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https://www.readbyqxmd.com/read/28734115/regularized-estimation-in-sparse-high-dimensional-multivariate-regression-with-application-to-a-dna-methylation-study
#1
Haixiang Zhang, Yinan Zheng, Grace Yoon, Zhou Zhang, Tao Gao, Brian Joyce, Wei Zhang, Joel Schwartz, Pantel Vokonas, Elena Colicino, Andrea Baccarelli, Lifang Hou, Lei Liu
In this article, we consider variable selection for correlated high dimensional DNA methylation markers as multivariate outcomes. A novel weighted square-root LASSO procedure is proposed to estimate the regression coefficient matrix. A key feature of this method is tuning-insensitivity, which greatly simplifies the computation by obviating cross validation for penalty parameter selection. A precision matrix obtained via the constrained ℓ1 minimization method is used to account for the within-subject correlation among multivariate outcomes...
July 26, 2017: Statistical Applications in Genetics and Molecular Biology
https://www.readbyqxmd.com/read/28729729/a-novel-methodology-using-ct-imaging-biomarkers-to-quantify-radiation-sensitivity-in-the-esophagus-with-application-to-clinical-trials
#2
Joshua S Niedzielski, Jinzhong Yang, Francesco Stingo, Zhongxing Liao, Daniel Gomez, Radhe Mohan, Mary Martel, Tina Briere, Laurence Court
Personalized cancer therapy seeks to tailor treatment to an individual patient's biology. Therefore, a means to characterize radiosensitivity is necessary. In this study, we investigated radiosensitivity in the normal esophagus using an imaging biomarker of radiation-response and esophageal toxicity, esophageal expansion, as a method to quantify radiosensitivity in 134 non-small-cell lung cancer patients, by using K-Means clustering to group patients based on esophageal radiosensitivity. Patients within the cluster of higher response and lower dose were labelled as radiosensitive...
July 20, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28727421/shallow-representation-learning-via-kernel-pca-improves-qsar-modelability
#3
Stefano E Rensi, Russ B Altman
Linear models offer a robust, flexible, and computationally efficient set of tools for modeling quantitative structure activity relationships (QSAR), but have been eclipsed in performance by non-linear methods. Support vector machines (SVMs) and neural networks are currently among the most popular and accurate QSAR methods because they learn new representations of the data that greatly improve modelability. In this work we use shallow representation learning to improve the accuracy of L1 regularized logistic regression (LASSO) and meet the performance of Tanimoto SVM...
July 20, 2017: Journal of Chemical Information and Modeling
https://www.readbyqxmd.com/read/28724076/gbs-based-genomic-selection-for-pea-grain-yield-under-severe-terminal-drought
#4
Paolo Annicchiarico, Nelson Nazzicari, Luciano Pecetti, Massimo Romani, Barbara Ferrari, Yanling Wei, E Charles Brummer
Terminal drought is the main stress that limits pea ( L.) grain yield in Mediterranean-climate regions. This study provides an unprecedented assessment of the predictive ability of genomic selection (GS) for grain yield under severe terminal drought using genotyping-by-sequencing (GBS) data. Additional aims were to assess the GS predictive ability for different GBS data quality filters and GS models, comparing intrapopulation with interpopulation GS predictive ability and to perform genome-wide association (GWAS) studies...
July 2017: Plant Genome
https://www.readbyqxmd.com/read/28719606/prescription-medicine-use-by-pedestrians-and-the-risk-of-injurious-road-traffic-crashes-a-case-crossover-study
#5
Mélanie Née, Marta Avalos, Audrey Luxcey, Benjamin Contrand, Louis-Rachid Salmi, Annie Fourrier-Réglat, Blandine Gadegbeku, Emmanuel Lagarde, Ludivine Orriols
BACKGROUND: While some medicinal drugs have been found to affect driving ability, no study has investigated whether a relationship exists between these medicines and crashes involving pedestrians. The aim of this study was to explore the association between the use of medicinal drugs and the risk of being involved in a road traffic crash as a pedestrian. METHODS AND FINDINGS: Data from 3 French nationwide databases were matched. We used the case-crossover design to control for time-invariant factors by using each case as its own control...
