[{"article_processing_charge":"No","year":"2024","date_created":"2025-01-29T12:42:21Z","acknowledgement":"This work is funded by MystenLabs. We thank the Mysten Labs Engineering teams for valuable feedback broadly, and specifically Dmitry Perelman and Todd Fiala for managing the implementation effort. A number of folks contributed to specific aspects of the implementation of Sui Lutris (amongst many other contributions to the overall blockchain): Francois Garillot, Laura Makdah, Mingwei Tian, Andrew Schran, Sadhan Sood and William Smith implemented and optimized aspects of both Sui Lutris and Narwhal / Bullshark consensus; Alonso de Gortari oversaw the cryptoeconomics of the blockchain, and Emma Zhong, Ade Adepoju, Tim Zakia and Dario Russi designed and implemented staking and gas mechanisms. Adam Welc designed several Move tools and provided great feedback on the manuscript. We also extend our thanks to Patrick Kuo, Ge Gao, Chris Li, and Arun Koshy for their work on the Sui Lutris SDK, clients, and RPC layer; Kostas Chalkias, Jonas Lindstrøm, and Joy Wang built cryptographic components.","external_id":{"arxiv":["2310.18042"],"isi":["001436367300178"]},"oa":1,"supplementarymaterial":"no","arxiv":1,"researchdata_availability":"no","day":"09","citation":{"ama":"Blackshear S, Chursin A, Danezis G, et al. Sui Lutris: A blockchain combining broadcast and consensus. In: <i>Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security</i>. ACM; 2024:2606-2620. doi:<a href=\"https://doi.org/10.1145/3658644.3670286\">10.1145/3658644.3670286</a>","chicago":"Blackshear, Sam, Andrey Chursin, George Danezis, Anastasios Kichidis, Eleftherios Kokoris Kogias, Xun Li, Mark Logan, et al. “Sui Lutris: A Blockchain Combining Broadcast and Consensus.” In <i>Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security</i>, 2606–20. ACM, 2024. <a href=\"https://doi.org/10.1145/3658644.3670286\">https://doi.org/10.1145/3658644.3670286</a>.","short":"S. Blackshear, A. Chursin, G. Danezis, A. Kichidis, E. Kokoris Kogias, X. Li, M. Logan, A. Menon, T. Nowacki, A. Sonnino, B. Williams, L. Zhang, in:, Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security, ACM, 2024, pp. 2606–2620.","mla":"Blackshear, Sam, et al. “Sui Lutris: A Blockchain Combining Broadcast and Consensus.” <i>Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security</i>, ACM, 2024, pp. 2606–20, doi:<a href=\"https://doi.org/10.1145/3658644.3670286\">10.1145/3658644.3670286</a>.","apa":"Blackshear, S., Chursin, A., Danezis, G., Kichidis, A., Kokoris Kogias, E., Li, X., … Zhang, L. (2024). Sui Lutris: A blockchain combining broadcast and consensus. In <i>Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security</i> (pp. 2606–2620). Salt Lake City, UT, United States: ACM. <a href=\"https://doi.org/10.1145/3658644.3670286\">https://doi.org/10.1145/3658644.3670286</a>","ieee":"S. Blackshear <i>et al.</i>, “Sui Lutris: A blockchain combining broadcast and consensus,” in <i>Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security</i>, Salt Lake City, UT, United States, 2024, pp. 2606–2620.","ista":"Blackshear S, Chursin A, Danezis G, Kichidis A, Kokoris Kogias E, Li X, Logan M, Menon A, Nowacki T, Sonnino A, Williams B, Zhang L. 2024. Sui Lutris: A blockchain combining broadcast and consensus. Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security. CCS: Conference on Computer and Communications Security, 2606–2620."},"title":"Sui Lutris: A blockchain combining broadcast and consensus","date_updated":"2026-10-01T11:04:52Z","author":[{"first_name":"Sam","last_name":"Blackshear","full_name":"Blackshear, Sam"},{"first_name":"Andrey","last_name":"Chursin","full_name":"Chursin, Andrey"},{"full_name":"Danezis, George","last_name":"Danezis","first_name":"George"},{"full_name":"Kichidis, Anastasios","last_name":"Kichidis","first_name":"Anastasios"},{"full_name":"Kokoris Kogias, Eleftherios","orcid":"0000-0002-8827-3382","id":"f5983044-d7ef-11ea-ac6d-fd1430a26d30","last_name":"Kokoris Kogias","first_name":"Eleftherios"},{"full_name":"Li, Xun","first_name":"Xun","last_name":"Li"},{"first_name":"Mark","last_name":"Logan","full_name":"Logan, Mark"},{"full_name":"Menon, Ashok","first_name":"Ashok","last_name":"Menon"},{"last_name":"Nowacki","first_name":"Todd","full_name":"Nowacki, Todd"},{"last_name":"Sonnino","first_name":"Alberto","full_name":"Sonnino, Alberto"},{"first_name":"Brandon","last_name":"Williams","full_name":"Williams, Brandon"},{"full_name":"Zhang, Lu","first_name":"Lu","last_name":"Zhang"}],"abstract":[{"lang":"eng","text":"Sui Lutris is the first smart-contract platform to sustainably achieve sub-second finality. It achieves this significant decrease by employing consensusless agreement not only for simple payments but for a large variety of transactions. Unlike prior work, Sui Lutris neither compromises expressiveness nor throughput and can run perpetually without restarts. Sui Lutris achieves this by safely integrating consensuless agreement with a high-throughput consensus protocol that is invoked out of the critical finality path but ensures that when a transaction is at risk of inconsistent concurrent accesses, its settlement is delayed until the total ordering is resolved. Building such a hybrid architecture is especially delicate during reconfiguration events, where the system needs to preserve the safety of the consensusless path without compromising the long-term liveness of potentially misconfigured clients. We thus develop a novel reconfiguration protocol, the first to provably show the safe and efficient reconfiguration of a consensusless blockchain. Sui Lutris is currently running in production and underpins the Sui smart-contract platform. Combined with the use of Objects instead of accounts it enables the safe execution of smart contracts that expose objects as a first-class resource. In our experiments Sui Lutris achieves latency lower than 0.5 seconds for throughput up to 5,000 certificates per second (150k ops/s with transaction blocks), compared to the state-of-the-art real-world consensus latencies of 3 seconds. Furthermore, it gracefully handles validators crash-recovery and does not suffer visible performance degradation during reconfiguration."}],"quality_controlled":"1","doi":"10.1145/3658644.3670286","publication_identifier":{"isbn":["9798400706363"]},"OA_type":"hybrid","fulldoi":"https://doi.org/10.1145/3658644.3670286","OA_place":"repository","department":[{"_id":"ElKo"}],"date_published":"2024-12-09T00:00:00Z","das_tickbox":"0","status":"public","month":"12","oa_version":"Preprint","_id":"18957","isi":1,"page":"2606-2620","publication_status":"published","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication":"Proceedings of the 2024 on ACM SIGSAC Conference on Computer and Communications Security","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2310.18042"}],"conference":{"end_date":"2024-10-18","start_date":"2024-10-14","name":"CCS: Conference on Computer and Communications Security","location":"Salt Lake City, UT, United States"},"type":"conference","publisher":"ACM"},{"oa_version":"Preprint","_id":"17269","scopus_import":"1","isi":1,"month":"09","page":"1492-1500","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1101/2022.07.17.500364"}],"related_material":{"link":[{"url":"https://ista.ac.at/en/news/a-railroad-of-cells/","description":"News on ISTA website","relation":"press_release"}]},"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication_status":"published","publication":"Nature Physics","language":[{"iso":"eng"}],"type":"journal_article","publisher":"Springer Nature","dataavailabilitystatement":"All data are available from the corresponding authors upon request. Source data are provided with this paper.","publication_identifier":{"issn":["1745-2473"],"eissn":["1745-2481"]},"doi":"10.1038/s41567-024-02532-x","quality_controlled":"1","corr_author":"1","department":[{"_id":"EdHa"}],"OA_place":"repository","ec_funded":1,"OA_type":"green","fulldoi":"https://doi.org/10.1038/s41567-024-02532-x","date_published":"2024-09-01T00:00:00Z","das_tickbox":"1","status":"public","researchdata_availability":"yes","volume":20,"citation":{"ista":"Vercruysse E, Brückner D, Gómez-González M, Remson A, Luciano M, Kalukula Y, Rossetti L, Trepat X, Hannezo EB, Gabriele S. 2024. Geometry-driven migration efficiency of autonomous epithelial cell clusters. Nature Physics. 20, 1492–1500.","apa":"Vercruysse, E., Brückner, D., Gómez-González, M., Remson, A., Luciano, M., Kalukula, Y., … Gabriele, S. (2024). Geometry-driven migration efficiency of autonomous epithelial cell clusters. <i>Nature Physics</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41567-024-02532-x\">https://doi.org/10.1038/s41567-024-02532-x</a>","ieee":"E. Vercruysse <i>et al.</i>, “Geometry-driven migration efficiency of autonomous epithelial cell clusters,” <i>Nature Physics</i>, vol. 20. Springer Nature, pp. 1492–1500, 2024.","mla":"Vercruysse, Eléonore, et al. “Geometry-Driven Migration Efficiency of Autonomous Epithelial Cell Clusters.” <i>Nature Physics</i>, vol. 20, Springer Nature, 2024, pp. 1492–500, doi:<a href=\"https://doi.org/10.1038/s41567-024-02532-x\">10.1038/s41567-024-02532-x</a>.","short":"E. Vercruysse, D. Brückner, M. Gómez-González, A. Remson, M. Luciano, Y. Kalukula, L. Rossetti, X. Trepat, E.B. Hannezo, S. Gabriele, Nature Physics 20 (2024) 1492–1500.","chicago":"Vercruysse, Eléonore, David Brückner, Manuel Gómez-González, Alexandre Remson, Marine Luciano, Yohalie Kalukula, Leone Rossetti, Xavier Trepat, Edouard B Hannezo, and Sylvain Gabriele. “Geometry-Driven Migration Efficiency of Autonomous Epithelial Cell Clusters.” <i>Nature Physics</i>. Springer Nature, 2024. <a href=\"https://doi.org/10.1038/s41567-024-02532-x\">https://doi.org/10.1038/s41567-024-02532-x</a>.","ama":"Vercruysse E, Brückner D, Gómez-González M, et al. Geometry-driven migration efficiency of autonomous epithelial cell clusters. <i>Nature Physics</i>. 2024;20:1492-1500. doi:<a href=\"https://doi.org/10.1038/s41567-024-02532-x\">10.1038/s41567-024-02532-x</a>"},"intvolume":"        20","project":[{"call_identifier":"H2020","name":"Design Principles of Branching Morphogenesis","_id":"05943252-7A3F-11EA-A408-12923DDC885E","grant_number":"851288"},{"grant_number":"ALTF 343-2022","_id":"34e2a5b5-11ca-11ed-8bc3-b2265616ef0b","name":"A mechano-chemical theory for stem cell fate decisions in organoid development"}],"day":"01","date_updated":"2026-10-01T11:02:43Z","title":"Geometry-driven migration efficiency of autonomous epithelial cell clusters","abstract":[{"lang":"eng","text":"The directed migration of epithelial cell collectives through coordinated movements plays a crucial role in various physiological processes and is increasingly understood at the level of large confluent monolayers. However, numerous processes rely on the migration of small groups of polarized epithelial clusters in complex environments, and their responses to external geometries remain poorly understood. To address this, we cultivate primary epithelial keratocyte tissues on adhesive microstripes to create autonomous epithelial clusters with well-defined geometries. We show that their migration efficiency is strongly influenced by the contact geometry and the orientation of cell–cell contacts with respect to the direction of migration. A combination of velocity and polarity alignment with contact regulation of locomotion in an active matter model captures quantitatively the experimental data. Furthermore, we predict that this combination of rules enables efficient navigation in complex geometries, which we confirm experimentally. Altogether, our findings provide a conceptual framework for extracting the interaction rules of active systems from their interaction with physical boundaries, as well as design principles for collective navigation in complex microenvironments."}],"author":[{"full_name":"Vercruysse, Eléonore","first_name":"Eléonore","last_name":"Vercruysse"},{"last_name":"Brückner","id":"e1e86031-6537-11eb-953a-f7ab92be508d","first_name":"David","orcid":"0000-0001-7205-2975","full_name":"Brückner, David"},{"first_name":"Manuel","last_name":"Gómez-González","full_name":"Gómez-González, Manuel"},{"last_name":"Remson","first_name":"Alexandre","full_name":"Remson, Alexandre"},{"last_name":"Luciano","first_name":"Marine","full_name":"Luciano, Marine"},{"first_name":"Yohalie","last_name":"Kalukula","full_name":"Kalukula, Yohalie"},{"last_name":"Rossetti","first_name":"Leone","full_name":"Rossetti, Leone"},{"last_name":"Trepat","first_name":"Xavier","full_name":"Trepat, Xavier"},{"full_name":"Hannezo, Edouard B","orcid":"0000-0001-6005-1561","first_name":"Edouard B","id":"3A9DB764-F248-11E8-B48F-1D18A9856A87","last_name":"Hannezo"},{"last_name":"Gabriele","first_name":"Sylvain","full_name":"Gabriele, Sylvain"}],"year":"2024","date_created":"2024-07-16T12:32:17Z","article_processing_charge":"No","external_id":{"isi":["001250246200004"]},"oa":1,"acknowledgement":"M.L., E.V. and S.G. acknowledge funding from the European Regional Development Fund (ERDF) Prostem Research Project (No. 1510614, Wallonia DG06), the Epiforce Project of the National Fund for Scientific Research, Belgium (FRS-FNRS; Project No. T.0092.21), the Cellsqueezer Project of FRS-FNRS (Project No. J.0061.23), the Optopattern Project of FRS-FNRS (Project no. U.NO26.22) and the Interreg MAT(T)ISSE project, which is financially supported by Interreg France-Wallonie-Vlaanderen, ERDF). A.R. and M.L. are financially supported by FRS-FNRS as a research fellow (Aspirant FNRS) and Postdoctoral Researcher (Chargée de Recherches FNRS), respectively. E.V. and Y.K. are financially supported by FRS-FNRS through grants from the Fund for Research Training in Industry and Agriculture (FRIA). This project was supported by the European Research Council under the European Union’s Horizon 2020 Research and Innovation Programme (Grant Agreement No. 851288 to E.H.) and Marie Skłodowska-Curie Actions (Grant Agreement No. 797621 to M.G.-G.). D.B.B. was supported by the NOMIS foundation as a NOMIS fellow and by the European Molecular Biology Organization (Postdoctoral Fellowship ALTF 343-2022) and performed this work in part at the Aspen Center for Physics, which is supported by the National Science Foundation (Grant No. PHY-1607611). X.T. and M.G.