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https://www.readbyqxmd.com/read/29793096/segmentation-of-histological-images-and-fibrosis-identification-with-a-convolutional-neural-network
#1
Xiaohang Fu, Tong Liu, Zhaohan Xiong, Bruce H Smaill, Martin K Stiles, Jichao Zhao
Segmentation of histological images is one of the most crucial tasks for many biomedical analyses involving quantification of certain tissue types, such as fibrosis via Masson's trichrome staining. However, challenges are posed by the high variability and complexity of structural features in such images, in addition to imaging artifacts. Further, the conventional approach of manual thresholding is labor-intensive, and highly sensitive to inter- and intra-image intensity variations. An accurate and robust automated segmentation method is of high interest...
May 16, 2018: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/29791438/identity-by-descent-analyses-for-measuring-population-dynamics-and-selection-in-recombining-pathogens
#2
Lyndal Henden, Stuart Lee, Ivo Mueller, Alyssa Barry, Melanie Bahlo
Identification of genomic regions that are identical by descent (IBD) has proven useful for human genetic studies where analyses have led to the discovery of familial relatedness and fine-mapping of disease critical regions. Unfortunately however, IBD analyses have been underutilized in analysis of other organisms, including human pathogens. This is in part due to the lack of statistical methodologies for non-diploid genomes in addition to the added complexity of multiclonal infections. As such, we have developed an IBD methodology, called isoRelate, for analysis of haploid recombining microorganisms in the presence of multiclonal infections...
May 23, 2018: PLoS Genetics
https://www.readbyqxmd.com/read/29791039/racial-differences-in-completion-of-the-living-kidney-donor-evaluation-process
#3
Komal Kumar, James M Tonascia, Abimereki D Muzaale, Tanjala S Purnell, Shane E Ottmann, Fawaz Al Ammary, Mary G Bowring, Anna Poon, Elizabeth A King, Allan B Massie, Eric K H Chow, Alvin G Thomas, Hao Ying, Marvin Borja, Jonathan M Konel, Macey Henderson, Andrew M Cameron, Jacqueline M Garonzik-Wang, Dorry L Segev
Racial disparities in living donor kidney transplantation (LDKT) persist but the most effective target to eliminate these disparities remains unknown. One potential target could be delays during completion of the live donor evaluation process. We studied racial differences in progression through the evaluation process for 247 African American (AA) and 664 non-AA living donor candidates at our center between January 2011-March 2015. AA candidates were more likely to be obese (38% vs. 22%: p<0.001), biologically-related (66% vs...
May 23, 2018: Clinical Transplantation
https://www.readbyqxmd.com/read/29790936/simextargid-a-comprehensive-package-for-real-time-lc-ms-data-acquisition-and-analysis
#4
William M B Edmands, Josie Hayes, Stephen M Rappaport
Summary: Liquid chromatography mass spectrometry (LC-MS) is the favored method for untargeted metabolomic analysis of small molecules in biofluids. Here we present SimExTargId, an open-source R package for autonomous analysis of metabolomic data and real-time observation of experimental runs. This simultaneous, fully automated and multi-threaded (optional) package is a wrapper for vendor-independent format conversion (ProteoWizard), xcms- and CAMERA- based peak-picking, MetMSLine-based pre-processing and covariate-based statistical analysis...
May 22, 2018: Bioinformatics
https://www.readbyqxmd.com/read/29790333/autonomous-scanning-probe-microscopy-in-situ-tip-conditioning-through-machine-learning
#5
Mohammad Rashidi, Robert A Wolkow
Atomic-scale characterization and manipulation with scanning probe microscopy rely upon the use of an atomically sharp probe. Here we present automated methods based on machine learning to automatically detect and recondition the quality of the probe of a scanning tunneling microscope. As a model system, we employ these techniques on the technologically relevant hydrogen-terminated silicon surface, training the network to recognize abnormalities in the appearance of surface dangling bonds. Of the machine learning methods tested, a convolutional neural network yielded the greatest accuracy, achieving a positive identification of degraded tips in 97% of the test cases...