July 2017: PLoS Medicine
https://www.readbyqxmd.com/read/28710702/bayesian-inference-for-biomarker-discovery-in-proteomics-an-analytic-solution
#6
Noura Dridi, Audrey Giremus, Jean-Francois Giovannelli, Caroline Truntzer, Melita Hadzagic, Jean-Philippe Charrier, Laurent Gerfault, Patrick Ducoroy, Bruno Lacroix, Pierre Grangeat, Pascal Roy
This paper addresses the question of biomarker discovery in proteomics. Given clinical data regarding a list of proteins for a set of individuals, the tackled problem is to extract a short subset of proteins the concentrations of which are an indicator of the biological status (healthy or pathological). In this paper, it is formulated as a specific instance of variable selection. The originality is that the proteins are not investigated one after the other but the best partition between discriminant and non-discriminant proteins is directly sought...
December 2017: EURASIP Journal on Bioinformatics & Systems Biology
https://www.readbyqxmd.com/read/28709428/a-systematic-comparison-of-statistical-methods-to-detect-interactions-in-exposome-health-associations
#7
Jose Barrera-Gómez, Lydiane Agier, Lützen Portengen, Marc Chadeau-Hyam, Lise Giorgis-Allemand, Valérie Siroux, Oliver Robinson, Jelle Vlaanderen, Juan R González, Mark Nieuwenhuijsen, Paolo Vineis, Martine Vrijheid, Roel Vermeulen, Rémy Slama, Xavier Basagaña
BACKGROUND: There is growing interest in examining the simultaneous effects of multiple exposures and, more generally, the effects of mixtures of exposures, as part of the exposome concept (being defined as the totality of human environmental exposures from conception onwards). Uncovering such combined effects is challenging owing to the large number of exposures, several of them being highly correlated. We performed a simulation study in an exposome context to compare the performance of several statistical methods that have been proposed to detect statistical interactions...
July 14, 2017: Environmental Health: a Global Access Science Source
https://www.readbyqxmd.com/read/28706810/a-simple-all-arthroscopic-knotless-suture-lasso-loop-technique-for-suprapectoral-biceps-tenodesis
#8
David Saper, Xinning Li
A variety of pathology of the long head of the biceps tendon can contribute to anterior shoulder pain in adults that can be managed with either arthroscopic tenotomy or tenodesis when conservative treatment fails. Biceps deformity or the Popeye sign is a major concern in patients after tenotomy. Biceps tenodesis can be performed in a variety of ways with different sized anchors and at different locations (suprapectoral or subpectoral). Several studies have shown that patient outcomes and complication rates are similar between all-arthroscopic suprapectoral biceps tenodesis and open subpectoral biceps tenodesis...
June 2017: Arthroscopy Techniques
https://www.readbyqxmd.com/read/28706808/transosseous-posterior-meniscal-root-reinsertion-using-knotless-anchor-for-tibial-fixation
#9
Alejandro Espejo-Baena, Alejandro Espejo-Reina, María Josefa Espejo-Reina, María Belén Martín-Castilla, Jaime Dalla-Rosa Nogales, Enrique Sevillano-Pérez
A technique for posterior meniscal root reinsertion is presented. With the arthroscope in the central transtendinous portal for a better view, a 5-mm transtibial tunnel is created with the aid of an anterior cruciate ligament guide open to 45°. A suture device, which consists of a long needle with an eyelet on its tip, is introduced through the tunnel with a suture thread inserted through the eyelet, while the meniscus is stabilized with a grasper inserted through the anterior portal. The meniscus is pierced with the device, and the suture thread is recovered with said grasper...
June 2017: Arthroscopy Techniques
https://www.readbyqxmd.com/read/28696674/lasso-peptide-benenodin-1-is-a-thermally-actuated-1-rotaxane-switch
#10
Chuhan Zong, Michelle Jennifer Wu, Jason Z Qin, A James Link
Mechanically interlocked molecules that change their conformation in response to stimuli have been developed by synthetic chemists as building blocks for molecular machines. Here we describe a natural product, the lasso peptide benenodin-1, which exhibits conformational switching between two distinct threaded conformers upon actuation by heat. We have determined the structures of both conformers and have characterized the kinetics and energetics of the conformational switch. Single amino acid substitutions to benenodin-1 generate peptides that are biased to a single conformer, showing that the switching behavior is potentially an evolvable trait in these peptides...
