{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T14:34:01Z","timestamp":1772634841134,"version":"3.50.1"},"reference-count":15,"publisher":"Oxford University Press (OUP)","issue":"21","license":[{"start":{"date-parts":[[2019,5,16]],"date-time":"2019-05-16T00:00:00Z","timestamp":1557964800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000265","name":"MRC","doi-asserted-by":"publisher","award":["MR\/K501335\/1"],"award-info":[{"award-number":["MR\/K501335\/1"]}],"id":[{"id":"10.13039\/501100000265","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000268","name":"BBSRC","doi-asserted-by":"publisher","award":["BB\/J013854\/1"],"award-info":[{"award-number":["BB\/J013854\/1"]}],"id":[{"id":"10.13039\/501100000268","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100004440","name":"Wellcome Trust","doi-asserted-by":"publisher","award":["202789\/Z\/16\/Z"],"award-info":[{"award-number":["202789\/Z\/16\/Z"]}],"id":[{"id":"10.13039\/100004440","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100000294","name":"Medical Research Scotland","doi-asserted-by":"publisher","award":["56"],"award-info":[{"award-number":["56"]}],"id":[{"id":"10.13039\/501100000294","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Summary<\/jats:title>\n                  <jats:p>MyelinJ is a free user friendly ImageJ macro for high throughput analysis of fluorescent micrographs such as 2D-myelinating cultures and statistical analysis using R. MyelinJ can analyse single images or complex experiments with multiple conditions, where the ggpubr package in R is automatically used for statistical analysis and the production of publication quality graphs. The main outputs are percentage (%) neurite density and % myelination. % neurite density is calculated using the normalize local contrast algorithm, followed by thresholding, to adjust for differences in intensity. For % myelination the myelin sheaths are selected using the Frangi vesselness algorithm, in conjunction with a grey scale morphology filter and the removal of cell bodies using a high intensity mask. MyelinJ uses a simple graphical user interface and user name system for reproducibility and sharing that will be useful to the wider scientific community that study 2D-myelination in vitro.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>MyelinJ is freely available at https:\/\/github.com\/BarnettLab\/MyelinJ. For statistical analysis the freely available R and the ggpubr package are also required. MyelinJ has a user guide (Supplementary Material) and has been tested on both Windows (Windows 10) and Mac (High Sierra) operating systems.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btz403","type":"journal-article","created":{"date-parts":[[2019,5,7]],"date-time":"2019-05-07T23:26:09Z","timestamp":1557271569000},"page":"4528-4530","source":"Crossref","is-referenced-by-count":38,"title":["MyelinJ: an ImageJ macro for high throughput analysis of myelinating cultures"],"prefix":"10.1093","volume":"35","author":[{"given":"Michael J","family":"Whitehead","sequence":"first","affiliation":[{"name":"Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow , Glasgow, UK"}]},{"given":"George A","family":"McCanney","sequence":"additional","affiliation":[{"name":"Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow , Glasgow, UK"}]},{"given":"Hugh J","family":"Willison","sequence":"additional","affiliation":[{"name":"Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow , Glasgow, UK"}]},{"given":"Susan C","family":"Barnett","sequence":"additional","affiliation":[{"name":"Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow , Glasgow, UK"}]}],"member":"286","published-online":{"date-parts":[[2019,5,16]]},"reference":[{"key":"2023062712534440900_btz403-B2","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1002\/glia.22278","article-title":"The development of a rat in vitro model of spinal cord injury demonstrating the additive effects of Rho and ROCK inhibitors on neurite outgrowth and myelination","volume":"60","author":"Boomkamp","year":"2012","journal-title":"Glia"},{"key":"2023062712534440900_btz403-B1","first-page":"130","author":"Frangi","year":"1998"},{"key":"2023062712534440900_btz403-B3","first-page":"175","article-title":"Multiple sclerosis review","volume":"37","author":"Goldenberg","year":"2012","journal-title":"Pharm. 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