Genome-wide case-control study in GAW17 using coalesced rare variants

Genome-wide association studies have successfully identified numerous loci at which common variants influence disease risks or quantitative traits of interest. Despite these successes, the variants identified by these studies have generally explained only a small fraction of the variations in the phenotype. One explanation may be that many rare variants that are not included in the common genotyping platforms may contribute substantially to the genetic variations of the diseases. Next-generation sequencing, which would better allow for the analysis of rare variants, is now becoming available and affordable; however, the presence of a large number of rare variants challenges the statistical endeavor to stably identify these disease-causing genetic variants. We conduct a genome-wide association study of Genetic Analysis Workshop 17 case-control data produced by the next-generation sequencing technique and propose that collapsing rare variants within each genetic region through a supervised dimension reduction algorithm leads to several macrovariants constructed for rare variants within each genetic region. A simultaneous association of the phenotype to all common variants and macrovariants is undertaken using a linear discriminant analysis using the penalized orthogonal-components regression algorithm. The results suggest that the proposed analysis strategy shows promise but needs further development

Bayesian profiling of molecular signatures to predict event times

BACKGROUND: It is of particular interest to identify cancer-specific molecular signatures for early diagnosis, monitoring effects of treatment and predicting patient survival time. Molecular information about patients is usually generated from high throughput technologies such as microarray and mass spectrometry. Statistically, we are challenged by the large number of candidates but only a small number of patients in the study, and the right-censored clinical data further complicate the analysis. RESULTS: We present a two-stage procedure to profile molecular signatures for survival outcomes. Firstly, we group closely-related molecular features into linkage clusters, each portraying either similar or opposite functions and playing similar roles in prognosis; secondly, a Bayesian approach is developed to rank the centroids of these linkage clusters and provide a list of the main molecular features closely related to the outcome of interest. A simulation study showed the superior performance of our approach. When it was applied to data on diffuse large B-cell lymphoma (DLBCL), we were able to identify some new candidate signatures for disease prognosis. CONCLUSION: This multivariate approach provides researchers with a more reliable list of molecular features profiled in terms of their prognostic relationship to the event times, and generates dependable information for subsequent identification of prognostic molecular signatures through either biological procedures or further data analysis

Long-term follow-up outcome and reintervention analysis of ultrasound-guided high intensity focused ultrasound treatment for uterine fibroids

Objective To investigate the long-term reintervention of ultrasound-guided high intensity focused ultrasound (USgHIFU) treatment for uterine fibroids and analyze the factors affecting reintervention rate after USgHIFU. Materials and methods Three hundred and eight-one patients with uterine fibroids treated by USgHIFU at the third Xiangya Hospital of Central South University from April 2012 to December 2014 were retrospectively reviewed. The factors that affect the reintervention rate were analyzed. Results The mean follow-up time was 70.0 ± 9.0 months. During the follow-up period, 86.4% (329/381) of the patients reported symptomatic relief and the fibroids shrank after USgHIFU treatment. Seventy-nine patients received reintervention included myomectomy, a second session of HIFU, and hysterectomy. The overall reintervention rate was 20.7% (79/381). The reasons for reintervention included symptomatic recurrence in 50 (50/79, 63.3%) patients, psychological factors in 14 (14/79, 17.7%) patients, fertility requirement in three (3/79, 3.8%) patients, suspected uterine sarcoma in two (2/79, 2.5%) patients and others in 10 (10/79, 12.7%) patients. The reintervention rate has significant correlation with some factors including age, size, type and the signal intensity on T2 weighted image (T2WI) of the uterine fibroids. Conclusion USgHIFU for uterine fibroids is effective due to low reintervention rate in a long-term follow-up

Dynamic Modeling of a 2-RPU+2-UPS Hybrid Manipulator for Machining Application

This paper presents a novel 5-DOF gantry hybrid machine tool, designed with a 2-RPU+2-UPS parallel mechanism for 3T2R motion. The 2-RPU+2-UPS parallel mechanism is connected to a long linear guide to realize 5-axis machining. A dynamic model is developed for this parallel-serial hybrid system. Screw theory is adopted to establish the kinematic equations of the system, upon which the dynamics model is developed by utilizing the principle of virtual work. A numerical example for processing slender structural parts is included to show the validity of the analytical dynamic model developed

A Transmission Efficiency Evaluation Method of Adaptive Coding Modulation for Ka-Band Data-Transmission of LEO EO Satellites

