{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"institution":[{"name":"bioRxiv"}],"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T01:12:48Z","timestamp":1768525968658,"version":"3.49.0"},"posted":{"date-parts":[[2025,7,3]]},"group-title":"Neuroscience","reference-count":27,"publisher":"openRxiv","license":[{"start":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T00:00:00Z","timestamp":1751500800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"funder":[{"name":"National Institutes of Health Ruth L. Kirschstein National Research Service Award","award":["1F31EY036280-01"],"award-info":[{"award-number":["1F31EY036280-01"]}]},{"DOI":"10.13039\/100005984","name":"Dr. Miriam and Sheldon G. Adelson Medical Research Foundation","doi-asserted-by":"crossref","id":[{"id":"10.13039\/100005984","id-type":"DOI","asserted-by":"crossref"}]},{"name":"The Stein Innovation Award for Research to Prevent Blindness"},{"name":"The Advanced Research Projects Agency for Health"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"accepted":{"date-parts":[[2025,7,3]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                <jats:p>\n                  Recent advances in experimental strategies that promote axon regeneration in adult mammals lay the foundation for future therapies. Reliable and unbiased quantification of regenerated axons is challenging, yet essential for comparing the efficacy of individual treatments and identification of most efficacious combinatorial therapies. Here, we introduce\n                  <jats:italic>AxoMetric<\/jats:italic>\n                  , a user-friendly and freely available software for the rapid quantification of regenerated axons in longitudinal nerve tissue sections.\n                  <jats:italic>AxoMetric<\/jats:italic>\n                  automatically identifies and traces regenerated axons, generating quantitative measurements that closely match conventional manual quantification but with significantly greater speed. Key features include length-dependent axon quantification at defined intervals from the injury site and normalization of axon density to nerve diameter to account for anatomical variability. To facilitate high-throughput analysis, the software includes an image queuing function. Additional features of\n                  <jats:italic>AxoMetric<\/jats:italic>\n                  allow quantification of a range of labeled cellular structures. As a proof of concept, we demonstrate accurate quantification of regenerated axons in the optic nerve, retinal ganglion cells density in retinal flat-mounts, and regenerated axon bundles in injured sciatic nerves. Collectively, we introduce a new platform that is expected to streamline and standardize regenerative outcome assessments across diverse experimental conditions and laboratories.\n                <\/jats:p>\n                <jats:sec>\n                  <jats:title>Graphical Abstract<\/jats:title>\n                  <jats:fig id=\"ufig1\" position=\"float\" fig-type=\"figure\" orientation=\"portrait\">\n                    <jats:graphic xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"662816v1_ufig1\" position=\"float\" orientation=\"portrait\"\/>\n                  <\/jats:fig>\n                <\/jats:sec>","DOI":"10.1101\/2025.07.02.662816","type":"posted-content","created":{"date-parts":[[2025,7,3]],"date-time":"2025-07-03T23:30:16Z","timestamp":1751585416000},"source":"Crossref","is-referenced-by-count":0,"title":["AxoMetric: A Rapid and Unbiased Tool for Automated Quantification of Axon Regeneration in Tissue Sections"],"prefix":"10.64898","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6742-206X","authenticated-orcid":false,"given":"Matthew C.","family":"Finneran","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tara","family":"Rhamani","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Isma\u00ebl Valentin","family":"Salioski","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1570-6543","authenticated-orcid":false,"given":"Ligia B.","family":"Schmitd","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7485-1313","authenticated-orcid":false,"given":"Ryan","family":"Passino","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Craig N.","family":"Johnson","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2926-3336","authenticated-orcid":false,"given":"Roman