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https://www.readbyqxmd.com/read/28330676/stromal-gene-expression-is-predictive-for-metastatic-primary-prostate-cancer
#1
Fan Mo, Dong Lin, Mandeep Takhar, Varune Rohan Ramnarine, Xin Dong, Robert H Bell, Stanislav V Volik, Kendric Wang, Hui Xue, Yuwei Wang, Anne Haegert, Shawn Anderson, Sonal Brahmbhatt, Nicholas Erho, Xinya Wang, Peter W Gout, James Morris, R Jeffrey Karnes, Robert B Den, Eric A Klein, Edward M Schaeffer, Ashley Ross, Shancheng Ren, S Cenk Sahinalp, Yingrui Li, Xun Xu, Jun Wang, Jian Wang, Martin E Gleave, Elai Davicioni, Yinghao Sun, Yuzhuo Wang, Colin C Collins
BACKGROUND: Clinical grading systems using clinical features alongside nomograms lack precision in guiding treatment decisions in prostate cancer (PCa). There is a critical need for identification of biomarkers that can more accurately stratify patients with primary PCa. OBJECTIVE: To identify a robust prognostic signature to better distinguish indolent from aggressive prostate cancer (PCa). DESIGN, SETTING, AND PARTICIPANTS: To develop the signature, whole-genome and whole-transcriptome sequencing was conducted on five PCa patient-derived xenograft (PDX) models collected from independent foci of a single primary tumor and exhibiting variable metastatic phenotypes...
March 19, 2017: European Urology
https://www.readbyqxmd.com/read/28321948/gene-networks-show-associations-with-seed-region-connectivity
#2
Marie Forest, Yasser Iturria-Medina, Jennifer S Goldman, Claudia L Kleinman, Amanda Lovato, Kathleen Oros Klein, Alan Evans, Antonio Ciampi, Aurélie Labbe, Celia M T Greenwood
Primary patterns in adult brain connectivity are established during development by coordinated networks of transiently expressed genes; however, neural networks remain malleable throughout life. The present study hypothesizes that structural connectivity from key seed regions may induce effects on their connected targets, which are reflected in gene expression at those targeted regions. To test this hypothesis, analyses were performed on data from two brains from the Allen Human Brain Atlas, for which both gene expression and DW-MRI were available...
March 21, 2017: Human Brain Mapping
https://www.readbyqxmd.com/read/28318267/magnetic-microlassos-for-reversible-cargo-capture-transport-and-release
#3
Tao Yang, Tonguc Onur Tasci, Keith B Neeves, Ning Wu, David W M Marr
Microbot propulsion has seen increasing interest in recent years as artificial methods that overcome the well-established reversible and challenging nature of microscale fluid mechanics. While controlled movement is an important feature of microbot action, many envisioned applications also involve cargo transport where microbots must be able to load and unload contents on command while tolerating complex solution chemistry. Here we introduce a physical method that uses flexible and linked superparamagnetic colloidal chains, which can form closed rings or "lassos" in the presence of a planar rotating magnetic field...
March 20, 2017: Langmuir: the ACS Journal of Surfaces and Colloids
https://www.readbyqxmd.com/read/28315741/individual-classification-of-alzheimer-s-disease-with-diffusion-magnetic-resonance-imaging
#4
Tijn M Schouten, Marisa Koini, Frank de Vos, Stephan Seiler, Mark de Rooij, Anita Lechner, Reinhold Schmidt, Martijn van den Heuvel, Jeroen van der Grond, Serge A R B Rombouts
Diffusion magnetic resonance imaging (MRI) is a powerful non-invasive method to study white matter integrity, and is sensitive to detect differences in Alzheimer's disease (AD) patients. Diffusion MRI may be able to contribute towards reliable diagnosis of AD. We used diffusion MRI to classify AD patients (N=77), and controls (N=173). We use different methods to extract information from the diffusion MRI data. First, we use the voxel-wise diffusion tensor measures that have been skeletonised using tract based spatial statistics...
March 15, 2017: NeuroImage
https://www.readbyqxmd.com/read/28293424/application-of-penalized-linear-regression-methods-to-the-selection-of-environmental-enteropathy-biomarkers
#5
Miao Lu, Jianhui Zhou, Caitlin Naylor, Beth D Kirkpatrick, Rashidul Haque, William A Petri, Jennie Z Ma
BACKGROUND: Environmental Enteropathy (EE) is a subclinical condition caused by constant fecal-oral contamination and resulting in blunting of intestinal villi and intestinal inflammation. Of primary interest in the clinical research is to evaluate the association between non-invasive EE biomarkers and malnutrition in a cohort of Bangladeshi children. The challenges are that the number of biomarkers/covariates is relatively large, and some of them are highly correlated. METHODS: Many variable selection methods are available in the literature, but which are most appropriate for EE biomarker selection remains unclear...
2017: Biomarker Research
https://www.readbyqxmd.com/read/28292895/diagnosis-of-prostate-cancer-by-desorption-electrospray-ionization-mass-spectrometric-imaging-of-small-metabolites-and-lipids
#6
Shibdas Banerjee, Richard N Zare, Robert J Tibshirani, Christian A Kunder, Rosalie Nolley, Richard Fan, James D Brooks, Geoffrey A Sonn
Accurate identification of prostate cancer in frozen sections at the time of surgery can be challenging, limiting the surgeon's ability to best determine resection margins during prostatectomy. We performed desorption electrospray ionization mass spectrometry imaging (DESI-MSI) on 54 banked human cancerous and normal prostate tissue specimens to investigate the spatial distribution of a wide variety of small metabolites, carbohydrates, and lipids. In contrast to several previous studies, our method included Krebs cycle intermediates (m/z <200), which we found to be highly informative in distinguishing cancer from benign tissue...
March 14, 2017: Proceedings of the National Academy of Sciences of the United States of America
https://www.readbyqxmd.com/read/28288110/hrdetect-is-a-predictor-of-brca1-and-brca2-deficiency-based-on-mutational-signatures
#7
Helen Davies, Dominik Glodzik, Sandro Morganella, Lucy R Yates, Johan Staaf, Xueqing Zou, Manasa Ramakrishna, Sancha Martin, Sandrine Boyault, Anieta M Sieuwerts, Peter T Simpson, Tari A King, Keiran Raine, Jorunn E Eyfjord, Gu Kong, Åke Borg, Ewan Birney, Hendrik G Stunnenberg, Marc J van de Vijver, Anne-Lise Børresen-Dale, John W M Martens, Paul N Span, Sunil R Lakhani, Anne Vincent-Salomon, Christos Sotiriou, Andrew Tutt, Alastair M Thompson, Steven Van Laere, Andrea L Richardson, Alain Viari, Peter J Campbell, Michael R Stratton, Serena Nik-Zainal
Approximately 1-5% of breast cancers are attributed to inherited mutations in BRCA1 or BRCA2 and are selectively sensitive to poly(ADP-ribose) polymerase (PARP) inhibitors. In other cancer types, germline and/or somatic mutations in BRCA1 and/or BRCA2 (BRCA1/BRCA2) also confer selective sensitivity to PARP inhibitors. Thus, assays to detect BRCA1/BRCA2-deficient tumors have been sought. Recently, somatic substitution, insertion/deletion and rearrangement patterns, or 'mutational signatures', were associated with BRCA1/BRCA2 dysfunction...
March 13, 2017: Nature Medicine
https://www.readbyqxmd.com/read/28287983/feature-selection-based-on-structured-sparsity-a-comprehensive-study
#8
Jie Gui, Zhenan Sun, Shuiwang Ji, Dacheng Tao, Tieniu Tan
Feature selection (FS) is an important component of many pattern recognition tasks. In these tasks, one is often confronted with very high-dimensional data. FS algorithms are designed to identify the relevant feature subset from the original features, which can facilitate subsequent analysis, such as clustering and classification. Structured sparsity-inducing feature selection (SSFS) methods have been widely studied in the last few years, and a number of algorithms have been proposed. However, there is no comprehensive study concerning the connections between different SSFS methods, and how they have evolved...
April 22, 2016: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28285186/inflammatory-markers-in-late-pregnancy-in-association-with-postpartum-depression-a-nested-case-control-study
#9
Emma Bränn, Fotios Papadopoulos, Emma Fransson, Richard White, Åsa Edvinsson, Charlotte Hellgren, Masood Kamali-Moghaddam, Adrian Boström, Helgi B Schiöth, Inger Sundström-Poromaa, Alkistis Skalkidou
Recent studies indicate that the immune system adaptation during pregnancy could play a significant role in the pathophysiology of perinatal depression. The aim of this study was to investigate if inflammation markers in a late pregnancy plasma sample can predict the presence of depressive symptoms at eight weeks postpartum. Blood samples from 291 pregnant women (median and IQR for days to delivery, 13 and 7-23days respectively) comprising 63 individuals with postpartum depressive symptoms, as assessed by the Edinburgh postnatal depression scale (EPDS≥12) and/or the Mini International Neuropsychiatric Interview (M...
February 28, 2017: Psychoneuroendocrinology
https://www.readbyqxmd.com/read/28284819/associations-between-long-term-exposure-to-pm2-5-component-species-and-blood-dna-methylation-age-in-the-elderly-the-va-normative-aging-study
#10
Jamaji C Nwanaji-Enwerem, Lingzhen Dai, Elena Colicino, Youssef Oulhote, Qian Di, Itai Kloog, Allan C Just, Lifang Hou, Pantel Vokonas, Andrea A Baccarelli, Marc G Weisskopf, Joel D Schwartz
BACKGROUND: Long-term PM2.5 exposure and aging have been implicated in multiple shared diseases; studying their relationship is a promising strategy to further understand the adverse impact of PM2.5 on human health. OBJECTIVE: We assessed the relationship of major PM2.5 component species (ammonium, elemental carbon, organic carbon, nitrate, and sulfate) with Horvath and Hannum DNA methylation (DNAm) age, two DNA methylation-based predictors of chronological age...
March 8, 2017: Environment International
https://www.readbyqxmd.com/read/28280617/identifying-prognostic-intratumor-heterogeneity-using-pre-and-post-radiotherapy-18f-fdg-pet-images-for-pancreatic-cancer-patients
#11
Yong Yue, Arsen Osipov, Benedick Fraass, Howard Sandler, Xiao Zhang, Nicholas Nissen, Andrew Hendifar, Richard Tuli
BACKGROUND: To stratify risks of pancreatic adenocarcinoma (PA) patients using pre- and post-radiotherapy (RT) PET/CT images, and to assess the prognostic value of texture variations in predicting therapy response of patients. METHODS: Twenty-six PA patients treated with RT from 2011-2013 with pre- and post-treatment 18F-FDG-PET/CT scans were identified. Tumor locoregional texture was calculated using 3D kernel-based approach, and texture variations were identified by fitting discrepancies of texture maps of pre- and post-treatment images...
February 2017: Journal of Gastrointestinal Oncology
https://www.readbyqxmd.com/read/28280088/radiomics-features-of-multiparametric-mri-as-novel-prognostic-factors-in-advanced-nasopharyngeal-carcinoma
#12
Shuixing Zhang, Bin Zhang, Jie Tian, Di Dong, Dong Sheng Gu, Yu Hao Dong, Lu Zhang, Zhou Yang Lian, Jing Liu, Xiao Ning Luo, Shu Fang Pei, Xiao Kai Mo, Wen Hui Huang, Fu Sheng Ouyang, Bao Liang Guo, Long Liang, Wenbo Chen, Chang H Liang
PURPOSE: To identify MRI-based radiomics as prognostic factors in patients with advanced nasopharyngeal carcinoma (NPC). EXPERIMENTAL DESIGN: One-hundred and eighteen patients (training cohort: n = 88; validation cohort: n = 30) with advanced NPC were enrolled. A total of 970 radiomics features were extracted from T2-weighted (T2-w) and contrast-enhanced T1-weighted (CET1-w) MRI. Least absolute shrinkage and selection operator (LASSO) regression was applied to select features for progression-free survival (PFS) nomograms...
March 9, 2017: Clinical Cancer Research: An Official Journal of the American Association for Cancer Research
https://www.readbyqxmd.com/read/28275541/pitchperfect-primary-intracranial-hemorrhage-probability-estimation-using-random-forests-on-ct
#13
John Muschelli, Elizabeth M Sweeney, Natalie L Ullman, Paul Vespa, Daniel F Hanley, Ciprian M Crainiceanu
INTRODUCTION: Intracerebral hemorrhage (ICH), where a blood vessel ruptures into areas of the brain, accounts for approximately 10-15% of all strokes. X-ray computed tomography (CT) scanning is largely used to assess the location and volume of these hemorrhages. Manual segmentation of the CT scan using planimetry by an expert reader is the gold standard for volume estimation, but is time-consuming and has within- and across-reader variability. We propose a fully automated segmentation approach using a random forest algorithm with features extracted from X-ray computed tomography (CT) scans...
2017: NeuroImage: Clinical
https://www.readbyqxmd.com/read/28274574/a-risk-model-for-prediction-of-1-year-mortality-in-patients-undergoing-mitraclip-implantation
#14
Sergio Buccheri, Davide Capodanno, Marco Barbanti, Antonio Popolo Rubbio, Maria Elena Di Salvo, Salvatore Scandura, Sarah Mangiafico, Giuseppe Ronsivalle, Marta Chiarandà, Piera Capranzano, Carmelo Grasso, Corrado Tamburino
There is a lack of specific tools for risk stratification in patients who undergo MitraClip implantation. We aimed at combining preprocedural variables with prognostic impact into a specific risk model for the prediction of 1-year mortality in patients undergoing MitraClip implantation. A total of 311 consecutive patients who underwent MitraClip implantation were included. A lasso-penalized Cox-proportional hazard regression model was used to identify independent predictors of 1-year all-cause mortality. A nomogram (GRASP [Getting Reduction of mitrAl inSufficiency by Percutaneous clip implantation] nomogram) was obtained from the Cox model...
February 10, 2017: American Journal of Cardiology
https://www.readbyqxmd.com/read/28273693/outcome-adaptive-lasso-variable-selection-for-causal-inference
#15
Susan M Shortreed, Ashkan Ertefaie
Methodological advancements, including propensity score methods, have resulted in improved unbiased estimation of treatment effects from observational data. Traditionally, a "throw in the kitchen sink" approach has been used to select covariates for inclusion into the propensity score, but recent work shows including unnecessary covariates can impact both the bias and statistical efficiency of propensity score estimators. In particular, the inclusion of covariates that impact exposure but not the outcome, can inflate standard errors without improving bias, while the inclusion of covariates associated with the outcome but unrelated to exposure can improve precision...
March 8, 2017: Biometrics
https://www.readbyqxmd.com/read/28269553/decoding-force-from-deep-brain-electrodes-in-parkinsonian-patients
#16
Syed A Shah, Huiling Tan, Peter Brown
Limitations of many Brain Machine Interface (BMI) systems using invasive electrodes include reliance on single neurons and decoding limited to kinematics only. This study investigates whether force-related information is present in the local field potential (LFP) recorded with deep brain electrodes using data from 14 patients with Parkinson's disease. A classifier based on logistic regression (LR) is developed to classify various force stages, using 10-fold cross validation. Least Absolute and Shrinkage Operator (Lasso) is then employed in order to identify the features with the most predictivity...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268987/identifying-individual-sleep-apnea-hypoapnea-epochs-using-smartphone-based-pulse-oximetry
#17
Ainara Garde, Parastoo Dekhordi, J Mark Ansermino, Guy A Dumont
Sleep apnea, characterized by frequent pauses in breathing during sleep, poses a serious threat to the healthy growth and development of children. Polysomnography (PSG), the gold standard for sleep apnea diagnosis, is resource intensive and confined to sleep laboratories, thus reducing its accessibility. Pulse oximetry alone, providing blood oxygen saturation (SpO2) and blood volume changes in tissue (PPG), has the potential to identify children with sleep apnea. Thus, we aim to develop a tool for at-home sleep apnea screening that provides a detailed and automated 30 sec epoch-by-epoch sleep apnea analysis...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268886/catheter-simulator-software-tool-to-generate-electrograms-of-any-multi-polar-diagnostic-catheter-from-3d-atrial-tissue
#18
Kristina E Shillieto, Prasanth Ganesan, Anthony J Salmin, Elizabeth M Cherry, Arkady M Pertsov, Behnaz Ghoraani
Simulations are excellent tools for assessing new therapeutic strategies and are often conducted before implementing new therapy options in a clinical practice. For patients suffering from a heart arrhythmia, the main source of information comes from an intracardiac catheter. One of the common catheters is a Lasso multi-pole diagnostic catheter, which is a catheter that has 20 electrodes in a circular pattern. In this paper, we developed algorithm and simulation software that allows the users to place a multi-pole catheter on the atrial endocardial surface and record electrograms...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268626/multistep-model-for-predicting-upper-limb-3d-isometric-force-application-from-pre-movement-electrocorticographic-features
#19
Jing Wu, Benjamin R Shuman, Bingni W Brunton, Katherine M Steele, Jared D Olson, Rajesh P N Rao, Jeffrey G Ojemann
Neural correlates of movement planning onset and direction may be present in human electrocorticography in the signal dynamics of both motor and non-motor cortical regions. We use a three-stage model of jPCA reduced-rank hidden Markov model (jPCA-RR-HMM), regularized shrunken-centroid discriminant analysis (RDA), and LASSO regression to extract direction-sensitive planning information and movement onset in an upper-limb 3D isometric force task in a human subject. This mode achieves a relatively high true positive force-onset prediction rate of 60% within 250ms, and an above-chance 36% accuracy (17% chance) in predicting one of six planned 3D directions of isometric force using pre-movement signals...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28268607/neural-decoding-of-code-modulated-visual-evoked-potentials-by-spatio-temporal-inverse-filtering-for-brain-computer-interfaces
#20
Jun-Ichi Sato, Yoshikazu Washizawa
This study addresses neural decoding of a code modulated visual evoked potentials (c-VEPs). c-VEP was recently developed, and applied to brain computer interfaces (BCIs). c-VEP BCI exhibits faster communication speed than existing VEP-based BCIs. In c-VEP BCI, the canonical correlation analysis (CCA) that maximizes the correlation between an averaged signal and single trial signals is often used for the spatial filter. However, CCA does not utilize information of given PN sequence, and hence, the filtered signal may not have properties of PN sequence...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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