The Frangi vesselness ( Frangi et al., 1998) plugin is used to select myelin sheaths. 2.1 Background subtractionīackground is first subtracted either using ImageJ’s ‘rolling ball’ background subtraction, or using the neurite image as a mask to remove any bleed through of neurite fluorescence, followed by subtraction of pixels below a user provided threshold (the user can also select no background subtraction). MyelinJ analyses % myelination and % neurite density of 2D fluorescent micrographs. (2019) and manual analysis of micrographs was performed according to Sorensen et al. (2008), demyelinated as described in McCanney et al. Myelinating cultures were made according to Sorensen et al. This study has only tested MyelinJ using myelinating cultures, however it is likely to also be useful for analysing slice cultures ( Hill et al., 2014) and tissue sections. MyelinJ aims to be widely applicable to the neuroscience community, because the settings can be easily adjusted/optimized specifically for your experiment. The user friendly graphical user interface (GUI) and username system support reproducibility and sharing. The macro produces the percentage (%) of myelination and the % of neurite density for each image and links to R ( R Core Team, 2013) for automated statistical analysis and graph production. The MyelinJ ImageJ plugin we have developed is a freely available ImageJ ( Schindelin et al., 2012) macro that allows for high throughput analysis of individual experiments or large studies. Currently, only a CellProfiler pipeline is freely available for analysis of in vitro myelination (available at ). One of the main bottlenecks for these screens is the accurate high throughput quantification of myelin sheaths. Consequently, myelinating cultures can be used as a high throughput screen for potential therapeutics that promote (re)myelination ( McCanney et al., 2018, 2019). Myelinating cultures generated from dissociated embryonic rodent spinal cords have been developed ( Kerman et al., 2015 Pang et al., 2012 Sorensen et al., 2008 Thomson et al., 2008) as a tool to study developmental myelination ( Ioannidou et al., 2012), characteristics of spinal cord injury ( Boomkamp et al., 2012) and demyelination ( Lindner and Linington, 2016). Ann Neurol 2:345–355Ĭarpenter AE, Jones TR, Lamprecht MR, Clarke C, Kang IH, Friman O, Guertin DA, Chang JH, Lindquist RA, Moffa TJ, Golland P, Sabatini DM (2006) Cell Profiler: image analysis software for identifying and quantifying cell phenotypes.Myelin is an essential component of the central nervous system (CNS) and its degeneration is associated with spinal cord injury and several CNS diseases, most notably multiple sclerosis ( Goldenberg, 2012). Seil FJ (1977) Tissue culture studies of demyelinating disease: a critical review. Exp Neurol 247:259–266īornstein MB, Appel SH (1965) Tissue culture studies of demyelination. Lindner M, Ng JK, Hochmeister S, Meinl E, Linington C (2013) Neurofascin 186 specific autoantibodies induce axonal injury and exacerbate disease severity in experimental autoimmune encephalomyelitis. Glia 56:750–763Įlliott C, Lindner M, Arthur A, Brennan K, Jarius S, Hussey J, Chan A, Stroet A, Olsson T, Willison H, Barnett SC, Meinl E, Linington C (2012) Functional identification of pathogenic autoantibody responses in patients with multiple sclerosis. Sorensen A, Moffat K, Thomson C, Barnett SC (2008) Astrocytes, but not olfactory ensheathing cells or Schwann cells, promote myelination of CNS axons in vitro. Schirmer L, Srivastava R, Hemmer B (2014) To look for a needle in a haystack: the search for autoantibodies in multiple sclerosis.
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