-G. acknowledge support from the Government of Catalonia (Grant No. AGAUR SGR-2017-01602 and a CERCA Programme), the Spanish Ministry for Science and Innovation and ERDF (Grant No. PGC2018-099645-B-I00), the European Research Council (Grant No. Adv-883739), Fundació la Marató de TV3 (201903-30-31-32), the European Commission (Grant No. H2020-FETPROACT-01-2016-731957), La Caixa Foundation and the Biomedical Research Center Consortium in Red (Grant No. CB15/00153) at the Carlos III Health Institute, Ministry of Science and Innovation. IBEC is recipient of a Severo Ochoa Award of Excellence from the Spanish Ministry of Economy, Trade and Business.","article_type":"original","supplementarymaterial":"yes"},{"article_type":"original","supplementarymaterial":"yes","acknowledgement":"We are grateful to the members of the Hiiragi laboratory for discussions and comments on the manuscript: R. Bloehs, S. Friese, S. Hozeifi, L. Pérez, and W. Schwarzer for their technical support; V. Janssen for establishing the PAB protocol; members of the Tsukiyama group for the animal care with monkeys, in particular H. Tsuchiya and M. Nakaya; Unité Commune d’Expérimentation Animale (UCEA, Jouy-en-Josas, France) for the animal care with rabbits; the EMBL electronic and mechanical workshops and the EMBL animal facility for their support; We thank Luxendo for the close collaboration in developing the light-sheet microscopy for mammalian embryos.\r\nFunding: This work was funded by the following: EMBL Interdisciplinary Postdoc Program (EIPOD) under Marie Sklodowska Curie Actions COFUND III RTD (to D.F.); JSPS Overseas Research Fellowship (to T.I.); Field of excellence “Complexity of life in basic research and innovation” of the University of Graz (to B.C.M.); European Research Council, ERC Advanced Grant “SelforganisingEmbryo”, grant agreement 742732; ERC Advanced Grant “COORDINATION” grant agreement 101055287 (to T.H.); Stichting LSH-TKI, grant LSHM21020 (to T.H.) JSPS KAKENHI grants JP21H05038 and JP22H05166 (to T.H.)","external_id":{"isi":["001422132300018"],"pmid":["39388574"]},"oa":1,"article_processing_charge":"No","date_created":"2024-10-20T22:02:06Z","year":"2024","author":[{"last_name":"Fabrèges","first_name":"Dimitri","full_name":"Fabrèges, Dimitri"},{"first_name":"Bernat","id":"43BE2298-F248-11E8-B48F-1D18A9856A87","last_name":"Corominas-Murtra","full_name":"Corominas-Murtra, Bernat","orcid":"0000-0001-9806-5643"},{"last_name":"Moghe","first_name":"Prachiti","full_name":"Moghe, Prachiti"},{"full_name":"Kickuth, Alison","first_name":"Alison","last_name":"Kickuth"},{"first_name":"Takafumi","last_name":"Ichikawa","full_name":"Ichikawa, Takafumi"},{"full_name":"Iwatani, Chizuru","last_name":"Iwatani","first_name":"Chizuru"},{"full_name":"Tsukiyama, Tomoyuki","first_name":"Tomoyuki","last_name":"Tsukiyama"},{"last_name":"Daniel","first_name":"Nathalie","full_name":"Daniel, Nathalie"},{"full_name":"Gering, Julie","last_name":"Gering","first_name":"Julie"},{"first_name":"Anniek","last_name":"Stokkermans","full_name":"Stokkermans, Anniek"},{"full_name":"Wolny, Adrian","last_name":"Wolny","first_name":"Adrian"},{"full_name":"Kreshuk, Anna","last_name":"Kreshuk","first_name":"Anna"},{"full_name":"Duranthon, Véronique","first_name":"Véronique","last_name":"Duranthon"},{"full_name":"Uhlman, Virginie","last_name":"Uhlman","first_name":"Virginie"},{"first_name":"Edouard B","id":"3A9DB764-F248-11E8-B48F-1D18A9856A87","last_name":"Hannezo","orcid":"0000-0001-6005-1561","full_name":"Hannezo, Edouard B"},{"full_name":"Hiiragi, Takashi","first_name":"Takashi","last_name":"Hiiragi"}],"abstract":[{"text":"How living systems achieve precision in form and function despite their intrinsic stochasticity is a fundamental yet ongoing question in biology. We generated morphomaps of preimplantation embryogenesis in mouse, rabbit, and monkey embryos, and these morphomaps revealed that although blastomere divisions desynchronized passively, 8-cell embryos converged toward robust three-dimensional shapes. Using topological analysis and genetic perturbations, we found that embryos progressively changed their cellular connectivity to a preferred topology, which could be predicted by a physical model in which actomyosin contractility and noise facilitate topological transitions, lowering surface energy. This mechanism favored regular embryo packing and promoted a higher number of inner cells in the 16-cell embryo. Synchronized division reduced embryo packing and generated substantially more misallocated cells and fewer inner-cell–mass cells. These findings suggest that stochasticity in division timing contributes to robust patterning.","lang":"eng"}],"title":"Temporal variability and cell mechanics control robustness in mammalian embryogenesis","date_updated":"2026-10-01T10:54:32Z","day":"11","volume":386,"intvolume":"       386","citation":{"short":"D. Fabrèges, B. Corominas-Murtra, P. Moghe, A. Kickuth, T. Ichikawa, C. Iwatani, T. Tsukiyama, N. Daniel, J. Gering, A. Stokkermans, A. Wolny, A. Kreshuk, V. Duranthon, V. Uhlman, E.B. Hannezo, T. Hiiragi, Science 386 (2024).","mla":"Fabrèges, Dimitri, et al. “Temporal Variability and Cell Mechanics Control Robustness in Mammalian Embryogenesis.” <i>Science</i>, vol. 386, no. 6718, eadh1145, AAAS, 2024, doi:<a href=\"https://doi.org/10.1126/science.adh1145\">10.1126/science.adh1145</a>.","chicago":"Fabrèges, Dimitri, Bernat Corominas-Murtra, Prachiti Moghe, Alison Kickuth, Takafumi Ichikawa, Chizuru Iwatani, Tomoyuki Tsukiyama, et al. “Temporal Variability and Cell Mechanics Control Robustness in Mammalian Embryogenesis.” <i>Science</i>. AAAS, 2024. <a href=\"https://doi.org/10.1126/science.adh1145\">https://doi.org/10.1126/science.adh1145</a>.","ista":"Fabrèges D, Corominas-Murtra B, Moghe P, Kickuth A, Ichikawa T, Iwatani C, Tsukiyama T, Daniel N, Gering J, Stokkermans A, Wolny A, Kreshuk A, Duranthon V, Uhlman V, Hannezo EB, Hiiragi T. 2024. Temporal variability and cell mechanics control robustness in mammalian embryogenesis. Science. 386(6718), eadh1145.","ieee":"D. Fabrèges <i>et al.</i>, “Temporal variability and cell mechanics control robustness in mammalian embryogenesis,” <i>Science</i>, vol. 386, no. 6718. AAAS, 2024.","apa":"Fabrèges, D., Corominas-Murtra, B., Moghe, P., Kickuth, A., Ichikawa, T., Iwatani, C., … Hiiragi, T. (2024). Temporal variability and cell mechanics control robustness in mammalian embryogenesis. <i>Science</i>. AAAS. <a href=\"https://doi.org/10.1126/science.adh1145\">https://doi.org/10.1126/science.adh1145</a>","ama":"Fabrèges D, Corominas-Murtra B, Moghe P, et al. Temporal variability and cell mechanics control robustness in mammalian embryogenesis. <i>Science</i>. 2024;386(6718). doi:<a href=\"https://doi.org/10.1126/science.adh1145\">10.1126/science.adh1145</a>"},"researchdata_availability":"yes","article_number":"eadh1145","pmid":1,"issue":"6718","status":"public","date_published":"2024-10-11T00:00:00Z","das_tickbox":"1","fulldoi":"https://doi.org/10.1126/science.adh1145","OA_type":"green","OA_place":"repository","department":[{"_id":"EdHa"}],"quality_controlled":"1","corr_author":"1","publication_identifier":{"eissn":["1095-9203"]},"doi":"10.1126/science.adh1145","dataavailabilitystatement":"All original code and data reported in this paper is publicly available as of the date of publication on Zenodo (124).\r\n124\r\nD. Fabrèges, B. Corominas-Murtra, P. Moghe, A. Kickuth, T. Ichikawa, C. Iwatani, T. Tsukiyama, N. Daniel, J. Gering, A. Stokkermans, A. Wolny, A. Kreshuk, V. Duranthon, V. Uhlmann, E. Hannezo, T. Hiiragi, Temporal variability and cell mechanics control robustness in mammalian embryogenesis, version 1.0, Zenodo (2024); https://doi.org/10.5281/ZENODO.12819781.","type":"journal_article","publisher":"AAAS","publication_status":"published","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication":"Science","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://hal.inrae.fr/hal-04447081v1/file/2023.01.24.525420.full.pdf","open_access":"1"}],"related_material":{"record":[{"status":"public","relation":"research_data","id":"23023"}]},"month":"10","_id":"18446","scopus_import":"1","oa_version":"Submitted Version","isi":1},{"day":"26","citation":{"mla":"Tsimos, Giorgos, et al. “HammerHead: Leader Reputation for Dynamic Scheduling.” <i>Proceedings - International Conference on Distributed Computing Systems</i>, IEEE, 2024, pp. 1377–87, doi:<a href=\"https://doi.org/10.1109/ICDCS60910.2024.00129\">10.1109/ICDCS60910.2024.00129</a>.","short":"G. Tsimos, A. Kichidis, A. Sonnino, E. Kokoris Kogias, in:, Proceedings - International Conference on Distributed Computing Systems, IEEE, 2024, pp. 1377–1387.","chicago":"Tsimos, Giorgos, Anastasios Kichidis, Alberto Sonnino, and Eleftherios Kokoris Kogias. “HammerHead: Leader Reputation for Dynamic Scheduling.” In <i>Proceedings - International Conference on Distributed Computing Systems</i>, 1377–87. IEEE, 2024. <a href=\"https://doi.org/10.1109/ICDCS60910.2024.00129\">https://doi.org/10.1109/ICDCS60910.2024.00129</a>.","ista":"Tsimos G, Kichidis A, Sonnino A, Kokoris Kogias E. 2024. HammerHead: Leader reputation for dynamic scheduling. Proceedings - International Conference on Distributed Computing Systems. ICDCS: International Conference on Distributed Computing Systems, 1377–1387.","ieee":"G. Tsimos, A. Kichidis, A. Sonnino, and E. Kokoris Kogias, “HammerHead: Leader reputation for dynamic scheduling,” in <i>Proceedings - International Conference on Distributed Computing Systems</i>, Jersey City, NJ, United States, 2024, pp. 1377–1387.","apa":"Tsimos, G., Kichidis, A., Sonnino, A., &#38; Kokoris Kogias, E. (2024). HammerHead: Leader reputation for dynamic scheduling. In <i>Proceedings - International Conference on Distributed Computing Systems</i> (pp. 1377–1387). Jersey City, NJ, United States: IEEE. <a href=\"https://doi.org/10.1109/ICDCS60910.2024.00129\">https://doi.org/10.1109/ICDCS60910.2024.00129</a>","ama":"Tsimos G, Kichidis A, Sonnino A, Kokoris Kogias E. HammerHead: Leader reputation for dynamic scheduling. In: <i>Proceedings - International Conference on Distributed Computing Systems</i>. IEEE; 2024:1377-1387. doi:<a href=\"https://doi.org/10.1109/ICDCS60910.2024.00129\">10.1109/ICDCS60910.2024.00129</a>"},"arxiv":1,"researchdata_availability":"no","author":[{"full_name":"Tsimos, Giorgos","first_name":"Giorgos","last_name":"Tsimos"},{"last_name":"Kichidis","first_name":"Anastasios","full_name":"Kichidis, Anastasios"},{"full_name":"Sonnino, Alberto","last_name":"Sonnino","first_name":"Alberto"},{"orcid":"0000-0002-8827-3382","full_name":"Kokoris Kogias, Eleftherios","last_name":"Kokoris Kogias","id":"f5983044-d7ef-11ea-ac6d-fd1430a26d30","first_name":"Eleftherios"}],"abstract":[{"lang":"eng","text":"Recent advancements on DAG-based consensus protocols allow for blockchains with improved metrics and properties, such as throughput and censorship-resistance. Variants of the Bullshark [18] consensus protocol are adopted for practical use by the Sui blockchain, for improved latency. However, the protocol is leader-based, and is strongly affected by crashed leaders that can lead to various performance issues, for example, decreased transaction throughput. In this paper, we propose HammerHead, a DAG-based consensus protocol, that is inspired by Carousel [8] and provides Leader-Utilization. Our proposal differs from Carousel, which is built for a chained consensus protocol; in HammerHead chain quality is inherited by the DAG. HammerHead needs to preserve safety and liveness, despite validators committing leader vertices asynchronously. The key idea is to update leader schedules dynamically, based on the validators' scores during the previous schedule. We implement HammerHead and show a minor improvement in performance for cases without faults. The major improvements in comparison to Bullshark appear in faulty settings. Specifically, we show a drastic, 2x-latency improvement and up to 40% increased throughput when crash faults occur (100 validators, 33 faults)."}],"title":"HammerHead: Leader reputation for dynamic scheduling","date_updated":"2026-10-01T11:04:17Z","article_processing_charge":"No","year":"2024","date_created":"2024-09-15T22:01:41Z","supplementarymaterial":"no","acknowledgement":"This work is supported by Mysten Labs. We thank the Mysten Labs Engineering teams for valuable feedback broadly, and specifically to Laura Makdah for helping implementing the early reputation score system for validators and Dmitry Perelman for managing the overall implementation effort.","external_id":{"arxiv":["2309.12713"],"isi":["001304430200120"]},"oa":1,"page":"1377-1387","month":"07","_id":"18071","oa_version":"Preprint","scopus_import":"1","isi":1,"conference":{"end_date":"2024-07-26","start_date":"2024-07-23","name":"ICDCS: International Conference on Distributed Computing Systems","location":"Jersey City, NJ, United States"},"type":"conference","publisher":"IEEE","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication_status":"published","language":[{"iso":"eng"}],"publication":"Proceedings - International Conference on Distributed Computing Systems","main_file_link":[{"url":"https://arxiv.org/abs/2309.12713","open_access":"1"}],"fulldoi":"https://doi.org/10.1109/ICDCS60910.2024.00129","department":[{"_id":"ElKo"}],"quality_controlled":"1","doi":"10.1109/ICDCS60910.2024.00129","publication_identifier":{"isbn":["9798350386059"],"eissn":["2575-8411"],"issn":["1063-6927"]},"status":"public","date_published":"2024-07-26T00:00:00Z","das_tickbox":"0"},{"file_date_updated":"2024-07-22T06:16:11Z","status":"public","pmid":1,"date_published":"2024-07-18T00:00:00Z","das_tickbox":"1","has_accepted_license":"1","department":[{"_id":"EM-Fac"},{"_id":"MiSi"},{"_id":"Bio"}],"ec_funded":1,"fulldoi":"https://doi.org/10.1038/s41586-024-07671-y","doi":"10.1038/s41586-024-07671-y","publication_identifier":{"issn":["0028-0836"],"eissn":["1476-4687"]},"file":[{"date_updated":"2024-07-22T06:16:11Z","creator":"dernst","access_level":"open_access","file_id":"17286","checksum":"aa004afc72d2489f0fb0fcbc9919fbbd","file_size":15704819,"file_name":"2024_Nature_Gaertner.pdf","success":1,"relation":"main_file","date_created":"2024-07-22T06:16:11Z","content_type":"application/pdf"}],"quality_controlled":"1","corr_author":"1","type":"journal_article","publisher":"Springer Nature","dataavailabilitystatement":"Imaging and flow cytometry raw data are available on request. scRNA-seq data are accessible at the GEO (GSE261996). Bulk RNA-seq data are accessible at the GEO (GSE185488). Source data are provided with this paper.","related_material":{"link":[{"url":"https://github.com/heiniglab/gaertner_megakaryocytes","relation":"software"}]},"publication_status":"published","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","language":[{"iso":"eng"}],"publication":"Nature","page":"645-653","_id":"17284","scopus_import":"1","oa_version":"Published Version","isi":1,"ddc":["570"],"month":"07","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"article_type":"original","supplementarymaterial":"yes","external_id":{"pmid":["38987596"],"isi":["001281636500020"]},"oa":1,"acknowledgement":"We thank S. Helmer, N. Blount, E. Raatz and Z. Sisic for technical assistance. This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) SFB 1123 (S.M. project B06); SFB 914 (S.M. projects B02 and Z01, H.I.