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https://www.readbyqxmd.com/read/28333586/modulation-of-context-dependent-spatiotemporal-patterns-within-packets-of-spiking-activity
#1
Miho Itoh, Timothée Leleu
Recent experiments have shown that stereotypical spatiotemporal patterns occur during brief packets of spiking activity in the cortex, and it has been suggested that top-down inputs can modulate these patterns according to the context. We propose a simple model that may explain important features of these experimental observations and is analytically tractable. The key mechanism underlying this model is that context-dependent top-down inputs can modulate the effective connection strengths between neurons because of short-term synaptic depression...
March 23, 2017: Neural Computation
https://www.readbyqxmd.com/read/28333183/machine-learning-algorithms-for-objective-remission-and-clinical-outcomes-with-thiopurines
#2
Akbar K Waljee, Kay Sauder, Anand Patel, Sandeep Segar, Boang Liu, Yiwei Zhang, Ji Zhu, Ryan W Stidham, Ulysses Balis, Peter D R Higgins
Background and Aims: Big data analytics leverage patterns in data to harvest valuable information, but are rarely implemented in clinical care. Optimising thiopurine therapy for inflammatory bowel disease [IBD] has proved difficult. Current methods using 6-thioguanine nucleotide [6-TGN] metabolites have failed in randomized controlled trials [RCTs], and have not been used to predict objective remission [OR]. Our aims were to: 1) develop machine learning algorithms [MLA] using laboratory values and age to identify patients in objective remission on thiopurines; and 2) determine whether achieving algorithm-predicted objective remission resulted in fewer clinical events per year...
March 14, 2017: Journal of Crohn's & Colitis
https://www.readbyqxmd.com/read/28327206/lessons-learned-from-additional-research-analyses-of-unsolved-clinical-exome-cases
#3
Mohammad K Eldomery, Zeynep Coban-Akdemir, Tamar Harel, Jill A Rosenfeld, Tomasz Gambin, Asbjørg Stray-Pedersen, Sébastien Küry, Sandra Mercier, Davor Lessel, Jonas Denecke, Wojciech Wiszniewski, Samantha Penney, Pengfei Liu, Weimin Bi, Seema R Lalani, Christian P Schaaf, Michael F Wangler, Carlos A Bacino, Richard Alan Lewis, Lorraine Potocki, Brett H Graham, John W Belmont, Fernando Scaglia, Jordan S Orange, Shalini N Jhangiani, Theodore Chiang, Harsha Doddapaneni, Jianhong Hu, Donna M Muzny, Fan Xia, Arthur L Beaudet, Eric Boerwinkle, Christine M Eng, Sharon E Plon, V Reid Sutton, Richard A Gibbs, Jennifer E Posey, Yaping Yang, James R Lupski
BACKGROUND: Given the rarity of most single-gene Mendelian disorders, concerted efforts of data exchange between clinical and scientific communities are critical to optimize molecular diagnosis and novel disease gene discovery. METHODS: We designed and implemented protocols for the study of cases for which a plausible molecular diagnosis was not achieved in a clinical genomics diagnostic laboratory (i.e. unsolved clinical exomes). Such cases were recruited to a research laboratory for further analyses, in order to potentially: (1) accelerate novel disease gene discovery; (2) increase the molecular diagnostic yield of whole exome sequencing (WES); and (3) gain insight into the genetic mechanisms of disease...
March 21, 2017: Genome Medicine
https://www.readbyqxmd.com/read/28326432/harnessing-scientific-literature-reports-for-pharmacovigilance-prototype-software-analytical-tool-development-and-usability-testing
#4
Alfred Sorbello, Anna Ripple, Joseph Tonning, Monica Munoz, Rashedul Hasan, Thomas Ly, Henry Francis, Olivier Bodenreider
OBJECTIVES: We seek to develop a prototype software analytical tool to augment FDA regulatory reviewers' capacity to harness scientific literature reports in PubMed/MEDLINE for pharmacovigilance and adverse drug event (ADE) safety signal detection. We also aim to gather feedback through usability testing to assess design, performance, and user satisfaction with the tool. METHODS: A prototype, open source, web-based, software analytical tool generated statistical disproportionality data mining signal scores and dynamic visual analytics for ADE safety signal detection and management...
March 22, 2017: Applied Clinical Informatics
https://www.readbyqxmd.com/read/28325448/diagnosis-of-autism-through-eeg-processed-by-advanced-computational-algorithms-a-pilot-study
#5
Enzo Grossi, Chiara Olivieri, Massimo Buscema
BACKGROUND: Multi-Scale Ranked Organizing Map coupled with Implicit Function as Squashing Time algorithm(MS-ROM/I-FAST) is a new, complex system based on Artificial Neural networks (ANNs) able to extract features of interest in computerized EEG through the analysis of few minutes of their EEG without any preliminary pre-processing. A proof of concept study previously published showed accuracy values ranging from 94%-98% in discerning subjects with Mild Cognitive Impairment and/or Alzheimer's Disease from healthy elderly people...
April 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28325118/is-asthma-associated-with-cognitive-impairments-a-meta-analytic-review
#6
Farzin Irani, Jordan Mark Barbone, Janet Beausoleil, Lynn Gerald
INTRODUCTION: Asthma is a chronic disease with significant health burden and socioeconomic and racial/ethnic disparities related to diagnosis and treatment. Asthma primarily affects the lungs, but can impact brain function through direct and indirect mechanisms. Some studies have suggested that asthma negatively impacts cognition, while others have failed to identify asthma-related cognitive compromise. We aimed to conduct a meta-analysis of cognition in individuals with asthma compared to that in healthy controls...
March 21, 2017: Journal of Clinical and Experimental Neuropsychology
https://www.readbyqxmd.com/read/28324853/discursive-junctions-in-flood-risk-governance-a-comparative-understanding-in-six-european-countries
#7
Maria Kaufmann, Mark Wiering
Flood risks are managed differently across Europe. While a number of research studies aim to understand these differences, they tend to pay little attention to the social constructionist aspects of flood risk governance, i.e. the meaning that societies give to flood risk and governance. This paper aims to address this gap by understanding differences in flood risk management approaches (FRMA) from a discursive-institutional perspective. Based on this perspective, an analytical framework was developed to systematically analyse and compare discourses pertaining to flood risk and its governance in six European member states (England (the United Kingdom), Flanders (Belgium), France, the Netherlands, Poland and Sweden)...
March 18, 2017: Journal of Environmental Management
https://www.readbyqxmd.com/read/28323285/utilization-of-machine-learning-for-prediction-of-post-traumatic-stress-a-re-examination-of-cortisol-in-the-prediction-and-pathways-to-non-remitting-ptsd
#8
I R Galatzer-Levy, S Ma, A Statnikov, R Yehuda, A Y Shalev
To date, studies of biological risk factors have revealed inconsistent relationships with subsequent post-traumatic stress disorder (PTSD). The inconsistent signal may reflect the use of data analytic tools that are ill equipped for modeling the complex interactions between biological and environmental factors that underlay post-traumatic psychopathology. Further, using symptom-based diagnostic status as the group outcome overlooks the inherent heterogeneity of PTSD, potentially contributing to failures to replicate...
March 21, 2017: Translational Psychiatry
https://www.readbyqxmd.com/read/28316639/feature-extraction-and-classification-of-ehg-between-pregnancy-and-labour-group-using-hilbert-huang-transform-and-extreme-learning-machine
#9
Lili Chen, Yaru Hao
Preterm birth (PTB) is the leading cause of perinatal mortality and long-term morbidity, which results in significant health and economic problems. The early detection of PTB has great significance for its prevention. The electrohysterogram (EHG) related to uterine contraction is a noninvasive, real-time, and automatic novel technology which can be used to detect, diagnose, or predict PTB. This paper presents a method for feature extraction and classification of EHG between pregnancy and labour group, based on Hilbert-Huang transform (HHT) and extreme learning machine (ELM)...
