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https://www.readbyqxmd.com/read/27907900/insulin-resistance-in-polycystic-ovary-syndrome-a-systematic-review-and-meta-analysis-of-euglycaemic-hyperinsulinaemic-clamp-studies
#1
Samantha Cassar, Marie L Misso, William G Hopkins, Christopher S Shaw, Helena J Teede, Nigel K Stepto
STUDY QUESTION: What is the degree of intrinsic insulin resistance (IR) in women with polycystic ovary syndrome (PCOS) and the relative contribution of BMI to overall IR based on meta-analysis of gold standard insulin clamp studies? SUMMARY ANSWER: We report an inherent reduction (-27%) of insulin sensitivity (IS) in PCOS patients, which was independent of BMI. WHAT IS ALREADY KNOWN: PCOS is prevalent, complex and underpinned by IR but controversies surround the degree of intrinsic IR in PCOS, the effect of BMI and the impact of the different diagnostic criteria (NIH versus Rotterdam) in PCOS...
November 2016: Human Reproduction
https://www.readbyqxmd.com/read/27907891/analysis-of-translation-using-polysome-profiling
#2
Héloïse Chassé, Sandrine Boulben, Vlad Costache, Patrick Cormier, Julia Morales
During the past decade, there has been growing interest in the role of translational regulation of gene expression in many organisms. Polysome profiling has been developed to infer the translational status of a specific mRNA species or to analyze the translatome, i.e. the subset of mRNAs actively translated in a cell. Polysome profiling is especially suitable for emergent model organisms for which genomic data are limited. In this paper, we describe an optimized protocol for the purification of sea urchin polysomes and highlight the critical steps involved in polysome purification...
October 7, 2016: Nucleic Acids Research
https://www.readbyqxmd.com/read/27900688/degradation-network-reconstruction-guided-by-metagenomic-data
#3
Rafael Bargiela, Manuel Ferrer
Network reconstruction procedures based on meta-"omics" data are an invaluable tool for inferring total and active set of reactions mediated by different members in a microbial community. Within them, network-based methods for automatic analysis of catabolic capacities in metagenomes are currently limited. Here, we describe the complete workflow, scripts, and commands allowing the automatic reconstruction of biodegradation networks using as an input meta-sequences generated by direct DNA sequencing.
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/27900388/data-driven-modeling-for-precision-medicine-in-pediatric-acute-liver-failure
#4
Ruben Zamora, Yoram Vodovotz, Qi Mi, Derek Barclay, Jinling Yin, Simon Horslen, David Rudnick, Kathleen M Loomes, Robert H Squires
Absence of early outcome biomarkers for Pediatric Acute Liver Failure (PALF) hinders medical and liver transplant decisions. We sought to define dynamic interactions among circulating inflammatory mediators to gain insights into PALF outcome sub-groups. Serum samples from 101 participants in the PALF study, collected over the first 7 days following enrollment, were assayed for 27 inflammatory mediators. Outcomes (Spontaneous survivors [S, n=61], Non-survivors [NS, n=12], and liver transplant patients [LTx, n=28]) were assessed at 21 days post-enrollment...
November 23, 2016: Molecular Medicine
https://www.readbyqxmd.com/read/27899995/systematic-tracking-of-disrupted-modules-identifies-significant-genes-and-pathways-in-hepatocellular-carcinoma
#5
Meng-Hui Zhang, Qin-Hai Shen, Zhao-Min Qin, Qiao-Ling Wang, Xi Chen
The objective of the present study is to identify significant genes and pathways associated with hepatocellular carcinoma (HCC) by systematically tracking the dysregulated modules of re-weighted protein-protein interaction (PPI) networks. Firstly, normal and HCC PPI networks were inferred and re-weighted based on Pearson correlation coefficient. Next, modules in the PPI networks were explored by a clique-merging algorithm, and disrupted modules were identified utilizing a maximum weight bipartite matching in non-increasing order...
November 2016: Oncology Letters
https://www.readbyqxmd.com/read/27899626/a-prior-based-integrative-framework-for-functional-transcriptional-regulatory-network-inference
#6
Alireza F Siahpirani, Sushmita Roy
No abstract text is available yet for this article.
November 29, 2016: Nucleic Acids Research
https://www.readbyqxmd.com/read/27898842/inferring-phenotypic-causal-structures-among-meat-quality-traits-and-the-application-of-a-structural-equation-model-in-japanese-black-cattle
#7
K Inoue, B D Valente, N Shoji, T Honda, K Oyama, G J M Rosa
Meat quality is one of the most important traits determining carcass price in the Japanese beef market. Optimized breeding goals and management practices for the improvement of meat quality traits requires knowledge regarding any potential functional relationships between them. In this context, the objective of this research was to infer phenotypic causal networks involving beef marbling score (BMS), beef color score (BCL), firmness of beef (FIR), texture of beef (TEX), beef fat color score (BFS), and the ratio of MUFA to SFA (MUS) from 11,855 Japanese Black cattle...