Nowadays low Earth orbit (LEO) Earth observation (EO) satellites commonly use constant coding modulation (CCM) or variable coding modulation (VCM) schemes for data transmission to ground stations (G/S). Compared with CCM and VCM, the adaptive coding modulation (ACM) could further improve the data throughput of the link by making full use of link resource and the time-varying characteristics of atmospheric attenuation. In order to comprehensively study the data transmission performance, one new index which could be utilized as a quantitative index for the satellite-to-ground data transmission scheme selection, the transmission efficiency factor (TEF) of LEO satellites is proposed and defined as “the product of the link availability and the average useful data rate”. Then, the transmission efficiency of CCM, VCM and ACM at typical G/S with different weather characteristics at Ka-band is compared and analyzed. The results show that ACM is more suitable for the G/S with moderate and abundant rainfall. Compared with the CCM of MCS 28, for Beijing G/S and Sanya G/S, ACM not only improves the transmission efficiency with the TEF increased by 3.62% and 24.51%, respectively, but also improves the link availability with the outage period reduced by 82.47% and 75.18%, respectively

Candida albicans-induced activation of the TGF-β/Smad pathway and upregulation of IL-6 may contribute to intrauterine adhesion

Abstract Iatrogenic injury to endometrial tissue is the main cause of intrauterine adhesions (IUA) and infection can also damage the endometrium. The microbiota plays an important role in the health of the female reproductive tract. However, the mechanism is still unclear. In total, 908 patients with IUA and 11,389 healthy individuals were retrospectively selected for this clinical study. Participant information including vaginal microecological results and human papillomavirus (HPV) status were collected. Univariate and multivariate logistic regression analyses were used to identify the factors related to IUA. Next, animal experiments were performed in a curettage-induced IUA rat model. After the procedure, rats in the experimental group received a vaginal infusion of a Candida albicans (C. albicans) fungal solution. On days 3, 7, and 14 after curettage and infusion, the expression levels of IL-6, fibrotic pathway-related factors (TGF-β1, Smad 2, and COL1), and estrogen receptor (ER) and progesterone receptor (PR) in rat endometrial tissues were assessed. Fungal infection of the reproductive tract was found to be an independent risk factor for IUA (P < 0.05). The inflammatory response and degree of fibrosis were greater in rats infected with C. albicans than in the controls. The levels of IL-6, TGF-β1, Smad 2, and COL1 expression in endometrial tissues were significantly higher in the experimental group than in the control group (P < 0.05). However, the ER and PR levels were lower in the IUA group than in the non-IUA group (P < 0.05). C. albicans infection may be related to IUA. C. albicans elicits a strong inflammatory response that can lead to more severe endometrial fibrosis

Spectral&ndash;Spatial Complementary Decision Fusion for Hyperspectral Anomaly Detection

Hyperspectral anomaly detection has become an important branch of remote&ndash;sensing image processing due to its important theoretical value and wide practical application prospects. However, some anomaly detection methods mainly exploit the spectral feature and do not make full use of spatial features, thus limiting the performance improvement of anomaly detection methods. Here, a novel hyperspectral anomaly detection method, called spectral&ndash;spatial complementary decision fusion, is proposed, which combines the spectral and spatial features of a hyperspectral image (HSI). In the spectral dimension, the three&ndash;dimensional Hessian matrix was first utilized to obtain three&ndash;directional feature images, in which the background pixels of the HSI were suppressed. Then, to more accurately separate the sparse matrix containing the anomaly targets in the three&ndash;directional feature images, low&ndash;rank and sparse matrix decomposition (LRSMD) with truncated nuclear norm (TNN) was adopted to obtain the sparse matrix. After that, the rough detection map was obtained from the sparse matrix through finding the Mahalanobis distance. In the spatial dimension, two&ndash;dimensional attribute filtering was employed to extract the spatial feature of HSI with a smooth background. The spatial weight image was subsequently obtained by fusing the spatial feature image. Finally, to combine the complementary advantages of each dimension, the final detection result was obtained by fusing all rough detection maps and the spatial weighting map. In the experiments, one synthetic dataset and three real&ndash;world datasets were used. The visual detection results, the three&ndash;dimensional receiver operating characteristic (3D ROC) curve, the corresponding two&ndash;dimensional ROC (2D ROC) curves, and the area under the 2D ROC curve (AUC) were utilized as evaluation indicators. Compared with nine state&ndash;of&ndash;the&ndash;art alternative methods, the experimental results demonstrate that the proposed method can achieve effective and excellent anomaly detection results