2017: Computational and Mathematical Methods in Medicine
https://www.readbyqxmd.com/read/28316582/what-we-do-and-do-not-know-about-teaching-medical-image-interpretation
#10
Ellen M Kok, Koos van Geel, Jeroen J G van Merriënboer, Simon G F Robben
Educators in medical image interpretation have difficulty finding scientific evidence as to how they should design their instruction. We review and comment on 81 papers that investigated instructional design in medical image interpretation. We distinguish between studies that evaluated complete offline courses and curricula, studies that evaluated e-learning modules, and studies that evaluated specific educational interventions. Twenty-three percent of all studies evaluated the implementation of complete courses or curricula, and 44% of the studies evaluated the implementation of e-learning modules...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28315459/dynamic-reorganization-of-intrinsic-functional-networks-in-the-mouse-brain
#11
Joanes Grandjean, Maria Giulia Preti, Thomas A W Bolton, Michaela Buerge, Erich Seifritz, Christopher R Pryce, Dimitri Van De Ville, Markus Rudin
Functional connectivity (FC) derived from resting-state functional magnetic resonance imaging (rs-fMRI) allows for the integrative study of neuronal processes at a macroscopic level. The majority of studies to date have assumed stationary interactions between brain regions, without considering the dynamic aspects of network organization. Only recently has the latter received increased attention, predominantly in human studies. Applying dynamic FC (dFC) analysis to mice is attractive given the relative simplicity of the mouse brain and the possibility to explore mechanisms underlying network dynamics using pharmacological, environmental or genetic interventions...
March 14, 2017: NeuroImage
https://www.readbyqxmd.com/read/28300971/culture-versus-the-law-in-the-decision-not-to-vaccinate-children-meanings-assigned-by-middle-class-couples-in-s%C3%A3-o-paulo-brazil
#12
Carolina Luisa Alves Barbieri, Márcia Thereza Couto, Fernando Mussa Abujamra Aith
This study aimed to learn how middle-class parents in the city of São Paulo, Brazil, interpreted the country's prevailing vaccination requirements, based on their experiences with vaccinating, selectively vaccinating, or not vaccinating their children. A qualitative approach was used with in-depth interviews. The analytical process was guided by content analysis and the theoretical framework of the anthropology of the law and morality. For parents that vaccinated, Brazil's culture of immunization outweighed the feeling of compliance with the law; for selective parents, selection of vaccines was not perceived as deviating from the law...
March 9, 2017: Cadernos de Saúde Pública
https://www.readbyqxmd.com/read/28300343/medical-student-use-of-digital-learning-resources
#13
Karen Scott, Anne Morris, Ben Marais
BACKGROUND: University students expect to use technology as part of their studies, yet health professional teachers can struggle with the change in student learning habits fuelled by technology. Our research aimed to document the learning habits of contemporary medical students during a clinical rotation by exploring the use of locally and externally developed digital and print self-directed learning resources, and study groups. METHODS: We investigated the learning habits of final-stage medical students during their clinical paediatric rotation using mixed methods, involving learning analytics and a student questionnaire...
March 16, 2017: Clinical Teacher
https://www.readbyqxmd.com/read/28294468/memory-impairment-and-the-mediating-role-of-task-difficulty-in-patients-with-schizophrenia
#14
REVIEW
Kyrsten M Grimes, Anosha Zanjani, Konstantine K Zakzanis, C Psych
Using meta-analytic methods, we sought to synthesize the research literature on memory impairment in schizophrenia. Additionally, we compared performances across memory measures to determine if task difficulty (e.g., effortful encoding and retrieval versus non effortful encoding and retrieval) could account for variance across studies. Our primary measures of interest included the California Verbal Learning Test, Wechsler Memory Scale, Rey Auditory Verbal Learning Test, Hopkins Verbal Learning Test, Rey Osterrieth Complex Figure Test, and the Benton Visual Retention Test...
March 14, 2017: Psychiatry and Clinical Neurosciences
https://www.readbyqxmd.com/read/28293681/community-level-differences-in-the-microbiome-of-healthy-wild-mallards-and-those-infected-by-influenza-a-viruses
#15
Holly H Ganz, Ladan Doroud, Alana J Firl, Sarah M Hird, Jonathan A Eisen, Walter M Boyce
Waterfowl, especially ducks and geese, are primary reservoirs for influenza A viruses (IAVs) that evolve and emerge as important pathogens in domestic animals and humans. In contrast to humans, where IAVs infect the respiratory tract and cause significant morbidity and mortality, IAVs infect the gastrointestinal tract of waterfowl and cause little or no pathology and are spread by fecal-oral transmission. For this reason, we examined whether IAV infection is associated with differences in the cloacal microbiome of mallards (Anas platyrhyncos), an important host of IAVs in North America and Eurasia...