May 23, 2018: ACS Nano
https://www.readbyqxmd.com/read/29789714/estrogen-receptor-%C3%AE-promotes-renal-cell-carcinoma-progression-via-regulating-lncrna-hotair-mir-138-200c-204-217-associated-cerna-network
#6
Jie Ding, Chiuan-Ren Yeh, Yin Sun, Changyi Lin, Joshua Chou, Zhenyu Ou, Chawnshang Chang, Jun Qi, Shuyuan Yeh
Recent studies indicated that the estrogen receptor beta (ERβ) could affect the progression of prostate and bladder tumors, however, its roles in the renal cell carcinoma (RCC), remain to be elucidated. Here, we provide clinical evidence that ERβ expression is correlated in a negative manner with the overall survival/disease-free survival in RCC patients. Mechanism dissection revealed that targeting ERβ with ERβ-shRNA and stimulating the transactivation of ERβ with 17β-estradiol or environmental endocrine disrupting chemicals, all resulted in altering the lncRNA HOTAIR expression...
May 23, 2018: Oncogene
https://www.readbyqxmd.com/read/29789374/identification-and-characterization-of-a-novel-spontaneously-active-bursty-gabaergic-interneuron-in-the-mouse-striatum
#7
Maxime Assous, Thomas W Faust, Robert Assini, Fulva Shah, Yacouba Sidibe, James M Tepper
The recent availability of different transgenic mouse lines coupled with other modern molecular techniques has led to the discovery of an unexpectedly large cellular diversity and synaptic specificity in striatal interneuronal circuitry. Prior research has described three spontaneously active interneuron types in mouse striatal slices; the cholinergic interneuron, the neuropeptide Y-low threshold spike interneuron, and the tyrosine hydroxylase interneurons (THINs). Using transgenic Htr3a-Cre mice we now characterize a fourth population of spontaneously active striatal GABAergic interneurons termed spontaneously active bursty interneurons (SABI) because of their unique burst-firing pattern in cell-attached recordings...
May 22, 2018: Journal of Neuroscience: the Official Journal of the Society for Neuroscience
https://www.readbyqxmd.com/read/29789371/identification-of-new-risk-factors-for-rolandic-epilepsy-cnv-at-xp22-31-and-alterations-at-cholinergic-synapses
#8
Laura Addis, William Sproviero, Sanjeev V Thomas, Roberto H Caraballo, Stephen J Newhouse, Kumudini Gomez, Elaine Hughes, Maria Kinali, David McCormick, Siobhan Hannan, Silvia Cossu, Jacqueline Taylor, Cigdem I Akman, Steven M Wolf, David E Mandelbaum, Rajesh Gupta, Rick A van der Spek, Dario Pruna, Deb K Pal
BACKGROUND: Rolandic epilepsy (RE) is the most common genetic childhood epilepsy, consisting of focal, nocturnal seizures and frequent neurodevelopmental impairments in speech, language, literacy and attention. A complex genetic aetiology is presumed in most, with monogenic mutations in GRIN2A accounting for >5% of cases. OBJECTIVE: To identify rare, causal CNV in patients with RE. METHODS: We used high-density SNP arrays to analyse the presence of rare CNVs in 186 patients with RE from the UK, the USA, Sardinia, Argentina and Kerala, India...
May 22, 2018: Journal of Medical Genetics
https://www.readbyqxmd.com/read/29788739/identification-of-recurrent-risk-related-genes-and-establishment-of-support-vector-machine-prediction-model-for-gastric-cancer
#9
B Liu, J Tan, X Wang, X Liu
This study sought to investigate genes related to recurrent risk and establish a support vector machine (SVM) classifier for prediction of recurrent risk in gastric cancer (GC).Based on the gene expression profiling dataset GSE26253, feature genes that were significantly associated with survival time and status were screened out. Subsequently, protein-protein interaction (PPI) network was constructed for these feature genes, and genes in this network was optimized using betweenness centrality algorithm in order to identify genes potentially correlated with GC (named as GCGs)...
