Protein synthesis-dependent formation of protein kinase Mζ in long-term potentiation

The maintenance of long-term potentiation (LTP) in the CA1 region of the hippocampus has been reported to require both a persistent increase in phosphorylation and the synthesis of new proteins. The increased activity of protein kinase C (PKC) during the maintenance phase of LTP may result from the formation of PKMζ, the constitutively active fragment of a specific PKC isozyme. To define the relationship among PKMζ, longterm EPSP responses, and the requirement for new protein synthesis, we examined the regulation of PKMζ after subthreshold stimulation that produced short-term potentiation (STP) and after suprathreshold stimulation by single and multiple tetanic trains that produced LTP. We found that, although no persistent increase in PKMζ followed STP, the degree of long-term EPSP potentiation was linearly correlated with the increase of PKMζ. The increase was first observed 10 min after a tetanus that induced LTP and lasted for at least 2 hr, in parallel with the persistence of EPSP enhancement. Both the maintenance of LTP and the long-term increase in PKMζ were blocked by the protein synthesis inhibitors anisomycin and cycloheximide. These results suggest that PKMζ is a component of a protein synthesis-dependent mechanism for persistent phosphorylation in LTP

Characterization and correction of time-varying eddy currents for diffusion MRI

Purpose: To develop and test a method for reducing artifacts due to time-varying eddy currents in oscillating gradient spin-echo (OGSE) diffusion images. Methods: An in-house algorithm (TVEDDY), that for the first time retrospectively models eddy current decay, was tested on pulsed gradient spin echo and OGSE brain images acquired at 7 T. Image pairs were acquired using opposite polarity diffusion gradients. A three-parameter exponential decay model (two amplitudes and a time constant) was used to characterize and correct eddy current distortions by minimizing the intensity difference between image pairs. Correction performance was compared with conventional correction methods by evaluating the mean squared error (MSE) between diffusion-weighted images acquired with opposite polarity diffusion gradients. As a ground-truth comparison, images were corrected using field dynamics up to third order in space, measured using a field monitoring system. Results: Time-varying eddy currents were observed for OGSE, which introduced blurring that was not reduced using the traditional approach but was diminished considerably with TVEDDY and field monitoring–informed model-based reconstruction. No MSE difference was observed between the conventional approach and TVEDDY for pulsed gradient spin echo, but for OGSE TVEDDY resulted in significantly lower MSE than the conventional approach. The field-monitoring reconstruction had the lowest MSE for both pulsed gradient spin echo and OGSE. Conclusion: This work establishes that it is possible to estimate time-varying eddy currents from the actual diffusion data, which provides substantial image-quality improvements for gradient-intensive diffusion MRI acquisitions like OGSE

Antiepileptic drugs and bone metabolism

Anti-epileptic medications encompass a wide range of drugs including anticonvulsants, benzodiazepines, enzyme inducers or inhibitors, with a variety effects, including induction of cytochrome P450 and other enzyme, which may lead to catabolism of vitamin D and hypocalcemia and other effects that may significantly effect the risk for low bone mass and fractures. With the current estimates of 50 million people worldwide with epilepsy together with the rapid increase in utilization of these medications for other indications, bone disease associated with the use of anti-epileptic medications is emerging as a serious health threat for millions of people. Nevertheless, it usually goes unrecognized and untreated. In this review we discuss the pathophysiologic mechanisms of bone disease associated with anti-epileptic use, including effect of anti-epileptic agents on bone turnover and fracture risk, highlighting various strategies for prevention of bone loss and associated fractures a rapidly increasing vulnerable population

Deep execution monitor for robot assistive tasks

We consider a novel approach to high-level robot task execution for a robot assistive task. In this work we explore the problem of learning to predict the next subtask by introducing a deep model for both sequencing goals and for visually evaluating the state of a task. We show that deep learning for monitoring robot tasks execution very well supports the interconnection between task-level planning and robot operations. These solutions can also cope with the natural non-determinism of the execution monitor. We show that a deep execution monitor leverages robot performance. We measure the improvement taking into account some robot helping tasks performed at a warehouse

Parametric investigation of lateral spreading of gently sloping liquefied ground

This paper investigates the main parameters affecting the anticipated maximum surface displacements due to earthquake-induced lateral spreading of mildly sloping ground. The main tool used for this purpose is a numerical methodology employing a bounding surface plasticity model implemented in a finite difference code, which has been thoroughly validated against 16 published centrifuge lateral spreading experiments. This study shows that important problem parameters are the mean ground (surface) acceleration, the duration of strong shaking following the onset of liquefaction, the corrected SPT blowcount, the depth to the sliding plane, the inclination of the ground surface and the fines content of the liquefied soil layers. A new approximate multi-variable relation is proposed for the estimation of ground surface displacements due to lateral spreading in gently sloping ground, which includes the foregoing parameters. The form of the relation builds upon sliding block theory, but its final formulation is based on statistical analysis of the input data and the results from 120 parametric analyses performed with the validated numerical methodology. Comparison of the predictions of the proposed relation for ground surface displacement against pertinent field data (from 256 case histories) and centrifuge test measurements shows satisfactory accuracy. Furthermore, the variation of lateral displacements with depth is explored and distinct displacement patterns are proposed for uniform, 2-layer and 4-layer ground profiles. (C) 2010 Elsevier Ltd. All rights reserved

Efficient context management and personalized user recommendations in a smart social TV environment

With the emergence of Smart TV and related interconnected devices, second screen solutions have rapidly appeared to provide more content for end-users and enrich their TV experience. Given the various data and sources involved - videos, actors, social media and online databases-the aforementioned market poses great challenges concerning user context management and sophisticated recommendations that can be addressed to the end-users. This paper presents an innovative Context Management model and a related first and second screen recommendation service, based on a user-item graph analysis as well as collaborative filtering techniques in the context of a Dynamic Social & Media Content Syndication (SAM) platform. The model evaluation provided is based on datasets collected online, presenting a comparative analysis concerning efficiency and effectiveness of the current approach, and illustrating its added value. © Springer International Publishing AG 2017

Loopbaan- en diversiteitsplannen: naar een evolutie in plaats van een revolutie van het systeem

status: publishe