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.

Natural actor-critic algorithms

We present four new reinforcement learning algorithms based on actor-critic, natural-gradient and functi approximation ideas,and we provide their convergence proofs. Actor-critic reinforcement learning methods are online approximations to policy iteration in which the value-function parameters are estimated using temporal difference learning and the policy parameters are updated by stochastic gradient descent. Methods based on policy gradients in this way are of special interest because of their compatibility with function-approximation methods, which are needed to handle large or infinite state spaces. The use of temporal difference learning in this way is of special interest because in many applications it dramatically reduces the variance of the gradient estimates. The use of the natural gradient is of interest because it can produce better conditioned parameterizations and has been shown to further reduce variance in some cases. Our results extend prior two-timescale convergence results for actor-critic methods by Konda and Tsitsiklis by using temporal difference learning in the actor and by incorporating natural gradients. Our results extend prior empirical studies of natural actor-critic methods by Peters, Vijayakumar and Schaal by providing the first convergence proofs and the first fully incremental algorithms.

Prevalence and analysis of t(14;18) and t(11;14) chromosomal translocations in healthy Indian population

Hematopoietic malignancies like leukemia and lymphoma are characteristically associated with various chromosomal translocations. Follicular lymphoma (FL) and mantle cell lymphoma (MCL) are two subtypes of non-Hodgkin's lymphoma which possess t(14;18) and t(11;14) translocations, respectively. The incidence of FL and MCL is higher in the western countries as compared to India. Interestingly, the associated translocations are also found in healthy individuals in western population, which is 50-80% for t(14;18), whereas t(11;14) occurs at a very low frequency. However, there are no studies to explore thes translocations in healthy Indian population, which could explain the lower incidence of FL and MCL. We employed Southern hybridization following nested PCR to detect above translocations in healthy individuals from India. Our results suggest that this assay can detect one t(14;18) translocation event in up to 10(7) normal cells where as one t(11;14) in 10(8) normal cells. According to our results, 87 out of 253 individuals carry t(14;18) indicating 34% prevalence in the population. The presence of this translocation was also detectable at the transcript level. Although, no gender-based difference was observed, an age-dependent increase in the prevalence of translocation was found in adults. However, even after studying 210 people, we could not detect any t(11;14) translocation, indicating that it is uncommon in Indian population. These results suggest that lower incidence of FL and MCL in India could be attributed to lower prevalence of these translocations in healthy individuals.

Beyond Gauss: Image-set matching on the Riemannian manifold of PDFs

State-of-the-art image-set matching techniques typically implicitly model each image-set with a Gaussian distribution. Here, we propose to go beyond these representations and model image-sets as probability distribution functions (PDFs) using kernel density estimators. To compare and match image-sets, we exploit Csiszar´ f-divergences, which bear strong connections to the geodesic distance defined on the space of PDFs, i.e., the statistical manifold. Furthermore, we introduce valid positive definite kernels on the statistical manifold, which let us make use of more powerful classification schemes to match image-sets. Finally, we introduce a supervised dimensionality reduction technique that learns a latent space where f-divergences reflect the class labels of the data. Our experiments on diverse problems, such as video-based face recognition and dynamic texture classification, evidence the benefits of our approach over the state-of-the-art image-set matching methods.

NUVIEW:software for display and interactive manipulation of nucleic acid models

The NUVIEW software package allows skeletal models of any double helical nucleic acid molecule to be displayed out a graphics monitor and to apply various rotations, translations and scaling transformations interactively, through the keyboard. The skeletal model is generated by connecting any pair of representative points, one from each of the bases in the basepair. In addition to the above mentioned manipulations, the base residues can be identified by using a locator and the distance between any pair of residues can be obtained. A sequence based color coded display allows easy identification of sequence repeats, such as runs of Adenines. The real time interactive manipulation of such skeletal models for large DNA/RNA double helices, can be used to trace the path of the nucleic acid chain in three dimensions and hence get a better idea of its topology, location of linear or curved regions, distances between far off regions in the sequence etc. A physical picture of these features will assist in understanding the relationship between base sequence, structure and biological function in nucleic acids.

NUPARM and NUCGEN: software for analysis and generation of sequence dependent nucleic acid structures

Software packages NUPARM and NUCGEN, are described, which can be used to understand sequence directed structural variations in nucleic acids, by analysis and generation of non-uniform structures. A set of local inter basepair parameters (viz. tilt, roll, twist, shift, slide and rise) have been defined, which use geometry and coordinates of two successive basepairs only and can be used to generate polymeric structures with varying geometries for each of the 16 possible dinucleotide steps. Intra basepair parameters, propeller, buckle, opening and the C6...C8 distance can also be varied, if required, while the sugar phosphate backbone atoms are fixed in some standard conformation ill each of the nucleotides. NUPARM can be used to analyse both DNA and RNA structures, with single as well as double stranded helices. The NUCGEN software generates double helical models with the backbone fixed in B-form DNA, but with appropriate modifications in the input data, it can also generate A-form DNA ar rd RNA duplex structures.

Semi-active vibration isolation using a near-zero-spring-rate device:steady state analysis of a single-degree-of-freedom model

A vibration isolator is described which incorporates a near-zero-spring-rate device within its operating range. The device is an assembly of a vertical spring in parallel with two inclined springs. A low spring rate is achieved by combining the equivalent stiffness in the vertical direction of the inclined springs with the stiffness of the vertical central spring. It is shown that there is a relation between the geometry and the stiffness of the individual springs that results in a low spring rate. Computer simulation studies of a single-degree-of-freedom model for harmonic base input show that the performance of the proposed scheme is superior to that of the passive schemes with linear springs and skyhook damping configuration. The response curves show that, for small to large amplitudes of base disturbance, the system goes into resonance at low frequencies of excitation. Thus, it is possible to achieve very good isolation over a wide low-frequency band. Also, the damper force requirements for the proposed scheme are much lower than for the damper force of a skyhook configuration or a conventional linear spring with a semi-active damper.