-A. project Z01, S.S. project A06, K.S. project B02, C. Schulz project A10, B.W. project A02, C. Scheiermann project B09); SFB 1054 (T.B. project B03); FOR2033 (F.G., R.A.J.O., S.M.); Individual research grant project ID: 514478744 (F.G.); Heisenberg Programme project ID: 514477451 (F.G.); the DZHK (German Center for Cardiovascular Research) (MHA 1.4VD (S.M.), Postdoc Start-up Grant, 81×3600213 (F.G.)); and LMUexcellence NFF (F.G.). W.F. received funding from China Scholarship Council (CSC, no. 201306270012). P.B. is supported by the German Research Foundation (DFG, project IDs 322900939, 432698239 and 445703531), European Research Council (ERC Consolidator grant no. 101001791) and the Federal Ministry of Education and Research (BMBF, STOP-FSGS-01GM2202C and NATON within the framework of the Network of University Medicine, no. 01KX2121). S.v.S. is supported by the START-Program of the Faculty of Medicine of the RWTH Aachen University (AZ 125/17). A.D. and S.E. are supported by the German Research Foundation (SFB TRR 267); S.E. by the BMBF in the framework of the Cluster4future program (CNATM—Cluster for Nucleic Acid Therapeutics Munich). This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement no. 833440 to S.M.). F.G. received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 747687. The project is funded by the European Union (ERC, MEKanics, 101078110). Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council Executive Agency. Neither the European Union nor the granting authority can be held responsible for them.","year":"2024","date_created":"2024-07-21T22:01:02Z","article_processing_charge":"Yes (in subscription journal)","author":[{"last_name":"Gärtner","id":"397A88EE-F248-11E8-B48F-1D18A9856A87","first_name":"Florian R","full_name":"Gärtner, Florian R","orcid":"0000-0001-6120-3723"},{"full_name":"Ishikawa-Ankerhold, Hellen","first_name":"Hellen","last_name":"Ishikawa-Ankerhold"},{"full_name":"Stutte, Susanne","first_name":"Susanne","last_name":"Stutte"},{"last_name":"Fu","first_name":"Wenwen","full_name":"Fu, Wenwen"},{"full_name":"Weitz, Jutta","last_name":"Weitz","first_name":"Jutta"},{"full_name":"Dueck, Anne","last_name":"Dueck","first_name":"Anne"},{"first_name":"Bhavishya","last_name":"Nelakuditi","full_name":"Nelakuditi, Bhavishya"},{"full_name":"Fumagalli, Valeria","first_name":"Valeria","last_name":"Fumagalli"},{"full_name":"Van Den Heuvel, Dominic","first_name":"Dominic","last_name":"Van Den Heuvel"},{"full_name":"Belz, Larissa","last_name":"Belz","first_name":"Larissa"},{"full_name":"Sobirova, Gulnoza","last_name":"Sobirova","first_name":"Gulnoza"},{"last_name":"Zhang","first_name":"Zhe","full_name":"Zhang, Zhe"},{"last_name":"Titova","first_name":"Anna","full_name":"Titova, Anna"},{"full_name":"Navarro, Alejandro Martinez","first_name":"Alejandro Martinez","last_name":"Navarro"},{"full_name":"Pekayvaz, Kami","first_name":"Kami","last_name":"Pekayvaz"},{"full_name":"Lorenz, Michael","last_name":"Lorenz","first_name":"Michael"},{"last_name":"Von Baumgarten","first_name":"Louisa","full_name":"Von Baumgarten, Louisa"},{"full_name":"Kranich, Jan","last_name":"Kranich","first_name":"Jan"},{"full_name":"Straub, Tobias","first_name":"Tobias","last_name":"Straub"},{"last_name":"Popper","first_name":"Bastian","full_name":"Popper, Bastian"},{"full_name":"Zheden, Vanessa","orcid":"0000-0002-9438-4783","last_name":"Zheden","id":"39C5A68A-F248-11E8-B48F-1D18A9856A87","first_name":"Vanessa"},{"last_name":"Kaufmann","id":"3F99E422-F248-11E8-B48F-1D18A9856A87","first_name":"Walter","orcid":"0000-0001-9735-5315","full_name":"Kaufmann, Walter"},{"last_name":"Guo","first_name":"Chenglong","full_name":"Guo, Chenglong"},{"last_name":"Piontek","first_name":"Guido","full_name":"Piontek, Guido"},{"full_name":"Von Stillfried, Saskia","first_name":"Saskia","last_name":"Von Stillfried"},{"full_name":"Boor, Peter","last_name":"Boor","first_name":"Peter"},{"first_name":"Marco","last_name":"Colonna","full_name":"Colonna, Marco"},{"first_name":"Sebastian","last_name":"Clauß","full_name":"Clauß, Sebastian"},{"first_name":"Christian","last_name":"Schulz","full_name":"Schulz, Christian"},{"full_name":"Brocker, Thomas","last_name":"Brocker","first_name":"Thomas"},{"full_name":"Walzog, Barbara","last_name":"Walzog","first_name":"Barbara"},{"first_name":"Christoph","last_name":"Scheiermann","full_name":"Scheiermann, Christoph"},{"full_name":"Aird, William C.","last_name":"Aird","first_name":"William C."},{"first_name":"Claus","last_name":"Nerlov","full_name":"Nerlov, Claus"},{"first_name":"Konstantin","last_name":"Stark","full_name":"Stark, Konstantin"},{"last_name":"Petzold","first_name":"Tobias","full_name":"Petzold, Tobias"},{"first_name":"Stefan","last_name":"Engelhardt","full_name":"Engelhardt, Stefan"},{"orcid":"0000-0002-6620-9179","full_name":"Sixt, Michael K","last_name":"Sixt","id":"41E9FBEA-F248-11E8-B48F-1D18A9856A87","first_name":"Michael K"},{"id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87","last_name":"Hauschild","first_name":"Robert","full_name":"Hauschild, Robert","orcid":"0000-0001-9843-3522"},{"full_name":"Rudelius, Martina","last_name":"Rudelius","first_name":"Martina"},{"last_name":"Oostendorp","first_name":"Robert A.J.","full_name":"Oostendorp, Robert A.J."},{"last_name":"Iannacone","first_name":"Matteo","full_name":"Iannacone, Matteo"},{"last_name":"Heinig","first_name":"Matthias","full_name":"Heinig, Matthias"},{"full_name":"Massberg, Steffen","last_name":"Massberg","first_name":"Steffen"}],"abstract":[{"lang":"eng","text":"Platelet homeostasis is essential for vascular integrity and immune defence1,2. Although the process of platelet formation by fragmenting megakaryocytes (MKs; thrombopoiesis) has been extensively studied, the cellular and molecular mechanisms required to constantly replenish the pool of MKs by their progenitor cells (megakaryopoiesis) remains unclear3,4. Here we use intravital imaging to track the cellular dynamics of megakaryopoiesis over days. We identify plasmacytoid dendritic cells (pDCs) as homeostatic sensors that monitor the bone marrow for apoptotic MKs and deliver IFNα to the MK niche triggering local on-demand proliferation and maturation of MK progenitors. This pDC-dependent feedback loop is crucial for MK and platelet homeostasis at steady state and under stress. pDCs are best known for their ability to function as vigilant detectors of viral infection5. We show that virus-induced activation of pDCs interferes with their function as homeostatic sensors of megakaryopoiesis. Consequently, activation of pDCs by SARS-CoV-2 leads to excessive megakaryopoiesis. Together, we identify a pDC-dependent homeostatic circuit that involves innate immune sensing and demand-adapted release of inflammatory mediators to maintain homeostasis of the megakaryocytic lineage."}],"date_updated":"2026-10-01T11:17:11Z","title":"Plasmacytoid dendritic cells control homeostasis of megakaryopoiesis","volume":631,"citation":{"apa":"Gärtner, F. R., Ishikawa-Ankerhold, H., Stutte, S., Fu, W., Weitz, J., Dueck, A., … Massberg, S. (2024). Plasmacytoid dendritic cells control homeostasis of megakaryopoiesis. <i>Nature</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41586-024-07671-y\">https://doi.org/10.1038/s41586-024-07671-y</a>","ieee":"F. R. Gärtner <i>et al.</i>, “Plasmacytoid dendritic cells control homeostasis of megakaryopoiesis,” <i>Nature</i>, vol. 631. Springer Nature, pp. 645–653, 2024.","ista":"Gärtner FR, Ishikawa-Ankerhold H, Stutte S, Fu W, Weitz J, Dueck A, Nelakuditi B, Fumagalli V, Van Den Heuvel D, Belz L, Sobirova G, Zhang Z, Titova A, Navarro AM, Pekayvaz K, Lorenz M, Von Baumgarten L, Kranich J, Straub T, Popper B, Zheden V, Kaufmann W, Guo C, Piontek G, Von Stillfried S, Boor P, Colonna M, Clauß S, Schulz C, Brocker T, Walzog B, Scheiermann C, Aird WC, Nerlov C, Stark K, Petzold T, Engelhardt S, Sixt MK, Hauschild R, Rudelius M, Oostendorp RAJ, Iannacone M, Heinig M, Massberg S. 2024. Plasmacytoid dendritic cells control homeostasis of megakaryopoiesis. Nature. 631, 645–653.","chicago":"Gärtner, Florian R, Hellen Ishikawa-Ankerhold, Susanne Stutte, Wenwen Fu, Jutta Weitz, Anne Dueck, Bhavishya Nelakuditi, et al. “Plasmacytoid Dendritic Cells Control Homeostasis of Megakaryopoiesis.” <i>Nature</i>. Springer Nature, 2024. <a href=\"https://doi.org/10.1038/s41586-024-07671-y\">https://doi.org/10.1038/s41586-024-07671-y</a>.","mla":"Gärtner, Florian R., et al. “Plasmacytoid Dendritic Cells Control Homeostasis of Megakaryopoiesis.” <i>Nature</i>, vol. 631, Springer Nature, 2024, pp. 645–53, doi:<a href=\"https://doi.org/10.1038/s41586-024-07671-y\">10.1038/s41586-024-07671-y</a>.","short":"F.R. Gärtner, H. Ishikawa-Ankerhold, S. Stutte, W. Fu, J. Weitz, A. Dueck, B. Nelakuditi, V. Fumagalli, D. Van Den Heuvel, L. Belz, G. Sobirova, Z. Zhang, A. Titova, A.M. Navarro, K. Pekayvaz, M. Lorenz, L. Von Baumgarten, J. Kranich, T. Straub, B. Popper, V. Zheden, W. Kaufmann, C. Guo, G. Piontek, S. Von Stillfried, P. Boor, M. Colonna, S. Clauß, C. Schulz, T. Brocker, B. Walzog, C. Scheiermann, W.C. Aird, C. Nerlov, K. Stark, T. Petzold, S. Engelhardt, M.K. Sixt, R. Hauschild, M. Rudelius, R.A.J. Oostendorp, M. Iannacone, M. Heinig, S. Massberg, Nature 631 (2024) 645–653.","ama":"Gärtner FR, Ishikawa-Ankerhold H, Stutte S, et al. Plasmacytoid dendritic cells control homeostasis of megakaryopoiesis. <i>Nature</i>. 2024;631:645-653. doi:<a href=\"https://doi.org/10.1038/s41586-024-07671-y\">10.1038/s41586-024-07671-y</a>"},"intvolume":"       631","project":[{"call_identifier":"H2020","name":"Mechanical Adaptation of Lamellipodial Actin Networks in Migrating Cells","_id":"260AA4E2-B435-11E9-9278-68D0E5697425","grant_number":"747687"}],"day":"18","researchdata_availability":"upon request"},{"oa":1,"external_id":{"pmid":["38598627"]},"acknowledgement":"We acknowledge (i) the Cryo-Electron Microscopy and Tomography Core Facility and Proteomics Core Facility of the Central European Institute of Technology (CEITEC), Masaryk University, supported by the Ministry of Education, Youth, and Sports of the Czech Republic (grant LM2018127); (ii) the Cellular Imaging Core Facility supported by the Czech-BioImaging large RI project (LM2018129 funded by MEYS CR); and (iii) Plant Sciences Core Facility for support with obtaining scientific data presented here. We acknowledge support from the project National Institute of Virology and Bacteriology (Program EXCELES, ID project no. LX22NPO5103), funded by the European Union - Next Generation EU. This work received funding from the Czech Science Foundation grant GX 19-259882X to P.P., from European Regional Development Fund-Project “MSCAfellow2@MUNI” (no. CZ.02.2.69/0.0/0.0/18_070/0009846) to C.R.B., and from Brno PhD talent scholarship funded by Brno city municipality to M.H.","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"supplementarymaterial":"yes","article_type":"original","year":"2024","date_created":"2025-01-27T14:32:34Z","article_processing_charge":"Yes","date_updated":"2026-10-01T11:15:30Z","title":"Structure and replication cycle of a virus infecting climate-modulating alga Emiliania huxleyi","author":[{"full_name":"Homola, Miroslav","first_name":"Miroslav","last_name":"Homola"},{"full_name":"Büttner, Renate Carina","last_name":"Büttner","id":"3b7984c9-17ff-11ed-b6fe-f943c4a5b626","first_name":"Renate Carina"},{"first_name":"Tibor","last_name":"Füzik","full_name":"Füzik, Tibor"},{"full_name":"Křepelka, Pavel","first_name":"Pavel","last_name":"Křepelka"},{"full_name":"Holbová, Radka","first_name":"Radka","last_name":"Holbová"},{"last_name":"Nováček","first_name":"Jiří","full_name":"Nováček, Jiří"},{"full_name":"Chaillet, Marten L.","first_name":"Marten L.","last_name":"Chaillet"},{"full_name":"Žák, Jakub","first_name":"Jakub","last_name":"Žák"},{"full_name":"Grybchuk, Danyil","first_name":"Danyil","last_name":"Grybchuk"},{"last_name":"Förster","first_name":"Friedrich","full_name":"Förster, Friedrich"},{"last_name":"Wilson","first_name":"William H.","full_name":"Wilson, William H."},{"first_name":"Declan C.","last_name":"Schroeder","full_name":"Schroeder, Declan C."},{"full_name":"Plevka, Pavel","first_name":"Pavel","last_name":"Plevka"}],"abstract":[{"text":"The globally distributed marine alga Emiliania huxleyi has cooling effect on the Earth’s climate. The population density of E. huxleyi is restricted by Nucleocytoviricota viruses, including E. huxleyi virus 201 (EhV-201). Despite the impact of E. huxleyi viruses on the climate, there is limited information about their structure and replication. Here, we show that the dsDNA genome inside the EhV-201 virion is protected by an inner membrane, capsid, and outer membrane. EhV-201 virions infect E. huxleyi by using fivefold vertices to bind to and fuse the virus’ inner membrane with the cell plasma membrane. Progeny virions assemble in the cytoplasm at the surface of endoplasmic reticulum–derived membrane segments. Genome packaging initiates synchronously with the capsid assembly and completes through an aperture in the forming capsid. The genome-filled capsids acquire an outer membrane by budding into intracellular vesicles. EhV-201 infection induces a loss of surface protective layers from E. huxleyi cells, which enables the continuous release of virions by exocytosis.","lang":"eng"}],"article_number":"eadk1954 ","researchdata_availability":"yes","intvolume":"        10","citation":{"ama":"Homola M, Büttner RC, Füzik T, et al. Structure and replication cycle of a virus infecting climate-modulating alga Emiliania huxleyi. <i>Science Advances</i>. 2024;10(15). doi:<a href=\"https://doi.org/10.1126/sciadv.adk1954\">10.1126/sciadv.adk1954</a>","ieee":"M. Homola <i>et al.