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https://www.readbyqxmd.com/read/28428864/integrating-biogeography-threat-and-evolutionary-data-to-explore-extinction-crisis-in-the-taxonomic-group-of-cycads
#1
Kowiyou Yessoufou, Barnabas H Daru, Respinah Tafirei, Hosam O Elansary, Isaac Rampedi
Will the ongoing extinction crisis cause a severe loss of evolutionary information accumulated over millions of years on the tree of life? This question has been largely explored, particularly for vertebrates and angiosperms. However, no equivalent effort has been devoted to gymnosperms. Here, we address this question focusing on cycads, the gymnosperm group exhibiting the highest proportion of threatened species in the plant kingdom. We assembled the first complete phylogeny of cycads and assessed how species loss under three scenarios would impact the cycad tree of life...
April 2017: Ecology and Evolution
https://www.readbyqxmd.com/read/28428140/automated-annotation-and-classification-of-bi-rads-assessment-from-radiology-reports
#2
Sergio M Castro, Eugene Tseytlin, Olga Medvedeva, Kevin Mitchell, Shyam Visweswaran, Tanja Bekhuis, Rebecca S Jacobson
The Breast Imaging Reporting and Data System (BI-RADS) was developed to reduce variation in the descriptions of findings. Manual analysis of breast radiology report data is challenging but is necessary for clinical and healthcare quality assurance activities. The objective of this study is to develop a natural language processing (NLP) system for automated BI-RADS categories extraction from breast radiology reports. We evaluated an existing rule-based NLP algorithm, and then we developed and evaluated our own method using a supervised machine learning approach...
April 17, 2017: Journal of Biomedical Informatics
https://www.readbyqxmd.com/read/28427384/imbalanced-target-prediction-with-pattern-discovery-on-clinical-data-repositories
#3
Tak-Ming Chan, Yuxi Li, Choo-Chiap Chiau, Jane Zhu, Jie Jiang, Yong Huo
BACKGROUND: Clinical data repositories (CDR) have great potential to improve outcome prediction and risk modeling. However, most clinical studies require careful study design, dedicated data collection efforts, and sophisticated modeling techniques before a hypothesis can be tested. We aim to bridge this gap, so that clinical domain users can perform first-hand prediction on existing repository data without complicated handling, and obtain insightful patterns of imbalanced targets for a formal study before it is conducted...
April 20, 2017: BMC Medical Informatics and Decision Making
https://www.readbyqxmd.com/read/28426676/economic-injury-levels-for-asian-citrus-psyllid-control-in-process-oranges-from-mature-trees-with-high-incidence-of-huanglongbing
#4
Cesar Monzo, Philip A Stansly
The Asian citrus psyllid (ACP), Diaphorina citri Kuwayama, is the key pest of citrus wherever it occurs due to its role as vector of huanglongbing (HLB) also known as citrus greening disease. Insecticidal vector control is considered to be the primary strategy for HLB management and is typically intense owing to the severity of this disease. While this approach slows spread and also decreases severity of HLB once the disease is established, economic viability of increasingly frequent sprays is uncertain. Lacking until now were studies evaluating the optimum frequency of insecticide applications to mature trees during the growing season under conditions of high HLB incidence...
2017: PloS One
https://www.readbyqxmd.com/read/28425947/deep-count-fruit-counting-based-on-deep-simulated-learning
#5
Maryam Rahnemoonfar, Clay Sheppard
Recent years have witnessed significant advancement in computer vision research based on deep learning. Success of these tasks largely depends on the availability of a large amount of training samples. Labeling the training samples is an expensive process. In this paper, we present a simulated deep convolutional neural network for yield estimation. Knowing the exact number of fruits, flowers, and trees helps farmers to make better decisions on cultivation practices, plant disease prevention, and the size of harvest labor force...