March 14, 2018: Neoplasma
https://www.readbyqxmd.com/read/29788237/diagnostic-yield-of-next-generation-sequencing-in-very-early-onset-inflammatory-bowel-diseases-a-multicenter-study
#10
Fabienne Charbit-Henrion, Marianna Parlato, Sylvain Hanein, Rémi Duclaux-Loras, Jan Nowak, Bernadette Begue, Sabine Rakotobe, Julie Bruneau, Cécile Fourrage, Olivier Alibeu, Frédéric Rieux-Laucat, Eva Lévy, Marie-Claude Stolzenberg, Fabienne Mazerolles, Sylvain Latour, Christelle Lenoir, Alain Fischer, Capucine Picard, Marina Aloi, Jorge Amil Dias, Mongi Ben Hariz, Anne Bourrier, Christian Breuer, Anne Breton, Jiri Bronski, Stephan Buderus, Mara Cananzi, Stéphanie Coopman, Clara Crémilleux, Alain Dabadie, Clémentine Dumant-Forest, Odul Egritas Gurkan, Alexandre Fabre, Aude Fischer, Marta German Diaz, Yago Gonzalez-Lama, Olivier Goulet, Graziella Guariso, Neslihan Gurcan, Matjaz Homan, Jean-Pierre Hugot, Eric Jeziorski, Evi Karanika, Alain Lachaux, Peter Lewindon, Rosa Lima, Fernando Magro, Janos Major, Georgia Malamut, Emmanuel Mas, Istvan Mattyus, Luisa M Mearin, Jan Melek, Victor Manuel Navas-Lopez, Anders Paerregaard, Cecile Pelatan, Bénédicte Pigneur, Isabel Pinto Pais, Julie Rebeuh, Claudio Romano, Nadia Siala, Caterina Strisciuglio, Michela Tempia-Caliera, Patrick Tounian, Dan Turner, Vaidotas Urbonas, Stéphanie Willot, Frank M Ruemmele, Nadine Cerf-Bensussan
Background and Aims: An expanding number of monogenic defects have been identified as causative of severe forms of very early-onset inflammatory bowel diseases (VEO-IBD). The present study aimed at defining how next-generation sequencing (NGS) methods can be used to improve identification of known molecular diagnosis and adapt treatment. Methods: 207 children were recruited in 45 Paediatric centres through an international collaborative network (ESPGHAN GENIUS working group) with a clinical presentation of severe VEO-IBD (n=185) or an anamnesis suggestive of a monogenic disorder (n=22)...
May 18, 2018: Journal of Crohn's & Colitis
https://www.readbyqxmd.com/read/29787785/junior-temperament-character-inventory-together-with-quantitative-eeg-discriminate-children-with-attention-deficit-hyperactivity-disorder-combined-subtype-from-children-with-attention-deficit-hyperactivity-disorder-combined-subtype-plus-oppositional-defiant
#11
Giuseppe A Chiarenza, Stefania Villa, Lidice Galan, Pedro Valdes-Sosa, Jorge Bosch-Bayard
Oppositional defiant disorder (ODD) is frequently associated with Attention Deficit Hyperactivity Disorder (ADHD) but no clear neurophysiological evidence exists that distinguishes the two groups. Our aim was to identify biomarkers that distinguish children with Attention Deficit Hyperactivity Disorder combined subtype (ADHD_C) from children with ADHD_C + ODD, by combining the results of quantitative EEG (qEEG) and the Junior Temperament Character Inventory (JTCI). 28 ADHD_C and 22 ADHD_C + ODD children who met the DSMV criteria participated in the study...
May 19, 2018: International Journal of Psychophysiology
https://www.readbyqxmd.com/read/29787591/pharmacophore-modeling-for-identification-of-anti-igf-1r-drugs-and-in-vitro-validation-of-fulvestrant-as-a-potential-inhibitor
#12
Samra Khalid, Rumeza Hanif, Ishrat Jabeen, Qaisar Mansoor, Muhammad Ismail
Insulin-like growth factor 1 receptor (IGF-1R) is an important therapeutic target for breast cancer treatment. The alteration in the IGF-1R associated signaling network due to various genetic and environmental factors leads the system towards metastasis. The pharmacophore modeling and logical approaches have been applied to analyze the behaviour of complex regulatory network involved in breast cancer. A total of 23 inhibitors were selected to generate ligand based pharmacophore using the tool, Molecular Operating Environment (MOE)...