July 11, 2017: Journal of the American Chemical Society
https://www.readbyqxmd.com/read/28690368/on-the-impact-of-model-selection-on-predictor-identification-and-parameter-inference
#11
Ruth M Pfeiffer, Andrew Redd, Raymond J Carroll
We assessed the ability of several penalized regression methods for linear and logistic models to identify outcome-associated predictors and the impact of predictor selection on parameter inference for practical sample sizes. We studied effect estimates obtained directly from penalized methods (Algorithm 1), or by refitting selected predictors with standard regression (Algorithm 2). For linear models, penalized linear regression, elastic net, smoothly clipped absolute deviation (SCAD), least angle regression and LASSO had a low false negative (FN) predictor selection rates but false positive (FP) rates above 20 % for all sample and effect sizes...
2017: Computational Statistics
https://www.readbyqxmd.com/read/28682248/fused-estimation-of-sparse-connectivity-patterns-from-rest-fmri-application-to-comparison-of-children-and-adult-brains
#12
Pascal Zille, Vince D Calhoun, Julia M Stephen, Tony W Wilson, Yu-Ping Wang
In this work, we consider the problem of estimating multiple sparse, co-activated brain regions from functional magnetic resonance imaging (fMRI) observations belonging to different classes. More precisely, we propose a method to analyze similarities and differences in functional connectivity between children and young adults. Often, analysis is conducted on each class separately, and differences across classes are identified with an additional postprocessing step using adequate statistical tools. Here, we propose to rely on a generalized fused Lasso penalty, which allows us to make use of the entire dataset in order to estimate connectivity patterns that are either shared across classes, or specific to a given group...
June 29, 2017: IEEE Transactions on Medical Imaging
https://www.readbyqxmd.com/read/28678717/joint-estimation-of-multiple-conditional-gaussian-graphical-models
#13
Feihu Huang, Songcan Chen, Sheng-Jun Huang
In this paper, we propose a joint conditional graphical Lasso to learn multiple conditional Gaussian graphical models, also known as Gaussian conditional random fields, with some similar structures. Our model builds on the maximum likelihood method with the convex sparse group Lasso penalty. Moreover, our model is able to model multiple multivariate linear regressions with unknown noise covariances via a convex formulation. In addition, we develop an efficient approximated Newton's method for optimizing our model...
June 28, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28678022/eigentumors-for-prediction-of-treatment-failure-in-patients-with-early-stage-breast-cancer-using-dynamic-contrast-enhanced-mri-a-feasibility-study
#14
Hui Shan M Chan, Bas H M van der Velden, Claudette E Loo, Kenneth G A Gilhuijs
We present a radiomics model to discriminate between patients at low risk and those at high risk of treatment failure at long-term follow-up based on eigentumors: principal components computed from volumes encompassing tumors in washin and washout images of pre-treatment dynamic contrast-enhanced (DCE-) MR images. Eigentumors were computed from the images of 563 patients from the MARGINS study. Subsequently, a least absolute shrinkage selection operator (LASSO) selected candidates from the components that contained 90% of the variance of the data...
July 5, 2017: Physics in Medicine and Biology
https://www.readbyqxmd.com/read/28672073/prediction-of-treatment-outcomes-to-exercise-in-patients-with-nonremitted-major-depressive-disorder
#15
Chad D Rethorst, Charles C South, A John Rush, Tracy L Greer, Madhukar H Trivedi
BACKGROUND: Only one-third of patients with major depressive disorder (MDD) achieve remission with initial treatment. Consequently, current clinical practice relies on a "trial-and-error" approach to identify an effective treatment for each patient. The purpose of this report was to determine whether we could identify a set of clinical and biological parameters with potential clinical utility for prescription of exercise for treatment of MDD in a secondary analysis of the Treatment with Exercise Augmentation in Depression (TREAD) trial...
July 3, 2017: Depression and Anxiety
https://www.readbyqxmd.com/read/28671033/regularized-approach-for-data-missing-not-at-random
#16
Chi-Hong Tseng, Yi-Hau Chen
It is common in longitudinal studies that missing data occur due to subjects' no response, missed visits, dropout, death or other reasons during the course of study. To perform valid analysis in this setting, data missing not at random (MNAR) have to be considered. However, models for data MNAR often suffer from the identifiability issue and hence result in difficulty in estimation and computational convergence. To ameliorate this issue, we propose the LASSO and ridge-regularized selection models that regularize the missing data mechanism model to handle data MNAR, with the regularization parameter selected via a cross-validation procedure...
January 1, 2017: Statistical Methods in Medical Research
https://www.readbyqxmd.com/read/28670966/malnutrition-in-hiv-infected-children-is-an-indicator-of-severe-disease-with-an-impaired-response-to-antiretroviral-therapy
#17
Maximilian Muenchhoff, Michael Healy, Ravesh Singh, Julia Roider, Andreas Groll, Chirjeev Kindra, Thobekile Sibaya, Angeline Moonsamy, Callum McGregor, Michelle Q Phan, Alejandro Palma, Henrik Kloverpris, Alasdair Leslie, Raziya Bobat, Philip S LaRussa, Thumbi Ndung'u, Philip Jr Goulder, Magdalena E Sobieszczyk, Mohendran Archary
Objectives This observational study aimed to describe immunopathogenesis and treatment outcomes in children with and without severe acute malnutrition (SAM) and HIV-infection. Design We studied markers of microbial translocation (16sDNA), intestinal damage (iFABP), monocyte activation (sCD14), T-cell activation (CD38, HLA-DR) and immune exhaustion (PD1) in 32 HIV-infected children with and 41 HIV-infected children without SAM prior to initiation of antiretroviral therapy (ART) and cross-sectionally compared these children to 15 HIV-uninfected children with and 19 HIV-uninfected children without SAM...
July 2, 2017: AIDS Research and Human Retroviruses
https://www.readbyqxmd.com/read/28667105/bacteriocins-of-non-aureus-staphylococci-isolated-from-bovine-milk
#18
Domonique A Carson, Herman W Barkema, Sohail Naushad, Jeroen De Buck
Non-aureus staphylococci (NAS), the bacteria most commonly isolated from the bovine udder, potentially protect the udder against infection by major mastitis pathogens due to bacteriocin production. In this study, we determined the inhibitory capability of 441 bovine NAS isolates (comprising 26 species) against bovine S. aureus Furthermore, inhibiting isolates were tested against a human methicillin-resistant S. aureus (MRSA) isolate using a cross-streaking method. We determined the presence of bacteriocin clusters in NAS whole genomes using genome mining tools, BLAST, and comparison of genomes of closely related inhibiting and non-inhibiting isolates and determined the genetic organization of any identified bacteriocin biosynthetic gene clusters...
June 30, 2017: Applied and Environmental Microbiology
https://www.readbyqxmd.com/read/28666881/distinguishing-early-and-late-brain-aging-from-the-alzheimer-s-disease-spectrum-consistent-morphological-patterns-across-independent-samples
#19
Nhat Trung Doan, Andreas Engvig, Krystal Zaske, Karin Persson, Martina Jonette Lund, Tobias Kaufmann, Aldo Cordova-Palomera, Dag Alnæs, Torgeir Moberget, Anne Brækhus, Maria Lage Barca, Jan Egil Nordvik, Knut Engedal, Ingrid Agartz, Geir Selbæk, Ole A Andreassen, Lars T Westlye
Alzheimer's disease (AD) is a debilitating age-related neurodegenerative disorder. Accurate identification of individuals at risk is complicated as AD shares cognitive and brain features with aging. We applied linked independent component analysis (LICA) on three complementary measures of gray matter structure: cortical thickness, area and gray matter density of 137 AD, 78 mild (MCI) and 38 subjective cognitive impairment patients, and 355 healthy adults aged 18-78 years to identify dissociable multivariate morphological patterns sensitive to age and diagnosis...
June 27, 2017: NeuroImage
https://www.readbyqxmd.com/read/28665450/predicting-mirna-targets-for-head-and-neck-squamous-cell-carcinoma-using-an-ensemble-method
#20
Hong Gao, Hui Jin, Guijun Li
BACKGROUND: This study aimed to uncover potential microRNA (miRNA) targets in head and neck squamous cell carcinoma (HNSCC) using an ensemble method which combined 3 different methods: Pearson's correlation coefficient (PCC), Lasso and a causal inference method (i.e., intervention calculus when the directed acyclic graph (DAG) is absent [IDA]), based on Borda count election. METHODS: The Borda count election method was used to integrate the top 100 predicted targets of each miRNA generated by individual methods...
June 19, 2017: International Journal of Biological Markers
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