Synthesis and Characteristics of Mesoporous Copper Cobalt Oxides Using the Inverse Micelle Method Fabricated for Supercapacitors.

Mesoporous materials have gained considerable attention in the fabrication of supercapacitor electrodes because of their large surface areas and controlled porosities. This study reports the synthesis of mesoporous CuCo2O4 powders using the inverse micelle method. X-ray diffraction, N2 sorption measurement, transmission electron microscopy, and X-ray photoelectron spectroscopy were performed to investigate the properties of the powders. After heat treatment at 250 °C in a vacuum atmosphere, the mesoporous CuCo2O4 powders exhibited a large specific surface area of 116.32 m2 g-1 and a high crystallinity. The electrode fabricated by using the as-prepared mesoporous CuCo2O4 powder exhibited enhanced electrical properties with a maximum specific capacitance of 140 F g-1 and capacitance retention of 91.4% after 3000 continuous charge-discharge cycles. Therefore, the as-prepared mesoporous CuCo2O4 powders hold great potential in the fabrication of supercapacitor electrodes to be used for a wide range of electrochemical applications.

A secure SNP panel scheme using homomorphically encrypted K-mers without SNP calling on the user side.

BACKGROUND: Single Nucleotide Polymorphism (SNP) in the genome has become crucial information for clinical use. For example, the targeted cancer therapy is primarily based on the information which clinically important SNPs are detectable from the tumor. Many hospitals have developed their own panels that include clinically important SNPs. The genome information exchange between the patient and the hospital has become more popular. However, the genome sequence information is innate and irreversible and thus its leakage has serious consequences. Therefore, protecting one's genome information is critical. On the other side, hospitals may need to protect their own panels. There is no known secure SNP panel scheme to protect both. RESULTS: In this paper, we propose a secure SNP panel scheme using homomorphically encrypted K-mers without requiring SNP calling on the user side and without revealing the panel information to the user. Use of the powerful homomorphic encryption technique is desirable, but there is no known algorithm to efficiently align two homomorphically encrypted sequences. Thus, we designed and implemented a novel secure SNP panel scheme utilizing the computationally feasible equality test on two homomorphically encrypted K-mers. To make the scheme work correctly, in addition to SNPs in the panel, sequence variations at the population level should be addressed. We designed a concept of Point Deviation Tolerance (PDT) level to address the false positives and false negatives. Using the TCGA BRCA dataset, we demonstrated that our scheme works at the level of over a hundred thousand somatic mutations. In addition, we provide a computational guideline for the panel design, including the size of K-mer and the number of SNPs. CONCLUSIONS: The proposed method is the first of its kind to protect both the user's sequence and the hospital's panel information using the powerful homomorphic encryption scheme. We demonstrated that the scheme works with a simulated dataset and the TCGA BRCA dataset. In this study, we have shown only the feasibility of the proposed scheme and much more efforts should be done to make the scheme usable for clinical use.

DeepFam: deep learning based alignment-free method for protein family modeling and prediction.

Motivation: A large number of newly sequenced proteins are generated by the next-generation sequencing technologies and the biochemical function assignment of the proteins is an important task. However, biological experiments are too expensive to characterize such a large number of protein sequences, thus protein function prediction is primarily done by computational modeling methods, such as profile Hidden Markov Model (pHMM) and k-mer based methods. Nevertheless, existing methods have some limitations; k-mer based methods are not accurate enough to assign protein functions and pHMM is not fast enough to handle large number of protein sequences from numerous genome projects. Therefore, a more accurate and faster protein function prediction method is needed. Results: In this paper, we introduce DeepFam, an alignment-free method that can extract functional information directly from sequences without the need of multiple sequence alignments. In extensive experiments using the Clusters of Orthologous Groups (COGs) and G protein-coupled receptor (GPCR) dataset, DeepFam achieved better performance in terms of accuracy and runtime for predicting functions of proteins compared to the state-of-the-art methods, both alignment-free and alignment-based methods. Additionally, we showed that DeepFam has a power of capturing conserved regions to model protein families. In fact, DeepFam was able to detect conserved regions documented in the Prosite database while predicting functions of proteins. Our deep learning method will be useful in characterizing functions of the ever increasing protein sequences. Availability and implementation: Codes are available at https://bhi-kimlab.github.io/DeepFam.

