox2, Nanog, KLF4, and MYC. In addition, many intracellular signaling pathways, such as Wnt, NF-κB (nuclear factor-κB), Notch, Hedgehog, JAK-STAT (Janus kinase/signal transducers and activators of transcription), PI3K/AKT/mTOR (phosphoinositide 3-kinase/AKT/mammalian target of rapamycin), TGF (transforming growth factor)/SMAD, and PPAR (peroxisome proliferator-activated receptor), as well as extracellular factors, such as vascular niches, hypoxia, tumor-associated macrophages, cancer-associated fibroblasts, cancer-associated mesenchymal stem cells, extracellular matrix, and exosomes, have been shown to be very important regulators of CSCs. Molecules, vaccines, antibodies, and CAR-T (chimeric antigen receptor T cell) cells have been developed to specifically target CSCs, and some of these factors are already undergoing clinical trials. This review summarizes the characterization and identification of CSCs, depicts major factors and pathways that regulate CSC development, and discusses potential targeted therapy for CSCs.

Near-Infrared Light-Triggered Nitric-Oxide-Enhanced Photodynamic Therapy and Low-Temperature Photothermal Therapy for Biofilm Elimination.

Abstract: Photothermal treatment (PTT) involving a combination of therapeutic modalities recently emerged as an efficient alternative for combating biofilm. However, PTT-related local high temperature may destroy the surrounding healthy tissues. Herein, we present an all-in-one phototherapeutic nanoplatform consisting of l-arginine (l-Arg), indocyanine green (ICG), and mesoporous polydopamine (MPDA), namely, AI-MPDA, to eliminate the already-formed biofilm. The fabrication process included surface modification of MPDA with l-Arg and further adsorption of ICG via π-π stacking. Under near-infrared (NIR) exposure, AI-MPDA not only generated heat but also produced reactive oxygen species, causing a cascade catalysis of l-Arg to release nitric oxide (NO). Under NIR irradiation, biofilm elimination was attributed to the NO-enhanced photodynamic therapy and low-temperature PTT (≤45 °C). Notably, the NIR-triggered all-in-one strategy resulted in severe destruction of bacterial membranes. The phototherapeutic AI-MPDA also displayed good cytocompatibility. NIR-irradiated AI-MPDA nanoparticles not only prevented bacterial colonization but also realized a rapid recovery of infected wounds. More importantly, the all-in-one phototherapeutic platform displayed effective biofilm elimination with an efficiency of around 100% in a abscess formation model. Overall, this low-temperature phototherapeutic platform provides a reliable tool for combating already-formed biofilms in clinical applications.

Transition‐Metal Phosphides: Activity Origin, Energy‐Related Electrocatalysis Applications, and Synthetic Strategies

Abstract: Developing highly efficient and stable electrocatalysts plays an important role in energy‐related electrocatalysis fields. Transition‐metal phosphides (TMPs) possess a series of advantages, such as high conductivity, earth‐abundance reserves, and good physicochemical properties, therefore arousing wide attention. In this review, the electrochemical activity origin of TMPs, allowing the rational design and construction of phosphides toward various energy‐relevant reactions is first discussed. Subsequently, their unique energy‐related electrocatalysis nature toward hydrogen evolution reaction (HER), oxygen evolution reaction (OER), oxygen reduction reaction (ORR), hydrogen oxidation reaction (HOR), carbon dioxide reduction reaction (CO2RR), nitrogen reduction reaction (NRR), urea oxidation reaction (UOR), methanol oxidation reaction (MOR), and others is highlighted. Then, the TMPs’ synthetic strategies are analyzed and summarized systematically. Finally, the existing key issues, countermeasures, and the future challenges of TMPs toward efficient energy‐related electrocatalysis are briefly discussed.

Mapping essential urban land use categories in China (EULUC-China): preliminary results for 2018

Abstract: Land use reflects human activities on land. Urban land use is the highest level human alteration on Earth, and it is rapidly changing due to population increase and urbanization. Urban areas have widespread effects on local hydrology, climate, biodiversity, and food production. However, maps, that contain knowledge on the distribution, pattern and composition of various land use types in urban areas, are limited to city level. The mapping standard on data sources, methods, land use classification schemes varies from city to city, due to differences in financial input and skills of mapping personnel. To address various national and global environmental challenges caused by urbanization, it is important to have urban land uses at the national and global scales that are derived from the same or consistent data sources with the same or compatible classification systems and mapping methods. This is because, only with urban land use maps produced with similar criteria, consistent environmental policies can be made, and action efforts can be compared and assessed for large scale environmental administration. However, despite of the fact that a number of urban-extent maps exist at global scales [3,4], more detailed urban land use maps do not exist at the same scale. Even at big country or regional levels such as for the United States, China and European Union, consistent land use mapping efforts are rare.

