{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T15:47:22Z","timestamp":1792684042378,"version":"4.5.0"},"reference-count":0,"publisher":"International Union of Crystallography (IUCr)","issue":"6","license":[{"start":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T00:00:00Z","timestamp":1792022400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"},{"start":{"date-parts":[[2026,10,15]],"date-time":"2026-10-15T00:00:00Z","timestamp":1792022400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"name":"Natural Science Foundation of China","award":["T2350011"],"award-info":[{"award-number":["T2350011"]}]}],"content-domain":{"domain":["iucr.org","wiley.com","iucrj.org"],"crossmark-restriction":true},"short-container-title":["IUCrJ","IUCr J","Int Union Crystallogr J","Int Union Cryst J"],"accepted":{"date-parts":[[2026,9,23]]},"published-print":{"date-parts":[[2026,11,1]]},"abstract":"<jats:p>\n                    Accurate particle picking remains a critical step in cryo-electron microscopy (cryo-EM) single-particle analysis, and the field has witnessed the development of a broad spectrum of approaches \u2013 from classical template-based methods to modern deep learning frameworks \u2013 to address this task. Here we present\n                    <jats:italic>CryoQSeg<\/jats:italic>\n                    , a particle segmentation and picking framework that represents a paradigm shift toward leveraging a state-of-the-art visual large model. Built upon Qwen-Image-Edit-2511 as its core backbone,\n                    <jats:italic>CryoQSeg<\/jats:italic>\n                    is fine-tuned through supervised fine-tuning and reinforcement learning on the public CryoPPP benchmark dataset, enabling the generation of high-fidelity, pixel-level particle masks directly from raw micrographs. To translate these masks into precise particle coordinates, we further integrate a hybrid post-processing pipeline that couples Hough circle detection with the segment anything model, forming a seamless end-to-end workflow from raw image input to accurate localization. We evaluate\n                    <jats:italic>CryoQSeg<\/jats:italic>\n                    on five representative benchmark datasets, demonstrating competitive performance across a range of protein types and imaging conditions in comparison to mainstream methods including\n                    <jats:italic>Topaz<\/jats:italic>\n                    and\n                    <jats:italic>CryoSegNet<\/jats:italic>\n                    . Furthermore, we validate the framework on the heterogeneous Crt-SPARTA-gRNA-tDNA complex, where it successfully resolves three distinct oligomeric states \u2013 monomer, dimer and tetramer \u2013 at high resolutions, despite using a fraction of the micrographs employed in the original study. By bridging modern visual large models with classical and foundation-model-based post-processing strategies,\n                    <jats:italic>CryoQSeg<\/jats:italic>\n                    demonstrates the potential of this emerging paradigm to deliver a robust and automated solution for cryo-EM particle picking, thereby contributing to a solid foundation for high-resolution three-dimensional structural determination of biological macromolecules.\n                  <\/jats:p>","DOI":"10.1107\/s2052252526009887","type":"journal-article","created":{"date-parts":[[2026,10,6]],"date-time":"2026-10-06T14:27:28Z","timestamp":1791296848000},"update-policy":"https:\/\/doi.org\/10.1107\/cm_01","source":"Crossref","is-referenced-by-count":0,"title":["<i>CryoQSeg<\/i>\n                    : robust particle segmentation for cryo-EM with Qwen-Image-Edit"],"prefix":"10.1107","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-3794-8263","authenticated-orcid":true,"given":"Yunhai","family":"Sun","sequence":"first","affiliation":[{"id":[{"id":"https:\/\/ror.org\/034t30j35","id-type":"ROR","asserted-by":"publisher"}],"department":["Laboratory of Soft Matter Physics, Institute of Physics"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8312-7300","authenticated-orcid":true,"given":"Jiahao","family":"Zhao","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/034t30j35","id-type":"ROR","asserted-by":"publisher"}],"department":["Institute of Automation"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9794-7262","authenticated-orcid":true,"given":"Nan","family":"Xu","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/034t30j35","id-type":"ROR","asserted-by":"publisher"}],"department":["Institute of Automation"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lei","family":"Wang","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/034t30j35","id-type":"ROR","asserted-by":"publisher"}],"department":["Institute of Automation"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4368-8215","authenticated-orcid":true,"given":"Wei","family":"Ding","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/034t30j35","id-type":"ROR","asserted-by":"publisher"}],"department":["Laboratory of Soft Matter Physics, Institute of Physics"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5328-5826","authenticated-orcid":true,"given":"Ming","family":"Li","sequence":"additional","affiliation":[{"id":[{"id":"https:\/\/ror.org\/034t30j35","id-type":"ROR","asserted-by":"publisher"}],"department":["Laboratory of Soft Matter Physics, Institute of Physics"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"329","published-online":{"date-parts":[[2026,10,15]]},"container-title":["IUCrJ"],"original-title":[],"link":[{"URL":"https:\/\/journals.iucr.org\/m\/issues\/2026\/06\/00\/eh5028\/eh5028.pdf","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.iucr.org\/m\/issues\/2026\/06\/00\/eh5028\/eh5028.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,10,22]],"date-time":"2026-10-22T15:36:13Z","timestamp":1792683373000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.iucr.org\/paper?S2052252526009887"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,10,15]]},"references-count":0,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2026,11]]}},"alternative-id":["S2052252526009887"],"URL":"https:\/\/doi.org\/10.1107\/s2052252526009887","relation":{"is-supplemented-by":[{"id-type":"uri","id":"https:\/\/github.com\/BioinfoMachineLearning\/cryoppp","asserted-by":"subject"}]},"ISSN":["2052-2525"],"issn-type":[{"value":"2052-2525","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,10,15]]},"assertion":[{"value":"IUCrJ","order":0,"name":"journal","label":"Publication","explanation":{"URL":"https:\/\/www.iucrj.org\/"},"group":{"name":"general","label":"General"}},{"value":"research 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2026","order":2,"name":"published_online","label":"Published online","group":{"name":"publication_history","label":"Publication history"}},{"value":"This article has supporting information","name":"supplementary_materials","label":"Supplementary materials","explanation":{"URL":"https:\/\/scripts.iucr.org\/cgi-bin\/sendsup?eh5028"}},{"value":"\u00a9 2026 Yunhai Sun\n                      et al.","order":0,"name":"copyright","label":"Copyright","explanation":{"URL":"https:\/\/journals.iucr.org\/services\/copyrightpolicy.html"},"group":{"name":"copyright_and_licencing","label":"Copyright and licencing"}},{"value":"Creative Commons Attribution (CC-BY)","order":1,"name":"license","label":"Licence","explanation":{"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"},"group":{"name":"copyright_and_licencing","label":"Copyright and licencing"}}]}}