PINTnet: construction of condition-specific pathway interaction network by computing shortest paths on weighted PPI.

BACKGROUND: Identifying perturbed pathways in a given condition is crucial in understanding biological phenomena. In addition to identifying perturbed pathways individually, pathway analysis should consider interactions among pathways. Currently available pathway interaction prediction methods are based on the existence of overlapping genes between pathways, protein-protein interaction (PPI) or functional similarities. However, these approaches just consider the pathways as a set of genes, thus they do not take account of topological features. In addition, most of the existing approaches do not handle the explicit gene expression quantity information that is routinely measured by RNA-sequecing. RESULTS: To overcome these technical issues, we developed a new pathway interaction network construction method using PPI, closeness centrality and shortest paths. We tested our approach on three different high-throughput RNA-seq data sets: pregnant mice data to reveal the role of serotonin on beta cell mass, bone-metastatic breast cancer data and autoimmune thyroiditis data to study the role of IFN- α. Our approach successfully identified the pathways reported in the original papers. For the pathways that are not directly mentioned in the original papers, we were able to find evidences of pathway interactions by the literature search. Our method outperformed two existing approaches, overlapping gene-based approach (OGB) and protein-protein interaction-based approach (PB), in experiments with the three data sets. CONCLUSION: Our results show that PINTnet successfully identified condition-specific perturbed pathways and the interactions between the pathways. We believe that our method will be very useful in characterizing biological mechanisms at the pathway level. PINTnet is available at http://biohealth.snu.ac.kr/software/PINTnet/ .

CLIP-GENE: a web service of the condition specific context-laid integrative analysis for gene prioritization in mouse TF knockout experiments.

MOTIVATION: Transcriptome data from the gene knockout experiment in mouse is widely used to investigate functions of genes and relationship to phenotypes. When a gene is knocked out, it is important to identify which genes are affected by the knockout gene. Existing methods, including differentially expressed gene (DEG) methods, can be used for the analysis. However, existing methods require cutoff values to select candidate genes, which can produce either too many false positives or false negatives. This hurdle can be addressed either by improving the accuracy of gene selection or by providing a method to rank candidate genes effectively, or both. Prioritization of candidate genes should consider the goals or context of the knockout experiment. As of now, there are no tools designed for both selecting and prioritizing genes from the mouse knockout data. Hence, the necessity of a new tool arises. RESULTS: In this study, we present CLIP-GENE, a web service that selects gene markers by utilizing differentially expressed genes, mouse transcription factor (TF) network, and single nucleotide variant information. Then, protein-protein interaction network and literature information are utilized to find genes that are relevant to the phenotypic differences. One of the novel features is to allow researchers to specify their contexts or hypotheses in a set of keywords to rank genes according to the contexts that the user specify. We believe that CLIP-GENE will be useful in characterizing functions of TFs in mouse experiments. AVAILABILITY: http://epigenomics.snu.ac.kr/CLIP-GENE REVIEWERS: This article was reviewed by Dr. Lee and Dr. Pongor.

BioVLAB-mCpG-SNP-EXPRESS: A system for multi-level and multi-perspective analysis and exploration of DNA methylation, sequence variation (SNPs), and gene expression from multi-omics data.

Measuring gene expression, DNA sequence variation, and DNA methylation status is routinely done using high throughput sequencing technologies. To analyze such multi-omics data and explore relationships, reliable bioinformatics systems are much needed. Existing systems are either for exploring curated data or for processing omics data in the form of a library such as R. Thus scientists have much difficulty in investigating relationships among gene expression, DNA sequence variation, and DNA methylation using multi-omics data. In this study, we report a system called BioVLAB-mCpG-SNP-EXPRESS for the integrated analysis of DNA methylation, sequence variation (SNPs), and gene expression for distinguishing cellular phenotypes at the pairwise and multiple phenotype levels. The system can be deployed on either the Amazon cloud or a publicly available high-performance computing node, and the data analysis and exploration of the analysis result can be conveniently done using a web-based interface. In order to alleviate analysis complexity, all the process are fully automated, and graphical workflow system is integrated to represent real-time analysis progression. The BioVLAB-mCpG-SNP-EXPRESS system works in three stages. First, it processes and analyzes multi-omics data as input in the form of the raw data, i.e., FastQ files. Second, various integrated analyses such as methylation vs. gene expression and mutation vs. methylation are performed. Finally, the analysis result can be explored in a number of ways through a web interface for the multi-level, multi-perspective exploration. Multi-level interpretation can be done by either gene, gene set, pathway or network level and multi-perspective exploration can be explored from either gene expression, DNA methylation, sequence variation, or their relationship perspective. The utility of the system is demonstrated by performing analysis of phenotypically distinct 30 breast cancer cell line data set. BioVLAB-mCpG-SNP-EXPRESS is available at http://biohealth.snu.ac.kr/software/biovlab_mcpg_snp_express/.