October 2016: Journal of Animal Science
https://www.readbyqxmd.com/read/27897008/tracing-co-regulatory-network-dynamics-in-noisy-single-cell-transcriptome-trajectories
#8
Pablo Cordero, Joshua M Stuart
The availability of gene expression data at the single cell level makes it possible to probe the molecular underpinnings of complex biological processes such as differentiation and oncogenesis. Promising new methods have emerged for reconstructing a progression 'trajectory' from static single-cell transcriptome measurements. However, it remains unclear how to adequately model the appreciable level of noise in these data to elucidate gene regulatory network rewiring. Here, we present a framework called Single Cell Inference of MorphIng Trajectories and their Associated Regulation (SCIMITAR) that infers progressions from static single-cell transcriptomes by employing a continuous parametrization of Gaussian mixtures in high-dimensional curves...
2016: Pacific Symposium on Biocomputing
https://www.readbyqxmd.com/read/27896968/exploring-the-reproducibility-of-probabilistic-causal-molecular-network-models
#9
Ariella Cohain, Aparna A Divaraniya, Kuixi Zhu, Joseph R Scarpa, Andrew Kasarskis, Jun Zhu, Rui Chang, Joel T Dudley, Eric E Schadt
Network reconstruction algorithms are increasingly being employed in biomedical and life sciences research to integrate large-scale, high-dimensional data informing on living systems. One particular class of probabilistic causal networks being applied to model the complexity and causal structure of biological data is Bayesian networks (BNs). BNs provide an elegant mathematical framework for not only inferring causal relationships among many different molecular and higher order phenotypes, but also for incorporating highly diverse priors that provide an efficient path for incorporating existing knowledge...
2016: Pacific Symposium on Biocomputing
https://www.readbyqxmd.com/read/27896738/inferring-genome-wide-interaction-networks
#10
Gökmen Altay, Onur Mendi
The inference of gene regulatory networks is an important process that contributes to a better understanding of biological and biomedical problems. These networks aim to capture the causal molecular interactions of biological processes and provide valuable information about normal cell physiology. In this book chapter, we introduce GNI methods, namely C3NET, RN, ARACNE, CLR, and MRNET and describe their components and working mechanisms. We present a comparison of the performance of these algorithms using the results of our previously published studies...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/27896737/construction-of-functional-gene-networks-using-phylogenetic-profiles
#11
Junha Shin, Insuk Lee
Functional constraints between genes display similar patterns of gain or loss during speciation. Similar phylogenetic profiles, therefore, can be an indication of a functional association between genes. The phylogenetic profiling method has been applied successfully to the reconstruction of gene pathways and the inference of unknown gene functions. This method requires only sequence data to generate phylogenetic profiles. This method therefore has the potential to take advantage of the recent explosion in available sequence data to reveal a significant number of functional associations between genes...
2017: Methods in Molecular Biology
https://www.readbyqxmd.com/read/27893217/multi-relational-measurement-for-latent-construct-networks
#12
Laura M Koehly, Christopher Steven Marcum
Multiple item scales have long been used to measure latent constructs on individual-level data. This is appropriate when an otherwise unobserved construct is indirectly measured by combining observable correlated characteristics that are thought to measure slightly different dimensions of that construct. Network data, which consist of observations on the relationships between a set of actors, however, are typically drawn from single-relation measurements. While this approach is sufficient for learning about discrete relations (communication, coauthorship, etc...
November 28, 2016: Psychological Methods
https://www.readbyqxmd.com/read/27892813/thinking-about-social-and-nonsocial-alternative-possibilities-in-premature-preschoolers
#13
María Dolores Roldán-Tapia, Sergio Moreno-Ríos, Rosa Cánovas-López
INTRODUCTION: Prematurely born preschoolers show developmental cognitive delay compared to full-term children. There are important neurological networks developing at preschool age related to perspective taking about the attribution of belief and to deduction with contrary-to-fact situations. Other deductive abilities may be completed during that period. METHOD: A group of very prematurely born children (N = 35) aged between 4 and 5 years was compared with a control group of children born at full term (N = 35)...
November 28, 2016: Journal of Clinical and Experimental Neuropsychology
https://www.readbyqxmd.com/read/27890449/independent-evolution-of-genomic-characters-during-major-metazoan-transitions
#14
REVIEW
Oleg Simakov, Takeshi Kawashima
Metazoan evolution encompasses a vast evolutionary time scale spanning over 600 million years. Our ability to infer ancestral metazoan characters, both morphological and functional, is limited by our understanding of the nature and evolutionary dynamics of the underlying regulatory networks. Increasing coverage of metazoan genomes enables us to identify the evolutionary changes of the relevant genomic characters such as the loss or gain of coding sequences, gene duplications, micro- and macro-synteny, and non-coding element evolution in different lineages...