Dopant-Free Organic Hole-Transporting Material for Efficient and Stable Inverted All-Inorganic and Hybrid Perovskite Solar Cells.

Abstract: Designing new hole-transporting materials (HTMs) with desired chemical, electrical, and electronic properties is critical to realize efficient and stable inverted perovskite solar cells (PVSCs) with a p-i-n structure. Herein, the synthesis of a novel 3D small molecule named TPE-S and its application as an HTM in PVSCs are shown. The all-inorganic inverted PVSCs made using TPE-S, processed without any dopant or post-treatment, are highly efficient and stable. Compared to control devices based on the commonly used HTM, PEDOT:PSS, devices based on TPE-S exhibit improved optoelectronic properties, more favorable interfacial energetics, and reduced recombination due to an improved trap passivation effect. As a result, the all-inorganic CsPbI2 Br PVSCs based on TPE-S demonstrate a remarkable efficiency of 15.4% along with excellent stability, which is the one of the highest reported values for inverted all-inorganic PVSCs. Meanwhile, the TPE-S layer can also be generally used to improve the performance of organic/inorganic hybrid inverted PVSCs, which show an outstanding power conversation efficiency of 21.0%, approaching the highest reported efficiency for inverted PVSCs. This work highlights the great potential of TPE-S as a simple and general dopant-free HTM for different types of high-performance PVSCs.

A Janus Fe‑SnO 2 Catalyst that Enables Bifunctional Electrochemical Nitrogen Fixation

Abstract: Electrochemical N2 reduction reactions (NRR) and the N2 oxidation reaction (NOR), using H2 O and N2 , are a sustainable approach to N2 fixation. To date, owing to the chemical inertness of nitrogen, emerging electrocatalysts for the electrochemical NRR and NOR at room temperature and atmospheric pressure remain largely underexplored. Herein, a new-type Fe-SnO2 was designed as a Janus electrocatalyst for achieving highly efficient NRR and NOR catalysis. A high NH3 yield of 82.7 μg h-1 mgcat. -1 and a Faraday efficiency (FE) of 20.4 % were obtained for NRR. This catalyst can also serve as an excellent NOR electrocatalyst with a NO3 - yields of 42.9 μg h-1 mgcat. -1 and a FE of 0.84 %. By means of experiments and DFT calculations, it is revealed that the oxygen vacancy-anchored single-atom Fe can effectively adsorb and activate chemical inert N2 molecules, lowering the energy barrier for the vital breakage of N≡N and resulting in the enhanced N2 fixation performance.

Diagnosis of Acute Respiratory Syndrome Coronavirus 2 Infection by Detection of Nucleocapsid Protein

Abstract: BACKGROUND Nucleic acid test and antibody assay have been employed in the diagnosis for SARS-CoV-2 infection, but the use of viral antigen for diagnosis has not been successfully developed. Theoretically, viral antigen is the specific marker of the virus and precedes antibody appearance within the infected population. There is a clear need of detection of viral antigen for rapid and early diagnosis. METHODS We included a cohort of 239 participants with suspected SARS-CoV-2 infection from 7 centers for the study. We measured nucleocapsid protein in nasopharyngeal swab samples in parallel with the nucleic acid test. Nucleic acid test was taken as the reference standard, and statistical evaluation was taken in blind. We detected nucleocapsid protein in 20 urine samples in another center, employing nasopharyngeal swab nucleic acid test as reference standard. RESULTS We developed a fluorescence immunochromatographic assay for detecting nucleocapsid protein of SARS-CoV-2 in nasopharyngeal swab sample and urine within 10 minutes. 100% of nucleocapsid protein positive and negative participants accord with nucleic acid test for same samples. Further, earliest participant after 3 days of fever can be identified by the method. In an additional preliminary study, we detected nucleocapsid protein in urine in 73.6% of diagnosed COVID-19 patients. CONCLUSIONS Those findings indicate that nucleocapsid protein assay is an accurate, rapid, early and simple method for diagnosis of COVID-19. Appearance of nucleocapsid protein in urine coincides our finding of the SARS-CoV-2 invading kidney and might be of diagnostic value.

