Rechargeable sodium‐ion batteries (SIBs) are considered attractive alternatives to lithium‐ion batteries for next‐generation sustainable and large‐scale electrochemical energy storage. Organic ...sodium‐ion batteries (OSIBs) using environmentally benign organic materials as electrodes, which demonstrate high energy/power density and good structural designability, have recently attracted great attention. Nevertheless, the practical applications and popularization of OSIBs are generally restricted by the intrinsic disadvantages related to organic electrodes, such as their low conductivity, poor stability, and high solubility in electrolytes. Here, the latest research progress with regard to electrode materials of OSIBs, ranging from small molecules to organic polymers, is systematically reviewed, with the main focus on the molecular structure design/modification, the electrochemical behavior, and the corresponding charge‐storage mechanism. Particularly, the challenges faced by OSIBs and the effective design strategies are comprehensively summarized from three aspects: function‐oriented molecular design, micromorphology regulation, and construction of organic–inorganic composites. Finally, the perspectives and opportunities in the research of organic electrode materials are discussed.
This paper comprehensively reviews the recent progress in the research and development of organic electrode materials for organic sodium‐ion batteries with an emphasis on the material design/synthesis/characterization and electrochemical reaction mechanisms to obtain a fundamental understanding of organic cathode materials and their performance. Several strategies to improve the electrochemical performance are summarized and discussed.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Absorbers with lightweight, low filler loading and broad absorption band are highly desirable for electromagnetic wave absorption field. Here, hollow Co1–xS microspheres constructed by nanosheets are ...fabricated via a facile synthetic method based on hydrothermal route. As an efficient wave absorber, the Co1–xS hollow spheres demonstrate excellent microwave absorption performance. With a weight content of only 3 wt%, the maximum reflection loss (RL) can reach as strong as −46.1 dB at 13.92 GHz and its qualified frequency bandwidth (with RL value over −10 dB) remarkably achieves 5.6 GHz, covering 35% of the entire measured bandwidth. In addition, compared with other cobalt sulfides (such as CoS2 and Co9S8), the Co1–xS microspheres with hollow structure exhibit more superior absorption intensity and broader qualified bandwidth. Therefore, this work provides a promising approach for the design and synthesis of hollow Co1–xS microspheres with lightweight and high‐performance microwave absorption.
The hollow Co1–xS microspheres with understanding microwave absorption performance are successfully fabricated through a facile hydrothermal route. The RLmax can reach to −46.1 dB at 13.92 GHz with an ultralow filler loading (3 wt%) and the effective frequency bandwidth is up to 5.6 GHz. Moreover, the possible wave absorption mechanism is also depicted comprehensively in this article.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Accumulating clinical researches have shown that specific microbes with abnormal levels are closely associated with the development of various human diseases. Knowledge of microbe-disease ...associations can provide valuable insights for complex disease mechanism understanding as well as the prevention, diagnosis and treatment of various diseases. However, little effort has been made to predict microbial candidates for human complex diseases on a large scale.
In this work, we developed a new computational model for predicting microbe-disease associations by combining two single recommendation methods. Based on the assumption that functionally similar microbes tend to get involved in the mechanism of similar disease, we adopted neighbor-based collaborative filtering and a graph-based scoring method to compute association possibility of microbe-disease pairs. The promising prediction performance could be attributed to the use of hybrid approach based on two single recommendation methods as well as the introduction of Gaussian kernel-based similarity and symptom-based disease similarity.
To evaluate the performance of the proposed model, we implemented leave-one-out and fivefold cross validations on the HMDAD database, which is recently built as the first database collecting experimentally-confirmed microbe-disease associations. As a result, NGRHMDA achieved reliable results with AUCs of 0.9023 ± 0.0031 and 0.9111 in the validation frameworks of fivefold CV and LOOCV. In addition, 78.2% microbe samples and 66.7% disease samples are found to be consistent with the basic assumption of our work that microbes tend to get involved in the similar disease clusters, and vice versa.
