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https://www.readbyqxmd.com/read/28813537/metabolite-patterns-predicting-sex-and-age-in-participants-of-the-karlsruhe-metabolomics-and-nutrition-karmen-study
#1
Manuela J Rist, Alexander Roth, Lara Frommherz, Christoph H Weinert, Ralf Krüger, Benedikt Merz, Diana Bunzel, Carina Mack, Björn Egert, Achim Bub, Benjamin Görling, Pavleta Tzvetkova, Burkhard Luy, Ingrid Hoffmann, Sabine E Kulling, Bernhard Watzl
Physiological and functional parameters, such as body composition, or physical fitness are known to differ between men and women and to change with age. The goal of this study was to investigate how sex and age-related physiological conditions are reflected in the metabolome of healthy humans and whether sex and age can be predicted based on the plasma and urine metabolite profiles. In the cross-sectional KarMeN (Karlsruhe Metabolomics and Nutrition) study 301 healthy men and women aged 18-80 years were recruited...
2017: PloS One
https://www.readbyqxmd.com/read/28808826/use-of-evidence-in-a-categorization-task-analytic-and-holistic-processing-modes
#2
Alberto Greco, Stefania Moretti
Category learning performance can be influenced by many contextual factors, but the effects of these factors are not the same for all learners. The present study suggests that these differences can be due to the different ways evidence is used, according to two main basic modalities of processing information, analytically or holistically. In order to test the impact of the information provided, an inductive rule-based task was designed, in which feature salience and comparison informativeness between examples of two categories were manipulated during the learning phases, by introducing and progressively reducing some perceptual biases...
August 14, 2017: Cognitive Processing
https://www.readbyqxmd.com/read/28807860/hidden-markov-modeling-of-frequency-following-responses-to-mandarin-lexical-tones
#3
Fernando Llanos, Zilong Xie, Bharath Chandrasekaran
BACKGROUND: The frequency-following response (FFR) is a scalp-recorded electrophysiological potential reflecting phase-locked activity from neural ensembles in the auditory system. The FFR is often used to assess the robustness of subcortical pitch processing. Due to low signal-to-noise ratio at the single-trial level, FFRs are typically averaged across thousands of stimulus repetitions. Prior work using this approach has shown that subcortical encoding of linguistically-relevant pitch patterns is modulated by long-term language experience...
August 11, 2017: Journal of Neuroscience Methods
https://www.readbyqxmd.com/read/28796238/a-proposed-approach-to-accelerate-evidence-generation-for-genomic-based-technologies-in-the-context-of-a-learning-health-system
#4
REVIEW
Christine Y Lu, Marc S Williams, Geoffrey S Ginsburg, Sengwee Toh, Jeff S Brown, Muin J Khoury
Genomic technologies should demonstrate analytical and clinical validity and clinical utility prior to wider adoption in clinical practice. However, the question of clinical utility remains unanswered for many genomic technologies. In this paper, we propose three building blocks for rapid generation of evidence on clinical utility of promising genomic technologies that underpin clinical and policy decisions. We define promising genomic tests as those that have proven analytical and clinical validity. First, risk-sharing agreements could be implemented between payers and manufacturers to enable temporary coverage that would help incorporate promising technologies into routine clinical care...
August 10, 2017: Genetics in Medicine: Official Journal of the American College of Medical Genetics
https://www.readbyqxmd.com/read/28791882/cooperative-co-evolution-with-formula-based-variable-grouping-for-large-scale-global-optimization
#5
Yuping Wang, Haiyan Liu, Fei Wei, Tingting Zong, Xiaodong Li
For a large-scale global optimization (LSGO) problem, divide-and-conquer is usually considered as an effective strategy to decompose the problem into smaller subproblems, each of which can be then solved individually. Among these decomposition methods, variable grouping is shown to be promising in recent years. Existing variable grouping methods usually assume the problem to be black-box (i.e., assuming that an analytical model of the objective function is unknown), and they attempt to learn appropriate variable grouping that would allow for a better decomposition of the problem...
