Demyelination and axonal preservation in a transgenic mouse model of Pelizaeus-Merzbacher disease

It is widely thought that demyelination contributes to the degeneration of axons and, in combination with acute inflammatory injury, is responsible for progressive axonal loss and persistent clinical disability in inflammatory demyelinating disease. In this study we sought to characterize the relationship between demyelination, inflammation and axonal transport changes using a Plp1-transgenic mouse model of Pelizaeus-Merzbacher disease. In the optic pathway of this non-immune mediated model of demyelination, myelin loss progresses from the optic nerve head towards the brain, over a period of months. Axonal transport is functionally perturbed at sites associated with local inflammation and 'damaged' myelin. Surprisingly, where demyelination is complete, naked axons appear well preserved despite a significant reduction of axonal transport. Our results suggest that neuroinflammation and/or oligodendrocyte dysfunction are more deleterious for axonal health than demyelination per se, at least in the short ter

Promoting occupational health through gamification and e-coaching: A 5-month user engagement study

Social gamification systems have shown potential for promoting healthy lifestyles, but applying them to occupational settings faces unique design challenges. While occupational settings offer natural communities for social interaction, fairness issues due to heterogeneous personal goals and privacy concerns increase the difficulty of designing engaging games. We explored a two-level game-design, where the first level related to achieving personal goals and the second level was a privacy-protected social competition to maximize goal compliance among colleagues. The solution was strengthened by employing occupational physicians who personalized users’ goals and coached them remotely. The design was evaluated in a 5-month study with 53 employees from a Dutch university. Results suggested that the application helped half of the participants to improve their lifestyles, and most appreciated the role of the physician in goal-setting. However, long-term user engagement was undermined by the scalability-motivated design choice of one-way communication between employees and their physician. Implications for social gamification design in occupational health are discussed

Application of a low cost array-based technique — TAB-Array — for quantifying and mapping both 5mC and 5hmC at single base resolution in human pluripotent stem cells

Abstract5-hydroxymethylcytosine (5hmC), an oxidized derivative of 5-methylcytosine (5mC), has been implicated as an important epigenetic regulator of mammalian development. Current procedures use DNA sequencing methods to discriminate 5hmC from 5mC, limiting their accessibility to the scientific community. Here we report a method that combines TET-assisted bisulfite conversion with Illumina 450K DNA methylation arrays for a low-cost high-throughput approach that distinguishes 5hmC and 5mC signals at base resolution. Implementing this approach, termed “TAB-array”, we assessed DNA methylation dynamics in the differentiation of human pluripotent stem cells into cardiovascular progenitors and neural precursor cells. With the ability to discriminate 5mC and 5hmC, we identified a large number of novel dynamically methylated genomic regions that are implicated in the development of these lineages. The increased resolution and accuracy afforded by this approach provides a powerful means to investigate the distinct contributions of 5mC and 5hmC in human development and disease

2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation: executive summary.

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Pulse coupled neural networks for automatic oil spill detection from satellite SAR images

It is known that one of the most critical issues for the implementation of a fully automatic processing dedicated to the detection of oil spills from SAR imagery is the extraction of the oil spill candidate. In fact, the segmentation of the image is the first of three necessary steps, the other two being the characterization of the extracted black spot by using a set of features and the classification between oil spill and look-alike. In this paper we investigate an unsupervised neural network approach for automatically extracting oil spill candidates from ERS and ENVISAT SAR images. The technique is based on the use of Pulse-Coupled Neural Networks (PCNN) which is a relatively novel technique based on models of the visual cortex of small mammals. When applied to image processing, it yields a series of binary pulsed signals, each associated to one pixel or to a cluster. In literature, interesting results have been already reported by several authors in applications of this model to image segmentation, including, in few cases, the use of satellite data. The architecture of PCNN is rather simpler than most other neural network implementations. PCNN do not have multiple layers and receive input directly from the original image, forming a resulting “pulse” image. The network consists of multiple nodes coupled together with their neighbors within a definite distance, forming a grid (2D-vector). The PCNN neuron has two input compartments: linking and feeding. The feeding compartment receives both an external and a local stimulus, whereas the linking compartment only receives a local stimulus. When the internal activity becomes larger than an internal threshold, the neuron fires and the threshold sharply increases. Afterward, it begins to decay until once again the internal activity becomes larger. This process gives rise to the pulsing nature of PCNN, forming a wave signature which is invariant to rotation, scale, shift or skew of an object within the image. This study discusses the use of PCNN technique in a fully automatic chain for oil spill detection from SAR images. The objects segmented by the PCNN are successively processed by a more standard Multi-Layer Perceptron Neural Network, which provides the classification response between real oil spill and look-alike. The performance yielded by the PCNN-MLP chain is evaluated and critically discussed for a set of ERS-SAR and ENVISAT ASAR images. The application of the methodology to the very-high resolution SAR images taken by COSMO-Skymed and TerraSAR-X satellites will be also considered