Compared with other methods, the prediction results yielded by NGRHMDA demonstrate its effective prediction performance for microbe-disease associations. It is anticipated that NGRHMDA can be used as a useful tool to search the most potential microbial candidates for various diseases, and therefore boosts the medical knowledge and drug development. The codes and dataset of our work can be downloaded from https://github.com/yahuang1991/NGRHMDA .
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Results from various studies reveal that the role of G protein‐coupled oestrogen receptor (GPER) is cancer‐context dependent, and the function of GPER in non–small‐cell lung cancer (NSCLC) is still ...unclear. The present study demonstrated that neoplasm lung tissues expressed higher level of GPER compared with the normal lung tissues. The clinical data also showed that GPER expression level was positively correlated with the tumour stage of NSCLC. Our experimental data confirmed that GPER played an oncogenic role to promote cell growth of NSCLC cells. Mechanistic dissection revealed that GPER could modulate the NOTCH1 pathway to regulate cell growth in NSCLC cells. Further exploration of the mechanism demonstrated that GPER could up‐regulate circNOTCH1, which could compete with NOTCH1 mRNA for METTL14 binding. Because of the lack of m6A modification by METTL14 on the NOTCH1 mRNA, NOTCH1 mRNA was more stable and much easier to undergo protein translation. Subsequently, we found that GPER could prevent YAP1 phosphorylation and promote YAP1‐TEAD's transcriptional regulation on QKI, a transacting RNA‐binding factor involved in circRNA biogenesis, to facilitate circNOTCH1 generation. Supportively, data from preclinical mice model with implantation of H1299 cells also demonstrated that knock‐down of circNOTCH1 could block GPER‐induced NOTCH1 to suppress NSCLC tumour growth. Together, our data showed that GPER could promote NSCLC cell growth via regulating the YAP1/QKI/circNOTCH1/m6A methylated NOTCH1 pathway, and targeting our identified molecules may be a potentially therapeutic approach to suppress NSCLC development.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Surface-enhanced Raman spectroscopy (SERS) sensing of DNA bases by plasmonic nanopores could pave a way to novel methods for DNA analyses and new generation single-molecule sequencing platforms. The ...SERS discrimination of single DNA bases depends critically on the time that a DNA strand resides within the plasmonic hot spot. In fact, DNA molecules flow through the nanopores so rapidly that the SERS signals collected are not sufficient for single-molecule analysis. Here, we report an approach to control the residence time of molecules in the hot spot by an electro-plasmonic trapping effect. By directly adsorbing molecules onto a gold nanoparticle and then trapping the single nanoparticle in a plasmonic nanohole up to several minutes, we demonstrate single-molecule SERS detection of all four DNA bases as well as discrimination of single nucleobases in a single oligonucleotide. Our method can be extended easily to label-free sensing of single-molecule amino acids and proteins.
Current knowledge and data on miRNA-lncRNA interactions is still limited and little effort has been made to predict target lncRNAs of miRNAs. Accumulating evidences suggest that the interaction ...patterns between lncRNAs and miRNAs are closely related to relative expression level, forming a titration mechanism. It could provide an effective approach for characteristic feature extraction. In addition, using the coding non-coding co-expression network and sequence data could also help to measure the similarities among miRNAs and lncRNAs. By mathematically analyzing these types of similarities, we come up with two findings that (i) lncRNAs/miRNAs tend to collaboratively interact with miRNAs/lncRNAs of similar expression profiles, and vice versa, and (ii) those miRNAs interacting with a cluster of common target genes tend to jointly target at the common lncRNAs.
In this work, we developed a novel group preference Bayesian collaborative filtering model called GBCF for picking up a top-k probability ranking list for an individual miRNA or lncRNA based on the known miRNA-lncRNA interaction network.
To evaluate the effectiveness of GBCF, leave-one-out and k-fold cross validations as well as a series of comparison experiments were carried out. GBCF achieved the values of area under ROC curve of 0.9193, 0.8354+/- 0.0079, 0.8615+/- 0.0078, and 0.8928+/- 0.0082 based on leave-one-out, 2-fold, 5-fold, and 10-fold cross validations respectively, demonstrating its reliability and robustness.