August 9, 2017: Evolutionary Computation
https://www.readbyqxmd.com/read/28777762/systematic-review-and-knowledge-translation-a-framework-for-synthesizing-heterogeneous-research-evidence
#6
Robert Gould, Sarah Parker Harris, Glenn Fujiura
BACKGROUND: Participatory methodologies in disability and rehabilitation research are used to capture the perspectives of people with disabilities and to recognize the agency of stakeholder groups. Existing resources for conducting systematic reviews seldom provide details about how to integrate stakeholder input into the methodological process. OBJECTIVES: This article considers how knowledge translation strategies can support and advance systematic reviews that include diverse types of research...
August 1, 2017: Work: a Journal of Prevention, Assessment, and Rehabilitation
https://www.readbyqxmd.com/read/28771776/developing-and-rewarding-teachers-as-educators-and-scholars-remarkable-progress-and-daunting-challenges
#7
David M Irby, Patricia S O'Sullivan
CONTEXT: This article describes the scholarly work that has addressed the fifth recommendation of the 1988 World Conference on Medical Education: 'Train teachers as educators, not content experts alone, and reward excellence in this field as fully as excellence in biomedical research or clinical practice'. PROGRESS: Over the past 30 years, scholars have defined the preparation needed for teaching and other educator roles, and created faculty development delivery systems to train teachers as educators...
August 3, 2017: Medical Education
https://www.readbyqxmd.com/read/28770216/translating-big-data-into-smart-data-for-veterinary-epidemiology
#8
Kimberly VanderWaal, Robert B Morrison, Claudia Neuhauser, Carles Vilalta, Andres M Perez
The increasing availability and complexity of data has led to new opportunities and challenges in veterinary epidemiology around how to translate abundant, diverse, and rapidly growing "big" data into meaningful insights for animal health. Big data analytics are used to understand health risks and minimize the impact of adverse animal health issues through identifying high-risk populations, combining data or processes acting at multiple scales through epidemiological modeling approaches, and harnessing high velocity data to monitor animal health trends and detect emerging health threats...
2017: Frontiers in Veterinary Science
https://www.readbyqxmd.com/read/28769778/improving-cross-day-eeg-based-emotion-classification-using-robust-principal-component-analysis
#9
Yuan-Pin Lin, Ping-Keng Jao, Yi-Hsuan Yang
Constructing a robust emotion-aware analytical framework using non-invasively recorded electroencephalogram (EEG) signals has gained intensive attentions nowadays. However, as deploying a laboratory-oriented proof-of-concept study toward real-world applications, researchers are now facing an ecological challenge that the EEG patterns recorded in real life substantially change across days (i.e., day-to-day variability), arguably making the pre-defined predictive model vulnerable to the given EEG signals of a separate day...
2017: Frontiers in Computational Neuroscience
https://www.readbyqxmd.com/read/28769060/a-diver-operated-hyperspectral-imaging-and-topographic-surveying-system-for-automated-mapping-of-benthic-habitats
#10
Arjun Chennu, Paul Färber, Glenn De'ath, Dirk de Beer, Katharina E Fabricius
We developed a novel integrated technology for diver-operated surveying of shallow marine ecosystems. The HyperDiver system captures rich multifaceted data in each transect: hyperspectral and color imagery, topographic profiles, incident irradiance and water chemistry at a rate of 15-30 m(2) per minute. From surveys in a coral reef following standard diver protocols, we show how the rich optical detail can be leveraged to generate photopigment abundance and benthic composition maps. We applied machine learning techniques, with a minor annotation effort (<2% of pixels), to automatically generate cm-scale benthic habitat maps of high taxonomic resolution and accuracy (93-97%)...
August 2, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28767373/mixed-neural-network-approach-for-temporal-sleep-stage-classification
#11
Hao Dong, Akara Supratak, Wei Pan, Chao Wu, Paul M Matthews, Yike Guo
This paper proposes a practical approach to addressing limitations posed by using of single-channel electroencephalography (EEG) for sleep stage classification. EEG-based characterizations of sleep stage progression contribute the diagnosis and monitoring of the many pathologies of sleep. Several prior reports explored ways of automating the analysis of sleep EEG and of reducing the complexity of the data needed for reliable discrimination of sleep stages at lower cost in the home. However, these reports have involved recordings from electrodes placed on the cranial vertex or occiput, which are both uncomfortable and difficult to position...
