Gut dysbiosis has the potential to reduce sexual attractiveness of female mice

Here, we showed that antibiotic treatment significantly restructured gut microbiota composition of both mouse males and females. Males, regardless of antibiotic treatment, exhibited higher propensity to interact with the control females than the antibiotic-treated females

KGG: A systematic biological Knowledge-based mining system for Genome-wide Genetic studies

  KGG (Knowledge-based mining system for Genome-wide Genetic studies) is a software tool to perform knowledge-based secondary analyses of p-values from genome-wide association studies (GWAS). The knowledge-based secondary analyses include gene-based, gene-pair-based and gene-set based association analysis.It is implemented by Java with a user-friendly graphic interface to facilitate data analysis and result visualization. Build on advanced algorithms, it is able to process up to 10 million variants in several hours with 15GB RAM on a workstation.  KGG4 currently provides 6 types of secondary analyses:  Gene-based association;   Conditional gene-based association;  Multivariate gene-based association;    Gene-pair-based association;  Gene-set-based association;  Driver-tissue estimation. For more details of KGG, see http://grass.cgs.hku.hk/limx/kgg.</p

KGG: A systematic biological Knowledge-based mining system for Genome-wide Genetic studies

KGG (Knowledge-based mining system for Genome-wide Genetic studies) is a software tool to perform knowledge-based secondary analyses of p-values from genome-wide association studies (GWAS). The knowledge-based secondary analyses include gene-based, gene-pair-based and gene-set based association analysis.It is implemented by Java with a user-friendly graphic interface to facilitate data analysis and result visualization. Build on advanced algorithms, it is able to process up to 10 million variants in several hours with 15GB RAM on a workstation.  KGG4 currently provides 6 types of secondary analyses:  Gene-based association;   Conditional gene-based association;  Multivariate gene-based association;    Gene-pair-based association;  Gene-set-based association;  Driver-tissue estimation. For details and an executable version of KGG, see http://grass.cgs.hku.hk/limx/kgg.</p

A Sliding Window Variational Outlier-Robust Kalman Filter based on Student's t Noise Modelling

Existing robust state estimation methods are generally unable to distinguish model uncertainties (state outliers) from measurement outliers as they only exploit the current measurement. In this paper, the measurements in a sliding window are therefore utilized to better distinguish them, and an adaptive method is embedded, leading to a sliding window variational outlier-robust Kalman filter based on Student's t noise modelling. Target tracking simulations and experiments show that the tracking accuracy and consistency of the proposed filter are superior to those of the existing state-of-the-art outlier-robust methods thanks to the improved ability to identify the outliers but at a cost of greater computational burden.</p

Presentation_1_Genome-Wide Association Study Identifies New Risk Loci for Progression of Schistosomiasis Among the Chinese Population.pptx

Schistosoma japonicum infections, which lead to local inflammatory responses to schistosome eggs trapped in host tissues, can result in long-term, severe complications. The development of schistosomiasis may result from a complex interaction between the pathogenic, environmental, and host genetic components. Notably, the genetic factors that influence the development of schistosomiasis complications are poorly understood. Here we performed a genome-wide association study on multiple schistosomiasis-related phenotypes of 637 unrelated schistosomiasis patients in the Chinese population. Among three indicators of liver damage, we identified two novel, genome-wide significant single-nucleotide polymorphisms (SNPs) rs34486793 (P = 1.415 × 10-8) and rs2008259 (P = 6.78 × 10-8) at locus 14q32.2 as well as a gene, PMEPA1, at 20q13.31 (index rs62205791, P = 6.52 × 10-7). These were significantly associated with serum levels of hyaluronic acid (HA). In addition, RASIP1 and MAMSTR at 19q13.33 (index rs62132778, P = 1.72 × 10-7) were significantly associated with serum levels of aspartate aminotransferase (AST), and TPM1 at 15q22.2 (index rs12442303, P = 4.39 × 10-7) was significantly associated with serum levels of albumin. In schistosomiasis clinical signs, ITIH4 at 3p21.1 (index rs2239548) was associated with portal vein diameter (PVD) class, an indicator of portal hypertension, and OGDHL at 10q11.23 (index rs1258172) was related to ascites grade. We also detected an increased expression of these six genes in livers of mice with severe schistosomiasis. Summary data-based Mendelian randomization analyses indicated that ITIH4, PMEPA1 and MAMSTR were pleiotropically associated with PVD class, HA and AST, respectively.</p