</i>, “Structure and replication cycle of a virus infecting climate-modulating alga Emiliania huxleyi,” <i>Science Advances</i>, vol. 10, no. 15. American Association for the Advancement of Science, 2024.","apa":"Homola, M., Büttner, R. C., Füzik, T., Křepelka, P., Holbová, R., Nováček, J., … Plevka, P. (2024). Structure and replication cycle of a virus infecting climate-modulating alga Emiliania huxleyi. <i>Science Advances</i>. American Association for the Advancement of Science. <a href=\"https://doi.org/10.1126/sciadv.adk1954\">https://doi.org/10.1126/sciadv.adk1954</a>","ista":"Homola M, Büttner RC, Füzik T, Křepelka P, Holbová R, Nováček J, Chaillet ML, Žák J, Grybchuk D, Förster F, Wilson WH, Schroeder DC, Plevka P. 2024. Structure and replication cycle of a virus infecting climate-modulating alga Emiliania huxleyi. Science Advances. 10(15), eadk1954.","chicago":"Homola, Miroslav, Renate Carina Büttner, Tibor Füzik, Pavel Křepelka, Radka Holbová, Jiří Nováček, Marten L. Chaillet, et al. “Structure and Replication Cycle of a Virus Infecting Climate-Modulating Alga Emiliania Huxleyi.” <i>Science Advances</i>. American Association for the Advancement of Science, 2024. <a href=\"https://doi.org/10.1126/sciadv.adk1954\">https://doi.org/10.1126/sciadv.adk1954</a>.","short":"M. Homola, R.C. Büttner, T. Füzik, P. Křepelka, R. Holbová, J. Nováček, M.L. Chaillet, J. Žák, D. Grybchuk, F. Förster, W.H. Wilson, D.C. Schroeder, P. Plevka, Science Advances 10 (2024).","mla":"Homola, Miroslav, et al. “Structure and Replication Cycle of a Virus Infecting Climate-Modulating Alga Emiliania Huxleyi.” <i>Science Advances</i>, vol. 10, no. 15, eadk1954, American Association for the Advancement of Science, 2024, doi:<a href=\"https://doi.org/10.1126/sciadv.adk1954\">10.1126/sciadv.adk1954</a>."},"volume":10,"day":"01","das_tickbox":"1","has_accepted_license":"1","date_published":"2024-04-01T00:00:00Z","file_date_updated":"2025-01-27T14:40:08Z","status":"public","issue":"15","pmid":1,"publication_identifier":{"eissn":["2375-2548"]},"file":[{"date_created":"2025-01-27T14:40:08Z","content_type":"application/pdf","success":1,"relation":"main_file","file_size":40623405,"checksum":"291dd7ceccbe6bfd8e0a9157584f88e9","file_name":"2024_ScienceAdv_Homola.pdf","creator":"dernst","date_updated":"2025-01-27T14:40:08Z","access_level":"open_access","file_id":"18921"}],"doi":"10.1126/sciadv.adk1954","quality_controlled":"1","OA_place":"publisher","department":[{"_id":"EM-Fac"}],"OA_type":"gold","fulldoi":"https://doi.org/10.1126/sciadv.adk1954","related_material":{"link":[{"url":" https://github.com/fuzikt/tomostarpy.","relation":"software"}],"record":[{"relation":"research_data","id":"23025","status":"public"}]},"publication":"Science Advances","language":[{"iso":"eng"}],"publication_status":"published","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publisher":"American Association for the Advancement of Science","type":"journal_article","dataavailabilitystatement":"Cryo-EM maps and structure coordinates were deposited to the Electron Microscopy Data Bank (EMDB) and Protein Data Bank (PDB), respectively, with the following accession numbers: (i) EhV-201 virion vertex reconstructed using a single-particle approach and a mask with the diameter of 50 nm (EMD-17650); (ii) EhV-201 virion vertex reconstructed using sub-tomogram averaging and a mask with the diameter of 50 nm (EMD-17649); (iii) EhV-201 virion vertex reconstructed using sub-tomogram averaging and a mask with the diameter of 50 nm and a mask covering only the capsid layer (EMD-19036) and the fitted structure of AlphaFold2 predicted EhV-201 major capsid protein and penton protein (PDB 8RBT); (iv) EhV-201 virion vertex reconstructed by sub-tomogram averaging and a mask with the diameter of 120 nm (EMD-17651); and (v) composite map of the EhV201 virion (EMD-19035) and corresponding structure of icosahedral asymmetric unit (PDB 8RBS). All custom scripts used during tomographic reconstruction have been made available at https://github.com/fuzikt/tomostarpy. Additional files have been made available at https://doi.org/10.5061/dryad.p5hqbzkw0: (i) cryo-ET tilt series of lamellas of control and EhV-201 infected E. huxleyi cells; (ii) segmentations of cryo-tomograms of infected and control cells; (iii) block face imaging data series of high-pressure frozen and resin-embedded E. huxleyi infected by EhV-201; (iv) scripts used during tomographic reconstruction; (v) fluorescence microscopy images of E. huxleyi infected by EhV-201; and (vi) mass spectrometry report of EhV-201 virion protein composition. Cryo-ET tilt series used for EhV-201 virion structure determination were deposited to EMPIAR and linked to the file EMD-17649. All other data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials.","oa_version":"Published Version","_id":"18920","scopus_import":"1","ddc":["570"],"month":"04","DOAJ_listed":"1"},{"page":"123-137","_id":"18052","oa_version":"None","scopus_import":"1","month":"08","type":"book_chapter","publisher":"Springer Nature","editor":[{"first_name":"Joachim H.R. ","last_name":"Lübke","full_name":"Lübke, Joachim H.R. "},{"last_name":"Rollenhagen","first_name":"Astrid","full_name":"Rollenhagen, Astrid"}],"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication_status":"published","publication":"New Aspects in Analyzing the Synaptic Organization of the Brain","language":[{"iso":"eng"}],"department":[{"_id":"EM-Fac"},{"_id":"RySh"}],"ec_funded":1,"fulldoi":"https://doi.org/10.1007/978-1-0716-4019-7_8","doi":"10.1007/978-1-0716-4019-7_8","publication_identifier":{"issn":["0893-2336"],"isbn":["9781071640180"],"eissn":["1940-6045"],"eisbn":["9781071640197"]},"quality_controlled":"1","acknowledged_ssus":[{"_id":"EM-Fac"}],"edition":"1","corr_author":"1","status":"public","date_published":"2024-08-27T00:00:00Z","place":"New York","das_tickbox":"0","project":[{"call_identifier":"H2020","grant_number":"694539","name":"In situ analysis of single channel subunit composition in neurons: physiological implication in synaptic plasticity and behaviour","_id":"25CA28EA-B435-11E9-9278-68D0E5697425"}],"citation":{"ama":"Kleindienst D, Costanzo T, Shigemoto R. Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning. In: Lübke JHR, Rollenhagen A, eds. <i>New Aspects in Analyzing the Synaptic Organization of the Brain</i>. 1st ed. New York: Springer Nature; 2024:123-137. doi:<a href=\"https://doi.org/10.1007/978-1-0716-4019-7_8\">10.1007/978-1-0716-4019-7_8</a>","ieee":"D. Kleindienst, T. Costanzo, and R. Shigemoto, “Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning,” in <i>New Aspects in Analyzing the Synaptic Organization of the Brain</i>, 1st ed., J. H. R. Lübke and A. Rollenhagen, Eds. New York: Springer Nature, 2024, pp. 123–137.","apa":"Kleindienst, D., Costanzo, T., &#38; Shigemoto, R. (2024). Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning. In J. H. R. Lübke &#38; A. Rollenhagen (Eds.), <i>New Aspects in Analyzing the Synaptic Organization of the Brain</i> (1st ed., pp. 123–137). New York: Springer Nature. <a href=\"https://doi.org/10.1007/978-1-0716-4019-7_8\">https://doi.org/10.1007/978-1-0716-4019-7_8</a>","ista":"Kleindienst D, Costanzo T, Shigemoto R. 2024.Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning. In: New Aspects in Analyzing the Synaptic Organization of the Brain. Neuromethods, , 123–137.","chicago":"Kleindienst, David, Tommaso Costanzo, and Ryuichi Shigemoto. “Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning.” In <i>New Aspects in Analyzing the Synaptic Organization of the Brain</i>, edited by Joachim H.R.  Lübke and Astrid Rollenhagen, 1st ed., 123–37. New York: Springer Nature, 2024. <a href=\"https://doi.org/10.1007/978-1-0716-4019-7_8\">https://doi.org/10.1007/978-1-0716-4019-7_8</a>.","short":"D. Kleindienst, T. Costanzo, R. Shigemoto, in:, J.H.R. Lübke, A. Rollenhagen (Eds.), New Aspects in Analyzing the Synaptic Organization of the Brain, 1st ed., Springer Nature, New York, 2024, pp. 123–137.","mla":"Kleindienst, David, et al. “Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning.” <i>New Aspects in Analyzing the Synaptic Organization of the Brain</i>, edited by Joachim H.R.  Lübke and Astrid Rollenhagen, 1st ed., Springer Nature, 2024, pp. 123–37, doi:<a href=\"https://doi.org/10.1007/978-1-0716-4019-7_8\">10.1007/978-1-0716-4019-7_8</a>."},"alternative_title":["Neuromethods"],"day":"27","researchdata_availability":"no","author":[{"full_name":"Kleindienst, David","first_name":"David","id":"42E121A4-F248-11E8-B48F-1D18A9856A87","last_name":"Kleindienst"},{"full_name":"Costanzo, Tommaso","orcid":"0000-0001-9732-3815","first_name":"Tommaso","last_name":"Costanzo","id":"D93824F4-D9BA-11E9-BB12-F207E6697425"},{"orcid":"0000-0001-8761-9444","full_name":"Shigemoto, Ryuichi","first_name":"Ryuichi","id":"499F3ABC-F248-11E8-B48F-1D18A9856A87","last_name":"Shigemoto"}],"abstract":[{"text":"Sodium dodecyl sulfate-digested freeze-fracture replica labeling (SDS-FRL) is an electron microscope (EM) sample preparation technique which allows for high-resolution visualization of membrane proteins with high sensitivity. However, image acquisition of specific replica profiles such as synapses in a large field of EM view needs a valid experience and a long time for manual searching. Here, we describe how to utilize deep learning for automatizing image acquisition of specific profiles of interest in replica samples. This protocol facilitates the labor-intensive collection of EM images, in particular for rare profiles. We provide instructions for using SerialEM image acquisition software in conjunction with object detection by our newly developed deep learning software DarEM, to automatically acquire tilt series of all synapses in a selected region. We then show how to perform a mostly automated analysis of gold particle labeling in the acquired images by utilizing Darea software.","lang":"eng"}],"date_updated":"2026-10-01T11:17:28Z","title":"Automated Imaging and Analysis of Synapses in Freeze-Fracture Replica Samples with Deep Learning","year":"2024","date_created":"2024-09-10T12:32:38Z","article_processing_charge":"No","supplementarymaterial":"no","acknowledgement":"This research was supported by the European Research Council Advanced Grant 694539 to RS and by the Scientific Service Units of IST Austria through resources provided by the Electron Microscopy Facility."},{"pmid":1,"status":"public","issue":"1","das_tickbox":"0","date_published":"2024-01-08T00:00:00Z","fulldoi":"https://doi.org/10.1016/j.cub.2023.11.039","department":[{"_id":"EvBe"}],"corr_author":"1","quality_controlled":"1","doi":"10.1016/j.cub.2023.11.039","publication_identifier":{"eissn":["1879-0445"]},"publisher":"Elsevier","type":"other_academic_publication","language":[{"iso":"eng"}],"publication":"Current Biology","publication_status":"published","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1016/j.cub.2023.11.039"}],"page":"R3-R5","ddc":["580"],"month":"01","_id":"14842","oa_version":"Published Version","supplementarymaterial":"no","oa":1,"external_id":{"pmid":["38194926"]},"article_processing_charge":"No","date_created":"2024-01-21T23:00:56Z","year":"2024","abstract":[{"text":"Eva Benkova received a PhD in Biophysics at the Institute of Biophysics of the Czech Academy of Sciences in 1998. After working as a postdoc at the Max Planck Institute in Cologne and the Center for Plant Molecular Biology (ZMBP) in Tübingen, she became a group leader at the Plant Systems Biology Department of the Vlaams Instituut voor Biotechnologie (VIB) in Gent. In 2012, she transitioned to an Assistant Professor position at the Institute of Science and Technology Austria (ISTA) where she was later promoted to Professor. Since 2021, she has served as the Dean of the ISTA Graduate School. As a plant developmental biologist, she focuses on unraveling the molecular mechanisms and principles that underlie hormonal interactions in plants. In her current work, she explores the intricate connections between hormones and regulatory pathways that mediate the perception of environmental stimuli, including abiotic stress and nitrate availability.","lang":"eng"}],"author":[{"full_name":"Benková, Eva","orcid":"0000-0002-8510-9739","first_name":"Eva","id":"38F4F166-F248-11E8-B48F-1D18A9856A87","last_name":"Benková"}],"title":"Eva Benkova","date_updated":"2026-10-01T11:17:58Z","day":"08","intvolume":"        34","citation":{"mla":"Benková, Eva. “Eva Benkova.” <i>Current Biology</i>, vol. 34, no. 1, Elsevier, 2024, pp. R3–5, doi:<a href=\"https://doi.org/10.1016/j.cub.2023.11.039\">10.1016/j.cub.2023.11.039</a>.","short":"E. Benková, Eva Benkova, Elsevier, 2024.","chicago":"Benková, Eva. <i>Eva Benkova</i>. <i>Current Biology</i>. Vol. 34. Elsevier, 2024. <a href=\"https://doi.org/10.1016/j.cub.2023.11.039\">https://doi.org/10.1016/j.cub.2023.11.039</a>.","ista":"Benková E. 2024. Eva Benkova, Elsevier,p.","ieee":"E. Benková, <i>Eva Benkova</i>, vol. 34, no. 1. Elsevier, 2024, pp. R3–R5.","apa":"Benková, E. (2024). <i>Eva Benkova</i>. <i>Current Biology</i> (Vol. 34, pp. R3–R5). Elsevier. <a href=\"https://doi.org/10.1016/j.cub.2023.11.039\">https://doi.org/10.1016/j.cub.2023.11.039</a>","ama":"Benková E. <i>Eva Benkova</i>. Vol 34. Elsevier; 2024:R3-R5. doi:<a href=\"https://doi.org/10.1016/j.cub.2023.11.039\">10.1016/j.cub.2023.11.039</a>"},"volume":34,"researchdata_availability":"not applicable"},{"month":"02","ddc":["570"],"_id":"23025","oa_version":"None","day":"07","citation":{"ama":"Homola M, Büttner C, Füzik T, et al. Data: Structure and replication cycle of a virus infecting climate-modulating alga Emiliania huxleyi. 2024. doi:<a href=\"https://doi.org/10.5061/dryad.p5hqbzkw0\">10.5061/dryad.p5hqbzkw0</a>","chicago":"Homola, Miroslav, Carina Büttner, Tibor Füzik, Pavel Krepelka, Radka Holbová, Marten Chaillet, Jiří Nováček, et al. “Data: Structure and Replication Cycle of a Virus Infecting Climate-Modulating Alga Emiliania Huxleyi.” Dryad, 2024. <a href=\"https://doi.org/10.5061/dryad.p5hqbzkw0\">https://doi.org/10.5061/dryad.p5hqbzkw0</a>.","mla":"Homola, Miroslav, et al. <i>Data: Structure and Replication Cycle of a Virus Infecting Climate-Modulating Alga Emiliania Huxleyi</i>. Dryad, 2024, doi:<a href=\"https://doi.org/10.5061/dryad.p5hqbzkw0\">10.5061/dryad.p5hqbzkw0</a>.","short":"M. Homola, C. Büttner, T. Füzik, P. Krepelka, R. Holbová, M. Chaillet, J. Nováček, F. Förster, W. Wilson, D. Schroeder, P. Plevka, (2024).","apa":"Homola, M., Büttner, C., Füzik, T., Krepelka, P., Holbová, R., Chaillet, M., … Plevka, P. (2024). Data: Structure and replication cycle of a virus infecting climate-modulating alga Emiliania huxleyi. Dryad. <a href=\"https://doi.org/10.5061/dryad.p5hqbzkw0\">https://doi.org/10.5061/dryad.p5hqbzkw0</a>","ieee":"M. Homola <i>et al.