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https://www.readbyqxmd.com/read/29238347/langerhans-cells-programmed-by-the-epidermis
#1
REVIEW
Kalum Clayton, Andres F Vallejo, James Davies, Sofia Sirvent, Marta E Polak
Langerhans cells (LCs) reside in the epidermis as a dense network of immune system sentinels. These cells determine the appropriate adaptive immune response (inflammation or tolerance) by interpreting the microenvironmental context in which they encounter foreign substances. In a normal physiological, "non-dangerous" situation, LCs coordinate a continuous state of immune tolerance, preventing unnecessary and harmful immune activation. Conversely, when they sense a danger signal, for example during infection or when the physical integrity of skin has been compromised as a result of a trauma, they instruct T lymphocytes of the adaptive immune system to mount efficient effector responses...
2017: Frontiers in Immunology
https://www.readbyqxmd.com/read/29237567/integrated-metabolomics-and-proteomics-analysis-of-hippocampus-in-a-rat-model-of-depression
#2
Yuqing Zhang, Shuai Yuan, Juncai Pu, Lining Yang, Xinyu Zhou, Lanxiang Liu, Xiaofeng Jiang, Hanping Zhang, Teng Teng, Lu Tian, Peng Xie
Major depressive disorder (MDD) is a prevalent and serious mental disorder with high rates of suicide and disability. However, the underlying pathogenesis of MDD is complicated and remains largely unclear. An integrated analysis of multiple types of omics data may improve comprehensive understanding of the entire molecular mechanism of MDD. In this study, we applied an integrated analysis of gas chromatography/mass spectrometry (GC-MS)-based metabolomics and isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomics to investigate changes in the hippocampus in the chronic unpredictable mild stress (CUMS) rat model of depression...
December 10, 2017: Neuroscience
https://www.readbyqxmd.com/read/29233928/integrated-molecular-characterization-of-the-lethal-pediatric-cancer-pancreatoblastoma
#3
Tomoya Isobe, Masafumi Seki, Kenichi Yoshida, Masahiro Sekiguchi, Yusuke Shiozawa, Yuichi Shiraishi, Shunsuke Kimura, Misa Yoshida, Yoshikage Inoue, Akira Yokoyama, Nobuyuki Kakiuchi, Hiromichi Suzuki, Keisuke Kataoka, Yusuke Sato, Tomoko Kawai, Kenichi Chiba, Hiroko Tanaka, Teppei Shimamura, Motohiro Kato, Akihiro Iguchi, Asahito Hama, Tomoaki Taguchi, Masaharu Akiyama, Junya Fujimura, Akiko Inoue, Tsuyoshi Ito, Takao Deguchi, Chikako Kiyotani, Tomoko Iehara, Hajime Hosoi, Akira Oka, Masashi Sanada, Yukichi Tanaka, Kenichiro Hata, Satoru Miyano, Seishi Ogawa, Junko Takita
Pancreatoblastoma (PBL) is a rare pediatric pancreatic malignancy for which the molecular pathogenesis is not understood. In this study, we report the findings of an integrated multi-omics study of whole exome and RNA sequencing as well as genome-wide copy number and methylation analyses of 10 PBL cases. The PBL genome was characterized by a high frequency of aberrant activation of the Wnt signaling pathway, either via somatic mutations of CTNNB1 (90%) and copy-neutral loss of heterozygosity (CN-LOH) of APC (10%)...
December 12, 2017: Cancer Research
https://www.readbyqxmd.com/read/29232470/how-can-molecular-abnormalities-influence-our-clinical-approach
#4
W Wei, F Giulia, S Luffer, R Kumar, B Wu, M Tavallai, R T Bekele, M J Birrer
Background: Despite improvements in diagnostics and treatment, the clinical outcome of epithelial ovarian cancer remains poor over the last three decades. Recent high-throughput genomic studies have demonstrated ovarian cancer as a highly heterogeneous entity with distinctive molecular signatures among different or even within the same histotype. In this article, we review the molecular genetics of epithelial ovarian cancer and how they have been translated into modern clinical trials, as well as their implications in patient stratification for more targeted and personalized approaches...
