Mining Brain Networks using Multiple Side Views for Neurological Disorder Identification

Mining discriminative subgraph patterns from graph data has attracted great interest in recent years. It has a wide variety of applications in disease diagnosis, neuroimaging, etc. Most research on subgraph mining focuses on the graph representation alone. However, in many real-world applications, the side information is available along with the graph data. For example, for neurological disorder identification, in addition to the brain networks derived from neuroimaging data, hundreds of clinical, immunologic, serologic and cognitive measures may also be documented for each subject. These measures compose multiple side views encoding a tremendous amount of supplemental information for diagnostic purposes, yet are often ignored. In this paper, we study the problem of discriminative subgraph selection using multiple side views and propose a novel solution to find an optimal set of subgraph features for graph classification by exploring a plurality of side views. We derive a feature evaluation criterion, named gSide, to estimate the usefulness of subgraph patterns based upon side views. Then we develop a branch-and-bound algorithm, called gMSV, to efficiently search for optimal subgraph features by integrating the subgraph mining process and the procedure of discriminative feature selection. Empirical studies on graph classification tasks for neurological disorders using brain networks demonstrate that subgraph patterns selected by the multi-side-view guided subgraph selection approach can effectively boost graph classification performances and are relevant to disease diagnosis.Comment: in Proceedings of IEEE International Conference on Data Mining (ICDM) 201

Microstructure and texture evolutions in FeCrAl cladding tube during pilger processing

The microstructure of FeCrAl cladding tubes depends on the fabricating process history. In this study, the microstructural characteristics of wrought FeCrAl alloys during industrial pilger processing into thin-walled tubes were investigated. The hot extruded tube showed ∼100 μm equiaxed grains with weak α∗-fiber in {h11}<1/h12> texture, while pilger rolling process change the microstructure to fragmented and elongated grains along the rolling direction. The pilgered textures could be predicted with the VPSC model. The inter-pass annealing at 800–850 \ub0C for 1 h results in recovery and recrystallization of the ferric matrix and restoration of ductility. The final finished tube shows fine recrystallized grains (∼11 μm) with dominant γ-fiber in three dimensions. Pilger rolling enhanced α-fiber while annealing reduced α-fiber and enhanced γ-fiber. Microstructural evolution in the Laves precipitates followed the sequence of faceted needle-like → spherical → faceted ellipsoidal. Thermomechanical processing resulted in cladding tubes with an area fraction of ∼5% and a number density of 5 7 10−11 m−2 in Laves precipitates, which is half that of the first-pilgered tube. Laves precipitates pin the grain boundaries to control the microstructure and prevent grain coarsening

Directional mechanical stability of Bacteriophage φ29 motor’s 3WJ-pRNA: Extraordinary robustness along portal axis

The molecular motor exploited by bacteriophage φ29 to pack DNA into its capsid is regarded as one of the most powerful mechanical devices present in viral, bacterial, and eukaryotic systems alike. Acting as a linker element, a prohead RNA (pRNA) effectively joins the connector and ATPase (adenosine triphosphatase) components of the φ29 motor. During DNA packing, this pRNA needs to withstand enormous strain along the capsid’s portal axis—how this remarkable stability is achieved remains to be elucidated. We investigate the mechanical properties of the φ29 motor’s three-way junction (3WJ)–pRNA using a combined steered molecular dynamics and atomic force spectroscopy approach. The 3WJ exhibits strong resistance to stretching along its coaxial helices, demonstrating its super structural robustness. This resistance disappears, however, when external forces are applied to the transverse directions. From a molecular standpoint, we demonstrate that this direction-dependent stability can be attributed to two Mg clamps that cooperate and generate mechanical resistance in the pRNA’s coaxial direction. Our results suggest that the asymmetric nature of the 3WJ’s mechanical stability is entwined with its biological function: Enhanced rigidity along the portal axis is likely essential to withstand the strain caused by DNA condensation, and flexibility in other directions should aid in the assembly of the pRNA and its association with other motor components

Correlation-driven eightfold magnetic anisotropy in a two-dimensional oxide monolayer.

