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https://www.readbyqxmd.com/read/29778680/land-use-regression-models-to-assess-air-pollution-exposure-in-mexico-city-using-finer-spatial-and-temporal-input-parameters
#1
Yeongkwon Son, Álvaro R Osornio-Vargas, Marie S O'Neill, Perry Hystad, José L Texcalac-Sangrador, Pamela Ohman-Strickland, Qingyu Meng, Stephan Schwander
The Mexico City Metropolitan Area (MCMA) is one of the largest and most populated urban environments in the world and experiences high air pollution levels. To develop models that estimate pollutant concentrations at fine spatiotemporal scales and provide improved air pollution exposure assessments for health studies in Mexico City. We developed finer spatiotemporal land use regression (LUR) models for PM2.5 , PM10 , O3 , NO2 , CO and SO2 using mixed effect models with the Least Absolute Shrinkage and Selection Operator (LASSO)...
May 17, 2018: Science of the Total Environment
https://www.readbyqxmd.com/read/29770256/network-inference-via-the-time-varying-graphical-lasso
#2
David Hallac, Youngsuk Park, Stephen Boyd, Jure Leskovec
Many important problems can be modeled as a system of interconnected entities, where each entity is recording time-dependent observations or measurements. In order to spot trends, detect anomalies, and interpret the temporal dynamics of such data, it is essential to understand the relationships between the different entities and how these relationships evolve over time. In this paper, we introduce the time-varying graphical lasso (TVGL) , a method of inferring time-varying networks from raw time series data...
August 2017: KDD: Proceedings
https://www.readbyqxmd.com/read/29765161/expanding-the-blup-alphabet-for-genomic-prediction-adaptable-to-the-genetic-architectures-of-complex-traits
#3
Jiabo Wang, Zhengkui Zhou, Zhe Zhang, Hui Li, Di Liu, Qin Zhang, Peter J Bradbury, Edward S Buckler, Zhiwu Zhang
Improvement of statistical methods is crucial for realizing the potential of increasingly dense genetic markers. Bayesian methods treat all markers as random effects, exhibit an advantage on dense markers, and offer the flexibility of using different priors. In contrast, genomic best linear unbiased prediction (gBLUP) is superior in computing speed, but only superior in prediction accuracy for extremely complex traits. Currently, the existing variety in the BLUP method is insufficient for adapting to new sequencing technologies and traits with different genetic architectures...
May 16, 2018: Heredity
https://www.readbyqxmd.com/read/29761595/radiomics-analysis-of-apparent-diffusion-coefficient-in-cervical-cancer-a-preliminary-study-on-histological-grade-evaluation
#4
Ying Liu, Yuwei Zhang, Runfen Cheng, Shichang Liu, Fangyuan Qu, Xiaoyu Yin, Qin Wang, Bohan Xiao, Zhaoxiang Ye
BACKGROUND: The role of apparent diffusion coefficient (ADC)-based radiomics features in evaluating histopathological grade of cervical cancer is unresolved. PURPOSE: To determine if there is a difference between radiomics features derived from center-slice 2D versus whole-tumor volumetric 3D for ADC measurements in patients with cervical cancer regarding tumor histopathological grade, and systematically assess the impact of the b value on radiomics analysis in ADC quantifications...
May 14, 2018: Journal of Magnetic Resonance Imaging: JMRI
https://www.readbyqxmd.com/read/29760737/injection-laryngoplasty-using-autologous-fat-enriched-with-adipose-derived-regenerative-stem-cells-a-safe-therapeutic-option-for-the-functional-reconstruction-of-the-glottal-gap-after-unilateral-vocal-fold-paralysis
#5
José M Lasso, Daniel Poletti, Batolomé Scola, Pedro Gómez-Vilda, Ana I García-Martín, María Eugenia Fernández-Santos
Background: Paralysis of one vocal fold leads to glottal gap and vocal fold insufficiency that has significant impact upon a patient's quality of life. Fillers have been tested to perform intracordal injections, but they do not provide perdurable results. Early data suggest that enriching fat grafts with adipose-derived regenerative cells (ADRCs) promote angiogenesis and modulate the immune response, improving graft survival. The aim of this study is to propose ADRC-enriched adipose tissue grafts as effective filler for the paralyzed vocal fold to use it for functional reconstruction of the glottal gap...
