Heterogeneous network embedding enabling accurate disease association predictions.

BackgroundIt is significant to identificate complex biological mechanisms of various diseases in biomedical research. Recently, the growing generation of tremendous amount of data in genomics, epigenomics, metagenomics, proteomics, metabolomics, nutriomics, etc., has resulted in the rise of systematic biological means of exploring complex diseases. However, the disparity between the production of the multiple data and our capability of analyzing data has been broaden gradually. Furthermore, we observe that networks can represent many of the above-mentioned data, and founded on the vector representations learned by network embedding methods, entities which are in close proximity but at present do not actually possess direct links are very likely to be related, therefore they are promising candidate subjects for biological investigation.ResultsWe incorporate six public biological databases to construct a heterogeneous biological network containing three categories of entities (i.e., genes, diseases, miRNAs) and multiple types of edges (i.e., the known relationships). To tackle the inherent heterogeneity, we develop a heterogeneous network embedding model for mapping the network into a low dimensional vector space in which the relationships between entities are preserved well. And in order to assess the effectiveness of our method, we conduct gene-disease as well as miRNA-disease associations predictions, results of which show the superiority of our novel method over several state-of-the-arts. Furthermore, many associations predicted by our method are verified in the latest real-world dataset.ConclusionsWe propose a novel heterogeneous network embedding method which can adequately take advantage of the abundant contextual information and structures of heterogeneous network. Moreover, we illustrate the performance of the proposed method on directing studies in biology, which can assist in identifying new hypotheses in biological investigation

Challenges and recent advancements of functionalization of two-dimensional nanostructured molybdenum trioxide and dichalcogenides

Atomically-thin two-dimensional (2D) semiconductors are the thinnest functional semiconducting materials available today. Among them, both molybdenum trioxide and chalcogenides (MT&Ds) represent key components within the family of the different 2D semiconductors for various electronic, optoelectronic and electrochemical applications due to their unique electronic, optical, mechanical and electrochemical properties. However, despite great progress in research dedicated to the development and fabrication of 2D MT&Ds observed within the last decade, there are significant challenges affected their charge transport behavior, fabrication on a large scale as well as high dependence of the carrier mobility on thickness. In this article, we review the recent progress on the carrier mobility engineering of 2D MT&Ds and elaborate devised strategies dedicated to the optimization of MT&Ds properties. Specifically, the latest physical and chemical methods towards the surface functionalization and optimization of the major factors influencing the extrinsic transport at the electrode-2D semiconductor interface are discusse

Heteroatom Doped High Porosity Carbon Nanomaterials as Electrodes for Energy Storage in Electrochemical Capacitors: A Review

At present it is indispensable to develop and implement new/state-of-the-art carbon nanomaterials as electrodes in electrochemical capacitors, since conventional activated carbon based supercapacitor cells cannot fulfil the growing demand of high energy and power densities of electronic devices of the present era, as a result of the rapid developments in this field. Functionalized carbon nanomaterials symbolize the type of materials with huge potential for their use in energy related applications in general and as an electrode active material for electrochemical capacitors in particular. Nitrogen doping of carbons has shown promising results in the field of energy storage in electrochemical capacitors, gaining attention of researchers to evaluate the performance of new heteroatoms functionalised materials such as sulphur, phosphorus and boron lately. Literature is widely available on nitrogen doped materials research for energy storage applications; however, there has been a limited number of review works on other functional materials beyond nitrogen. This review article thus aims to provide important insights and an up-to-date analysis of the most recent developments, the directions of future research, and the techniques used for the synthesis of these functional materials. A critical review of the electrochemical performance including specific capacitance and energy/power densities is made, when these single doped or co-doped active materials are used as electrodes in electrochemical capacitors

Graphene-Based Nanocomposites for Energy Storage

Since the first report of using micromechanical cleavage method to produce graphene sheets in 2004, graphene/graphene-based nanocomposites have attracted wide attention both for fundamental aspects as well as applications in advanced energy storage and conversion systems. In comparison to other materials, graphene-based nanostructured materials have unique 2D structure, high electronic mobility, exceptional electronic and thermal conductivities, excellent optical transmittance, good mechanical strength, and ultrahigh surface area. Therefore, they are considered as attractive materials for hydrogen (H2) storage and high-performance electrochemical energy storage devices, such as supercapacitors, rechargeable lithium (Li)-ion batteries, Li–sulfur batteries, Li–air batteries, sodium (Na)-ion batteries, Na–air batteries, zinc (Zn)–air batteries, and vanadium redox flow batteries (VRFB), etc., as they can improve the efficiency, capacity, gravimetric energy/power densities, and cycle life of these energy storage devices. In this article, recent progress reported on the synthesis and fabrication of graphene nanocomposite materials for applications in these aforementioned various energy storage systems is reviewed. Importantly, the prospects and future challenges in both scalable manufacturing and more energy storage-related applications are discussed

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

The disruption of proteostasis in neurodegenerative diseases

Cells count on surveillance systems to monitor and protect the cellular proteome which, besides being highly heterogeneous, is constantly being challenged by intrinsic and environmental factors. In this context, the proteostasis network (PN) is essential to achieve a stable and functional proteome. Disruption of the PN is associated with aging and can lead to and/or potentiate the occurrence of many neurodegenerative diseases (ND). This not only emphasizes the importance of the PN in health span and aging but also how its modulation can be a potential target for intervention and treatment of human diseases.info:eu-repo/semantics/publishedVersio