2018: PloS One
https://www.readbyqxmd.com/read/29787382/machine-learning-based-dual-energy-ct-parametric-mapping
#13
Kuan-Hao Su, Jung-Wen Kuo, David W Jordan, Steven Van Hedent, Paul Klahr, Zhouping Wei, Rose Al Helo, Fan Liang, Pengjiang Qian, Gisele C Pereira, Negin Rassouli, Robert C Gilkeson, Bryan J Traughber, Chee-Wai Cheng, Raymond F Muzic
The aim is to develop and evaluate machine learning methods for generating quantitative parametric maps of effective atomic number (Z&lt;sub&gt;eff&lt;/sub&gt;), relative electron density (ρ&lt;sub&gt;e&lt;/sub&gt;), mean excitation energy (&lt;i&gt;I&lt;sub&gt;x&lt;/sub&gt;&lt;/i&gt;), and relative stopping power (RSP) from clinical dual-energy CT data. The maps could be used for material identification and radiation dose calculation. &#13; Machine learning methods of historical centroid (HC), random forest (RF), and artificial neural networks (ANN) were used to learn the relationship between dual-energy CT input data and ideal output parametric maps calculated for phantoms from the known compositions of 13 tissue substitutes...
May 22, 2018: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/29786871/gender-specific-effects-of-selection-for-drinking-in-the-dark-on-the-network-roles-of-coding-and-non-coding-rnas
#14
Ovidiu Dan Iancu, Alex Colville, Beth Wilmot, Robert Searles, Priscila Darakjian, Christina Zheng, Shannon McWeeney, Sunita Kawane, John C Crabbe, Pamela Metten, Denesa Oberbeck, Robert Hitzemann
BACKGROUND: Transcriptional differences between Heterogeneous stock (HS/NPT) mice and High Drinking in the Dark (HDID) selected mouse lines have previously been described based on microarray technology coupled with network based analysis (Iancu et al., 2013b). The network changes were reproducible in two independent selections and largely confined to two distinct network modules; in contrast differential expression appeared more specific to each selected line. The current study extends these results by utilizing RNA-Seq technology, allowing evaluation of the relationship between genetic risk and transcription of non-coding RNA; we additionally evaluate sex-specific transcriptional effects of selection...
May 22, 2018: Alcoholism, Clinical and Experimental Research
https://www.readbyqxmd.com/read/29786556/assessment-of-stem-cell-differentiation-based-on-genome-wide-expression-profiles
#15
REVIEW
Patricio Godoy, Wolfgang Schmidt-Heck, Birte Hellwig, Patrick Nell, David Feuerborn, Jörg Rahnenführer, Kathrin Kattler, Jörn Walter, Nils Blüthgen, Jan G Hengstler
In recent years, protocols have been established to differentiate stem and precursor cells into more mature cell types. However, progress in this field has been hampered by difficulties to assess the differentiation status of stem cell-derived cells in an unbiased manner. Here, we present an analysis pipeline based on published data and methods to quantify the degree of differentiation and to identify transcriptional control factors explaining differences from the intended target cells or tissues. The pipeline requires RNA-Seq or gene array data of the stem cell starting population, derived 'mature' cells and primary target cells or tissue...