</i>, “Data: Structure and replication cycle of a virus infecting climate-modulating alga Emiliania huxleyi.” Dryad, 2024.","ista":"Homola M, Büttner C, Füzik T, Krepelka P, Holbová R, Chaillet M, Nováček J, Förster F, Wilson W, Schroeder D, Plevka P. 2024. Data: Structure and replication cycle of a virus infecting climate-modulating alga Emiliania huxleyi, Dryad, <a href=\"https://doi.org/10.5061/dryad.p5hqbzkw0\">10.5061/dryad.p5hqbzkw0</a>."},"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","title":"Data: Structure and replication cycle of a virus infecting climate-modulating alga Emiliania huxleyi","main_file_link":[{"url":"https://doi.org/10.5061/dryad.p5hqbzkw0","open_access":"1"}],"related_material":{"record":[{"id":"18920","relation":"used_in_publication","status":"public"}]},"date_updated":"2026-10-01T11:15:29Z","abstract":[{"text":"The globally distributed marine alga Emiliania huxleyi produces reflective calcite disks (coccoliths) that increase the albedo of ocean water and thus reduce the heat absorption in the ocean, which cools the Earth’s climate. The population density of E. huxleyi is restricted by Nucleocytoviricota viruses, including E. huxleyi virus 201 (EhV-201). Despite the impact of E. huxleyi viruses on the climate, there is limited information about their structure and replication. Here we show that the dsDNA genome inside the EhV-201 virion is protected by an inner membrane, capsid, and outer membrane decorated with numerous transmembrane proteins. The virions are prone to deformation, and parts of their capsids deviate from the icosahedral arrangement. EhV-201 virions infect E. huxleyi by using their fivefold vertex to bind to a host cell and fuse the virus’s inner membrane with the plasma membrane. Whereas the replication of EhV-201 probably occurs in the nucleus, virions assemble in the cytoplasm at the surface of endoplasmic reticulum-derived membrane segments. Genome packaging initiates synchronously with the capsid assembly and completes through an aperture in the forming capsid. Upon the completion of genome packaging, the capsids change conformation, which enables them to acquire an outer membrane by budding into intracellular vesicles. EhV-201 infection induces a loss of surface protective layers from E. huxleyi cells, which allows the continuous release of virions by exocytosis. Our results provide insight into how EhVs bypass the surface protective layers of E. huxleyi and exploit the organelles of an infected cell for progeny assembly.","lang":"eng"}],"author":[{"full_name":"Homola, Miroslav","first_name":"Miroslav","last_name":"Homola"},{"first_name":"Carina","last_name":"Büttner","full_name":"Büttner, Carina"},{"full_name":"Füzik, Tibor","last_name":"Füzik","first_name":"Tibor"},{"full_name":"Krepelka, Pavel","first_name":"Pavel","last_name":"Krepelka"},{"full_name":"Holbová, Radka","last_name":"Holbová","first_name":"Radka"},{"full_name":"Chaillet, Marten","first_name":"Marten","last_name":"Chaillet"},{"last_name":"Nováček","first_name":"Jiří","full_name":"Nováček, Jiří"},{"full_name":"Förster, Friedrich","last_name":"Förster","first_name":"Friedrich"},{"full_name":"Wilson, William","last_name":"Wilson","first_name":"William"},{"full_name":"Schroeder, Declan","first_name":"Declan","last_name":"Schroeder"},{"last_name":"Plevka","first_name":"Pavel","full_name":"Plevka, Pavel"}],"type":"research_data_reference","publisher":"Dryad","doi":"10.5061/dryad.p5hqbzkw0","OA_type":"green","fulldoi":"https://doi.org/10.5061/dryad.p5hqbzkw0","article_processing_charge":"No","date_created":"2026-10-01T11:13:02Z","year":"2024","department":[{"_id":"EM-Fac"}],"OA_place":"repository","date_published":"2024-02-07T00:00:00Z","oa":1,"status":"public"},{"volume":223,"citation":{"ama":"Zens B, Fäßler F, Hansen J, et al. Lift-out cryo-FIBSEM and cryo-ET reveal the ultrastructural landscape of extracellular matrix. <i>Journal of Cell Biology</i>. 2024;223(6). doi:<a href=\"https://doi.org/10.1083/jcb.202309125\">10.1083/jcb.202309125</a>","short":"B. Zens, F. Fäßler, J. Hansen, R. Hauschild, J. Datler, V.-V. Hodirnau, V. Zheden, J.H. Alanko, M.K. Sixt, F.K. Schur, Journal of Cell Biology 223 (2024).","mla":"Zens, Bettina, et al. “Lift-out Cryo-FIBSEM and Cryo-ET Reveal the Ultrastructural Landscape of Extracellular Matrix.” <i>Journal of Cell Biology</i>, vol. 223, no. 6, e202309125, Rockefeller University Press, 2024, doi:<a href=\"https://doi.org/10.1083/jcb.202309125\">10.1083/jcb.202309125</a>.","chicago":"Zens, Bettina, Florian Fäßler, Jesse Hansen, Robert Hauschild, Julia Datler, Victor-Valentin Hodirnau, Vanessa Zheden, Jonna H Alanko, Michael K Sixt, and Florian KM Schur. “Lift-out Cryo-FIBSEM and Cryo-ET Reveal the Ultrastructural Landscape of Extracellular Matrix.” <i>Journal of Cell Biology</i>. Rockefeller University Press, 2024. <a href=\"https://doi.org/10.1083/jcb.202309125\">https://doi.org/10.1083/jcb.202309125</a>.","ista":"Zens B, Fäßler F, Hansen J, Hauschild R, Datler J, Hodirnau V-V, Zheden V, Alanko JH, Sixt MK, Schur FK. 2024. Lift-out cryo-FIBSEM and cryo-ET reveal the ultrastructural landscape of extracellular matrix. Journal of Cell Biology. 223(6), e202309125.","apa":"Zens, B., Fäßler, F., Hansen, J., Hauschild, R., Datler, J., Hodirnau, V.-V., … Schur, F. K. (2024). Lift-out cryo-FIBSEM and cryo-ET reveal the ultrastructural landscape of extracellular matrix. <i>Journal of Cell Biology</i>. Rockefeller University Press. <a href=\"https://doi.org/10.1083/jcb.202309125\">https://doi.org/10.1083/jcb.202309125</a>","ieee":"B. Zens <i>et al.</i>, “Lift-out cryo-FIBSEM and cryo-ET reveal the ultrastructural landscape of extracellular matrix,” <i>Journal of Cell Biology</i>, vol. 223, no. 6. Rockefeller University Press, 2024."},"intvolume":"       223","project":[{"name":"Structure and isoform diversity of the Arp2/3 complex","_id":"9B954C5C-BA93-11EA-9121-9846C619BF3A","grant_number":"P33367"},{"name":"In Situ Actin Structures via Hybrid Cryo-electron Microscopy","_id":"7bd318a1-9f16-11ee-852c-cc9217763180","grant_number":"E435"},{"grant_number":"724373","_id":"25FE9508-B435-11E9-9278-68D0E5697425","name":"Cellular Navigation Along Spatial Gradients","call_identifier":"H2020"},{"name":"NÖ-Fonds Preis für die Jungforscherin des Jahres am IST Austria","_id":"059B463C-7A3F-11EA-A408-12923DDC885E"},{"grant_number":"21317","_id":"2615199A-B435-11E9-9278-68D0E5697425","name":"Spatiotemporal regulation of chemokine-induced signalling in leukocyte chemotaxis"},{"grant_number":"CZI01","name":"CryoMinflux-guided in-situ visual proteomics and structure determination","_id":"62909c6f-2b32-11ec-9570-e1476aab5308"}],"day":"20","article_number":"e202309125","researchdata_availability":"yes","abstract":[{"lang":"eng","text":"The extracellular matrix (ECM) serves as a scaffold for cells and plays an essential role in regulating numerous cellular processes, including cell migration and proliferation. Due to limitations in specimen preparation for conventional room-temperature electron microscopy, we lack structural knowledge on how ECM components are secreted, remodeled, and interact with surrounding cells. We have developed a 3D-ECM platform compatible with sample thinning by cryo-focused ion beam milling, the lift-out extraction procedure, and cryo-electron tomography. Our workflow implements cell-derived matrices (CDMs) grown on EM grids, resulting in a versatile tool closely mimicking ECM environments. This allows us to visualize ECM for the first time in its hydrated, native context. Our data reveal an intricate network of extracellular fibers, their positioning relative to matrix-secreting cells, and previously unresolved structural entities. Our workflow and results add to the structural atlas of the ECM, providing novel insights into its secretion and assembly."}],"author":[{"first_name":"Bettina","id":"45FD126C-F248-11E8-B48F-1D18A9856A87","last_name":"Zens","orcid":"0000-0002-9561-1239","full_name":"Zens, Bettina"},{"orcid":"0000-0001-7149-769X","full_name":"Fäßler, Florian","last_name":"Fäßler","id":"404F5528-F248-11E8-B48F-1D18A9856A87","first_name":"Florian"},{"first_name":"Jesse","last_name":"Hansen","id":"1063c618-6f9b-11ec-9123-f912fccded63","full_name":"Hansen, Jesse","orcid":"0000-0001-7967-2085"},{"full_name":"Hauschild, Robert","orcid":"0000-0001-9843-3522","id":"4E01D6B4-F248-11E8-B48F-1D18A9856A87","last_name":"Hauschild","first_name":"Robert"},{"full_name":"Datler, Julia","orcid":"0000-0002-3616-8580","last_name":"Datler","id":"3B12E2E6-F248-11E8-B48F-1D18A9856A87","first_name":"Julia"},{"orcid":"0000-0003-3904-947X","full_name":"Hodirnau, Victor-Valentin","first_name":"Victor-Valentin","id":"3661B498-F248-11E8-B48F-1D18A9856A87","last_name":"Hodirnau"},{"id":"39C5A68A-F248-11E8-B48F-1D18A9856A87","last_name":"Zheden","first_name":"Vanessa","full_name":"Zheden, Vanessa","orcid":"0000-0002-9438-4783"},{"id":"2CC12E8C-F248-11E8-B48F-1D18A9856A87","last_name":"Alanko","first_name":"Jonna H","full_name":"Alanko, Jonna H","orcid":"0000-0002-7698-3061"},{"orcid":"0000-0002-6620-9179","full_name":"Sixt, Michael K","id":"41E9FBEA-F248-11E8-B48F-1D18A9856A87","last_name":"Sixt","first_name":"Michael K"},{"full_name":"Schur, Florian KM","orcid":"0000-0003-4790-8078","first_name":"Florian KM","id":"48AD8942-F248-11E8-B48F-1D18A9856A87","last_name":"Schur"}],"date_updated":"2026-10-01T11:24:27Z","title":"Lift-out cryo-FIBSEM and cryo-ET reveal the ultrastructural landscape of extracellular matrix","date_created":"2024-03-21T06:45:51Z","year":"2024","article_processing_charge":"Yes (via OA deal)","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"article_type":"original","supplementarymaterial":"yes","external_id":{"pmid":["38506714"],"isi":["001264190100001"]},"oa":1,"acknowledgement":"Open Access funding provided by IST Austria. We thank Armel Nicolas and his team at the ISTA proteomics facility, Alois Schloegl, Stefano Elefante, and colleagues at the ISTA Scientific Computing facility, Tommaso Constanzo and Ludek Lovicar at the Electron Microsocpy Facility (EMF), and Thomas Menner at the Miba Machine shop for their support. We also thank Wanda Kukulski (University of Bern) as well as Darío Porley, Andreas Thader, and other members of the Schur group for helpful discussions. Matt Swulius and Jessica Heebner provided great support in using Dragonfly. We thank Dorotea Fracciolla (Art & Science) for support in figure illustration.\r\n\r\nThis research was supported by the Scientific Service Units of ISTA through resources provided by Scientific Computing, the Lab Support Facility, and the Electron Microscopy Facility. We acknowledge funding support from the following sources: Austrian Science Fund (FWF) grant P33367 (to F.K.M. Schur), the Federation of European Biochemical Societies (to F.K.M. Schur), Niederösterreich (NÖ) Fonds (to B. Zens), FWF grant E435 (to J.M. Hansen), European Research Council under the European Union’s Horizon 2020 research (grant agreement No. 724373) (to M. Sixt), and Jenny and Antti Wihuri Foundation (to J. Alanko). This publication has been made possible in part by CZI grant DAF2021-234754 and grant DOI https://doi.org/10.37921/812628ebpcwg from the Chan Zuckerberg Initiative DAF, an advised fund of Silicon Valley Community Foundation (to F.K.M. Schur).","_id":"15146","oa_version":"Published Version","scopus_import":"1","isi":1,"ddc":["570"],"month":"03","type":"journal_article","publisher":"Rockefeller University Press","dataavailabilitystatement":"Representative tomograms containing the data shown in Fig. 3, and Figs. S5 and S9 have been deposited in the Electron Microscopy Data Bank under accession codes: EMD-18490, EMD-18491, EMD-18492, EMD-18493, and EMD-18494. All tilt series, including frames, raw tilt series, and reconstructed IsoNet-filtered tomograms, were deposited in the Electron Microscopy Public Image Archive database under the accession code EMPIAR-11897.","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication_status":"published","language":[{"iso":"eng"}],"publication":"Journal of Cell Biology","department":[{"_id":"FlSc"},{"_id":"MiSi"},{"_id":"Bio"},{"_id":"EM-Fac"}],"ec_funded":1,"fulldoi":"https://doi.org/10.1083/jcb.202309125","publication_identifier":{"issn":["0021-9525"],"eissn":["1540-8140"]},"file":[{"file_size":11907016,"checksum":"90d1984a93660735e506c2a304bc3f73","file_name":"2024_JCB_Zens.pdf","creator":"dernst","date_updated":"2024-03-25T12:52:04Z","access_level":"open_access","file_id":"15188","date_created":"2024-03-25T12:52:04Z","content_type":"application/pdf","success":1,"relation":"main_file"}],"doi":"10.1083/jcb.202309125","acknowledged_ssus":[{"_id":"LifeSc"},{"_id":"ScienComp"},{"_id":"EM-Fac"},{"_id":"M-Shop"}],"quality_controlled":"1","corr_author":"1","issue":"6","status":"public","file_date_updated":"2024-03-25T12:52:04Z","pmid":1,"date_published":"2024-03-20T00:00:00Z","das_tickbox":"1","has_accepted_license":"1"},{"article_type":"original","supplementarymaterial":"yes","tmp":{"name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)","image":"/images/cc_by_nc_nd.png","short":"CC BY-NC-ND (4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode"},"acknowledgement":"We thank D. D. Sahtoe, R. D. Kiber, Y. Hsia, N. Bethel and A. Favor for helpful discussions and K. VanWormer and L. Goldschmidt for technical support. We also thank X. Li and M. Lamb for mass spectrometry support. This work was supported by the Washington Research Foundation Postdoctoral Fellowship (grant no. GR027504, A. Pillai), a National Science Foundation Graduate Research Fellowship (grant no. DGE-2140004, A.I.), a Human Frontier Science Program Long Term Fellowship (grant no. LT000880/2019, F.P.), the Audacious Project at the Institute for Protein Design (A.B., A. Pillai, A. Philomin, A.I. and D.B.), a National Energy Research Scientific Computing Centre award (grant no. BER-ERCAP0022018), the Howard Hughes Medical Institute (D.B.), the Open Philanthropy Project Improving Protein Design Fund (P.J.Y.L., C.D. and D.B.) a gift from Microsoft (D.B.) and a grant from DARPA supporting the Harnessing Enzymatic Activity for Lifesaving Remedies programme (grant no. HR001120S0052, contract no. HR0011-21-2-0012, D.B.).","external_id":{"pmid":["39143214"],"isi":["001300534300019"]},"oa":1,"article_processing_charge":"Yes (in subscription journal)","year":"2024","date_created":"2024-08-25T22:01:08Z","abstract":[{"lang":"eng","text":"Allosteric modulation of protein function, wherein the binding of an effector to a protein triggers conformational changes at distant functional sites, plays a central part in the control of metabolism and cell signalling1,2,3. There has been considerable interest in designing allosteric systems, both to gain insight into the mechanisms underlying such ‘action at a distance’ modulation and to create synthetic proteins whose functions can be regulated by effectors4,5,6,7. However, emulating the subtle conformational changes distributed across many residues, characteristic of natural allosteric proteins, is a significant challenge8,9. Here, inspired by the classic Monod–Wyman–Changeux model of cooperativity10, we investigate the de novo design of allostery through rigid-body coupling of peptide-switchable hinge modules11 to protein interfaces12 that direct the formation of alternative oligomeric states. We find that this approach can be used to generate a wide variety of allosterically switchable systems, including cyclic rings that incorporate or eject subunits in response to peptide binding and dihedral cages that undergo effector-induced disassembly. Size-exclusion chromatography, mass photometry13 and electron microscopy reveal that these designed allosteric protein assemblies closely resemble the design models in both the presence and absence of peptide effectors and can have ligand-binding cooperativity comparable to classic natural systems such as haemoglobin14. Our results indicate that allostery can arise from global coupling of the energetics of protein substructures without optimized side-chain–side-chain allosteric communication pathways and provide a roadmap for generating allosterically triggerable delivery systems, protein nanomachines and cellular feedback control circuitry."