EFMCDM: Evidential Fuzzy Multicriteria Decision Making Based on Belief Entropy

Abstract: Multicriteria decision making (MCDM) has become one of the most frequently applied decision making methodologies in various fields. However, uncertainty is inevitably involved in the process of MCDM due to the subjectivity of humans. To address this issue, a novel evidential fuzzy MCDM method, called EFMCDM, is proposed by integrating Dempster–Shafer theory with belief entropy. In particular, each criterion can be modeled as evidence, and all the alternatives compose the frame of discernment in the framework of Dempster–Shafer theory. To generate more appropriate basic probability assignments (BPAs) of the criteria, the EFMCDM method considers both the subjective and objective weighting of the criteria that are leveraged in MCDM problems. Thereafter, the classic Dempster's rule of combination is leveraged to fuse the multiple pieces of evidence into composite evidence. On this basis, the alternatives are ranked to determine the optimal alternative. In addition, the EFMCDM method can quantitatively model uncertainty and help to decrease the uncertainty caused by subjective human cognition to improve decision making. Finally, the rationality, effectiveness, and robustness of the EFMCDM method are demonstrated through experimental evaluations.

Size-controllable Fe-N/C single-atom nanozyme with exceptional oxidase-like activity for sensitive detection of alkaline phosphatase

Abstract: Nanozymes become currently a frontier of chemical research. However, exploiting a novel nanozyme with high activity, good stability and reproducibility is challenging. Here, size-controllable Fe-N/C nanozymes containing exclusive single Fe atoms coordinated Fe-Nx sites were succesfully prepared through a facile pyrolysis of size controllable Fe-Zn ZIFs precursors. The Fe-N/C nanozymes exhibit exceptional high oxidase-mimicking activity able to catalyze oxidation of colorless 3,3′,5,5′-tetramethylbenzidine (TMB) by dissolved oxygen to generate blue product. Their catalytic activities can be regulated by modulating the molar ratios of methanol to metal salts (e.g., Fe and Zn) through which the size controllable Fe-Zn ZIFs precursors are obtained. Upon introduction of ascorbic acid (AA) into Fe-N/C/TMB system, complete inhibition of TMB oxidation was observed, resulting in significant decline in absorbance with a clear color change. In the presence of alkaline phosphatase (ALP), ascorbic acid 2-phosphate (AAP) is hydrolyzed to produce AA. When coupled with AAP, a novel colorimetric biosensor platform was fabricated for ALP activity screening in the range of 0.05 U/L-100 U/L (four orders of magnitude) with an ultra-low limit of detection of 0.02 U/L. The work provides a promising strategy to rationally design the transition metal-N/C single-atom nanozyme with high oxidase-like activity.

Patterns of IgG and IgM antibody response in COVID-19 patients.

Abstract: Coronavirus disease 2019 (COVID-19), which emerged in Wuhan, China in December 2019, is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and has become a major global public h...

Completion Time and Energy Optimization in the UAV-Enabled Mobile-Edge Computing System

Abstract: Completion time and energy consumption of the unmanned aerial vehicle (UAV) are two important design aspects in UAV-enabled applications. In this article, we consider a UAV-enabled mobile-edge computing (MEC) system for Internet-of-Things (IoT) computation offloading with limited or no common cloud/edge infrastructure. We study the joint design of computation offloading and resource allocation, as well as UAV trajectory for minimization of energy consumption and completion time of the UAV, subject to the IoT devices’ task and energy budget constraints. We first consider the UAV energy minimization problem without predetermined completion time, a discretized nonconvex equivalent problem is obtained by using the path discretization technique. An efficient alternating optimization algorithm for the discretized problem is proposed by decoupling it into two subproblems and addressing the two subproblems with successive convex approximation (SCA)-based algorithms iteratively. Subsequently, we focus on the completion time minimization problem, which is nonconvex and challenging to solve. By using the same path discretization approximation model to reformulate problem, a similar alternating optimization algorithm is proposed. Furthermore, we study the Pareto-optimal solution that balances the tradeoff between the UAV energy and completion time. The simulation results are provided to corroborate this article and show that the proposed designs outperform the baseline schemes. Our results unveil the tradeoff between completion time and energy consumption of the UAV for the MEC system, and the proposed solution can provide the performance close to the lower bound.

