Minimal information for studies of extracellular vesicles 2018 (MISEV2018):a position statement of the International Society for Extracellular Vesicles and update of the MISEV2014 guidelines

The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles (“MISEV”) guidelines for the field in 2014. We now update these “MISEV2014” guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points

Simulation of pulsed laser material processing controlled by an extended self-organising Kohonen feature map

We have simulated the control of laser material processing. The process to control was surface polishing. In the simulations we assumed pulsed ultraviolet laser beams of 100 nanosecond duration. The controller was an artificial neural network (ANN): an extended self-organising Kohonen feature map. The controller was trained -- tuned -- on examples of laser evaporation of one dimensional `surfaces' by using a Widrow-Hoff type Delta-rule for error correction. Strength of the approach lies in the speed of parallel computing and the adaptive properties of the controller in a changing environment, like drift in laser properties, optical components, etc. Results show more than an order of magnitude improvement in surface roughness after an ANN designed laser shot onto a large surface. Restrictions of the model are discussed. Keywords: Neural control, laser processing. PACS numbers: 02.90.+p 44.90.+c 81.90.+c Correspondence : Andr'as Lorincz FAX : (36-1) 156-5045 1 Introduction Though com..

Self-Organizing Multi-Resolution Grid For Motion Planning And Control

mands to the control neurons via modifiable connections. This architecture forms the Multigrid Position-and-Direction-to-Action (MPDA) map. The architecture integrates reactive path planning and continuous motion control. It is also shown that the scheme leads to population coding for the actual command vector. 1. Introduction Controlling a manipulator can be enormously complex from the point of view of an analytical approach since it requires the sequential computation of the location of the target, the path to be followed to reach the target, the inverse joint kinematics that satisfies the constraints of the path and the obstacles, the inverse joint dynamics and eventually the command series while meeting the demand of changes of the plant's dynamics. Biological evidence strongly suggests that such a task can be solved with the help of learning. Effort along this route include various inverse system identification methods, such as the direct identification method (M