}],"author":[{"full_name":"Pillai, Arvind","last_name":"Pillai","first_name":"Arvind"},{"first_name":"Abbas","last_name":"Idris","full_name":"Idris, Abbas"},{"first_name":"Annika","last_name":"Philomin","full_name":"Philomin, Annika"},{"first_name":"Connor","last_name":"Weidle","full_name":"Weidle, Connor"},{"last_name":"Skotheim","first_name":"Rebecca","full_name":"Skotheim, Rebecca"},{"last_name":"Leung","first_name":"Philip J.Y.","full_name":"Leung, Philip J.Y."},{"last_name":"Broerman","first_name":"Adam","full_name":"Broerman, Adam"},{"full_name":"Demakis, Cullen","first_name":"Cullen","last_name":"Demakis"},{"last_name":"Borst","first_name":"Andrew J.","full_name":"Borst, Andrew J."},{"id":"dfec9381-4341-11ee-8fd8-faa02bba7d62","last_name":"Praetorius","first_name":"Florian M","full_name":"Praetorius, Florian M","orcid":"0000-0002-0806-8101"},{"last_name":"Baker","first_name":"David","full_name":"Baker, David"}],"title":"De novo design of allosterically switchable protein assemblies","date_updated":"2026-10-01T11:19:54Z","day":"22","volume":632,"citation":{"chicago":"Pillai, Arvind, Abbas Idris, Annika Philomin, Connor Weidle, Rebecca Skotheim, Philip J.Y. Leung, Adam Broerman, et al. “De Novo Design of Allosterically Switchable Protein Assemblies.” <i>Nature</i>. Springer Nature, 2024. <a href=\"https://doi.org/10.1038/s41586-024-07813-2\">https://doi.org/10.1038/s41586-024-07813-2</a>.","short":"A. Pillai, A. Idris, A. Philomin, C. Weidle, R. Skotheim, P.J.Y. Leung, A. Broerman, C. Demakis, A.J. Borst, F.M. Praetorius, D. Baker, Nature 632 (2024) 911–920.","mla":"Pillai, Arvind, et al. “De Novo Design of Allosterically Switchable Protein Assemblies.” <i>Nature</i>, vol. 632, Springer Nature, 2024, pp. 911–920, doi:<a href=\"https://doi.org/10.1038/s41586-024-07813-2\">10.1038/s41586-024-07813-2</a>.","apa":"Pillai, A., Idris, A., Philomin, A., Weidle, C., Skotheim, R., Leung, P. J. Y., … Baker, D. (2024). De novo design of allosterically switchable protein assemblies. <i>Nature</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41586-024-07813-2\">https://doi.org/10.1038/s41586-024-07813-2</a>","ieee":"A. Pillai <i>et al.</i>, “De novo design of allosterically switchable protein assemblies,” <i>Nature</i>, vol. 632. Springer Nature, pp. 911–920, 2024.","ista":"Pillai A, Idris A, Philomin A, Weidle C, Skotheim R, Leung PJY, Broerman A, Demakis C, Borst AJ, Praetorius FM, Baker D. 2024. De novo design of allosterically switchable protein assemblies. Nature. 632, 911–920.","ama":"Pillai A, Idris A, Philomin A, et al. De novo design of allosterically switchable protein assemblies. <i>Nature</i>. 2024;632:911–920. doi:<a href=\"https://doi.org/10.1038/s41586-024-07813-2\">10.1038/s41586-024-07813-2</a>"},"intvolume":"       632","researchdata_availability":"yes (supplementary data)","pmid":1,"file_date_updated":"2024-09-09T12:01:14Z","status":"public","date_published":"2024-08-22T00:00:00Z","has_accepted_license":"1","das_tickbox":"1","fulldoi":"https://doi.org/10.1038/s41586-024-07813-2","department":[{"_id":"FlPr"}],"quality_controlled":"1","license":"https://creativecommons.org/licenses/by-nc-nd/4.0/","corr_author":"1","doi":"10.1038/s41586-024-07813-2","publication_identifier":{"eissn":["1476-4687"],"issn":["0028-0836"]},"file":[{"content_type":"application/pdf","date_created":"2024-09-09T12:01:14Z","relation":"main_file","success":1,"file_name":"2024_Nature_Pillai.pdf","checksum":"39127601621a360ec0edc538627eb211","file_size":16572040,"file_id":"18005","creator":"dernst","date_updated":"2024-09-09T12:01:14Z","access_level":"open_access"}],"dataavailabilitystatement":"All data are available either in the main text or as Supplementary Information. PDB models and sequences for designs shown in main text figures are available in the attached Supplementary Information, along with source data for plots in main text figures. Structures determined by cryo-EM were deposited in the PDB as 8UP1, 8URE and 8UTM, and maps were deposited in the EMDB under accession numbers EMD-42442, EMD-42491 and EMD-42542.","type":"journal_article","publisher":"Springer Nature","publication_status":"published","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","language":[{"iso":"eng"}],"publication":"Nature","page":"911–920 ","ddc":["570"],"month":"08","_id":"17463","oa_version":"Published Version","scopus_import":"1","isi":1},{"article_number":"mr1","researchdata_availability":"yes","volume":35,"intvolume":"        35","citation":{"ama":"Sárkány Z, Figueiredo F, Macedo-Ribeiro S, Martins PM. NAGPKin: Nucleation-and-growth parameters from the kinetics of protein phase separation. <i>Molecular Biology of the Cell</i>. 2024;35(3). doi:<a href=\"https://doi.org/10.1091/mbc.e23-07-0289\">10.1091/mbc.e23-07-0289</a>","chicago":"Sárkány, Zsuzsa, Francisco Figueiredo, Sandra Macedo-Ribeiro, and Pedro M. Martins. “NAGPKin: Nucleation-and-Growth Parameters from the Kinetics of Protein Phase Separation.” <i>Molecular Biology of the Cell</i>. American Society for Cell Biology, 2024. <a href=\"https://doi.org/10.1091/mbc.e23-07-0289\">https://doi.org/10.1091/mbc.e23-07-0289</a>.","mla":"Sárkány, Zsuzsa, et al. “NAGPKin: Nucleation-and-Growth Parameters from the Kinetics of Protein Phase Separation.” <i>Molecular Biology of the Cell</i>, vol. 35, no. 3, mr1, American Society for Cell Biology, 2024, doi:<a href=\"https://doi.org/10.1091/mbc.e23-07-0289\">10.1091/mbc.e23-07-0289</a>.","short":"Z. Sárkány, F. Figueiredo, S. Macedo-Ribeiro, P.M. Martins, Molecular Biology of the Cell 35 (2024).","ieee":"Z. Sárkány, F. Figueiredo, S. Macedo-Ribeiro, and P. M. Martins, “NAGPKin: Nucleation-and-growth parameters from the kinetics of protein phase separation,” <i>Molecular Biology of the Cell</i>, vol. 35, no. 3. American Society for Cell Biology, 2024.","apa":"Sárkány, Z., Figueiredo, F., Macedo-Ribeiro, S., &#38; Martins, P. M. (2024). NAGPKin: Nucleation-and-growth parameters from the kinetics of protein phase separation. <i>Molecular Biology of the Cell</i>. American Society for Cell Biology. <a href=\"https://doi.org/10.1091/mbc.e23-07-0289\">https://doi.org/10.1091/mbc.e23-07-0289</a>","ista":"Sárkány Z, Figueiredo F, Macedo-Ribeiro S, Martins PM. 2024. NAGPKin: Nucleation-and-growth parameters from the kinetics of protein phase separation. Molecular Biology of the Cell. 35(3), mr1."},"day":"01","date_updated":"2026-10-01T11:22:53Z","title":"NAGPKin: Nucleation-and-growth parameters from the kinetics of protein phase separation","abstract":[{"text":"The assembly of biomolecular condensate in eukaryotic cells and the accumulation of amyloid deposits in neurons are processes involving the nucleation and growth (NAG) of new protein phases. To therapeutically target protein phase separation, drug candidates are tested in in vitro assays that monitor the increase in the mass or size of the new phase. Limited mechanistic insight is, however, provided if empirical or untestable kinetic models are fitted to these progress curves. Here we present the web server NAGPKin that quantifies NAG rates using mass-based or size-based progress curves as the input data. A report is generated containing the fitted NAG parameters and elucidating the phase separation mechanisms at play. The NAG parameters can be used to predict particle size distributions of, for example, protein droplets formed by liquid-liquid phase separation (LLPS) or amyloid fibrils formed by protein aggregation. Because minimal intervention is required from the user, NAGPKin is a good platform for standardized reporting of LLPS and protein self-assembly data. NAGPKin is useful for drug discovery as well as for fundamental studies on protein phase separation. NAGPKin is freely available (no login required) at https://nagpkin.i3s.up.pt .","lang":"eng"}],"author":[{"full_name":"Sárkány, Zsuzsa","first_name":"Zsuzsa","last_name":"Sárkány"},{"full_name":"Figueiredo, Francisco","first_name":"Francisco","id":"8125cbe2-9661-11ed-a754-afe96018f37d","last_name":"Figueiredo"},{"last_name":"Macedo-Ribeiro","first_name":"Sandra","full_name":"Macedo-Ribeiro, Sandra"},{"first_name":"Pedro M.","last_name":"Martins","full_name":"Martins, Pedro M."}],"date_created":"2025-01-29T07:58:40Z","year":"2024","article_processing_charge":"Yes (in subscription journal)","external_id":{"pmid":["38117593"]},"oa":1,"acknowledgement":"We thank Professor José Paulo Leal, Department of Computer Science − Faculdade de Ciências da Universidade do Porto, for his invaluable help during the Implementation of NAGPKin. This work is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 952334 (PhasAGE). This research was funded by the Portuguese Foundation for Science and Technology (FCT) in the framework of project PTDC/QUI-COL/2444/2021.","tmp":{"image":"/images/cc_by_nc_sa.png","name":"Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)","legal_code_url":"https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode","short":"CC BY-NC-SA (4.0)"},"article_type":"original","supplementarymaterial":"no","_id":"18934","oa_version":"Published Version","scopus_import":"1","month":"03","ddc":["570"],"publication_status":"published","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication":"Molecular Biology of the Cell","language":[{"iso":"eng"}],"type":"journal_article","publisher":"American Society for Cell Biology","publication_identifier":{"eissn":["1939-4586"],"issn":["1059-1524"]},"doi":"10.1091/mbc.e23-07-0289","file":[{"content_type":"application/pdf","date_created":"2025-01-29T08:12:11Z","relation":"main_file","success":1,"file_name":"2024_MolecularBioCell_Sarkany.pdf","file_size":1699180,"checksum":"d7deb6390f294da69321cfbe352ed611","file_id":"18935","date_updated":"2025-01-29T08:12:11Z","creator":"dernst","access_level":"open_access"}],"quality_controlled":"1","license":"https://creativecommons.org/licenses/by-nc-sa/4.0/","OA_place":"publisher","department":[{"_id":"FlSc"}],"fulldoi":"https://doi.org/10.1091/mbc.e23-07-0289","OA_type":"hybrid","date_published":"2024-03-01T00:00:00Z","has_accepted_license":"1","das_tickbox":"0","file_date_updated":"2025-01-29T08:12:11Z","issue":"3","status":"public","pmid":1},{"quality_controlled":"1","file":[{"success":1,"relation":"main_file","date_created":"2025-01-08T08:51:45Z","content_type":"application/pdf","access_level":"open_access","date_updated":"2025-01-08T08:51:45Z","creator":"dernst","file_id":"18774","checksum":"a4f0f906e4d5c1078208b317e78699d1","file_size":7445664,"file_name":"2024_eLife_Last.pdf"}],"doi":"10.7554/eLife.98552","publication_identifier":{"eissn":["2050-084X"]},"OA_type":"gold","fulldoi":"https://doi.org/10.7554/eLife.98552","OA_place":"publisher","department":[{"_id":"FlPr"}],"has_accepted_license":"1","das_tickbox":"1","date_published":"2024-12-20T00:00:00Z","pmid":1,"file_date_updated":"2025-01-08T08:51:45Z","status":"public","month":"12","ddc":["570"],"oa_version":"Published Version","_id":"18757","scopus_import":"1","DOAJ_listed":"1","language":[{"iso":"eng"}],"publication":"eLife","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication_status":"published","dataavailabilitystatement":"Source code is available via GitHub, (copy archived at Last, 2024), software available on the python package index as 'Ais-cryoET'. Trained neural networks have been uploaded to aiscryoet.org.","publisher":"eLife Sciences Publications","type":"journal_article","article_processing_charge":"Yes","year":"2024","date_created":"2025-01-05T23:01:57Z","acknowledgement":"We thank A Koster and M Barcena for helpful discussions and kindly sharing the coronaviral replication organelle datasets. We are also grateful to van den Hoek et al., 2022 and Wu et al., 2023, for uploading the data that we used for Figure 5 onto EMPIAR and EMDB, as well as to the authors of various other datasets uploaded to these databases that are not discussed in this manuscript but that were useful for testing the software. We also thank the reviewers, whose comments were very helpful in improving the manuscript and the software. Finally, we are grateful the early Ais users who provided us with feedback on the software and reported issues. This research was supported by the following grants to THS: European Research Council H202 Grant 759517; European Union’s Horizon Europe Program IMAGINE grant 101094250, and the Netherlands Organization for Scientific Research Grant VI.Vidi.193.014.","oa":1,"external_id":{"pmid":["39704648"]},"supplementarymaterial":"yes","article_type":"original","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"researchdata_availability":"yes","article_number":"98552","day":"20","citation":{"ama":"Last MGF, Abendstein L, Voortman LM, Sharp TH. Streamlining segmentation of cryo-electron tomography datasets with Ais. <i>eLife</i>. 