Microplastics in the agroecosystem: Are they an emerging threat to the plant-soil system?

Abstract: Despite plastics providing great benefits to our daily life, plastics accumulating in the environment, especially microplastics (MPs; defined as particles

Regulating Electron Density of NiFe-P nanosheets Electrocatalysts by a trifle of Ru for High-efficient Overall Water Splitting

Abstract: Highly active and stable catalysts toward hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) is extremely important but challenging for overall water splitting. Herein, a strategy by modulating surface electron densities is adopted to design new catalyst: the Ru-NiFe-P nanosheets on 3D self-supported nickel foam was developed by doping a small quantity of Ru into transition metals phosphates. The designed catalyst displays excellent electrocatalytic performance in 1.0 M KOH, with low overpotentials of 44 mV at 10 mA cm−2 for HER and 242 mV at 100 mA cm−2 for OER. Particularly, it only needs 1.47 V to yield 10 mA cm−2 for overall water splitting. Density functional theory calculations reveal that Ru-incorporated NiFe-P can generate new active sites on Ru atoms and increase the catalytic activity of original P sites leading to an optimal Gibbs free-energy on catalysts surface. This work offers a new perspective for designing admirable electrocatalysts.

Epilepsy Seizure Prediction on EEG Using Common Spatial Pattern and Convolutional Neural Network

Abstract: Epilepsy seizure prediction paves the way of timely warning for patients to take more active and effective intervention measures. Compared to seizure detection that only identifies the inter-ictal state and the ictal state, far fewer researches have been conducted on seizure prediction because the high similarity makes it challenging to distinguish between the pre-ictal state and the inter-ictal state. In this paper, a novel solution on seizure prediction is proposed using common spatial pattern (CSP) and convolutional neural network (CNN). Firstly, artificial pre-ictal EEG signals based on the original ones are generated by combining the segmented pre-ictal signals to solve the trial imbalance problem between the two states. Secondly, a feature extractor employing wavelet packet decomposition and CSP is designed to extract the distinguishing features in both the time domain and the frequency domain. It can improve overall accuracy while reducing the training time. Finally, a shallow CNN is applied to discriminate between the pre-ictal state and the inter-ictal state. Our proposed solution is evaluated on 23 patients’ data from Boston Children's Hospital-MIT scalp EEG dataset by employing a leave-one-out cross-validation, and it achieves a sensitivity of 92.2% and false prediction rate of 0.12/h. Experimental result demonstrates that the proposed approach outperforms most state-of-the-art methods.

Recent advances on cellulose nanocrystals for Pickering emulsions: Development and challenge

Abstract: Background Pickering emulsions stabilized by solid particles have captured a growing interest recently due to their outstanding stability. Among various solid stabilizers, cellulose nanocrystals (CNCs) mainly from agricultural and forestry wastes have emerged as promising materials in Pickering emulsions application due to their favorable properties such as nanostructure, high aspect ratio, biocompatibility, amphiphilicity, low toxicity, and renewability. Scope and approach In this review, the source and extraction methods of CNCs are summarized briefly. Then, the recent advances in CNCs stabilized Pickering emulsions are highlighted, including the factors affecting the emulsification performance of CNCs itself and the synergistic effect induced by other substances. Furthermore, the food-related research, safety issue and the promising research trends of CNCs stabilized Pickering emulsions are also outlined. Key findings and conclusions The properties of CNCs mainly depend on the cellulose sources and extraction processes. The morphology, surface charge, wettability and crystalline allomorph of CNCs can influence emulsifying ability as Pickering stabilizers. The synergistic effect induced by other substances (i.e. polysaccharide, protein, polyphenol, lignin, surfactant, and inorganic particle) increases potential of CNCs in Pickering emulsions application. The food-related research of CNCs stabilized Pickering emulsions currently focuses on delivering bioactive compounds, improving stability and controlling lipid digestion. Future studies could devote more efforts to effective and green extraction of CNCs, revealing stabilization mechanism in a multicomponent system and developing functional applications of CNCs-based Pickering emulsions. In addition, the safety assessment involving CNCs and their stabilized emulsions deserves more attention for food-related applications.