November 1, 2017: Annals of Oncology: Official Journal of the European Society for Medical Oncology
https://www.readbyqxmd.com/read/29227475/an-alox12-12-hete-gpr31-signaling-axis-is-a-key-mediator-of-hepatic-ischemia-reperfusion-injury
#5
Xiao-Jing Zhang, Xu Cheng, Zhen-Zhen Yan, Jing Fang, Xiaozhan Wang, Weijun Wang, Zhen-Yu Liu, Li-Jun Shen, Peng Zhang, Pi-Xiao Wang, Rufang Liao, Yan-Xiao Ji, Jun-Yong Wang, Song Tian, Xue-Yong Zhu, Yan Zhang, Rui-Feng Tian, Lin Wang, Xin-Liang Ma, Zan Huang, Zhi-Gang She, Hongliang Li
Hepatic ischemia-reperfusion (IR) injury is a common clinical issue lacking effective therapy and validated pharmacological targets. Here, using integrative 'omics' analysis, we identified an arachidonate 12-lipoxygenase (ALOX12)-12-hydroxyeicosatetraenoic acid (12-HETE)-G-protein-coupled receptor 31 (GPR31) signaling axis as a key determinant of the hepatic IR process. We found that ALOX12 was markedly upregulated in hepatocytes during ischemia to promote 12-HETE accumulation and that 12-HETE then directly binds to GPR31, triggering an inflammatory response that exacerbates liver damage...
December 11, 2017: Nature Medicine
https://www.readbyqxmd.com/read/29227469/integrative-single-cell-analysis-of-transcriptional-and-epigenetic-states-in-the-human-adult-brain
#6
Blue B Lake, Song Chen, Brandon C Sos, Jean Fan, Gwendolyn E Kaeser, Yun C Yung, Thu E Duong, Derek Gao, Jerold Chun, Peter V Kharchenko, Kun Zhang
Detailed characterization of the cell types in the human brain requires scalable experimental approaches to examine multiple aspects of the molecular state of individual cells, as well as computational integration of the data to produce unified cell-state annotations. Here we report improved high-throughput methods for single-nucleus droplet-based sequencing (snDrop-seq) and single-cell transposome hypersensitive site sequencing (scTHS-seq). We used each method to acquire nuclear transcriptomic and DNA accessibility maps for >60,000 single cells from human adult visual cortex, frontal cortex, and cerebellum...
December 11, 2017: Nature Biotechnology
https://www.readbyqxmd.com/read/29222764/optimization-of-multi-omic-genome-scale-models-methodologies-hands-on-tutorial-and-perspectives
#7
Supreeta Vijayakumar, Max Conway, Pietro Lió, Claudio Angione
Genome-scale metabolic models are valuable tools for assessing the metabolic potential of living organisms. Being downstream of gene expression, metabolism is increasingly being used as an indicator of the phenotypic outcome for drugs and therapies. We here present a review of the principal methods used for constraint-based modelling in systems biology, and explore how the integration of multi-omic data can be used to improve phenotypic predictions of genome-scale metabolic models. We believe that the large-scale comparison of the metabolic response of an organism to different environmental conditions will be an important challenge for genome-scale models...
2018: Methods in Molecular Biology
https://www.readbyqxmd.com/read/29218872/diffusion-mapping-of-drug-targets-on-disease-signaling-network-elements-reveals-drug-combination-strategies
#8
Jielin Xu, Kelly Regan-Fendt, Siyuan Deng, William E Carson, Philip R O Payne, Fuhai Li
The emergence of drug resistance to traditional chemotherapy and newer targeted therapies in cancer patients is a major clinical challenge. Reactivation of the same or compensatory signaling pathways is a common class of drug resistance mechanisms. Employing drug combinations that inhibit multiple modules of reactivated signaling pathways is a promising strategy to overcome and prevent the onset of drug resistance. However, with thousands of available FDA-approved and investigational compounds, it is infeasible to experimentally screen millions of possible drug combinations with limited resources...
2018: Pacific Symposium on Biocomputing
https://www.readbyqxmd.com/read/29215763/breast-cancer-the-translation-of-big-genomic-data-to-cancer-precision-medicine
#9
REVIEW
Siew-Kee Low, Hitoshi Zembutsu, Yusuke Nakamura
Cancer is a complex genetic disease that consequence from the accumulation of genomic alterations, in which germline variations predispose individuals to cancer and somatic alterations initiate and trigger the progression of cancer. For the past two decades, genomic research has advanced remarkably, evolving from single-gene to whole-genome screening by using genome-wide association study (GWAS) and next generation sequencing (NGS) that contributing to big genomic data. International collaborative efforts have contributed in curating these data to identify clinically significant alterations that could be used in the clinical settings...
December 7, 2017: Cancer Science
https://www.readbyqxmd.com/read/29215067/profiling-invasive-plasmodium-falciparum-merozoites-using-an-integrated-omics-approach
#10
Krishan Kumar, Prakash Srinivasan, Michael J Nold, J Kathleen Moch, Karine Reiter, Dan Sturdevant, Thomas D Otto, R Burke Squires, Raul Herrera, Vijayaraj Nagarajan, Julian C Rayner, Stephen F Porcella, Scott J Geromanos, J David Haynes, David L Narum
The symptoms of malaria are brought about by blood-stage parasites, which are established when merozoites invade human erythrocytes. Our understanding of the molecular events that underpin erythrocyte invasion remains hampered by the short-period of time that merozoites are invasive. To address this challenge, a Plasmodium falciparum gamma-irradiated long-lived merozoite (LLM) line was developed and investigated. Purified LLMs invaded erythrocytes by an increase of 10-300 fold compared to wild-type (WT) merozoites...