2024;13. doi:<a href=\"https://doi.org/10.7554/eLife.98552\">10.7554/eLife.98552</a>","mla":"Last, Mart G. F., et al. “Streamlining Segmentation of Cryo-Electron Tomography Datasets with Ais.” <i>ELife</i>, vol. 13, 98552, eLife Sciences Publications, 2024, doi:<a href=\"https://doi.org/10.7554/eLife.98552\">10.7554/eLife.98552</a>.","short":"M.G.F. Last, L. Abendstein, L.M. Voortman, T.H. Sharp, ELife 13 (2024).","chicago":"Last, Mart G.F., Leoni Abendstein, Lenard M. Voortman, and Thomas H. Sharp. “Streamlining Segmentation of Cryo-Electron Tomography Datasets with Ais.” <i>ELife</i>. eLife Sciences Publications, 2024. <a href=\"https://doi.org/10.7554/eLife.98552\">https://doi.org/10.7554/eLife.98552</a>.","ista":"Last MGF, Abendstein L, Voortman LM, Sharp TH. 2024. Streamlining segmentation of cryo-electron tomography datasets with Ais. eLife. 13, 98552.","ieee":"M. G. F. Last, L. Abendstein, L. M. Voortman, and T. H. Sharp, “Streamlining segmentation of cryo-electron tomography datasets with Ais,” <i>eLife</i>, vol. 13. eLife Sciences Publications, 2024.","apa":"Last, M. G. F., Abendstein, L., Voortman, L. M., &#38; Sharp, T. H. (2024). Streamlining segmentation of cryo-electron tomography datasets with Ais. <i>ELife</i>. eLife Sciences Publications. <a href=\"https://doi.org/10.7554/eLife.98552\">https://doi.org/10.7554/eLife.98552</a>"},"intvolume":"        13","volume":13,"title":"Streamlining segmentation of cryo-electron tomography datasets with Ais","date_updated":"2026-10-01T11:22:32Z","author":[{"full_name":"Last, Mart G.F.","last_name":"Last","first_name":"Mart G.F."},{"orcid":"0000-0001-7634-5353","full_name":"Abendstein, Leoni","id":"14f1f051-cd9d-11ef-9c94-8b942a882560","last_name":"Abendstein","first_name":"Leoni"},{"full_name":"Voortman, Lenard M.","first_name":"Lenard M.","last_name":"Voortman"},{"full_name":"Sharp, Thomas H.","first_name":"Thomas H.","last_name":"Sharp"}],"abstract":[{"lang":"eng","text":"Segmentation is a critical data processing step in many applications of cryo-electron tomography. Downstream analyses, such as subtomogram averaging, are often based on segmentation results, and are thus critically dependent on the availability of open-source software for accurate as well as high-throughput tomogram segmentation. There is a need for more user-friendly, flexible, and comprehensive segmentation software that offers an insightful overview of all steps involved in preparing automated segmentations. Here, we present Ais: a dedicated tomogram segmentation package that is geared towards both high performance and accessibility, available on GitHub. In this report, we demonstrate two common processing steps that can be greatly accelerated with Ais: particle picking for subtomogram averaging, and generating many-feature segmentations of cellular architecture based on in situ tomography data. Featuring comprehensive annotation, segmentation, and rendering functionality, as well as an open repository for trained models at aiscryoet.org, we hope that Ais will help accelerate research and dissemination of data involving cryoET."}]},{"date_created":"2024-10-20T22:02:05Z","year":"2024","article_processing_charge":"Yes (via OA deal)","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"article_type":"original","supplementarymaterial":"yes","external_id":{"pmid":["39366958"],"isi":["001409493300014"]},"oa":1,"acknowledgement":"The authors thank Z. Máté, G. Szabó, and F. Erdélyi for the custom generation of transgenic mouse lines, C. Fekete for Trh transgenic tissues (all from the Institute of Experimental Medicine, Hungarian Academy of Sciences, Budapest, Hungary), A. Goudmaeker for IVF recovery of a frozen mouse line (SSS animal facility, Université catholique de Louvain), and Y. Yanagawa (Department of Genetic and Behavioral Neuroscience, Gunma University Graduate School of Medicine, Maebashi, Japan) for providing GAD67gfp/+ mice. We also thank S. Cloer, D. Preininger, and A. Weissenbacher (Tiergarten Schönbrunn, Vienna, Austria) for providing naked mole rats, Seba’s fruit bats, and Indian flying foxes, as well as F. Aujard (CNRS, UMR 7179 ‘Adaptive mechanisms and evolution’, France) for Microcebus tissues. I. Milenkovic and G.G. Kovács (Clinical Institute of Neurology, Medical University of Vienna, Vienna, Austria) are acknowledged for providing post-mortem human brain samples. We are indebted to S. Rehman (Medical University of Vienna), M. Kalusa (University of Leipzig, Leipzig, Germany), and W. Reimann (Paul Flechsig Institute for Brain Research, Leipzig, Germany) for their technical assistance. C. elegans strains were provided by the National Bioresource Project for the nematode, Japan, and the CGC, with the latter being funded by the NIH Office of Research Infrastructure Programs (P40 OD010440). This work was supported by the Austrian Science Fund (FWF, P 34121-B; to E.K.), the Swedish Research Council (2023-03058, T.Ha; 2020-01688, T.Hö.), the Swedish Brain Foundation (Hjärnfonden, FO2022-0300, to T.Ha.), the Novo Nordisk Foundation (NNF23OC0084476, to T.Ha.), the European Research Council (FOODFORLIFE, ERC-2020-AdG-101021016; to T.Ha.), the Université Catholique de Louvain (‘Fonds spéciaux de recherche’-FSR, to F.C.), and Fonds de la Recherche Scientifique F.R.S.-FNRS (‘Project de recherche (PDR)’ #T.0039.21, to F.C.). S.J.E. is supported by the Simons Foundation #543069. I.L. is supported by a post-doctoral fellowship from the Human Frontiers Science Program (LT000335/2020-L). E.R. holds a PhD grant from the FRIA (F.R.S.-FNRS, Belgium). F.C. is a Research Director of the F.R.S.-FNRS (Belgium).\r\nOpen access funding provided by Karolinska Institute.","volume":15,"intvolume":"        15","citation":{"chicago":"Zupančič, Maja, Erik Keimpema, Evgenii O. Tretiakov, Stephanie J. Eder, Itamar Lev, Lukas Englmaier, Pradeep Bhandari, et al. “Concerted Transcriptional Regulation of the Morphogenesis of Hypothalamic Neurons by ONECUT3.” <i>Nature Communications</i>. Springer Nature, 2024. <a href=\"https://doi.org/10.1038/s41467-024-52762-z\">https://doi.org/10.1038/s41467-024-52762-z</a>.","mla":"Zupančič, Maja, et al. “Concerted Transcriptional Regulation of the Morphogenesis of Hypothalamic Neurons by ONECUT3.” <i>Nature Communications</i>, vol. 15, 8631, Springer Nature, 2024, doi:<a href=\"https://doi.org/10.1038/s41467-024-52762-z\">10.1038/s41467-024-52762-z</a>.","short":"M. Zupančič, E. Keimpema, E.O. Tretiakov, S.J. Eder, I. Lev, L. Englmaier, P. Bhandari, S.A. Fietz, W. Härtig, E. Renaux, A. Villunger, T. Hökfelt, M. Zimmer, F. Clotman, T. Harkany, Nature Communications 15 (2024).","apa":"Zupančič, M., Keimpema, E., Tretiakov, E. O., Eder, S. J., Lev, I., Englmaier, L., … Harkany, T. (2024). Concerted transcriptional regulation of the morphogenesis of hypothalamic neurons by ONECUT3. <i>Nature Communications</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41467-024-52762-z\">https://doi.org/10.1038/s41467-024-52762-z</a>","ieee":"M. Zupančič <i>et al.</i>, “Concerted transcriptional regulation of the morphogenesis of hypothalamic neurons by ONECUT3,” <i>Nature Communications</i>, vol. 15. Springer Nature, 2024.","ista":"Zupančič M, Keimpema E, Tretiakov EO, Eder SJ, Lev I, Englmaier L, Bhandari P, Fietz SA, Härtig W, Renaux E, Villunger A, Hökfelt T, Zimmer M, Clotman F, Harkany T. 2024. Concerted transcriptional regulation of the morphogenesis of hypothalamic neurons by ONECUT3. Nature Communications. 15, 8631.","ama":"Zupančič M, Keimpema E, Tretiakov EO, et al. Concerted transcriptional regulation of the morphogenesis of hypothalamic neurons by ONECUT3. <i>Nature Communications</i>. 2024;15. doi:<a href=\"https://doi.org/10.1038/s41467-024-52762-z\">10.1038/s41467-024-52762-z</a>"},"day":"05","article_number":"8631","researchdata_availability":"yes","author":[{"last_name":"Zupančič","first_name":"Maja","full_name":"Zupančič, Maja"},{"first_name":"Erik","last_name":"Keimpema","full_name":"Keimpema, Erik"},{"full_name":"Tretiakov, Evgenii O.","last_name":"Tretiakov","first_name":"Evgenii O."},{"full_name":"Eder, Stephanie J.","first_name":"Stephanie J.","last_name":"Eder"},{"full_name":"Lev, Itamar","first_name":"Itamar","last_name":"Lev"},{"full_name":"Englmaier, Lukas","last_name":"Englmaier","first_name":"Lukas"},{"first_name":"Pradeep","last_name":"Bhandari","id":"45EDD1BC-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0003-0863-4481","full_name":"Bhandari, Pradeep"},{"first_name":"Simone A.","last_name":"Fietz","full_name":"Fietz, Simone A."},{"first_name":"Wolfgang","last_name":"Härtig","full_name":"Härtig, Wolfgang"},{"first_name":"Estelle","last_name":"Renaux","full_name":"Renaux, Estelle"},{"last_name":"Villunger","first_name":"Andreas","full_name":"Villunger, Andreas"},{"last_name":"Hökfelt","first_name":"Tomas","full_name":"Hökfelt, Tomas"},{"full_name":"Zimmer, Manuel","first_name":"Manuel","last_name":"Zimmer"},{"first_name":"Frédéric","last_name":"Clotman","full_name":"Clotman, Frédéric"},{"full_name":"Harkany, Tibor","last_name":"Harkany","first_name":"Tibor"}],"abstract":[{"text":"Acquisition of specialized cellular features is controlled by the ordered expression of transcription factors (TFs) along differentiation trajectories. Here, we find a member of the Onecut TF family, ONECUT3, expressed in postmitotic neurons that leave their Ascl1+/Onecut1/2+ proliferative domain in the vertebrate hypothalamus to instruct neuronal differentiation. We combined single-cell RNA-seq and gain-of-function experiments for gene network reconstruction to show that ONECUT3 affects the polarization and morphogenesis of both hypothalamic GABA-derived dopamine and thyrotropin-releasing hormone (TRH)+ glutamate neurons through neuron navigator-2 (NAV2). In vivo, siRNA-mediated knockdown of ONECUT3 in neonatal mice reduced NAV2 mRNA, as well as neurite complexity in Onecut3-containing neurons, while genetic deletion of Onecut3/ceh-48 in C. elegans impaired neurocircuit wiring, and sensory discrimination-based behaviors. Thus, ONECUT3, conserved across neuronal subtypes and many species, underpins the polarization and morphological plasticity of phenotypically distinct neurons that descend from a common pool of Ascl1+ progenitors in the hypothalamus.","lang":"eng"}],"date_updated":"2026-10-01T12:17:25Z","title":"Concerted transcriptional regulation of the morphogenesis of hypothalamic neurons by ONECUT3","department":[{"_id":"RySh"}],"OA_place":"publisher","fulldoi":"https://doi.org/10.1038/s41467-024-52762-z","OA_type":"gold","file":[{"date_created":"2024-10-21T12:15:38Z","content_type":"application/pdf","success":1,"relation":"main_file","checksum":"03d6dd1b84efa24e9e9ede748d08764d","file_size":7215329,"file_name":"2024_NatureComm_Zupancic.pdf","date_updated":"2024-10-21T12:15:38Z","creator":"dernst","access_level":"open_access","file_id":"18460"}],"doi":"10.1038/s41467-024-52762-z","publication_identifier":{"eissn":["2041-1723"]},"quality_controlled":"1","status":"public","file_date_updated":"2024-10-21T12:15:38Z","pmid":1,"date_published":"2024-10-05T00:00:00Z","das_tickbox":"1","has_accepted_license":"1","DOAJ_listed":"1","_id":"18445","oa_version":"Published Version","scopus_import":"1","isi":1,"PlanS_conform":"1","ddc":["570"],"month":"10","type":"journal_article","publisher":"Springer Nature","dataavailabilitystatement":"The snRNA-seq data generated in this study have been deposited in the NCBI Gene Expression Omnibus database under accession code GSE132730 and as ‘Supplementary Data 1 - Neuro2a-onecut3-overexpression’. All other primary data were made publically available at https://github.com/Harkany-Lab/Zupancic_2023 and deposited to Figshare.com with https://doi.org/10.6084/m9.figshare.22680433. Source data are provided with this paper.","related_material":{"record":[{"id":"22961","relation":"research_data","status":"public"}]},"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication_status":"published","publication":"Nature Communications","language":[{"iso":"eng"}]},{"day":"03","citation":{"mla":"Lao, Dong, et al. “Divided Attention: Unsupervised Multi-Object Discovery with Contextually Separated Slots.” <i>1st Conference on Parsimony and Learning</i>, 2024.","short":"D. Lao, Z. Hu, F. Locatello, Y. Yang, S. Soatto, in:, 1st Conference on Parsimony and Learning, 2024.","chicago":"Lao, Dong, Zhengyang Hu, Francesco Locatello, Yanchao Yang, and Stefano Soatto. “Divided Attention: Unsupervised Multi-Object Discovery with Contextually Separated Slots.” In <i>1st Conference on Parsimony and Learning</i>, 2024.","ista":"Lao D, Hu Z, Locatello F, Yang Y, Soatto S. 2024. Divided attention: Unsupervised multi-object discovery with contextually separated slots. 1st Conference on Parsimony and Learning. CPAL: Conference on Parsimony and Learning.","ieee":"D. Lao, Z. Hu, F. Locatello, Y. Yang, and S. Soatto, “Divided attention: Unsupervised multi-object discovery with contextually separated slots,” in <i>1st Conference on Parsimony and Learning</i>, Hong Kong, China, 2024.","apa":"Lao, D., Hu, Z., Locatello, F., Yang, Y., &#38; Soatto, S. (2024). Divided attention: Unsupervised multi-object discovery with contextually separated slots. In <i>1st Conference on Parsimony and Learning</i>. Hong Kong, China.","ama":"Lao D, Hu Z, Locatello F, Yang Y, Soatto S. Divided attention: Unsupervised multi-object discovery with contextually separated slots. In: <i>1st Conference on Parsimony and Learning</i>. ; 2024."},"researchdata_availability":"no","arxiv":1,"author":[{"full_name":"Lao, Dong","last_name":"Lao","first_name":"Dong"},{"full_name":"Hu, Zhengyang","first_name":"Zhengyang","last_name":"Hu"},{"full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","first_name":"Francesco"},{"last_name":"Yang","first_name":"Yanchao","full_name":"Yang, Yanchao"},{"first_name":"Stefano","last_name":"Soatto","full_name":"Soatto, Stefano"}],"abstract":[{"lang":"eng","text":"We introduce a method to segment the visual field into independently moving regions, trained with no ground truth or supervision. It consists of an adversarial conditional encoder-decoder architecture based on Slot Attention, modified to use the image as context to decode optical flow without attempting to reconstruct the image itself. In the resulting multi-modal representation, one modality (flow) feeds the encoder to produce separate latent codes (slots), whereas the other modality (image) conditions the decoder to generate the first (flow) from the slots. This design frees the representation from having to encode complex nuisance variability in the image due to, for instance, illumination and reflectance properties of the scene. Since customary autoencoding based on minimizing the reconstruction error does not preclude the entire flow from being encoded into a single slot, we modify the loss to an adversarial criterion based on Contextual Information Separation. The resulting min-max optimization fosters the separation of objects and their assignment to different attention slots, leading to Divided Attention, or DivA. DivA outperforms recent unsupervised multi-object motion segmentation methods while tripling run-time speed up to 104FPS and reducing the performance gap from supervised methods to 12% or less. DivA can handle different numbers of objects and different image sizes at training and test time, is invariant to permutation of object labels, and does not require explicit regularization."