A Sliding Window Variational Outlier-Robust Kalman Filter based on Student's t Noise Modelling

Existing robust state estimation methods are generally unable to distinguish model uncertainties (state outliers) from measurement outliers as they only exploit the current measurement. In this paper, the measurements in a sliding window are therefore utilized to better distinguish them, and an adaptive method is embedded, leading to a sliding window variational outlier-robust Kalman filter based on Student's t noise modelling. Target tracking simulations and experiments show that the tracking accuracy and consistency of the proposed filter are superior to those of the existing state-of-the-art outlier-robust methods thanks to the improved ability to identify the outliers but at a cost of greater computational burden.</p

Table_1_Genome-Wide Association Study Identifies New Risk Loci for Progression of Schistosomiasis Among the Chinese Population.xlsx

Schistosoma japonicum infections, which lead to local inflammatory responses to schistosome eggs trapped in host tissues, can result in long-term, severe complications. The development of schistosomiasis may result from a complex interaction between the pathogenic, environmental, and host genetic components. Notably, the genetic factors that influence the development of schistosomiasis complications are poorly understood. Here we performed a genome-wide association study on multiple schistosomiasis-related phenotypes of 637 unrelated schistosomiasis patients in the Chinese population. Among three indicators of liver damage, we identified two novel, genome-wide significant single-nucleotide polymorphisms (SNPs) rs34486793 (P = 1.415 × 10-8) and rs2008259 (P = 6.78 × 10-8) at locus 14q32.2 as well as a gene, PMEPA1, at 20q13.31 (index rs62205791, P = 6.52 × 10-7). These were significantly associated with serum levels of hyaluronic acid (HA). In addition, RASIP1 and MAMSTR at 19q13.33 (index rs62132778, P = 1.72 × 10-7) were significantly associated with serum levels of aspartate aminotransferase (AST), and TPM1 at 15q22.2 (index rs12442303, P = 4.39 × 10-7) was significantly associated with serum levels of albumin. In schistosomiasis clinical signs, ITIH4 at 3p21.1 (index rs2239548) was associated with portal vein diameter (PVD) class, an indicator of portal hypertension, and OGDHL at 10q11.23 (index rs1258172) was related to ascites grade. We also detected an increased expression of these six genes in livers of mice with severe schistosomiasis. Summary data-based Mendelian randomization analyses indicated that ITIH4, PMEPA1 and MAMSTR were pleiotropically associated with PVD class, HA and AST, respectively.</p

Adaptive Recursive Decentralized Cooperative Localization for Multirobot Systems With Time-Varying Measurement Accuracy

Decentralized cooperative localization (DCL) is a promising method to determine accurate multi-robot poses (i.e., positions and orientations) for robot teams operating in an environment without absolutenavigation information. Existing DCL methods often use fixed measurement noise covariance matricesfor multi-robot pose estimation, however, their performance degrades when the measurement noisecovariance matrices are time-varying. To address this problem, in this paper, a novel adaptive recursiveDCL method is proposed for multi-robot systems with time-varying measurement accuracy. Each robotestimates its pose and measurement noise covariance matrices simultaneously in a decentralized mannerbased on the constructed hierarchical Gaussian models using the variational Bayesian approach. Sim-ulation and experimental results show that the proposed method has improved cooperative localization accuracy and estimation consistency but slightly heavier computational load than the existing recursive DCL method.<br

Summary of 45S rDNA FISH Signals and DNA methylation.

<p>Summary of 45S rDNA FISH Signals and DNA methylation.</p

FISH and karyogram analysis of <i>J. curcas</i> prometaphase chromosomes.

<p><b>A:</b> FISH image showing 45S rDNA probe signals on <i>J. curcas</i> metaphase chromosomes. <b>B:</b> Numbered <i>J. curcas</i> metaphase chromosomes from A. <b>C:</b> Karyogram of <i>J. curcas</i> somatic metaphase chromosomes. Scale bars = 5 µm.</p