April 20, 2017: Sensors
https://www.readbyqxmd.com/read/28424352/chromatin-module-inference-on-cellular-trajectories-identifies-key-transition-points-and-poised-epigenetic-states-in-diverse-developmental-processes
#6
Sushmita Roy, Rupa Sridharan
Changes in chromatin state play important roles in cell fate transitions. Current computational approaches to analyze chromatin modifications across multiple cell types do not model how the cell types are related on a lineage or over time. To overcome this limitation, we have developed a method called CMINT (Chromatin Module INference on Trees), a probabilistic clustering approach to systematically capture chromatin state dynamics across multiple cell types. Compared to existing approaches, CMINT can handle complex lineage topologies, capture higher quality clusters, and reliably detect chromatin transitions between cell types...
April 19, 2017: Genome Research
https://www.readbyqxmd.com/read/28424069/ankplex-algorithmic-structure-for-refinement-of-near-native-ankyrin-protein-docking
#7
Tanchanok Wisitponchai, Watshara Shoombuatong, Vannajan Sanghiran Lee, Kuntida Kitidee, Chatchai Tayapiwatana
BACKGROUND: Computational analysis of protein-protein interaction provided the crucial information to increase the binding affinity without a change in basic conformation. Several docking programs were used to predict the near-native poses of the protein-protein complex in 10 top-rankings. The universal criteria for discriminating the near-native pose are not available since there are several classes of recognition protein. Currently, the explicit criteria for identifying the near-native pose of ankyrin-protein complexes (APKs) have not been reported yet...
April 19, 2017: BMC Bioinformatics
https://www.readbyqxmd.com/read/28423633/novel-lincrna-slinky-is-a-prognostic-biomarker-in-kidney-cancer
#8
Xue Gong, Zurab Siprashvili, Okyaz Eminaga, Zhewei Shen, Yusuke Sato, Haruki Kume, Yukio Homma, Seishi Ogawa, Paul A Khavari, Jonathan R Pollack, James D Brooks
Clear cell renal cell carcinomas (ccRCC) show a broad range of clinical behavior, and prognostic biomarkers are needed to stratify patients for appropriate management. We sought to determine whether long intergenic non-coding RNAs (lincRNAs) might predict patient survival. Candidate prognostic lincRNAs were identified by mining The Cancer Genome Atlas (TCGA) transcriptome (RNA-seq) data on 466 ccRCC cases (randomized into discovery and validation sets) annotated for ~21,000 lncRNAs. A previously uncharacterized lincRNA, SLINKY (Survival-predictive LINcRNA in KidneY cancer), was the top-ranked prognostic lincRNA, and validated in an independent University of Tokyo cohort (P=0...
March 21, 2017: Oncotarget
https://www.readbyqxmd.com/read/28422671/structured-learning-of-tree-potentials-in-crf-for-image-segmentation
#9
Fayao Liu, Guosheng Lin, Ruizhi Qiao, Chunhua Shen
We propose a new approach to image segmentation, which exploits the advantages of both conditional random fields (CRFs) and decision trees. In the literature, the potential functions of CRFs are mostly defined as a linear combination of some predefined parametric models, and then, methods, such as structured support vector machines, are applied to learn those linear coefficients. We instead formulate the unary and pairwise potentials as nonparametric forests--ensembles of decision trees, and learn the ensemble parameters and the trees in a unified optimization problem within the large-margin framework...
April 13, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28422666/efficient-knn-classification-with-different-numbers-of-nearest-neighbors
#10
Shichao Zhang, Xuelong Li, Ming Zong, Xiaofeng Zhu, Ruili Wang
k nearest neighbor (kNN) method is a popular classification method in data mining and statistics because of its simple implementation and significant classification performance. However, it is impractical for traditional kNN methods to assign a fixed k value (even though set by experts) to all test samples. Previous solutions assign different k values to different test samples by the cross validation method but are usually time-consuming. This paper proposes a kTree method to learn different optimal k values for different test/new samples, by involving a training stage in the kNN classification...