July 28, 2017: IEEE Transactions on Neural Systems and Rehabilitation Engineering
https://www.readbyqxmd.com/read/28767364/learning-spatial-semantic-context-with-fully-convolutional-recurrent-network-for-online-handwritten-chinese-text-recognition
#12
Zecheng Xie, Zenghui Sun, Lianwen Jin, Hao Ni, Terry Lyons
Online handwritten Chinese text recognition (OHCTR) is a challenging problem as it involves a large-scale character set, ambiguous segmentation, and variable-length input sequences. In this paper, we exploit the outstanding capability of path signature to translate online pen-tip trajectories into informative signature feature maps, successfully capturing the analytic and geometric properties of pen strokes with strong local invariance and robustness. A multi-spatial-context fully convolutional recurrent network (MC-FCRN) is proposed to exploit the multiple spatial contexts from the signature feature maps and generate a prediction sequence while completely avoiding the difficult segmentation problem...
July 28, 2017: IEEE Transactions on Pattern Analysis and Machine Intelligence
https://www.readbyqxmd.com/read/28765560/machine-learning-assisted-network-inference-approach-to-identify-a-new-class-of-genes-that-coordinate-the-functionality-of-cancer-networks
#13
Mehrab Ghanat Bari, Choong Yong Ung, Cheng Zhang, Shizhen Zhu, Hu Li
Emerging evidence indicates the existence of a new class of cancer genes that act as "signal linkers" coordinating oncogenic signals between mutated and differentially expressed genes. While frequently mutated oncogenes and differentially expressed genes, which we term Class I cancer genes, are readily detected by most analytical tools, the new class of cancer-related genes, i.e., Class II, escape detection because they are neither mutated nor differentially expressed. Given this hypothesis, we developed a Machine Learning-Assisted Network Inference (MALANI) algorithm, which assesses all genes regardless of expression or mutational status in the context of cancer etiology...
August 1, 2017: Scientific Reports
https://www.readbyqxmd.com/read/28765444/an-interactive-online-approach-to-teaching-evidence-based-dentistry-with-web-2-0-technology
#14
Meixun Zheng, Daniel Bender, Laura Reid, Jim Milani
At many dental schools, evidence-based dentistry (EBD) is taught in a traditional lecture format. To avoid the constraints of lectures, in 2012 the EBD unit was redesigned for online delivery at the Arthur A. Dugoni School of Dentistry at the University of the Pacific with a Web 2.0 tool called Voicethread. The aim of this study was to assess the impact of Voicethread-based online learning on students' perceptions of learning EBD, their participation and engagement, and their acceptance of this new online delivery approach...
August 2017: Journal of Dental Education
https://www.readbyqxmd.com/read/28762755/astrazeneca-and-covance-laboratories-clinical-bioanalysis-alliance-an-evolutionary-outsourcing-model
#15
Cecilia Arfvidsson, Paul Severin, Victoria Holmes, Richard Mitchell, Christopher Bailey, Stephanie Cape, Yan Li, Tammy Harter
The AstraZeneca and Covance Laboratories Clinical Bioanalysis Alliance (CBioA) was launched in 2011 after a period of global economic recession. In this challenging environment, AstraZeneca elected to move to a full and centralized outsourcing model that could optimize the number of people supporting bioanalytical work and reduce the analytical cost. This paper describes the key aspects of CBioA, the innovative operational model implemented, and our ways of ensuring this was much more than simply a cost reduction exercise...
