Identification of a novel FGFRL1 MicroRNA target site polymorphism for bone mineral density in meta-analyses of genome-wide association studies

MicroRNAs (miRNAs) are critical post-transcriptional regulators. Based on a previous genome-wide association (GWA) scan, we conducted a polymorphism in microRNAs' Target Sites (poly-miRTS)-centric multistage meta-analysis for lumbar spine (LS)-, total hip (HIP)-, and femoral neck (FN)-bone mineral density (BMD). In stage I, 41,102 poly-miRTSs were meta-analyzed in 7 cohorts with a genome-wide significance (GWS) α=0.05/41,102=1.22×10-6. By applying α=5×10-5 (suggestive significance), 11 poly-miRTSs were selected, with FGFRL1 rs4647940 and PRR5 rs3213550 as top signals for FN-BMD (P-value=7.67×10-6 and 1.58×10-5) in gender-combined sample. In stage II in silico replication (two cohorts), FGFRL1 rs4647940 was the only signal marginally replicated for FN-BMD (P-value=5.08×10-3) at α=0.10/11=9.09×10-3. PRR5 rs3213550 was also selected based on biological significance. In stage III de novo genotyping replication (two cohorts), FGFRL1 rs4647940 was the only signal significantly replicated for FN-BMD (P-value=7.55×10-6) at α=0.05/2=0.025 in gender-combined sample. Aggregating three stages, FGFRL1 rs4647940 was the single stage I-discovered and stages II- and III-replicated signal attaining GWS for FN-BMD (P-value=8.87×10-12). Dual-luciferase reporter assays demonstrated that FGFRL1 3' untranslated region harboring rs4647940 appears to be hsa-miR-140-5p's target site. In a zebrafish microinjection experiment, dre-miR-140-5p is shown to exert a dramatic impact on craniofacial skeleton formation. Taken together, we provided functional evidence for a novel FGFRL1 poly-miRTS rs4647940 in a previously known 4p16.3 locus, and experimental and clinical genetics studies have shown both FGFRL1 and hsa-miR-140-5p are important for bone formation. © The Author 2015. Published by Oxford University Press. All rights reserved.

Multistage genome-wide association meta-analyses identified two new loci for bone mineral density

Aiming to identify novel genetic variants and to confirm previously identified genetic variants associated with bone mineral density (BMD), we conducted a three-stage genome-wide association (GWA) meta-analysis in 27 061 study subjects. Stage 1 meta-analyzed seven GWA samples and 11 140 subjects for BMDs at the lumbar spine, hip and femoral neck, followed by a Stage 2 in silico replication of 33 SNPs in 9258 subjects, and by a Stage 3 de novo validation of three SNPs in 6663 subjects. Combining evidence from all the stages, we have identified two novel loci that have not been reported previously at the genome-wide significance (GWS; 5.0 × 10-8) level: 14q24.2 (rs227425, P-value 3.98 × 10-13, SMOC1) in the combined sample of males and females and 21q22.13 (rs170183, P-value 4.15 × 10-9, CLDN14) in the female-specific sample. The two newly identified SNPs were also significant in the GEnetic Factors for OSteoporosis consortium (GEFOS, n 5 32 960) summary results. We have also independently confirmed 13 previously reported loci at the GWS level: 1p36.12 (ZBTB40), 1p31.3 (GPR177), 4p16.3 (FGFRL1), 4q22.1 (MEPE), 5q14.3 (MEF2C), 6q25.1 (C6orf97, ESR1), 7q21.3 (FLJ42280, SHFM1), 7q31.31 (FAM3C, WNT16), 8q24.12 (TNFRSF11B), 11p15.3 (SOX6), 11q13.4 (LRP5), 13q14.11 (AKAP11) and 16q24 (FOXL1). Gene expression analysis in osteogenic cells implied potential functional association of the two candidate genes (SMOC1 and CLDN14) in bone metabolism. Our findings independently confirm previously identified biological pathways underlying bone metabolism and contribute to the discovery of novel pathways, thus providing valuable insights into the intervention and treatment of osteoporosis. © The Author 2013. Published by Oxford University Press.

Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture

The extent to which low-frequency (minor allele frequency (MAF) between 1-5%) and rare (MAF density (BMD) is highly heritable, a major predictor of osteoporotic fractures, and has been previously associated with common genetic variants, as well as rare, population-specific, coding variants. Here we identify novel non-coding genetic variants with large effects on BMD (ntotal = 53,236) and fracture (ntotal = 508,253) in individuals of European ancestry from the general population. Associations for BMD were derived from whole-genome sequencing (n = 2,882 from UK10K (ref. 10); a population-based genome sequencing consortium), whole-exome sequencing (n = 3,549), deep imputation of genotyped samples using a combined UK10K/1000 Genomes reference panel (n = 26,534), and de novo replication genotyping (n = 20,271). We identified a low-frequency non-coding variant near a novel locus, EN1, with an effect size fourfold larger than the mean of previously reported common variants for lumbar spine BMD (rs11692564(T), MAF = 1.6%, replication effect size = +0.20 s.d., Pmeta = 2 x 10(-14)), which was also associated with a decreased risk of fracture (odds ratio = 0.85; P = 2 x 10(-11); ncases = 98,742 and ncontrols = 409,511). Using an En1(cre/flox) mouse model, we observed that conditional loss of En1 results in low bone mass, probably as a consequence of high bone turnover. We also identified a novel low-frequency non-coding variant with large effects on BMD near WNT16 (rs148771817(T), MAF = 1.2%, replication effect size = +0.41 s.d., Pmeta = 1 x 10(-11)). In general, there was an excess of association signals arising from deleterious coding and conserved non-coding variants. These findings provide evidence that low-frequency non-coding variants have large effects on BMD and fracture, thereby providing rationale for whole-genome sequencing and improved imputation reference panels to study the genetic architecture of complex traits and disease in the general population.

R1STM: One-class support tensor machine with randomised kernel

Identifying unusual or anomalous patterns in an underlying dataset is an important but challenging task in many applications. The focus of the unsupervised anomaly detection literature has mostly been on vectorised data. However, many applications are more naturally described using higher-order tensor representations. Approaches that vectorise tensorial data can destroy the structural information encoded in the high-dimensional space, and lead to the problem of the curse of dimensionality. In this paper we present the first unsupervised tensorial anomaly detection method, along with a randomised version of our method. Our anomaly detection method, the One-class Support Tensor Machine (1STM), is a generalisation of conventional one-class Support Vector Machines to higher-order spaces. 1STM preserves the multiway structure of tensor data, while achieving significant improvement in accuracy and efficiency over conventional vectorised methods. We then leverage the theory of nonlinear random projections to propose the Randomised 1STM (R1STM). Our empirical analysis on several real and synthetic datasets shows that our R1STM algorithm delivers comparable or better accuracy to a state-of-the-art deep learning method and traditional kernelised approaches for anomaly detection, while being approximately 100 times faster in training and testing.

The line transect method for estimating densities of large mammals in a tropical deciduous forest: An evaluation of models and field experiments

We have evaluated techniques of estimating animal density through direct counts using line transects during 1988-92 in the tropical deciduous forests of Mudumalai Sanctuary in southern India for four species of large herbivorous mammals, namely, chital (Axis axis), sambar (Cervus unicolor), Asian elephant (Elephas maximus) and gaur (Bos gauras). Density estimates derived from the Fourier Series and the Half-Normal models consistently had the lowest coefficient of variation. These two models also generated similar mean density estimates. For the Fourier Series estimator, appropriate cut-off widths for analysing line transect data for the four species are suggested. Grouping data into various distance classes did not produce any appreciable differences in estimates of mean density or their variances, although model fit is generally better when data are placed in fewer groups. The sampling effort needed to achieve a desired precision (coefficient of variation) in the density estimate is derived. A sampling effort of 800 km of transects returned a 10% coefficient of variation on estimate for chital; for the other species a higher effort was needed to achieve this level of precision. There was no statistically significant relationship between detectability of a group and the size of the group for any species. Density estimates along roads were generally significantly different from those in the interior af the forest, indicating that road-side counts may not be appropriate for most species.

On the growth of the Bergman kernel near an infinite-type point

We study diagonal estimates for the Bergman kernels of certain model domains in C-2 near boundary points that are of infinite type. To do so, we need a mild structural condition on the defining functions of interest that facilitates optimal upper and lower bounds. This is a mild condition; unlike earlier studies of this sort, we are able to make estimates for non-convex pseudoconvex domains as well. Thisn condition quantifies, in some sense, how flat a domain is at an infinite-type boundary point. In this scheme of quantification, the model domains considered below range-roughly speaking-from being mildly infinite-type'' to very flat at the infinite-type points.