April 12, 2017: IEEE Transactions on Neural Networks and Learning Systems
https://www.readbyqxmd.com/read/28421698/historical-harvests-reduce-neighboring-old-growth-basal-area-across-a-forest-landscape
#11
David M Bell, Thomas A Spies, Robert Pabst
While advances in remote sensing have made stand, landscape, and regional assessments of the direct impacts of disturbance on forests quite common, the edge influence of timber harvesting on the structure of neighboring unharvested forests has not been examined extensively. In this study, we examine the impact of historical timber harvests on basal area patterns of neighboring old-growth forests to assess the magnitude and scale of harvest edge influence in a forest landscape of western Oregon, USA. We used lidar data and forest plot measurements to construct 30-m resolution live tree basal area maps in lower and middle elevation mature and old-growth forests...
April 19, 2017: Ecological Applications: a Publication of the Ecological Society of America
https://www.readbyqxmd.com/read/28420333/strategies-and-cost-effectiveness-evaluation-of-persistent-albuminuria-screening-among-high-risk-population-of-chronic-kidney-disease
#12
Huaiyu Wang, Li Yang, Fang Wang, Luxia Zhang
BACKGROUND: Screening for persistent albuminuria among the high-risk population is important for early detection of CKD while studies regarding screening protocol and related cost-effectiveness analysis are limited. This study explored a feasible and cost-efficient screening strategy for detecting persistent albuminuria among the high-risk population. METHODS: A cohort study including 157 clinically stable outpatients with a risk factor of CKD and whose laboratory tests revealed an albumin-creatinine-ratio (ACR) between 30 and 300 mg/g of creatinine during the previous 12 months was conducted to assess the validity of alternative screening strategies...
April 18, 2017: BMC Nephrology
https://www.readbyqxmd.com/read/28420230/an-unambiguous-nomenclature-for-the-acyl-quinic-acids-commonly-known-as-chlorogenic-acids
#13
László Abrankó, Michael N Clifford
The history of the acyl-quinic acids is briefly reviewed, the merits and limitations of the various nomenclature systems applicable critically compared, and their limitations highlighted, in particular their inability to provide an unambiguous description of all quinic acid enantiomers and diastereo-isomers and associated acyl-quinic acids Recommendations are made for a nomenclature system which in combination with IUPAC numbering achieves this objective. A comprehensive set of structures for the quinic acid enantiomers and diastereo-isomers is presented...
April 18, 2017: Journal of Agricultural and Food Chemistry
https://www.readbyqxmd.com/read/28419509/automatic-diagnosis-of-vulvovaginal-candidiasis-from-pap-smear-images
#14
M Momenzadeh, M Sehhati, A Mehri Dehnavi, A Talebi, H Rabbani
Vulvovaginal candidiasis (VVC) is the most common genital infections that are seen every day in clinics. This infection is due to excessive growth of Candida that are normally present in the vagina in small numbers. Diagnosis of VVC is routinely done by direct microscopy of Pap smear samples and searching for the Candida in the Pap smear glass slides. This manual method is subjective, time consuming, labour-intensive and tedious. This study presents a computer-aided diagnostic (CAD) method to improve human diagnosis of VVC...
April 17, 2017: Journal of Microscopy
https://www.readbyqxmd.com/read/28419287/prediction-algorithm-for-surgical-intervention-in-neonatal-brachial-plexus-palsy
#15
Thomas J Wilson, Kate W C Chang, Lynda J S Yang
BACKGROUND: Neonatal brachial plexus palsy (NBPP) results in reduced function of the affected arm with profound ramifications on quality of life. Advances in surgical technique have shown improvements in outcomes for appropriately selected patients. Patient selection, however, remains difficult. OBJECTIVE: To develop a decision algorithm that could be applied at the individual patient level, early in life, to reliably predict persistent NBPP that would benefit from surgery...