GBCF could be used to select potential lncRNA targets of specific miRNAs and offer great insights for further researches on ceRNA regulation network.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
An efficient and reconfigurable rectifier circuit, with the capability of automatically switching from low-power to high-power operation mode, is presented in this paper. The new topology allows the ...rectifier to convert RF power to dc power efficiently over an extended input power range. The circuit consists of diodes as rectifying elements and of n-channel field effect transistor in a depletion mode acting as the automated switch. Without using an external dc source, the circuit directly uses the rectified output dc voltage to bias the transistor, allowing high conversion efficiency over a wide input power range. This results in a compact and self-contained circuit. A total of two prototypes optimized for near-field and far-field wireless power transfer systems are fabricated and the measured results show that the performance exceeds that of the conventional rectifier circuit, which can only stay efficient over a limited range of the input power. The proposed design can maintain more than 50% of conversion efficiency over more than 25-dB range of the input power, with peak efficiency of 88% and 80% for near-field and far-field rectifiers, respectively. A system-level validation also confirms the improvement of the proposed rectifier design.
Hard carbons, as one of the most commercializable anode materials for sodium‐ion batteries (SIBs), have to deal with the trade‐off between the rate capability and specific capacity or initial ...Columbic efficiency (ICE), and the fast performance decline at low temperature (LT) remains poorly understood. Here, a comprehensive regulation on the interfacial/bulk electrochemistry of hard carbons through atomic Zn doping is reported, which demonstrates a record‐high reversible capacity (546 mAh g−1), decent ICE (84%), remarkable rate capability (140 mAh g−1 @ 50 A g−1), and excellent LT capacity (443 mAh g−1 @ −40 °C), outperforming the state‐of‐the‐art literature. This work reveals that the Zn doping can generally induce a local electric field to enable fast bulk Na+ transportation, and meanwhile catalyze the decomposition of NaPF6 to form a robust inorganic‐rich solid‐electrolyte interphase, which elaborates the underlying origin of the boosted electrochemical performance. Importantly, distinguished from room temperature, the intrinsic Na+ migration/desolvation ability of the electrolyte is disclosed to be the crucial rate‐determining factors for the SIB performance at LT. This work provides a fundamental understanding on the charge‐storage kinetics at varied temperatures.
A novel Zn single‐atom‐regulated hard carbon with unprecedented sodium‐storage performance is reported. The Zn doping can induce a local electric field to enable the fast bulk Na+ transportation and meanwhile catalyze the decomposition of NaPF6 to form a robust inorganic‐rich solid‐electrolyte interphase and fast interfacial Na+ storage kinetics, both of which contribute to the boosted electrochemical performance.
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BFBNIB, FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
The interaction of miRNA and lncRNA is known to be important for gene regulations. However, the number of known lncRNA-miRNA interactions is still very limited and there are limited computational ...tools available for predicting new ones. Considering that lncRNAs and miRNAs share internal patterns in the partnership between each other, the underlying lncRNA-miRNA interactions could be predicted by utilizing the known ones, which could be considered as a semi-supervised learning problem. It is shown that the attributes of lncRNA and miRNA have a close relationship with the interaction between each other. Effective use of side information could be helpful for improving the performance especially when the training samples are limited. In view of this, we proposed an end-to-end prediction model called GCLMI (Graph Convolution for novel lncRNA-miRNA Interactions) by combining the techniques of graph convolution and auto-encoder. Without any preprocessing process on the feature information, our method can incorporate raw data of node attributes with the topology of the interaction network. Based on a real dataset collected from a public database, the results of experiments conducted on k-fold cross validations illustrate the robustness and effectiveness of the prediction performance of the proposed prediction model. We prove the graph convolution layer as designed in the proposed model able to effectively integrate the input data by filtering the graph with node features. The proposed model is anticipated to yield highly potential lncRNA-miRNA interactions in the scenario that different types of numerical features describing lncRNA or miRNA are provided by users, serving as a useful computational tool.
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