Plastic pollution in croplands threatens long-term food security

Abstract: Plastic pollution is a global concern given its prevalence in aquatic and terrestrial ecosystems. Studies have been conducted on the distribution and impact of plastic pollution in marine ecosystems, but little is known on terrestrial ecosystems. Plastic mulch has been widely used to increase crop yields worldwide, yet the impact of plastic residues in cropland soils to soil health and crop production in the long term remained unclear. In this paper, using a global meta-analysis, we found that the use of plastic mulch can indeed increase crop yields on average by 25%-42% in the immediate season due to the increase of soil temperature (+8%) and moisture (+17%). However, the unabated accumulation of film residues in the field negatively impacts its physicochemical properties linked to healthy soil and threatens food production in the long term. It has multiple negative impacts on plant growth including crop yield (at the mean rate of -3% for every additional 100 kg/ha of film residue), plant height (-2%) and root weight (-5%), and soil properties including soil water evaporation capacity (-2%), soil water infiltration rate (-8%), soil organic matter (-0.8%) and soil available phosphorus (-5%) based on meta-regression. Using a nationwide field survey of China, the largest user of plastic mulch worldwide, we found that plastic residue accumulation in cropland soils has reached 550,800 tonnes, with an estimated 6%-10% reduction in cotton yield in some polluted sites based on current level of plastic residue content. Immediate actions should be taken to ensure the recovery of plastic film mulch and limit further increase in film residue loading to maintain the sustainability of these croplands.

Generalization of Dempster–Shafer theory: A complex mass function

Abstract: Dempster–Shafer evidence theory has been widely used in various fields of applications, because of the flexibility and effectiveness in modeling uncertainties without prior information. However, the existing evidence theory is insufficient to consider the situations where it has no capability to express the fluctuations of data at a given phase of time during their execution, and the uncertainty and imprecision which are inevitably involved in the data occur concurrently with changes to the phase or periodicity of the data. In this paper, therefore, a generalized Dempster–Shafer evidence theory is proposed. To be specific, a mass function in the generalized Dempster–Shafer evidence theory is modeled by a complex number, called as a complex basic belief assignment, which has more powerful ability to express uncertain information. Based on that, a generalized Dempster’s combination rule is exploited. In contrast to the classical Dempster’s combination rule, the condition in terms of the conflict coefficient between the evidences is released in the generalized Dempster’s combination rule. Hence, it is more general and applicable than the classical Dempster’s combination rule. When the complex mass function is degenerated from complex numbers to real numbers, the generalized Dempster’s combination rule degenerates to the classical evidence theory under the condition that the conflict coefficient between the evidences is less than 1. In a word, this generalized Dempster–Shafer evidence theory provides a promising way to model and handle more uncertain information. Thanks to this advantage, an algorithm for decision-making is devised based on the generalized Dempster–Shafer evidence theory. Finally, an application in a medical diagnosis illustrates the efficiency and practicability of the proposed algorithm.

Rolling Circular Amplification (RCA)-Assisted CRISPR/Cas9 Cleavage (RACE) for Highly Specific Detection of Multiple Extracellular Vesicle MicroRNAs

Abstract: Multiplexed detection of extracellular vesicle (EV)-derived microRNAs (miRNAs) plays a critical role in facilitating disease diagnosis and prognosis evaluation. Herein, we developed a highly specific nucleic acid detection platform for simultaneous quantification of several EV-derived miRNAs in constant temperature by integrating the advantages of a clustered regularly interspaced short palindromic repeats/CRISPR associated nucleases (CRISPR/Cas) system and rolling circular amplification (RCA) techniques. Particularly, the proposed approach demonstrated single-base resolution attributed to the dual-specific recognition from both padlock probe-mediated ligation and protospacer adjacent motif (PAM)-triggered cleavage. The high consistency between the proposed approach RCA-assisted CRISPR/Cas9 cleavage (RACE) and reverse transcription quantitative polymerase chain reaction (RT-qPCR) in detecting EV-derived miRNAs' abundance from both cultured cancer cells and clinical lung cancer patients validated its robustness, revealing its potentials in the screening, diagnosis, and prognosis of various diseases. In summary, RACE is a powerful tool for multiplexed, specific detection of nucleic acids in point-of-care diagnostics and field-deployable analysis.