April 17, 2017: Neurosurgery
https://www.readbyqxmd.com/read/28419025/ensemble-methods-for-classification-of-physical-activities-from-wrist-accelerometry
#16
Alok Kumar Chowdhury, Dian Tjondronegoro, Vinod Chandran, Stewart G Trost
PURPOSE: To investigate whether the use of ensemble learning algorithms improve physical activity recognition accuracy compared to the single classifier algorithms, and to compare the classification accuracy achieved by three conventional ensemble machine learning methods (bagging, boosting, random forest) and a custom ensemble model comprising four algorithms commonly used for activity recognition (binary decision tree, k nearest neighbour, support vector machine, and neural network)...
April 18, 2017: Medicine and Science in Sports and Exercise
https://www.readbyqxmd.com/read/28418593/nonparametric-tree-based-predictive-modeling-of-storm-outages-on-an-electric-distribution-network
#17
Jichao He, David W Wanik, Brian M Hartman, Emmanouil N Anagnostou, Marina Astitha, Maria E B Frediani
This article compares two nonparametric tree-based models, quantile regression forests (QRF) and Bayesian additive regression trees (BART), for predicting storm outages on an electric distribution network in Connecticut, USA. We evaluated point estimates and prediction intervals of outage predictions for both models using high-resolution weather, infrastructure, and land use data for 89 storm events (including hurricanes, blizzards, and thunderstorms). We found that spatially BART predicted more accurate point estimates than QRF...
March 2017: Risk Analysis: An Official Publication of the Society for Risk Analysis
https://www.readbyqxmd.com/read/28415579/metabolite-marker-discovery-for-the-detection-of-bladder-cancer-by-comparative-metabolomics
#18
Chi-Hung Shao, Chien-Lun Chen, Jia-You Lin, Chao-Jung Chen, Shu-Hsuan Fu, Yi-Ting Chen, Yu-Sun Chang, Jau-Song Yu, Ke-Hung Tsui, Chiun-Gung Juo, Kun-Pin Wu
Bladder cancer is one of the most common urinary tract carcinomas in the world. Urine metabolomics is a promising approach for bladder cancer detection and marker discovery since urine is in direct contact with bladder epithelia cells; metabolites released from bladder cancer cells may be enriched in urine samples. In this study, we applied ultra-performance liquid chromatography time-of-flight mass spectrometry to profile metabolite profiles of 87 samples from bladder cancer patients and 65 samples from hernia patients...
March 21, 2017: Oncotarget
https://www.readbyqxmd.com/read/28414489/prospective-identification-of-adolescent-suicide-ideation-using-classification-tree-analysis-models-for-community-based-screening
#19
Ryan M Hill, Benjamin Oosterhoff, Julie B Kaplow
OBJECTIVE: Although a large number of risk markers for suicide ideation have been identified, little guidance has been provided to prospectively identify adolescents at risk for suicide ideation within community settings. The current study addressed this gap in the literature by utilizing classification tree analysis (CTA) to provide a decision-making model for screening adolescents at risk for suicide ideation. METHOD: Participants were N = 4,799 youth (Mage = 16...
April 17, 2017: Journal of Consulting and Clinical Psychology
https://www.readbyqxmd.com/read/28414209/polypharmacological-in-silico-bioactivity-profiling-and-experimental-validation-uncovers-sedative-hypnotic-effects-of-approved-and-experimental-drugs-in-rat
#20
Georgios Drakakis, Keith A Wafford, Suzanne C Brewerton, Michael J Bodkin, David A Evans, Andreas Bender
In this work, we describe the computational ('in silico') mode-of-action analysis of CNS-active drugs, which is taking both multiple simultaneous hypotheses as well as sets of protein targets for each mode-of-action into account, and which was followed by successful prospective in vitro and in vivo validation. Using sleep-related phenotypic readouts describing both efficacy and side-effects for 491 compounds tested in rat, we defined an 'optimal' (desirable) sleeping pattern. Compounds were subjected to in silico target prediction (which was experimentally confirmed for 21 out of 28 cases, corresponding to 75%), followed by the utilization of decision trees for deriving polypharmacological bioactivity profiles...
April 17, 2017: ACS Chemical Biology
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