December 7, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29215023/a-pilot-characterization-of-the-human-chronobiome
#11
Carsten Skarke, Nicholas F Lahens, Seth D Rhoades, Amy Campbell, Kyle Bittinger, Aubrey Bailey, Christian Hoffmann, Randal S Olson, Lihong Chen, Guangrui Yang, Thomas S Price, Jason H Moore, Frederic D Bushman, Casey S Greene, Gregory R Grant, Aalim M Weljie, Garret A FitzGerald
Physiological function, disease expression and drug effects vary by time-of-day. Clock disruption in mice results in cardio-metabolic, immunological and neurological dysfunction; circadian misalignment using forced desynchrony increases cardiovascular risk factors in humans. Here we integrated data from remote sensors, physiological and multi-omics analyses to assess the feasibility of detecting time dependent signals - the chronobiome - despite the "noise" attributable to the behavioral differences of free-living human volunteers...
December 7, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29214584/personalized-medicine-what-s-in-it-for-rare-diseases
#12
Sebastian Schee Genannt Halfmann, Laura Mählmann, Lada Leyens, Matthias Reumann, Angela Brand
Personalised Medicine has become a reality over the last years. The emergence of 'omics' and big data has started revolutionizing healthcare. New 'omics' technologies lead to a better molecular characterization of diseases and a new understanding of the complexity of diseases. The approach of PM is already successfully applied in different healthcare areas such as oncology, cardiology, nutrition and for rare diseases. However, health systems across the EU are often still promoting the 'one-size fits all' approach, even if it is known that patients do greatly vary in their molecular characteristics and response to drugs and other interventions...
2017: Advances in Experimental Medicine and Biology
https://www.readbyqxmd.com/read/29213276/an-integrated-multi-omics-comparison-of-embryo-and-endosperm-tissue-specific-features-and-their-impact-on-rice-seed-quality
#13
Marc Galland, Dongli He, Imen Lounifi, Erwann Arc, Gilles Clément, Sandrine Balzergue, Stéphanie Huguet, Gwendal Cueff, Béatrice Godin, Boris Collet, Fabienne Granier, Halima Morin, Joseph Tran, Benoit Valot, Loïc Rajjou
Although rice is a key crop species, few studies have addressed both rice seed physiological and nutritional quality, especially at the tissue level. In this study, an exhaustive "multi-omics" dataset on the mature rice seed was obtained by combining transcriptomics, label-free shotgun proteomics and metabolomics from embryo and endosperm, independently. These high-throughput analyses provide a new insight on the tissue-specificity related to rice seed quality. Foremost, we pinpointed that extensive post-transcriptional regulations occur at the end of rice seed development such that the embryo proteome becomes much more diversified than the endosperm proteome...
2017: Frontiers in Plant Science
https://www.readbyqxmd.com/read/29212543/gene-gravity-like-algorithm-for-disease-gene-prediction-based-on-phenotype-specific-network
#14
Limei Lin, Tinghong Yang, Ling Fang, Jian Yang, Fan Yang, Jing Zhao
BACKGROUND: Polygenic diseases are usually caused by the dysfunction of multiple genes. Unravelling such disease genes is crucial to fully understand the genetic landscape of diseases on molecular level. With the advent of 'omic' data era, network-based methods have prominently boosted disease gene discovery. However, how to make better use of different types of data for the prediction of disease genes remains a challenge. RESULTS: In this study, we improved the performance of disease gene prediction by integrating the similarity of disease phenotype, biological function and network topology...
December 6, 2017: BMC Systems Biology
https://www.readbyqxmd.com/read/29212468/a-comparison-of-graph-and-kernel-based-omics-data-integration-algorithms-for-classifying-complex-traits
#15
Kang K Yan, Hongyu Zhao, Herbert Pang
BACKGROUND: High-throughput sequencing data are widely collected and analyzed in the study of complex diseases in quest of improving human health. Well-studied algorithms mostly deal with single data source, and cannot fully utilize the potential of these multi-omics data sources. In order to provide a holistic understanding of human health and diseases, it is necessary to integrate multiple data sources. Several algorithms have been proposed so far, however, a comprehensive comparison of data integration algorithms for classification of binary traits is currently lacking...