Facile surface modification of anion-exchange membranes for improvement of diffusion dialysis performance.

In this study, a facile membrane modification method by spin-coating of pyrrole (Py) monomers dissolved in a volatile solvent followed by an interfacial polymerization is proposed. The surface of a commercial anion-exchange membrane (i.e., Neosepta-AFX, Astom Corp., Japan) was successfully modified with polypyrrole (Ppy) to improve the acid recovery performance in diffusion dialysis (DD). The result of DD experiments revealed that both the acid and metal ion transports are significantly influenced by the surface modification. The metal crossover through the membranes was largely reduced while mostly maintaining the acid permeability by introducing a thin Ppy layer with excellent repelling property to cations on the membrane surface. As a result, the anion-exchange membrane modified with the optimum content of Py monomer (5 vol.%) exhibited excellent acid dialysis coefficient (KAcid) and selectivity (KAcid/KMetal) which is approximately twice as high as that of the pristine membrane.

Anion control as a strategy to achieve high-mobility and high-stability oxide thin-film transistors.

Ultra-definition, large-area displays with three-dimensional visual effects represent megatrend in the current/future display industry. On the hardware level, such a "dream" display requires faster pixel switching and higher driving current, which in turn necessitate thin-film transistors (TFTs) with high mobility. Amorphous oxide semiconductors (AOS) such as In-Ga-Zn-O are poised to enable such TFTs, but the trade-off between device performance and stability under illumination critically limits their usability, which is related to the hampered electron-hole recombination caused by the oxygen vacancies. Here we have improved the illumination stability by substituting oxygen with nitrogen in ZnO, which may deactivate oxygen vacancies by raising valence bands above the defect levels. Indeed, the stability under illumination and electrical bias is superior to that of previous AOS-based TFTs. By achieving both mobility and stability, it is highly expected that the present ZnON TFTs will be extensively deployed in next-generation flat-panel displays.

Preparation of ion exchanger layered electrodes for advanced membrane capacitive deionization (MCDI).

A noble electrode for capacitive deionization (CDI) was prepared by embedding ion exchanger onto the surface of a carbon electrode to practice membrane capacitive deionization (MCDI). Bromomethylated poly (2, 6-dimethyl-1, 4-phenylene oxide) (BPPO) was sprayed on carbon cloth followed by sulfonation and amination to form cation exchange and anion exchange layers, respectively. The ion exchange layers were examined by Scanning electron microscopy (SEM) and Fourier transform infrared spectrometer (FT-IR). The SEM image showed that the woven carbon cloth was well coated and connected with BPPO. The FT-IR spectrum revealed that sulfonic and amine functional groups were attached on the cationexchange and anionexchange electrodes, respectively. The advantages of the developed carbon electrodes have been successively demonstrated in a batch and a continuous mode CDI operations without ion exchange membranes for salt removal using 100 mg/L NaCl solution.

Analyses of interfacial resistances in a membrane-electrode assembly for a proton exchange membrane fuel cell using symmetrical impedance spectroscopy.