Engineering magnetic anisotropy in two-dimensional systems has enormous scientific and technological implications. The uniaxial anisotropy universally exhibited by two-dimensional magnets has only two stable spin directions, demanding 180° spin switching between states. We demonstrate a previously unobserved eightfold anisotropy in magnetic SrRuO3 monolayers by inducing a spin reorientation in (SrRuO3)1/(SrTiO3) N superlattices, in which the magnetic easy axis of Ru spins is transformed from uniaxial 〈001〉 direction (N < 3) to eightfold 〈111〉 directions (N ≥ 3). This eightfold anisotropy enables 71° and 109° spin switching in SrRuO3 monolayers, analogous to 71° and 109° polarization switching in ferroelectric BiFeO3. First-principle calculations reveal that increasing the SrTiO3 layer thickness induces an emergent correlation-driven orbital ordering, tuning spin-orbit interactions and reorienting the SrRuO3 monolayer easy axis. Our work demonstrates that correlation effects can be exploited to substantially change spin-orbit interactions, stabilizing unprecedented properties in two-dimensional magnets and opening rich opportunities for low-power, multistate device applications

Atomic Sn–enabled high-utilization, large-capacity, and long-life Na anode

Constructing robust nucleation sites with an ultrafine size in a confined environment is essential toward simultaneously achieving superior utilization, high capacity, and long-term durability in Na metal-based energy storage, yet remains largely unexplored. Here, we report a previously unexplored design of spatially confined atomic Sn in hollow carbon spheres for homogeneous nucleation and dendrite-free growth. The designed architecture maximizes Sn utilization, prevents agglomeration, mitigates volume variation, and allows complete alloying-dealloying with high-affinity Sn as persistent nucleation sites, contrary to conventional spatially exposed large-size ones without dealloying. Thus, conformal deposition is achieved, rendering an exceptional capacity of 16 mAh cm−2 in half-cells and long cycling over 7000 hours in symmetric cells. Moreover, the well-known paradox is surmounted, delivering record-high Na utilization (e.g., 85%) and large capacity (e.g., 8 mAh cm−2) while maintaining extraordinary durability over 5000 hours, representing an important breakthrough for stabilizing Na anode

UBE2C Is a Potential Biomarker of Intestinal-Type Gastric Cancer With Chromosomal Instability

This study explored potential biomarkers associated with Lauren classification of gastric cancer. We screened microarray datasets on gastric cancer with information of Lauren classification in gene expression omnibus (GEO) database, and compared differentially expressing genes between intestinal-type or diffuse-type gastric cancer. Four sets of microarray data (GSE2669, GSE2680, GDS3438, and GDS4007) were enrolled into analysis. By differential gene analysis, UBE2C, CDH1, CENPF, ERO1L, SCD, SOX9, CKS1B, SPP1, MMP11, and ANLN were identified as the top genes related to intestinal-type gastric cancer, and MGP, FXYD1, FAT4, SIPA1L2, MUC5AC, MMP15, RAB23, FBLN1, ANXA10, and ADH1B were genes related to diffuse-type gastric cancer. We comprehensively validated the biological functions of the intestinal-type gastric cancer related gene UBE2C and evaluated its clinical significance on 1,868 cases of gastric cancer tissues from multiple medical centers of Shanghai, China. The gain of copy number on 20q was found in 4 out of 5 intestinal-type cancer cell lines, and no similar copy number variation (CNV) was found in any diffuse-type cancer cell line. Interfering UBE2C expression inhibited cell proliferation, migration and invasion in vitro, and tumorigenesis in vivo. Knockdown of UBE2C resulted in G2/M blockage in intestinal-type gastric cancer cells. Overexpression of UBE2C activated ERK signal pathway and promoted cancer cell proliferation. U0126, an inhibitor of ERK signaling pathway reversed the oncogenic phenotypes caused by UBE2C. Moreover, overexpression of UBE2C was identified in human intestinal-type gastric cancer. Overexpression of UBE2C protein predicted poor clinical outcome. Taken together, we characterized a group of Lauren classification-associated biomarkers, and clarified biological functions of UBE2C, an intestinal-type gastric cancer associated gene. Overexpression of UBE2C resulted in chromosomal instability that disturbed cell cycle and led to poor prognosis of intestinal-type gastric cancer

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO