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https://www.readbyqxmd.com/read/28080221/molecular-mechanisms-of-antisense-oligonucleotides
#1
Stanley T Crooke
In 1987, when I became interested in the notion of antisense technology, I returned to my roots in RNA biochemistry and began work to understand how oligonucleotides behave in biological systems. Since 1989, my research has focused primarily on this topic, although I have been involved in most areas of research in antisense technology. I believe that the art of excellent science is to frame large important questions that are perhaps not immediately answerable with existing knowledge and methods, and then conceive a long-term (multiyear) research strategy that begins by answering the most pressing answerable questions on the path to the long-term goals...
January 12, 2017: Nucleic Acid Therapeutics
https://www.readbyqxmd.com/read/28073590/objective-detection-of-apoptosis-in-rat-renal-tissue-sections-using-light-microscopy-and-free-image-analysis-software-with-subsequent-machine-learning-detection-of-apoptosis-in-renal-tissue
#2
Nayana Damiani Macedo, Aline Rodrigues Buzin, Isabela Bastos Binotti Abreu de Araujo, Breno Valentim Nogueira, Tadeu Uggere de Andrade, Denise Coutinho Endringer, Dominik Lenz
OBJECTIVE: The current study proposes an automated machine learning approach for the quantification of cells in cell death pathways according to DNA fragmentation. METHODS: A total of 17 images of kidney histological slide samples from male Wistar rats were used. The slides were photographed using an Axio Zeiss Vert.A1 microscope with a 40x objective lens coupled with an Axio Cam MRC Zeiss camera and Zen 2012 software. The images were analyzed using CellProfiler (version 2...
December 28, 2016: Tissue & Cell
https://www.readbyqxmd.com/read/28060347/high-resolution-quantitative-synaptic-proteome-profiling-of-mouse-brain-regions-after-auditory-discrimination-learning
#3
Angela Kolodziej, Karl-Heinz Smalla, Sandra Richter, Alexander Engler, Rainer Pielot, Daniela C Dieterich, Wolfgang Tischmeyer, Michael Naumann, Thilo Kähne
The molecular synaptic mechanisms underlying auditory learning and memory remain largely unknown. Here, the workflow of a proteomic study on auditory discrimination learning in mice is described. In this learning paradigm, mice are trained in a shuttle box Go/NoGo-task to discriminate between rising and falling frequency-modulated tones in order to avoid a mild electric foot-shock. The protocol involves the enrichment of synaptosomes from four brain areas, namely the auditory cortex, frontal cortex, hippocampus, and striatum, at different stages of training...
December 15, 2016: Journal of Visualized Experiments: JoVE
https://www.readbyqxmd.com/read/28059697/digital-literacy-knowledge-and-needs-of-pharmacy-staff-a-systematic-review
#4
Katie MacLure, Derek Stewart
OBJECTIVE: To explore the digital literacy knowledge and needs of pharmacy staff including pharmacists, graduate (pre-registration) pharmacists, pharmacy technicians, dispensing assistants and medicine counter assistants. METHODS: A systematic review was conducted following a pre-published protocol. Two reviewers systematically performed the reproducible search, followed by independent screening of titles/abstracts then full papers, before critical appraisal and data extraction...
October 7, 2016: Journal of Innovation in Health Informatics
https://www.readbyqxmd.com/read/28059691/establishing-data-intensive-healthcare-the-case-of-hospital-electronic-prescribing-and-medicines-administration-systems-in-scotland
#5
Kathrin Cresswell, Pam Smith, Charles Swainson, Angela Timoney, Aziz Sheikh
BACKGROUND: Creating learning health systems, characterised by the use and repeated reuse of demographic, process and clinical data to improve the safety, quality and efficiency of care, is a key aim in realising the potential benefits and efficiency savings associated with the implementation of health information technology. OBJECTIVES: We sought to investigate stakeholder perspectives on and experiences of the implementation of hospital electronic prescribing and medicines administration (HEPMA) systems in Scotland and use these to inform political decisions on approaches to promoting the use and reuse of digitised prescribing and medication administration data in order to improve care processes and outcomes...
October 4, 2016: Journal of Innovation in Health Informatics
https://www.readbyqxmd.com/read/28059472/promoting-active-learning-of-graduate-student-by-deep-reading-in-biochemistry-and-microbiology-pharmacy-curriculum
#6
Ren Peng
To promote graduate students' active learning, deep reading of high quality papers was done by graduate students enrolled in biochemistry and microbiology pharmacy curriculum offered by college of life science, Jiangxi Normal University from 2013 to 2015. The number of graduate students, who participated in the course in 2013, 2014, and 2015 were eleven, thirteen and fifteen, respectively. Through deep reading of papers, presentation, and group discussion in the lecture, these graduate students have improved their academic performances effectively, such as literature search, PPT document production, presentation management, specialty document reading, academic inquiry, and analytical and comprehensive ability...
January 6, 2017: Biochemistry and Molecular Biology Education
https://www.readbyqxmd.com/read/28056098/a-model-for-good-governance-of-healthcare-technology-management-in-the-public-sector-learning-from-evidence-informed-policy-development-and-implementation-in-benin
#7
P Th Houngbo, H L S Coleman, M Zweekhorst, Tj De Cock Buning, D Medenou, J F G Bunders
Good governance (GG) is an important concept that has evolved as a set of normative principles for low- and middle-income countries (LMICs) to strengthen the functional capacity of their public bodies, and as a conditional prerequisite to receive donor funding. Although much is written on good governance, very little is known on how to implement it. This paper documents the process of developing a strategy to implement a GG model for Health Technology Management (HTM) in the public health sector, based on lessons learned from twenty years of experience in policy development and implementation in Benin...
2017: PloS One
https://www.readbyqxmd.com/read/28055930/deep-learning-for-health-informatics
#8
Daniele Ravi, Charence Wong, Fani Deligianni, Melissa Berthelot, Javier Andreu Perez, Benny Lo, Guang-Zhong Yang
With a massive influx of multimodality data, the role of data analytics in health informatics has grown rapidly in the last decade. This has also prompted increasing interests in the generation of analytical, data driven models based on machine learning in health informatics. Deep learning, a technique with its foundation in artificial neural networks, is emerging in recent years as a powerful tool for machine learning, promising to reshape the future of artificial intelligence. Rapid improvements in computational power, fast data storage and parallelization have also contributed to the rapid uptake of the technology in addition to its predictive power and ability to generate automatically optimized high-level features and semantic interpretation from the input data...
December 29, 2016: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28055132/identifying-future-drinkers-behavioral-analysis-of-monkeys-initiating-drinking-to-intoxication-is-predictive-of-future-drinking-classification
#9
Erich J Baker, Nicole A R Walter, Alex Salo, Pablo Rivas, Sharon Moore, Steven Gonzales, Kathleen A Grant
BACKGROUND: The Monkey Alcohol and Tissue Research Resource (MATRR) is a repository and analytics platform for detailed data derived from well-documented Non-Human Primate (NHP) alcohol self-administration studies. This macaque model has demonstrated categorical drinking norms reflective of human drinking populations, resulting in consumption pattern classifications of Very Heavy Drinking (VHD), Heavy Drinking (HD), Binge Drinking (BD), and Low Drinking (LD) individuals. Here we expand on previous findings that suggest ethanol drinking patterns during initial drinking to intoxication can reliably predict future drinking category assignment...
January 5, 2017: Alcoholism, Clinical and Experimental Research
https://www.readbyqxmd.com/read/28048913/mo-de-bra-02-simac-a-simulation-tool-for-teaching-linear-accelerator-physics
#10
M Carlone, N Harnett, W Harris, B Norrlinger, M MacPherson, M Lamey, R Anderson, M Oldham
PURPOSE: The first goal of this work is to develop software that can simulate the physics of linear accelerators (linac). The second goal is to show that this simulation tool is effective in teaching linac physics to medical physicists and linac service engineers. METHODS: Linacs were modeled using analytical expressions that can correctly describe the physical response of a linac to parameter changes in real time. These expressions were programmed with a graphical user interface in order to produce an environment similar to that of linac service mode...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28048166/mo-de-207b-06-computer-aided-diagnosis-of-breast-ultrasound-images-using-transfer-learning-from-deep-convolutional-neural-networks
#11
B Huynh, K Drukker, M Giger
PURPOSE: To assess the performance of using transferred features from pre-trained deep convolutional networks (CNNs) in the task of classifying cancer in breast ultrasound images, and to compare this method of transfer learning with previous methods involving human-designed features. METHODS: A breast ultrasound dataset consisting of 1125 cases and 2393 regions of interest (ROIs) was used. Each ROI was labeled as cystic, benign, or malignant. Features were extracted from each ROI using pre-trained CNNs and used to train support vector machine (SVM) classifiers in the tasks of distinguishing non-malignant (benign+cystic) vs malignant lesions and benign vs malignant lesions...
June 2016: Medical Physics
https://www.readbyqxmd.com/read/28038504/-in-our-corner
#12
Justine S Sefcik, Darina Petrovsky, Megan Streur, Mark Toles, Melissa O'Connor, Connie M Ulrich, Sherry Marcantonio, Ken Coburn, Mary D Naylor, Helene Moriarty
The purpose of this study was to explore participants' experience in the Health Quality Partners (HQP) Care Coordination Program that contributed to their continued engagement. Older adults with multiple chronic conditions often have limited engagement in health care services and face fragmented health care delivery. This can lead to increased risk for disability, mortality, poor quality of life, and increased health care utilization. A qualitative descriptive design with two focus groups was conducted with a total of 20 older adults enrolled in HQP's Care Coordination Program...
December 1, 2016: Clinical Nursing Research
https://www.readbyqxmd.com/read/28038371/conventional-vs-e-learning-in-nursing-education-a-systematic-review-and-meta-analysis
#13
REVIEW
Ari Voutilainen, Terhi Saaranen, Marjorita Sormunen
BACKGROUND: By and large, in health professions training, the direction of the effect of e-learning, positive or negative, strongly depends on the learning outcome in question as well as on learning methods which e-learning is compared to. In nursing education, meta-analytically generated knowledge regarding the comparisons between conventional and e-learning is scarce. OBJECTIVES: The aim of this review is to discover the size of the effect of e-learning on learning outcomes in nursing education and to assess the quality of studies in which e-learning has been compared to conventional learning...
December 22, 2016: Nurse Education Today
https://www.readbyqxmd.com/read/28030776/block-regularized-m-%C3%A3-2-cross-validated-estimator-of-the-generalization-error
#14
Ruibo Wang, Yu Wang, Jihong Li, Xingli Yang, Jing Yang
A cross-validation method based on m replications of two-fold cross validation is called an m × 2 cross validation. An m × 2 cross validation is used in estimating the generalization error and comparing of algorithms' performance in machine learning. However, the variance of the estimator of the generalization error in m × 2 cross validation is easily affected by random partitions. Poor data partitioning may cause a large fluctuation in the number of overlapping samples between any two training (test) sets in m × 2 cross validation...
December 28, 2016: Neural Computation
https://www.readbyqxmd.com/read/28030375/self-injurious-behaviour-in-people-with-intellectual-disability-and-autism-spectrum-disorder
#15
Chris Oliver, Lucy Licence, Caroline Richards
PURPOSE OF REVIEW: This review summarises the recent trends in research in the field of self-injurious behaviour in people with intellectual disability and autism spectrum disorder. RECENT FINDINGS: New data on incidence, persistence and severity add to studies of prevalence to indicate the large scale of the clinical need. A number of person characteristics have been repeatedly identified in prevalence and cohort studies that: can be considered as risk markers (e...
December 26, 2016: Current Opinion in Psychiatry
https://www.readbyqxmd.com/read/28026792/a-deep-learning-approach-to-on-node-sensor-data-analytics-for-mobile-or-wearable-devices
#16
Daniele Ravi, Charence Wong, Benny Lo, Guang-Zhong Yang
The increasing popularity of wearable devices in recent years means that a diverse range of physiological and functional data can now be captured continuously for applications in sports, wellbeing, and healthcare. This wealth of information requires efficient methods of classification and analysis where deep learning is a promising technique for large-scale data analytics. Whilst deep learning has been successful in implementations that utilize high performance computing platforms, its use on low-power wearable devices is limited by resource constraints...
December 23, 2016: IEEE Journal of Biomedical and Health Informatics
https://www.readbyqxmd.com/read/28025069/does-reactivation-trigger-episodic-memory-change-a-meta-analysis
#17
Iiona D Scully, Lucy E Napper, Almut Hupbach
According to the reconsolidation hypothesis, long-term memories return to a plastic state upon their reactivation, leaving them vulnerable to interference effects and requiring re-storage processes or else these memories might be permanently lost. The present study used a meta-analytic approach to critically evaluate the evidence for reactivation-induced changes in human episodic memory. Results indicated that reactivation makes episodic memories susceptible to physiological and behavioral interference. When applied shortly after reactivation, interference manipulations altered the amount of information that could be retrieved from the original learning event...
December 23, 2016: Neurobiology of Learning and Memory
https://www.readbyqxmd.com/read/28009736/esophageal-cancer-associations-with-pn-lymph-node-metastases
#18
Thomas W Rice, Hemant Ishwaran, Wayne L Hofstetter, Paul H Schipper, Kenneth A Kesler, Simon Law, E M R Lerut, Chadrick E Denlinger, Jarmo A Salo, Walter J Scott, Thomas J Watson, Mark S Allen, Long-Qi Chen, Valerie W Rusch, Robert J Cerfolio, James D Luketich, Andre Duranceau, Gail E Darling, Manuel Pera, Carolyn Apperson-Hansen, Eugene H Blackstone
OBJECTIVES: To identify the associations of lymph node metastases (pN+), number of positive nodes, and pN subclassification with cancer, treatment, patient, geographic, and institutional variables, and to recommend extent of lymphadenectomy needed to accurately detect pN+ for esophageal cancer. SUMMARY BACKGROUND DATA: Limited data and traditional analytic techniques have precluded identifying intricate associations of pN+ with other cancer, treatment, and patient characteristics...
January 2017: Annals of Surgery
https://www.readbyqxmd.com/read/27998879/using-patient-flow-information-to-determine-risk-of-hospital-presentation-protocol-for-a-proof-of-concept-study
#19
Christopher M Pearce, Adam McLeod, Jon Patrick, Douglas Boyle, Marianne Shearer, Paula Eustace, Mary Catherine Pearce
BACKGROUND: Every day, patients are admitted to the hospital with conditions that could have been effectively managed in the primary care sector. These admissions are expensive and in many cases are possible to avoid if early intervention occurs. General practitioners are in the best position to identify those at risk of imminent hospital presentation and admission; however, it is not always possible for all the factors to be considered. A lack of shared information contributes significantly to the challenge of understanding a patient's full medical history...
December 20, 2016: JMIR Research Protocols
https://www.readbyqxmd.com/read/27993693/whole-brain-functional-connectivity-during-acquisition-of-novel-grammar-distinct-functional-networks-depend-on-language-learning-abilities
#20
Olga Kepinska, Mischa de Rover, Johanneke Caspers, Niels O Schiller
In an effort to advance the understanding of brain function and organisation accompanying second language learning, we investigate the neural substrates of novel grammar learning in a group of healthy adults, consisting of participants with high and average language analytical abilities (LAA). By means of an Independent Components Analysis, a data-driven approach to functional connectivity of the brain, the fMRI data collected during a grammar-learning task were decomposed into maps representing separate cognitive processes...
December 16, 2016: Behavioural Brain Research
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