November 24, 2016: Developmental Biology
https://www.readbyqxmd.com/read/27889536/compact-integration-of-multi-network-topology-for-functional-analysis-of-genes
#15
Hyunghoon Cho, Bonnie Berger, Jian Peng
The topological landscape of molecular or functional interaction networks provides a rich source of information for inferring functional patterns of genes or proteins. However, a pressing yet-unsolved challenge is how to combine multiple heterogeneous networks, each having different connectivity patterns, to achieve more accurate inference. Here, we describe the Mashup framework for scalable and robust network integration. In Mashup, the diffusion in each network is first analyzed to characterize the topological context of each node...
November 22, 2016: Cell Systems
https://www.readbyqxmd.com/read/27887570/metamis-a-metagenomic-microbial-interaction-simulator-based-on-microbial-community-profiles
#16
Grace Tzun-Wen Shaw, Yueh-Yang Pao, Daryi Wang
BACKGROUND: The complexity and dynamics of microbial communities are major factors in the ecology of a system. With the NGS technique, metagenomics data provides a new way to explore microbial interactions. Lotka-Volterra models, which have been widely used to infer animal interactions in dynamic systems, have recently been applied to the analysis of metagenomic data. RESULTS: In this paper, we present the Lotka-Volterra model based tool, the Metagenomic Microbial Interacticon Simulator (MetaMIS), which is designed to analyze the time series data of microbial community profiles...
November 25, 2016: BMC Bioinformatics
https://www.readbyqxmd.com/read/27883889/inferring-cell-state-transition-dynamics-from-lineage-trees-and-endpoint-single-cell-measurements
#17
Sahand Hormoz, Zakary S Singer, James M Linton, Yaron E Antebi, Boris I Shraiman, Michael B Elowitz
As they proliferate, living cells undergo transitions between specific molecularly and developmentally distinct states. Despite the functional centrality of these transitions in multicellular organisms, it has remained challenging to determine which transitions occur and at what rates without perturbations and cell engineering. Here, we introduce kin correlation analysis (KCA) and show that quantitative cell-state transition dynamics can be inferred, without direct observation, from the clustering of cell states on pedigrees (lineage trees)...
November 23, 2016: Cell Systems
https://www.readbyqxmd.com/read/27883053/measuring-intratumor-heterogeneity-by-network-entropy-using-rna-seq-data
#18
Youngjune Park, Sangsoo Lim, Jin-Wu Nam, Sun Kim
Intratumor heterogeneity (ITH) is observed at different stages of tumor progression, metastasis and reouccurence, which can be important for clinical applications. We used RNA-sequencing data from tumor samples, and measured the level of ITH in terms of biological network states. To model complex relationships among genes, we used a protein interaction network to consider gene-gene dependency. ITH was measured by using an entropy-based distance metric between two networks, nJSD, with Jensen-Shannon Divergence (JSD)...
November 24, 2016: Scientific Reports
https://www.readbyqxmd.com/read/27882678/a-molecular-transmission-network-of-recent-hepatitis-c-infection-in-people-with-and-without-hiv-implications-for-targeted-treatment-strategies
#19
S R Bartlett, J O Wertheim, R A Bull, G V Matthews, F M J Lamoury, K Scheffler, M Hellard, L Maher, G J Dore, A R Lloyd, T L Applegate, J Grebely
Combining phylogenetic and network methodologies has the potential to better inform targeted interventions to prevent and treat infectious diseases. This study reconstructed a molecular transmission network for people with recent hepatitis C virus (HCV) infection and modelled the impact of targeting directly acting antiviral (DAA) treatment for HCV in the network. Participants were selected from three Australian studies of recent HCV from 2004 to 2014. HCV sequence data (Core-E2) from participants at the time of recent HCV detection were analysed to infer a network by connecting pairs of sequences whose divergence was ≤...
November 24, 2016: Journal of Viral Hepatitis
https://www.readbyqxmd.com/read/27881803/inferring-animal-social-networks-and-leadership-applications-for-passive-monitoring-arrays
#20
David M P Jacoby, Yannis P Papastamatiou, Robin Freeman
Analyses of animal social networks have frequently benefited from techniques derived from other disciplines. Recently, machine learning algorithms have been adopted to infer social associations from time-series data gathered using remote, telemetry systems situated at provisioning sites. We adapt and modify existing inference methods to reveal the underlying social structure of wide-ranging marine predators moving through spatial arrays of passive acoustic receivers. From six months of tracking data for grey reef sharks (Carcharhinus amblyrhynchos) at Palmyra atoll in the Pacific Ocean, we demonstrate that some individuals emerge as leaders within the population and that this behavioural coordination is predicted by both sex and the duration of co-occurrences between conspecifics...
November 2016: Journal of the Royal Society, Interface
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