2018: Stem Cells International
https://www.readbyqxmd.com/read/29758038/novel-high-resolution-computed-tomography-based-radiomic-classifier-for-screen-identified-pulmonary-nodules-in-the-national-lung-screening-trial
#6
Tobias Peikert, Fenghai Duan, Srinivasan Rajagopalan, Ronald A Karwoski, Ryan Clay, Richard A Robb, Ziling Qin, JoRean Sicks, Brian J Bartholmai, Fabien Maldonado
PURPOSE: Optimization of the clinical management of screen-detected lung nodules is needed to avoid unnecessary diagnostic interventions. Herein we demonstrate the potential value of a novel radiomics-based approach for the classification of screen-detected indeterminate nodules. MATERIAL AND METHODS: Independent quantitative variables assessing various radiologic nodule features such as sphericity, flatness, elongation, spiculation, lobulation and curvature were developed from the NLST dataset using 726 indeterminate nodules (all ≥ 7 mm, benign, n = 318 and malignant, n = 408)...
2018: PloS One
https://www.readbyqxmd.com/read/29757605/structural-basis-for-natural-product-selection-and-export-by-bacterial-abc-transporters
#7
Maria Romano, Giuliana Fusco, Hassanul G Choudhury, Shahid Mehmood, Carol V Robinson, Séverine Zirah, Julian D Hegemann, Ewen Lescop, Mohamed A Marahiel, Sylvie Rebuffat, Alfonso De Simone, Konstantinos Beis
Bacteria under stress produce ribosomally synthesized and posttranslationally modified peptides (RiPPs) to target closely related species, such as the lasso peptide microcin J25 (MccJ25). These peptides are also toxic to the producing organisms that utilize dedicated ABC transporters to achieve self-immunity. MccJ25 is exported by the Escherichia coli ABC transporter McjD through a complex mechanism of recognition that has remained elusive. Here, we used biomolecular NMR to study this interaction and identified a region of the toxic peptide that is crucial to its recognition by the ABC transporter...
May 14, 2018: ACS Chemical Biology
https://www.readbyqxmd.com/read/29756499/machine-learning-for-outcome-prediction-in-electroencephalograph-eeg-monitored-children-in-the-intensive-care-unit
#8
Iván Sánchez Fernández, Arnold J Sansevere, Marina Gaínza-Lein, Kush Kapur, Tobias Loddenkemper
The aim of this study was to evaluate the performance of models predicting in-hospital mortality in critically ill children undergoing continuous electroencephalography (cEEG) in the intensive care unit (ICU). We evaluated the performance of machine learning algorithms for predicting mortality in a database of 414 critically ill children undergoing cEEG in the ICU. The area under the receiver operating characteristic curve (AUC) in the test subset was highest for stepwise selection/elimination models (AUC = 0...
January 1, 2018: Journal of Child Neurology
https://www.readbyqxmd.com/read/29754406/targeting-twist1-through-loss-of-function-inhibits-tumorigenicity-of-human-glioblastoma
#9
Andrei M Mikheev, Svetlana A Mikheeva, Liza J Severs, Cory C Funk, Lei Huang, José L McFaline-Figueroa, Jeanette Schwensen, Cole Trapnell, Nathan D Price, Stephen Wong, Robert C Rostomily
Twist1 (TW) is a bHLH transcription factor (TF) and master regulator of the epithelial to mesenchymal transition (EMT). In vitro, TW promotes mesenchymal change, invasion and self-renewal in glioblastoma (GBM) cells. However the potential therapeutic relevance of TW has not been established through loss of function studies in human GBM cell xenograft models. The effects of TW loss of function (gene editing and knock down) on inhibition of tumorigenicity of U87MG and GBM4 glioma stem cells were tested in orthotopic xenograft models and conditional knockdown in established flank xenograft tumors...
May 13, 2018: Molecular Oncology
https://www.readbyqxmd.com/read/29753048/grouped-gene-selection-and-multi-classification-of-acute-leukemia-via-new-regularized-multinomial-regression
#10
Juntao Li, Yanyan Wang, Tao Jiang, Huimin Xiao, Xuekun Song
Diagnosing acute leukemia is the necessary prerequisite to treating it. Multi-classification on the gene expression data of acute leukemia is help for diagnosing it which contains B-cell acute lymphoblastic leukemia (BALL), T-cell acute lymphoblastic leukemia (TALL) and acute myeloid leukemia (AML). However, selecting cancer-causing genes is a challenging problem in performing multi-classification. In this paper, weighted gene co-expression networks are employed to divide the genes into groups. Based on the dividing groups, a new regularized multinomial regression with overlapping group lasso penalty (MROGL) has been presented to simultaneously perform multi-classification and select gene groups...