Position preference and diffusion path of an oxygen ion in apatite-type lanthanum silicate La9.33Si6O26: A density functional study

Using density functional theory, we investigated the position preference and diffusion mechanisms of interstitial oxygen ions in lanthanum silicate La9.33Si6O26, which is an apatite-structured oxide and a promising candidate electrolyte material for solid oxide fuel cells. The reported lanthanum vacancies were explicitly taken into account by theoretically determining their arrangement with a supercell model. The most stable structures and the formation energies of oxygen interstitials were determined for each charged state. It was found that the double-negatively charged state is stable over a wide range of the Fermi level, and that the excess oxygen ions form split interstitials with the original oxygen ions, while the neutral and the single-negatively charged states preferably form molecular oxygen. These species were found near the lanthanum vacancy site. The theoretically determined migration pathway along the c-axis essentially follows an interstitialcy mechanism. The obtained migration barrier is sensitive to the charge state, and is also affected by the lanthanum vacancy. The barrier height of the double-negatively charged state was calculated to be 0.58 eV for the model structure, which is consistent with the measured activation energy.

Critical test for Altshuler-Aronov theory: Evolution of the density of states singularity in double perovskite Sr2FeMoO6 with controlled disorder

With high-resolution photoemission spectroscopy measurements, the density of states (DOS) near the Fermi level (E-F) of double perovskite Sr2FeMoO6 having different degrees of Fe/Mo antisite disorder has been investigated with varying temperature. The DOS near E-F showed a systematic depletion with increasing degree of disorder, and recovered with increasing temperature. Altshuler-Aronov (AA) theory of disordered metals well explains the dependences of the experimental results. Scaling analysis of the spectra provides experimental indication for the functional form of the AA DOS singularity.

Investigation of inter-ion interactions in N,N,N',N'-tetramethylethylenediammonium dithiocyanate via experimental and theoretical charge density studies

The crystal structure of the N,N,N',N'-tetramethylethylenediammonium dithiocyanate salt has been examined by experimental charge density studies from high-resolution X-ray diffraction data. The corresponding results are compared with multipole refinements, using theoretical structure factors obtained from a periodic density functional theory calculation at the B3LYP level with a 6-31G** basis set. The salt crystallizes in space group P (1) over bar and contains only a single ion pair with an inversion center in the cation. The salt has thus one unique classical N+-H center dot center dot center dot(NCS)(-) hydrogen bond but also has six other weaker interactions: four C-H center dot center dot center dot S, one C-H center dot center dot center dot N, and one C-H center dot center dot center dot C-pi. The nature of all these interactions has been examined topologically using Bader's quantum theory of "atoms in molecules" and all eight of the Koch-Popelier criteria. The experimental and theoretical approaches agree well and both show that the inter-ion interactions, even in this simplest of systems, play an integrated and complex role in the packing of the ions in the crystal. Electrostatic potential maps are derived from experimental charge densities. This is the first time such a system has been examined in detail by these methods.

Kernel-based spatial-color modeling for fast moving object tracking

Visual tracking has been a challenging problem in computer vision over the decades. The applications of Visual Tracking are far-reaching, ranging from surveillance and monitoring to smart rooms. Mean-shift (MS) tracker, which gained more attention recently, is known for tracking objects in a cluttered environment and its low computational complexity. The major problem encountered in histogram-based MS is its inability to track rapidly moving objects. In order to track fast moving objects, we propose a new robust mean-shift tracker that uses both spatial similarity measure and color histogram-based similarity measure. The inability of MS tracker to handle large displacements is circumvented by the spatial similarity-based tracking module, which lacks robustness to object's appearance change. The performance of the proposed tracker is better than the individual trackers for tracking fast-moving objects with better accuracy.

Chemically Programmed Ultrahigh Density Two-Dimensional Semiconductor Superlattice Array

Designing an ultrahigh density linear superlattice array consisting of periodic blocks of different semiconductors in the strong confinement regime via a direct synthetic route remains an unachieved challenge in nanotechnology. We report a general synthesis route for the formulation of a large-area ultrahigh density superlattice array that involves adjoining multiple units of ZnS rods by prolate US particles at the tips. A single one-dimensional wire is 300-500 nm long and consists of periodic quantum wells with a barrier width of 5 nm provided by ZnS and a well width of 1-2 nm provided by CdS, defining a superlattice structure. The synthesis route allows for tailoring of ultranarrow laserlike emissions (fwhm approximate to 125 meV) originating from strong interwell energy dispersion along with control of the width, pitch, and registry of the superlattice assembly. Such an exceptional high-density superlattice array could form the basis of ultrahigh density memories in addition to offering opportunities for technological advancement in conventional heterojunction-based device applications.