December 6, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/29209073/integrating-clinical-and-multiple-omics-data-for-prognostic-assessment-across-human-cancers
#16
Bin Zhu, Nan Song, Ronglai Shen, Arshi Arora, Mitchell J Machiela, Lei Song, Maria Teresa Landi, Debashis Ghosh, Nilanjan Chatterjee, Veera Baladandayuthapani, Hongyu Zhao
Multiple omic profiles have been generated for many cancer types; however, comprehensive assessment of their prognostic values across cancers is limited. We conducted a pan-cancer prognostic assessment and presented a multi-omic kernel machine learning method to systematically quantify the prognostic values of high-throughput genomic, epigenomic, and transcriptomic profiles individually, integratively, and in combination with clinical factors for 3,382 samples across 14 cancer types. We found that the prognostic performance varied substantially across cancer types...
December 5, 2017: Scientific Reports
https://www.readbyqxmd.com/read/29207610/integration-of-micrornaome-proteomics-and-metabolomics-to-analyze-arsenic-induced-malignant-cell-transformation
#17
Youyou Zhou, Yanfu Wang, Juan Su, Zheng Wu, Chao Wang, Weiming Zhong, Xiaomei Liu, Linhui Cui, Xiaoyu Zhou, Yufang Ma, Yi Xin, Jianglin Zhang, Lisha Wu, Xing Hu, Xiang Chen, Cong Peng, MingYang Gao
Long-term exposure to arsenic has been linked to tumorigenesis in different organs and tissues, such as skin; however, the detailed mechanism remains unclear. In this present study, we integrated "omics" including microRNAome, proteomics and metabolomics to investigate the potential molecular mechanisms. Compared with non-malignant human keratinocytes (HaCaT), twenty-six miRNAs were significantly altered in arsenic-induced transformed cells. Among these miRNAs, the differential expression of six miRNAs was confirmed using Q-RT-PCR, representing potential oxidative stress genes...
October 31, 2017: Oncotarget
https://www.readbyqxmd.com/read/29199021/an-integrated-systems-genetics-and-omics-toolkit-to-probe-gene-function
#18
Hao Li, Xu Wang, Daria Rukina, Qingyao Huang, Tao Lin, Vincenzo Sorrentino, Hongbo Zhang, Maroun Bou Sleiman, Danny Arends, Aaron McDaid, Peiling Luan, Naveed Ziari, Laura A Velázquez-Villegas, Karim Gariani, Zoltan Kutalik, Kristina Schoonjans, Richard A Radcliffe, Pjotr Prins, Stephan Morgenthaler, Robert W Williams, Johan Auwerx
Identifying genetic and environmental factors that impact complex traits and common diseases is a high biomedical priority. Here, we developed, validated, and implemented a series of multi-layered systems approaches, including (expression-based) phenome-wide association, transcriptome-/proteome-wide association, and (reverse-) mediation analysis, in an open-access web server (systems-genetics.org) to expedite the systems dissection of gene function. We applied these approaches to multi-omics datasets from the BXD mouse genetic reference population, and identified and validated associations between genes and clinical and molecular phenotypes, including previously unreported links between Rpl26 and body weight, and Cpt1a and lipid metabolism...
November 30, 2017: Cell Systems
https://www.readbyqxmd.com/read/29194470/idingo-integrative-differential-network-analysis-in-genomics-with-shiny-application
#19
Caleb A Class, Min Jin Ha, Veerabhadran Baladandayuthapani, Kim-Anh Do
Motivation: Differential network analysis is an important way to understand network rewiring involved in disease progression and development. Building differential networks from multiple `omics data provides insight into the holistic differences of the interactive system under different patient-specific groups. DINGO was developed to infer group-specific dependencies and build differential networks. However, DINGO and other existing tools are limited to analyze data arising from a single platform, and modeling each of the multiple 'omics data independently does not account for the hierarchical structure of the data...
November 29, 2017: Bioinformatics
https://www.readbyqxmd.com/read/29194424/functional-foods-and-lifestyle-approaches-for-diabetes-prevention-and-management
#20
REVIEW
Ahmad Alkhatib, Catherine Tsang, Ali Tiss, Theeshan Bahorun, Hossein Arefanian, Roula Barake, Abdelkrim Khadir, Jaakko Tuomilehto
Functional foods contain biologically active ingredients associated with physiological health benefits for preventing and managing chronic diseases, such as type 2 diabetes mellitus (T2DM). A regular consumption of functional foods may be associated with enhanced anti-oxidant, anti-inflammatory, insulin sensitivity, and anti-cholesterol functions, which are considered integral to prevent and manage T2DM. Components of the Mediterranean diet (MD)-such as fruits, vegetables, oily fish, olive oil, and tree nuts-serve as a model for functional foods based on their natural contents of nutraceuticals, including polyphenols, terpenoids, flavonoids, alkaloids, sterols, pigments, and unsaturated fatty acids...
December 1, 2017: Nutrients
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