Interfacial resistances between the polymer electrolyte membrane (PEM) and catalyst layer (CL) in membrane-electrode assemblies (MEAs) have yet to be systematically examined in spite of its great importance on the fuel cell performance. In order to investigate ionic transport through the PEM/CL interface, the symmetrical impedance mode (SIM) was employed in which the same type of gas was injected (H(2)/H(2)). In this study, the ionic transport resistance at the interface was controlled by the additionally sprayed outer ionomer on the surface of each CL. Effectiveness of the outer ionomer on ionic transport at the interface was quantitatively explained by the reduced contact, proton hydration, and charge transport resistances in the SIM. To characterize the ionic transport resistance, the concept of total resistance (R(tot)) in the SIM was introduced, representing the overall ohmic loss due to proton transport in an MEA. This concept was successfully supported via an agreement of the interpretation and the linear correlation that was obtained between the admittance (1/R(tot)) and the performance of a fuel cell in the ohmic loss region. This correlation will enable researchers to predict the performance of a fuel cell under the influence of proton transport by examining the R(tot) in the SIM.

Modifying a proton conductive membrane by embedding a "barrier".

For development of proton conductive membranes, it is a difficult dilemma to balance proton conductivity and methanol permeability; however, this research proposes a simple strategy to solve this problem, i.e., embedding a proton conductive "barrier" into the perflorosulfonated matrix. The strategy is exemplified by embedding the amphoteric sulfonated poly(phthalazinone ether sulfone kentone) (SPPESK) into a semicrystalline perflorosulfonic acid polymer matrix (FSP). After being annealed, the domain of SPPESK is converted to the barrier. Two acid-base interactions constitute the barrier for both the transfer of protons and the blockage of methanol, respectively. On one hand, poorly hydrophilic ionic acid-base interactions (-SO(3)(-)...NH(+)-) are formed between sulfonic acid group and phthalazinone group through annealing and are useful for methanol blocking. On the other hand, more hydrophilic hydrogen-bonded acid-base interaction (-SO(3)H...(H(2)O)(n)...N-, n ≤ 3) can also be formed under hydrated condition and facilitate proton transport according to the Grotthuss-type mechanism. As a result, the final membrane exhibits an extremely low methanol permeability (30% of that of Nafion-112) and an excellent fuel cell performance (as compared with Nafion-112 at 80 °C).

Synthesis of well dispersed uniform sub-4 nm Y2O3:Eu3+ colloidal nanocrystals.

Well dispersed uniform sub-4 nm Y2O3:Eu colloidal nanocrystals have been synthesized through the non-hydrolytic high-temperature thermal decomposition technique. The as-synthesized nanocrystals can be stably dispersed in nonpolar solvents due to the capping organic ligands on their surface. Compared with bulk materials, the nanocrystals exhibited different luminescence features, including the intensity enhancement of the 5D0 --> 7F4 transition observed in the emission spectrum.

Investigation on removal of hardness ions by capacitive deionization (CDI) for water softening applications.

Capacitive deionization (CDI) for removal of water hardness was investigated for water softening applications. In order to examine the wettability and pore structure of the activated carbon cloth and composites electrodes, surface morphological and electrochemical characteristics were observed. The highly wettable electrode surface exhibited faster adsorption/desorption of ions in a continuous treatment system. In addition, the stack as well as unit cell operations were performed to investigate preferential removal of the hardness ions, showing higher selectivity of divalent ions rather than that of the monovalent ion. Interestingly, competitive substitution was observed in which the adsorbed Na ions were replaced by more strongly adsorptive Ca and Mg ions. The preferential removal of divalent ions was explained in terms of ion selectivity and pore characteristics in electrodes. Finally, optimal pore size and structure of carbon electrodes for efficient removal of divalent ions were extensively discussed.

Hydrogen bonding: a channel for protons to transfer through acid-base pairs.

Different from H(3)O(+) transport as in the vehicle mechanism, protons find another channel to transfer through the poorly hydrophilic interlayers in a hydrated multiphase membrane. This membrane was prepared from poly(phthalazinone ether sulfone kentone) (SPPESK) and H(+)-form perfluorosulfonic resin (FSP), and poorly hydrophilic electrostatically interacted acid-base pairs constitute the interlayer between two hydrophilic phases (FSP and SPPESK). By hydrogen bonds forming and breaking between acid-base pairs and water molecules, protons transport directly through these poorly hydrophilic zones. The multiphase membrane, due to this unique transfer mechanism, exhibits better electrochemical performances during fuel cell tests than those of pure FSP and Nafion-112 membranes: 0.09-0.12 S cm(-1) of proton conductivity at 25 degrees C and 990 mW cm(-2) of the maximum power density at a current density of 2600 mA cm(-2) and a cell voltage of 0.38 V.