Computation of motion by T4 cells in the fly brain is more complex than previously believed. As indicated by their name, photoreceptor cells in the eye respond to light: is an image point bright or dark? They do not indicate the direction of a movement. This perception only arises in the brain through the comparative computations of light signals coming from adjacent image points. Engineers, physicists and neurobiologists have been debating the exact nature of these computations for around 50 years.
Scientists from the Max Planck Institute of Neurobiology have now combined two theories about these computations, which were previously considered to be alternative hypotheses – and discovered that they are carried out in a single neuron.Flies are usually very difficult to catch. No wonder – they invest around ten percent of their brain in the detection and processing of image motion. For the fly, a hand approaches in slow motion and the fly’s evasive manoeuvre has long been triggered before any real danger arises. Scientists have been researching for decades how the fly brain can perceive and process movements so quickly and accurately. “Our goal is slowly coming into view, and we are close to completely decoding the neuronal circuit of motion perception in the fly,” says Alexander Borst, who has been working on this problem with his Department at the Max Planck Institute of Neurobiology for quite some time. The scientists have now come one step closer to the answer: They have provided experimental data that combine two theories previously considered as alternatives.  More



Do you speak -omics? If you don't, Perseus ­– might be able to help you. Researchers from the Max Planck Institute in Martinsried have developed this free software platform for users of high-throughput techniques, such as mass spectrometry, in order to translate raw biological data into relevant findings. As reported in the current issue of Nature Methods, molecular signatures from cells, tissue and body fluids can be identified and characterized on this platform without the need for bioinformatic training. Perseus was designed to deal with proteomic studies in which data on thousands of proteins is processed. It has, however, also proven itself in other molecular studies and will be expanded accordingly.
Absolutely nothing in an organism works without proteins. These molecules operate as molecular machines, act as building materials and appear in a variety of other roles. However, they are rarely lone warriors, with the result that analyzing the sum total of all proteins in a cell, a tissue, a body fluid or even in an entire organism is essential. This can establish when and where a particular molecule appears in what quantity and with whom it interacts. Corresponding approaches exist for other biological molecules as well. Modern high-throughput techniques such as mass spectrometry provide the necessary raw data, often from several thousand different proteins. More



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Spadaro, M., Gerdes, L.A., Krumbholz, M., Ertl-Wagner, B., Thaler, F.S., Schuh, E., Metz, I., Blaschek, A., Dick, A., Bruck, W., Hohlfeld, R., Meinl, E., and Kumpfel, T.
Neurol Neuroimmunol Neuroinflamm, 2016, 3, e257.

Autoantibodies to MOG in a distinct subgroup of adult multiple sclerosis.

OBJECTIVES: To evaluate the presence of antibodies to conformation-intact myelin oligodendrocyte glycoprotein (MOG) in a subgroup of adult patients with clinically definite multiple sclerosis (MS) preselected for a specific clinical phenotype including severe spinal cord, optic nerve, and brainstem involvement.

METHODS: Antibodies to MOG were investigated using a cell-based assay in 3 groups of patients: 104 preselected patients with MS (group 1), 55 age- and sex-matched, otherwise unselected patients with MS (group 2), and in 22 brain-biopsied patients with demyelinating diseases of the CNS (n = 19 with MS), 4 of whom classified as MS type II (group 3). Recognized epitopes were identified with mutated variants of MOG.

RESULTS: Antibodies to MOG were found in about 5% (5/104) of preselected adult patients with MS. In contrast, in groups 2 and 3, none of the patients tested positive for MOG antibodies. Patients with MS with antibodies to MOG predominantly manifested with concomitant severe brainstem and spinal cord involvement and had a severe disease course with high relapse rates and failure to several disease-modifying therapies. Three of them had been treated with plasma exchange with a favorable response. All anti-MOG-positive patients with MS showed typical MS lesions on brain MRI. Longitudinal analysis up to 9 years revealed fluctuations and reappearance of anti-MOG reactivity. Epitope mapping indicated interindividual heterogeneity, yet intraindividual stability of the antibody response.

CONCLUSIONS: Antibodies to MOG can be found in a distinct subgroup of adult MS with a specific clinical phenotype and may indicate disease heterogeneity.