May 9, 2018: Gene
https://www.readbyqxmd.com/read/29752377/outcomes-and-management-of-patients-with-severe-pulmonary-vein-stenosis-from-prior-atrial-fibrillation-ablation
#11
Pejman Raeisi-Giglou, Oussama M Wazni, Walid I Saliba, Amr Barakat, Khaldoun G Tarakji, John Rickard, Daniel Cantillon, Bryan Baranowski, Patrick J Tchou, Mandeep Bhargava, Thomas J Dresing, Thomas D Callahan, Mohamed Kanj, Bruce D Lindsay, Ayman A Hussein
BACKGROUND: Pulmonary vein (PV) stenosis remains a feared complication of atrial fibrillation ablation. Little is known about outcomes in patients with severe PV stenosis, especially about repeat ablations. METHODS: In 10 368 patients undergoing atrial fibrillation ablation (2000-2015), computed tomography scans were obtained 3 to 6 months after ablation. The clinical outcomes in severe PV stenosis were determined. RESULTS: Severe PV stenosis was diagnosed in 52 patients (0...
May 2018: Circulation. Arrhythmia and Electrophysiology
https://www.readbyqxmd.com/read/29750847/order-selection-and-sparsity-in-latent-variable-models-via-the-ordered-factor-lasso
#12
Francis K C Hui, Emi Tanaka, David I Warton
Generalized linear latent variable models (GLLVMs) offer a general framework for flexibly analyzing data involving multiple responses. When fitting such models, two of the major challenges are selecting the order, that is, the number of factors, and an appropriate structure for the loading matrix, typically a sparse structure. Motivated by the application of GLLVMs to study marine species assemblages in the Southern Ocean, we propose the Ordered Factor LASSO or OFAL penalty for order selection and achieving sparsity in GLLVMs...
May 11, 2018: Biometrics
https://www.readbyqxmd.com/read/29748895/genomic-selection-of-agronomic-traits-in-hybrid-rice-using-an-ncii-population
#13
Yang Xu, Xin Wang, Xiaowen Ding, Xingfei Zheng, Zefeng Yang, Chenwu Xu, Zhongli Hu
BACKGROUND: Hybrid breeding is an effective tool to improve yield in rice, while parental selection remains the key and difficult issue. Genomic selection (GS) provides opportunities to predict the performance of hybrids before phenotypes are measured. However, the application of GS is influenced by several genetic and statistical factors. Here, we used a rice North Carolina II (NC II) population constructed by crossing 115 rice varieties with five male sterile lines as a model to evaluate effects of statistical methods, heritability, marker density and training population size on prediction for hybrid performance...
May 10, 2018: Rice
https://www.readbyqxmd.com/read/29745499/-generalized-interaction-lasso-based-on-alternating-direction-method-of-multipliers-for-liver-disease-classification
#14
Jing Li, Xiaoyun Tong, Jinjia Wang
Features and interaction between features of liver disease is of great significance for the classification of liver disease. Based on least absolute shrinkage and selection operator (LASSO) and interaction LASSO, the generalized interaction LASSO model is proposed in this paper for liver disease classification and compared with other methods. Firstly, the generalized interaction logistic classification model was constructed and the LASSO penalty constraints were added to the interactive model parameters. Then the model parameters were solved by an efficient alternating directions method of multipliers (ADMM) algorithm...
June 1, 2017: Sheng Wu Yi Xue Gong Cheng Xue za Zhi, Journal of Biomedical Engineering, Shengwu Yixue Gongchengxue Zazhi
https://www.readbyqxmd.com/read/29740534/genomic-dna-methylation-derived-algorithm-enables-accurate-detection-of-malignant-prostate-tissues
#15
Erfan Aref-Eshghi, Laila C Schenkel, Peter Ainsworth, Hanxin Lin, David I Rodenhiser, Jean-Claude Cutz, Bekim Sadikovic
Introduction: The current methodology involving diagnosis of prostate cancer (PCa) relies on the pathology examination of prostate needle biopsies, a method with high false negative rates partly due to temporospatial, molecular, and morphological heterogeneity of prostate adenocarcinoma. It is postulated that molecular markers have a potential to assign diagnosis to a considerable portion of undetected prostate tumors. This study examines the genome-wide DNA methylation changes in PCa in search of genomic markers for the development of a diagnostic algorithm for PCa screening...