August 1, 2017: Bioanalysis
https://www.readbyqxmd.com/read/28760670/standardization-of-8-color-flow-cytometry-across-different-flow-cytometer-instruments-a-feasibility-study-in-clinical-laboratories-in-switzerland
#16
Glier Hana, Heijnen Ingmar, Hauwel Mathieu, Dirks Jan, Quarroz Stéphane, Lehmann Thomas, Rovo Alicia, Arn Kornelius, Matthes Thomas, Hogan Cassandra, Keller Peter, Dudkiewicz Ewa, Stüssi Georg, Fernandez Paula
The EuroFlow Consortium developed a fully standardized flow cytometric approach from instrument settings, through antibody panel, reagents and sample preparation protocols, to data acquisition and analysis. The Swiss Cytometry Society (SCS) promoted a study to evaluate the feasibility of using such standardized measurements of 8-color data across two different flow cytometry platforms - Becton Dickinson (BD) FACSCanto II and Beckman Coulter (BC) Navios, aiming at increasing reproducibility and inter-laboratory comparability of immunophenotypic data in clinical laboratories in Switzerland...
July 28, 2017: Journal of Immunological Methods
https://www.readbyqxmd.com/read/28752518/the-color-of-cancer-margin-guidance-for-oral-cancer-resection-using-elastic-scattering-spectroscopy
#17
Gregory A Grillone, Zimmern Wang, Gintas P Krisciunas, Angela C Tsai, Vishnu R Kannabiran, Robert W Pistey, Qing Zhao, Eladio Rodriguez-Diaz, Ousama M A'Amar, Irving J Bigio
OBJECTIVES/HYPOTHESIS: To evaluate the usefulness of elastic scattering spectroscopy (ESS) as a diagnostic adjunct to frozen section analysis in patients with diagnosed squamous cell carcinoma of the oral cavity. STUDY DESIGN: Prospective analytic study. METHODS: Subjects for this single institution, institutional review board-approved study were recruited from among patients undergoing surgical resection for squamous cell cancer of the oral cavity...
July 28, 2017: Laryngoscope
https://www.readbyqxmd.com/read/28748430/inicu-integrated-neonatal-care-unit-capturing-neonatal-journey-in-an-intelligent-data-way
#18
Harpreet Singh, Gautam Yadav, Raghuram Mallaiah, Preetha Joshi, Vinay Joshi, Ravneet Kaur, Suneyna Bansal, Samir K Brahmachari
Neonatal period represents first 28 days of life, which is the most vulnerable time for a child's survival especially for the preterm babies. High neonatal mortality is a prominent and persistent problem across the globe. Non-availability of trained staff and infrastructure are the major recognized hurdles in the quality care of these neonates. Hourly progress growth charts and reports are still maintained manually by nurses along with continuous calculation of drug dosage and nutrition as per the changing weight of the baby...
August 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/28747877/combining-multiple-resting-state-fmri-features-during-classification-optimized-frameworks-and-their-application-to-nicotine-addiction
#19
Xiaoyu Ding, Yihong Yang, Elliot A Stein, Thomas J Ross
Machine learning techniques have been applied to resting-state fMRI data to predict neurological or neuropsychiatric disease states. Existing studies have used either a single type of resting-state feature or a few feature types (<4) in the prediction model. However, resting-state data can be processed in many different ways, yielding different feature types containing complementary and/or novel information, leaving uncertain the most informative features to provide to the classifier. In this study, multiple resting-state features were calculated from two main analytical categories: local measures and network measures...
2017: Frontiers in Human Neuroscience
https://www.readbyqxmd.com/read/28743607/comparative-characterization-of-crofelemer-samples-using-data-mining-and-machine-learning-approaches-with-analytical-stability-data-sets
#20
Maulik K Nariya, Jae Hyun Kim, Jian Xiong, Peter A Kleindl, Asha Hewarathna, Adam C Fisher, Sangeeta B Joshi, Christian Schöneich, M Laird Forrest, C Russell Middaugh, David B Volkin, Eric J Deeds
There is growing interest in generating physicochemical and biological analytical data sets to compare complex mixture drugs, for example products from different manufacturers. In this work, we compare various crofelemer samples prepared from a single lot by filtration with varying molecular weight cut-offs combined with incubation for different times at different temperatures. The two preceding manuscripts describe experimental data sets generated from analytical characterization of fractionated and degraded crofelemer samples...
July 22, 2017: Journal of Pharmaceutical Sciences
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