January 2017: MSystems
https://www.readbyqxmd.com/read/28293202/automating-individualized-formative-feedback-in-large-classes-based-on-a-directed-concept-graph
#16
Henry E Schaffer, Karen R Young, Emily W Ligon, Diane D Chapman
Student learning outcomes within courses form the basis for course completion and time-to-graduation statistics, which are of great importance in education, particularly higher education. Budget pressures have led to large classes in which student-to-instructor interaction is very limited. Most of the current efforts to improve student progress in large classes, such as "learning analytics," (LA) focus on the aspects of student behavior that are found in the logs of Learning Management Systems (LMS), for example, frequency of signing in, time spent on each page, and grades...
2017: Frontiers in Psychology
https://www.readbyqxmd.com/read/28292475/constrained-optimization-methods-in-health-services-research-an-introduction-report-1-of-the-ispor-optimization-methods-emerging-good-practices-task-force
#17
William Crown, Nasuh Buyukkaramikli, Praveen Thokala, Alec Morton, Mustafa Y Sir, Deborah A Marshall, Jon Tosh, William V Padula, Maarten J Ijzerman, Peter K Wong, Kalyan S Pasupathy
Providing health services with the greatest possible value to patients and society given the constraints imposed by patient characteristics, health care system characteristics, budgets, and so forth relies heavily on the design of structures and processes. Such problems are complex and require a rigorous and systematic approach to identify the best solution. Constrained optimization is a set of methods designed to identify efficiently and systematically the best solution (the optimal solution) to a problem characterized by a number of potential solutions in the presence of identified constraints...
March 2017: Value in Health: the Journal of the International Society for Pharmacoeconomics and Outcomes Research
https://www.readbyqxmd.com/read/28283691/-modulation-of-the-intestinal-microbiota-by-nutritional-interventions
#18
S Derer, H Lehnert, C Sina, A E Wagner
Humans live in symbiosis with billions of commensal bacteria. The so-called microbiota live on different biological interfaces such as the skin, the urogenital tract and the gastrointestinal tract. Commensal bacteria replace potentially pathogenic microbes, synthesize vitamins and ferment dietary fibre. An imbalance in the bacterial composition of the intestinal microbiota has been associated with various diseases including gut-associated disorders such as inflammatory bowel diseases, colorectal cancer and nonalcoholic fatty liver disease...
March 10, 2017: Der Internist
https://www.readbyqxmd.com/read/28282239/the-role-of-teamwork-in-the-analysis-of-big-data-a-study-of-visual-analytics-and-box-office-prediction
#19
Verica Buchanan, Yafeng Lu, Nathan McNeese, Michael Steptoe, Ross Maciejewski, Nancy Cooke
Historically, domains such as business intelligence would require a single analyst to engage with data, develop a model, answer operational questions, and predict future behaviors. However, as the problems and domains become more complex, organizations are employing teams of analysts to explore and model data to generate knowledge. Furthermore, given the rapid increase in data collection, organizations are struggling to develop practices for intelligence analysis in the era of big data. Currently, a variety of machine learning and data mining techniques are available to model data and to generate insights and predictions, and developments in the field of visual analytics have focused on how to effectively link data mining algorithms with interactive visuals to enable analysts to explore, understand, and interact with data and data models...
March 2017: Big Data
https://www.readbyqxmd.com/read/28281665/valuation-in-major-depression-is-intact-and-stable-in-a-non-learning-environment
#20
Dongil Chung, Kelly Kadlec, Jason A Aimone, Katherine McCurry, Brooks King-Casas, Pearl H Chiu
The clinical diagnosis and symptoms of major depressive disorder (MDD) have been closely associated with impairments in reward processing. In particular, various studies have shown blunted neural and behavioral responses to the experience of reward in depression. However, little is known about whether depression affects individuals' valuation of potential rewards during decision-making, independent from reward experience. To address this question, we used a gambling task and a model-based analytic approach to measure two types of individual sensitivity to reward values in participants with MDD: 'risk preference,' indicating how objective values are subjectively perceived, and 'inverse temperature,' determining the degree to which subjective value differences between options influence participants' choices...
March 10, 2017: Scientific Reports
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