2018: Frontiers in Oncology
https://www.readbyqxmd.com/read/29739422/measuring-productivity-and-its-relationship-to-community-health-worker-performance-in-uganda-a-cross-sectional-study
#16
Naoko Kozuki, Tana Wuliji
BACKGROUND: To explore the nature of the relationship between and factors associated with productivity and performance among the community health volunteer (CHV) cadre (Village Health Teams, VHT) in Busia District, Eastern Uganda. The study was carried out to contribute to the global evidence on strategies to improve CHV productivity and performance. METHODS: This cross-sectional study was conducted with 140 VHT members as subjects and respondents. Data were collected between March and May 2013 on the performance and productivity of VHT members related to village visits and activities for saving maternal and child lives, as well as on independent factors that may be associated with these measures...
May 9, 2018: BMC Health Services Research
https://www.readbyqxmd.com/read/29731525/using-the-em-algorithm-for-bayesian-variable-selection-in-logistic-regression-models-with-related-covariates
#17
M D Koslovsky, M D Swartz, L Leon-Novelo, W Chan, A V Wilkinson
We develop a Bayesian variable selection method for logistic regression models that can simultaneously accommodate qualitative covariates and interaction terms under various heredity constraints. We use expectation-maximization variable selection (EMVS) with a deterministic annealing variant as the platform for our method, due to its proven flexibility and efficiency. We propose a variance adjustment of the priors for the coefficients of qualitative covariates, which controls false-positive rates, and a flexible parameterization for interaction terms, which accommodates user-specified heredity constraints...
2018: Journal of Statistical Computation and Simulation
https://www.readbyqxmd.com/read/29730772/genome-annotation-and-comparative-genomic-analysis-of-bacillus-subtilis-mj01-a-new-bio-degradation-strain-isolated-from-oil-contaminated-soil
#18
Touraj Rahimi, Ali Niazi, Tahereh Deihimi, Seyed Mohsen Taghavi, Shahab Ayatollahi, Esmaeil Ebrahimie
One of the main challenges in elimination of oil contamination from polluted environments is improvement of biodegradation by highly efficient microorganisms. Bacillus subtilis MJ01 has been evaluated as a new resource for producing biosurfactant compounds. This bacterium, which produces surfactin, is able to enhance bio-accessibility to oil hydrocarbons in contaminated soils. The genome of B. subtilis MJ01 was sequenced and assembled by PacBio RS sequencing technology. One big contig with a length of 4,108,293 bp without any gap was assembled...
May 5, 2018: Functional & Integrative Genomics
https://www.readbyqxmd.com/read/29729489/gene-selection-for-microarray-gene-expression-classification-using-bayesian-lasso-quantile-regression
#19
Zakariya Yahya Algamal, Rahim Alhamzawi, Haithem Taha Mohammad Ali
Gene selection has been proven to be an effective way to improve the results of many classification methods. However, existing gene selection techniques in binary classification regression are sensitive to outliers of the data, heteroskedasticity or other anomalies of the latent response. In this paper, we propose a new Bayesian hierarchical model to overcome these problems in a relatively straightforward way. In particular, we propose a new Bayesian Lasso method that employs a skewed Laplace distribution for the errors and a scaled mixture of uniform distribution for the regression parameters, together with Bayesian MCMC estimation...
April 27, 2018: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/29728898/perceptions-of-health-related-community-reentry-challenges-among-incarcerated-drug-users-in-azerbaijan-kyrgyzstan-and-ukraine
#20
Julia Rozanova, Olga Morozova, Lyuba Azbel, Chethan Bachireddy, Jacob M Izenberg, Tetiana Kiriazova, Sergiy Dvoryak, Frederick L Altice
Facing competing demands with limited resources following release from prison, people who inject drugs (PWID) may neglect health needs, with grave implications including relapse, overdose, and non-continuous care. We examined the relative importance of health-related tasks after release compared to tasks of everyday life among a total sample of 577 drug users incarcerated in Ukraine, Azerbaijan, and Kyrgyzstan. A proxy measure of whether participants identified a task as applicable (easy or hard) versus not applicable was used to determine the importance of each task...
May 4, 2018: Journal of Urban Health: Bulletin of the New York Academy of Medicine
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