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Human diseases, especially infectious ones, have been evolving constantly. However, their treatment strategies are not developing quickly. Some diseases are caused by a variety of factors with very complex pathologies, and the use of a single drug cannot solve these problems. Traditional Chinese Medicine (TCM) medication is a unique treatment method in China. TCM formulae contain multiple herbs with multitarget, multichannel, and multilink characteristics. In recent years, with the flourishing development of network pharmacology, a new method for searching therapeutic drugs has emerged. The multitarget action in network pharmacology is consistent with the complex mechanisms of disease and drug action. Using network pharmacology to understand TCM is an emerging trend.

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BackgroundMicroRNAs (miRNAs) are short, non-coding RNAs that regulate the expression of multiple target genes. Deregulation of miRNAs is common in human tumorigenesis. Low level expression of miR-26b has been found in glioma cells. However, its underlying mechanism of action has not been determined.Methodology/Principal FindingsReal-time PCR was employed to measure the expression level of miR-26b in glioma patients and cells. The level of miR-26b was inversely correlated with the grade of glioma. Ectopic expression of miR-26b inhibited the proliferation, migration and invasion of human glioma cells. A binding site for miR-26b was identified in the 3′UTR of EphA2. Over-expression of miR-26b in glioma cells repressed the endogenous level of EphA2 protein. Vasculogenic mimicry (VM) experiments were performed to further confirm the effects of miR-26b on the regulation of EphA2, and the results showed that miR-26b inhibited the VM processes which regulated by EphA2.SignificanceThis study demonstrated that miR-26b may act as a tumor suppressor in glioma and it directly regulates EphA2 expression. EphA2 is a direct target of miR-26b, and the down-regulation of EphA2 mediated by miR-26b is dependent on the binding of miR-26b to a specific response element of microRNA in the 3′UTR region of EphA2 mRNA.

Hydrogel bioelectronics that can interface biological tissues and flexible electronics is at the core of the growing field of healthcare monitoring, smart drug systems, and wearable and implantable devices. Here, a simple strategy is demonstrated to prototype all‐hydrogel bioelectronics with embedded arbitrary conductive networks using tough hydrogels and liquid metal. Due to their excellent stretchability, the resultant all‐hydrogel bioelectronics exhibits stable electrochemical properties at large tensile stretch and various modes of deformation. The potential of fabricated all‐hydrogel bioelectronics is demonstrated as wearable strain sensors, cardiac patches, and near‐field communication (NFC) devices for monitoring various physiological conditions wirelessly. The presented simple platform paves the way of implantable hydrogel electronics for Internet‐of‐Things and tissue–machine interfacing applications.

Cross-lingual transfer, where a high-resource transfer language is used to improve the accuracy of a low-resource task language, is now an invaluable tool for improving performance of natural language processing (NLP) on lowresource languages. However, given a particular task language, it is not clear which language to transfer from, and the standard strategy is to select languages based on ad hoc criteria, usually the intuition of the experimenter. Since a large number of features contribute to the success of cross-lingual transfer (including phylogenetic similarity, typological properties, lexical overlap, or size of available data), even the most enlightened experimenter rarely considers all these factors for the particular task at hand. In this paper, we consider this task of automatically selecting optimal transfer languages as a ranking problem, and build models that consider the aforementioned features to perform this prediction. In experiments on representative NLP tasks, we demonstrate that our model predicts good transfer languages much better than ad hoc baselines considering single features in isolation, and glean insights on what features are most informative for each different NLP tasks, which may inform future ad hoc selection even without use of our method. 1 * Equal contribution 1 Code, data, and pre-trained models are available at

This paper focuses on a comparative study of the modeling and simulation of the first CIGRÉ HVDC benchmark system using two simulation tools PSCAD/EMTDC and PSB/SIMULINK; an interface between them (PSCAD-SIMULINK) has also been implemented and used as a simulator. The CIGRÉ HVDC system and its controller has been carefully modeled in all three simulation environments so that the differences are minimal. Comparison of steady-state and transient situations have been carried out, and a high degree of agreement in most of the cases has been observed.

A review for optical fiber hydrogen sensors based on palladium (Pd) and tungsten oxide (WO 3) thin films is presented, with specific focus on the measurement methods, probe structures, and sensing properties of different sensors. Firstly, the theoretical models behind the optical fiber hydrogen sensors, as well as their practical limitations, are addressed. Secondly, four mainstream measurement methods, including intensity, fiber Bragg grating (FBG), interferometer, surface plasmon resonance (SPR), which have been proposed to sense the physicochemical properties variations of sensitive thin films when exposed to hydrogen, are reviewed. Then, the advantages and disadvantages of all the above measurement methods are also discussed and compared. Finally, the existing problems and future prospects of optical fiber hydrogen sensors are pointed out.