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Here we introduce CELLECT, a contrastive embedding learning method for large-scale efficient cell tracking, and demonstrate it on the\n                    <jats:italic>Caenorhabditis elegans<\/jats:italic>\n                    dataset in the Cell Tracking Challenge. By contrastive learning of latent embeddings of diverse cellular structures, a CELLECT model pretrained on a single public dataset can be effectively applied across different imaging modalities and species with broad generalization. Using advanced two-photon imaging, CELLECT enables real-time 3D tracking of large-scale B cells with frequent divisions during germinal center formation in a mouse lymph node, quantitative identification of cell\u2013bacterium interactions in the mouse spleen and high-fidelity extraction of neural signals during strong nonrigid motions. We believe that these results demonstrate broad applications of CELLECT in immunology, pathology and neuroscience.\n                  <\/jats:p>","DOI":"10.1038\/s41592-025-02886-x","type":"journal-article","created":{"date-parts":[[2025,10,20]],"date-time":"2025-10-20T09:03:14Z","timestamp":1760950994000},"page":"2411-2422","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["CELLECT: contrastive embedding learning for large-scale efficient cell tracking"],"prefix":"10.1038","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1939-5922","authenticated-orcid":false,"given":"Hongyu","family":"Zhou","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1145-0336","authenticated-orcid":false,"given":"Seonghoon","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhifeng","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-1860-3729","authenticated-orcid":false,"given":"Jiaqi","family":"Fan","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wen","family":"Huang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinghua","family":"Sui","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8974-6540","authenticated-orcid":false,"given":"Lizhi","family":"Shao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Haoran","family":"An","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing-Ren","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3479-1026","authenticated-orcid":false,"given":"Jiamin","family":"Wu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7043-3061","authenticated-orcid":false,"given":"Qionghai","family":"Dai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,10,20]]},"reference":[{"key":"2886_CR1","doi-asserted-by":"crossref","DOI":"10.1126\/science.abf9277","volume":"373","author":"S Brioschi","year":"2021","unstructured":"Brioschi, S. et al. 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