July 5, 2018: Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
https://www.readbyqxmd.com/read/29786028/evaluation-of-a-distance-learning-academic-support-program-for-medical-graduates-during-rural-hospital-service-in-india
#16
Rashmi Vyas, Anand Zachariah, Isobel Swamidasan, Priya Doris, Ilene Harris
Background: Christian Medical College (CMC), Vellore, India, a tertiary care hospital, designed a year-long Fellowship in Secondary Hospital Medicine (FSHM) for CMC graduates, with the aim to support them during rural service and be motivated to consider practicing in these hospitals. The FSHM was a blend of 15 paper-based distance learning modules, 3 contact sessions, community project work, and networking. This paper reports on the evaluation of the FSHM program. Methods: The curriculum development process for the FSHM reflected the six-step approach including problem identification, needs assessment, formulating objectives, selecting educational strategies, implementation, and evaluation...
September 2017: Education for Health: Change in Training & Practice
https://www.readbyqxmd.com/read/29785561/reptb-a-gene-ontology-based-drug-repurposing-approach-for-tuberculosis
#17
Anurag Passi, Neeraj Kumar Rajput, David J Wild, Anshu Bhardwaj
Tuberculosis (TB) is the world's leading infectious killer with 1.8 million deaths in 2015 as reported by WHO. It is therefore imperative that alternate routes of identification of novel anti-TB compounds are explored given the time and costs involved in new drug discovery process. Towards this, we have developed RepTB. This is a unique drug repurposing approach for TB that uses molecular function correlations among known drug-target pairs to predict novel drug-target interactions. In this study, we have created a Gene Ontology based network containing 26,404 edges, 6630 drug and 4083 target nodes...
May 21, 2018: Journal of Cheminformatics
https://www.readbyqxmd.com/read/29785401/rheumatoid-arthritis-and-mirnas-a-critical-review-through-a-functional-view
#18
REVIEW
Maria Cristina Moran-Moguel, Stefania Petarra-Del Rio, Evangelina E Mayorquin-Galvan, Maria G Zavala-Cerna
Rheumatoid arthritis (RA) is a systemic autoimmune disease with severe joint inflammation and destruction associated with an inflammatory environment. The etiology behind RA remains to be elucidated; most updated concepts include the participation of environmental, proteomic, epigenetic, and genetic factors. Epigenetic is considered the missing link to explain genetic diversification among RA patients. Within epigenetic factors participating in RA, miRNAs are defined as small noncoding molecules with a length of approximately 22 nucleotides, capable of gene expression modulation, either negatively through inhibition of translation and degradation of the mRNA or positively through increasing the translation rate...
2018: Journal of Immunology Research
https://www.readbyqxmd.com/read/29785339/identification-of-potential-crucial-genes-and-pathways-associated-with-vein-graft-restenosis-based-on-gene-expression-analysis-in-experimental-rabbits
#19
Qiang Liu, Xiujie Yin, Mingzhu Li, Li Wan, Liqiao Liu, Xiang Zhong, Zhuoqi Liu, Qun Wang
Occlusive artery disease (CAD) is the leading cause of death worldwide. Bypass graft surgery remains the most prevalently performed treatment for occlusive arterial disease, and veins are the most frequently used conduits for surgical revascularization. However, the clinical efficacy of bypass graft surgery is highly affected by the long-term potency rates of vein grafts, and no optimal treatments are available for the prevention of vein graft restenosis (VGR) at present. Hence, there is an urgent need to improve our understanding of the molecular mechanisms involved in mediating VGR...
2018: PeerJ
https://www.readbyqxmd.com/read/29785071/identification-of-cis-regulatory-elements-associated-with-salinity-and-drought-stress-tolerance-in-rice-from-co-expressed-gene-interaction-networks
#20
Pragya Mishra, Nisha Singh, Ajay Jain, Neha Jain, Vagish Mishra, Pushplatha G, Kiran P Sandhya, Nagendra Kumar Singh, Vandna Rai
Rice, a staple food crop, is often subjected to drought and salinity stresses thereby limiting its yield potential. Since there is a cross talk between these abiotic stresses, identification of common and/or overlapping regulatory elements is pivotal for generating rice cultivars that showed tolerance towards them. Analysis of the gene interaction network (GIN) facilitates identifying the role of individual genes and their interactions with others that constitute important molecular determinants in sensing and signaling cascade governing drought and/or salinity stresses...
2018: Bioinformation
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