J.","family":"Giger","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"54368","reference":[{"key":"2025070714404403000_2025.07.02.662816v1.1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2018.09.005"},{"key":"2025070714404403000_2025.07.02.662816v1.2","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.1423221112"},{"key":"2025070714404403000_2025.07.02.662816v1.3","doi-asserted-by":"publisher","DOI":"10.5334\/jors.342"},{"issue":"14","key":"2025070714404403000_2025.07.02.662816v1.4","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1167\/tvst.10.14.22","article-title":"AxonDeep: Automated Optic Nerve Axon Segmentation in Mice With Deep Learning","volume":"10","year":"2021","journal-title":"Translational Vision Science & Techonology"},{"key":"2025070714404403000_2025.07.02.662816v1.5","doi-asserted-by":"publisher","DOI":"10.1016\/j.exer.2016.04.012"},{"key":"2025070714404403000_2025.07.02.662816v1.6","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-58917-4"},{"key":"2025070714404403000_2025.07.02.662816v1.7","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.1197-13.2013"},{"issue":"3","key":"2025070714404403000_2025.07.02.662816v1.8","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1167\/tvst.12.3.9","article-title":"AxoNet 2.0: A Deep Learning-Based Tool for Morphometric Analysis of Retinal Ganglion Cell Axons","volume":"12","year":"2023","journal-title":"Translational Vision Science & Technology"},{"issue":"6","key":"2025070714404403000_2025.07.02.662816v1.9","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1167\/tvst.9.6.28","article-title":"Software for Quantifying and Batch Processing Images of Brn3a and RBPMS Immunolabelled Retinal Ganglion Cells in Retinal Wholemounts","volume":"9","year":"2020","journal-title":"Translational Vision Science & Technology"},{"key":"2025070714404403000_2025.07.02.662816v1.10","doi-asserted-by":"publisher","DOI":"10.1523\/JNEUROSCI.20-12-04615.2000"},{"key":"2025070714404403000_2025.07.02.662816v1.11","doi-asserted-by":"publisher","DOI":"10.1016\/j.exer.2024.109881"},{"key":"2025070714404403000_2025.07.02.662816v1.12","doi-asserted-by":"publisher","DOI":"10.1088\/1741-2552\/ad31c3"},{"key":"2025070714404403000_2025.07.02.662816v1.13","doi-asserted-by":"publisher","DOI":"10.1167\/tvst.12.5.7"},{"key":"2025070714404403000_2025.07.02.662816v1.14","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-80308-y"},{"key":"2025070714404403000_2025.07.02.662816v1.15","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2016.01.021"},{"key":"2025070714404403000_2025.07.02.662816v1.16","doi-asserted-by":"publisher","DOI":"10.1016\/j.celrep.2024.113931"},{"key":"2025070714404403000_2025.07.02.662816v1.17","doi-asserted-by":"publisher","DOI":"10.1186\/s12868-018-0409-0"},{"key":"2025070714404403000_2025.07.02.662816v1.18","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btq046"},{"key":"2025070714404403000_2025.07.02.662816v1.19","doi-asserted-by":"publisher","DOI":"10.1016\/j.jneumeth.2023.109895"},{"key":"2025070714404403000_2025.07.02.662816v1.20","first-page":"371","article-title":"Automated Analysis of NeruonJ Tracing Data","volume":"4","year":"2009","journal-title":"Cytometry Part A"},{"key":"2025070714404403000_2025.07.02.662816v1.21","doi-asserted-by":"publisher","DOI":"10.1167\/iovs.11-9274"},{"key":"2025070714404403000_2025.07.02.662816v1.22","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-64898-1"},{"key":"2025070714404403000_2025.07.02.662816v1.23","doi-asserted-by":"publisher","DOI":"10.1101\/2024.03.04.583374"},{"key":"2025070714404403000_2025.07.02.662816v1.24","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-018-22181-4"},{"key":"2025070714404403000_2025.07.02.662816v1.25","doi-asserted-by":"publisher","DOI":"10.1038\/srep26559"},{"key":"2025070714404403000_2025.07.02.662816v1.26","doi-asserted-by":"publisher","DOI":"10.24272\/j.issn.2095-8137.2022.025"},{"key":"2025070714404403000_2025.07.02.662816v1.27","doi-asserted-by":"publisher","DOI":"10.7554\/elife.80881"}],"container-title":[],"original-title":[],"link":[{"URL":"https:\/\/syndication.highwire.org\/content\/doi\/10.1101\/2025.07.02.662816","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T09:03:31Z","timestamp":1768467811000},"score":1,"resource":{"primary":{"URL":"http:\/\/biorxiv.org\/lookup\/doi\/10.1101\/2025.07.02.662816"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,7,3]]},"references-count":27,"URL":"https:\/\/doi.org\/10.1101\/2025.07.02.662816","relation":{},"subject":[],"published":{"date-parts":[[2025,7,3]]},"subtype":"preprint"}}