}],"title":"Divided attention: Unsupervised multi-object discovery with contextually separated slots","date_updated":"2026-10-01T11:25:45Z","article_processing_charge":"No","year":"2024","date_created":"2023-08-22T14:19:59Z","supplementarymaterial":"no","oa":1,"external_id":{"arxiv":["2304.01430"]},"month":"01","ddc":["000"],"oa_version":"Published Version","_id":"14213","conference":{"location":"Hong Kong, China","name":"CPAL: Conference on Parsimony and Learning","start_date":"2024-01-03","end_date":"2024-01-03"},"type":"conference","publication":"1st Conference on Parsimony and Learning","language":[{"iso":"eng"}],"publication_status":"published","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","department":[{"_id":"FrLo"}],"quality_controlled":"1","file":[{"file_name":"2024_CPAL_Lao.pdf","file_size":8038511,"checksum":"8fad894c34f1b3d5a14fb8ffb12f7277","file_id":"14978","creator":"dernst","date_updated":"2024-02-12T08:40:36Z","access_level":"open_access","content_type":"application/pdf","date_created":"2024-02-12T08:40:36Z","relation":"main_file","success":1}],"status":"public","file_date_updated":"2024-02-12T08:40:36Z","has_accepted_license":"1","das_tickbox":"0","date_published":"2024-01-03T00:00:00Z"},{"OA_type":"diamond","OA_place":"publisher","department":[{"_id":"FrLo"}],"quality_controlled":"1","publication_identifier":{"eissn":["2640-3498"]},"status":"public","date_published":"2024-09-01T00:00:00Z","das_tickbox":"0","page":"40484-40501","month":"09","ddc":["000"],"_id":"18114","scopus_import":"1","oa_version":"Published Version","conference":{"name":"ICML: International Conference on Machine Learning","location":"Vienna, Austria","end_date":"2024-07-27","start_date":"2024-07-21"},"type":"conference","publisher":"ML Research Press","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication_status":"published","publication":"Proceedings of the 41st International Conference on Machine Learning","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2402.13077","open_access":"1"}],"related_material":{"link":[{"relation":"software","url":"https://github.com/alpz/mech-nn"}]},"article_processing_charge":"No","date_created":"2024-09-22T22:01:43Z","year":"2024","supplementarymaterial":"no","external_id":{"arxiv":["2402.13077"]},"oa":1,"alternative_title":["PMLR"],"day":"01","volume":235,"intvolume":"       235","citation":{"short":"A.A. Pervez, F. Locatello, E. Gavves, in:, Proceedings of the 41st International Conference on Machine Learning, ML Research Press, 2024, pp. 40484–40501.","mla":"Pervez, Adeel A., et al. “Mechanistic Neural Networks for Scientific Machine Learning.” <i>Proceedings of the 41st International Conference on Machine Learning</i>, vol. 235, ML Research Press, 2024, pp. 40484–501.","chicago":"Pervez, Adeel A, Francesco Locatello, and Efstratios Gavves. “Mechanistic Neural Networks for Scientific Machine Learning.” In <i>Proceedings of the 41st International Conference on Machine Learning</i>, 235:40484–501. ML Research Press, 2024.","ista":"Pervez AA, Locatello F, Gavves E. 2024. Mechanistic neural networks for scientific machine learning. Proceedings of the 41st International Conference on Machine Learning. ICML: International Conference on Machine Learning, PMLR, vol. 235, 40484–40501.","ieee":"A. A. Pervez, F. Locatello, and E. Gavves, “Mechanistic neural networks for scientific machine learning,” in <i>Proceedings of the 41st International Conference on Machine Learning</i>, Vienna, Austria, 2024, vol. 235, pp. 40484–40501.","apa":"Pervez, A. A., Locatello, F., &#38; Gavves, E. (2024). Mechanistic neural networks for scientific machine learning. In <i>Proceedings of the 41st International Conference on Machine Learning</i> (Vol. 235, pp. 40484–40501). Vienna, Austria: ML Research Press.","ama":"Pervez AA, Locatello F, Gavves E. Mechanistic neural networks for scientific machine learning. In: <i>Proceedings of the 41st International Conference on Machine Learning</i>. Vol 235. ML Research Press; 2024:40484-40501."},"arxiv":1,"researchdata_availability":"no","abstract":[{"lang":"eng","text":"This paper presents Mechanistic Neural Networks, a neural network design for machine learning applications in the sciences. It incorporates a new Mechanistic Block in standard architectures to explicitly learn governing differential equations as representations, revealing the underlying dynamics of data and enhancing interpretability and efficiency in data modeling. Central to our approach is a novel Relaxed Linear Programming Solver (NeuRLP) inspired by a technique that reduces solving linear ODEs to solving linear programs. This integrates well with neural networks and surpasses the limitations of traditional ODE solvers enabling scalable GPU parallel processing. Overall, Mechanistic Neural Networks demonstrate their versatility for scientific machine learning applications, adeptly managing tasks from equation discovery to dynamic systems modeling. We prove their comprehensive capabilities in analyzing and interpreting complex scientific data across various applications, showing significant performance against specialized state-of-the-art methods. Source code is available at https://github.com/alpz/mech-nn."}],"author":[{"full_name":"Pervez, Adeel A","first_name":"Adeel A","id":"fca6d90c-d47f-11ee-bc87-93ff51604981","last_name":"Pervez"},{"full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","first_name":"Francesco","last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4"},{"last_name":"Gavves","first_name":"Efstratios","full_name":"Gavves, Efstratios"}],"title":"Mechanistic neural networks for scientific machine learning","date_updated":"2026-10-01T11:26:09Z"},{"oa":1,"external_id":{"pmid":["38441122"]},"acknowledgement":"The research leading to these results has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme grant agreement No 742985 and Austrian Science Fund (FWF): I3630-775 B25 to J.F. This research was also supported by the Lab Support Facility (LSF) and the Imaging and Optics Facility (IOF) of IST Austria, namely Tereza Bělinová for her help with the imaging. JS was supported by FemTECH fellowship.","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"article_type":"original","year":"2024","date_created":"2024-04-02T11:35:58Z","article_processing_charge":"Yes","date_updated":"2026-10-02T07:48:48Z","title":"Rapid translocation of NGR proteins driving polarization of PIN-activating D6 protein kinase during root gravitropism","abstract":[{"lang":"eng","text":"Root gravitropic bending represents a fundamental aspect of terrestrial plant physiology. Gravity is perceived by sedimentation of starch-rich plastids (statoliths) to the bottom of the central root cap cells. Following gravity perception, intercellular auxin transport is redirected downwards leading to an asymmetric auxin accumulation at the lower root side causing inhibition of cell expansion, ultimately resulting in downwards bending. How gravity-induced statoliths repositioning is translated into asymmetric auxin distribution remains unclear despite PIN auxin efflux carriers and the Negative Gravitropic Response of roots (NGR) proteins polarize along statolith sedimentation, thus providing a plausible mechanism for auxin flow redirection. In this study, using a functional NGR1-GFP construct, we visualized the NGR1 localization on the statolith surface and plasma membrane (PM) domains in close proximity to the statoliths, correlating with their movements. We determined that NGR1 binding to these PM domains is indispensable for NGR1 functionality and relies on cysteine acylation and adjacent polybasic regions as well as on lipid and sterol PM composition. Detailed timing of the early events following graviperception suggested that both NGR1 repolarization and initial auxin asymmetry precede the visible PIN3 polarization. This discrepancy motivated us to unveil a rapid, NGR-dependent translocation of PIN-activating AGCVIII kinase D6PK towards lower PMs of gravity-perceiving cells, thus providing an attractive model for rapid redirection of auxin fluxes following gravistimulation."}],"author":[{"full_name":"Kulich, Ivan","id":"57a1567c-8314-11eb-9063-c9ddc3451a54","last_name":"Kulich","first_name":"Ivan"},{"first_name":"Julia","id":"07cf4637-baaf-11ee-9227-e1de57d1d69b","last_name":"Schmid","full_name":"Schmid, Julia"},{"full_name":"Teplova, Anastasiia","last_name":"Teplova","id":"e3736151-106c-11ec-b916-c2558e2762c6","first_name":"Anastasiia"},{"orcid":"0000-0001-5187-8401","full_name":"Qi, Linlin","last_name":"Qi","id":"44B04502-A9ED-11E9-B6FC-583AE6697425","first_name":"Linlin"},{"last_name":"Friml","id":"4159519E-F248-11E8-B48F-1D18A9856A87","first_name":"Jiří","orcid":"0000-0002-8302-7596","full_name":"Friml, Jiří"}],"article_number":"91523","intvolume":"        12","citation":{"ama":"Kulich I, Schmid J, Teplova A, Qi L, Friml J. Rapid translocation of NGR proteins driving polarization of PIN-activating D6 protein kinase during root gravitropism. <i>eLife</i>. 2024;12. doi:<a href=\"https://doi.org/10.7554/elife.91523\">10.7554/elife.91523</a>","chicago":"Kulich, Ivan, Julia Schmid, Anastasiia Teplova, Linlin Qi, and Jiří Friml. “Rapid Translocation of NGR Proteins Driving Polarization of PIN-Activating D6 Protein Kinase during Root Gravitropism.” <i>ELife</i>. eLife Sciences Publications, 2024. <a href=\"https://doi.org/10.7554/elife.91523\">https://doi.org/10.7554/elife.91523</a>.","short":"I. Kulich, J. Schmid, A. Teplova, L. Qi, J. Friml, ELife 12 (2024).","mla":"Kulich, Ivan, et al. “Rapid Translocation of NGR Proteins Driving Polarization of PIN-Activating D6 Protein Kinase during Root Gravitropism.” <i>ELife</i>, vol. 12, 91523, eLife Sciences Publications, 2024, doi:<a href=\"https://doi.org/10.7554/elife.91523\">10.7554/elife.91523</a>.","apa":"Kulich, I., Schmid, J., Teplova, A., Qi, L., &#38; Friml, J. (2024). Rapid translocation of NGR proteins driving polarization of PIN-activating D6 protein kinase during root gravitropism. <i>ELife</i>. eLife Sciences Publications. <a href=\"https://doi.org/10.7554/elife.91523\">https://doi.org/10.7554/elife.91523</a>","ieee":"I. Kulich, J. Schmid, A. Teplova, L. Qi, and J. Friml, “Rapid translocation of NGR proteins driving polarization of PIN-activating D6 protein kinase during root gravitropism,” <i>eLife</i>, vol. 12. eLife Sciences Publications, 2024.","ista":"Kulich I, Schmid J, Teplova A, Qi L, Friml J. 2024. Rapid translocation of NGR proteins driving polarization of PIN-activating D6 protein kinase during root gravitropism. eLife. 12, 91523."},"project":[{"call_identifier":"H2020","grant_number":"742985","name":"Tracing Evolution of Auxin Transport and Polarity in Plants","_id":"261099A6-B435-11E9-9278-68D0E5697425"},{"call_identifier":"FWF","name":"Molecular mechanisms of endocytic cargo recognition in plants","_id":"26538374-B435-11E9-9278-68D0E5697425","grant_number":"I03630"}],"volume":12,"day":"05","has_accepted_license":"1","date_published":"2024-03-05T00:00:00Z","keyword":["General Immunology and Microbiology","General Biochemistry","Genetics and Molecular Biology","General Medicine","General Neuroscience"],"file_date_updated":"2024-04-03T13:18:00Z","status":"public","pmid":1,"file":[{"content_type":"application/pdf","date_created":"2024-04-03T13:18:00Z","relation":"main_file","success":1,"file_name":"2024_eLife_Kulich.pdf","file_size":11451904,"checksum":"a73a84d3bf97a6d09d24308ca6dd0a0c","file_id":"15288","access_level":"open_access","creator":"dernst","date_updated":"2024-04-03T13:18:00Z"}],"doi":"10.7554/elife.91523","publication_identifier":{"issn":["2050-084X"]},"corr_author":"1","acknowledged_ssus":[{"_id":"LifeSc"},{"_id":"Bio"}],"quality_controlled":"1","department":[{"_id":"JiFr"}],"ec_funded":1,"fulldoi":"https://doi.org/10.7554/elife.91523","related_material":{"record":[{"relation":"dissertation_contains","id":"22984","status":"public"}],"link":[{"description":"News on ISTA website","url":"https://ista.ac.at/en/news/beneath-the-surface/","relation":"press_release"}]},"publication":"eLife","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_status":"published","publisher":"eLife Sciences Publications","type":"journal_article","_id":"15257","scopus_import":"1","oa_version":"Published Version","month":"03","ddc":["580"],"DOAJ_listed":"1"},{"month":"06","oa_version":"Preprint","_id":"18964","isi":1,"publication_status":"published","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication":"2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2406.09196","open_access":"1"}],"related_material":{"link":[{"relation":"software","url":"https://kfan21.github.io/AdaSlot/"}]},"conference":{"end_date":"2024-06-22","start_date":"2024-06-16","name":"CVPR: Conference on Computer Vision and Pattern Recognition","location":"Seattle, WA, United States"},"type":"conference","publisher":"IEEE","quality_controlled":"1","doi":"10.1109/cvpr52733.2024.02176","publication_identifier":{"eisbn":["9798350353006"]},"OA_type":"green","fulldoi":"https://doi.org/10.1109/cvpr52733.2024.02176","OA_place":"repository","department":[{"_id":"FrLo"}],"date_published":"2024-06-15T00:00:00Z","das_tickbox":"0","status":"public","arxiv":1,"researchdata_availability":"yes","day":"15","citation":{"ama":"Fan K, Bai Z, Xiao T, et al. Adaptive slot attention: Object discovery with dynamic slot number. In: <i>2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition</i>. IEEE; 2024. doi:<a href=\"https://doi.org/10.1109/cvpr52733.2024.02176\">10.1109/cvpr52733.2024.02176</a>","chicago":"Fan, Ke, Zechen Bai, Tianjun Xiao, Tong He, Max Horn, Yanwei Fu, Francesco Locatello, and Zheng Zhang. “Adaptive Slot Attention: Object Discovery with Dynamic Slot Number.” In <i>2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition</i>. IEEE, 2024. <a href=\"https://doi.org/10.1109/cvpr52733.2024.02176\">https://doi.org/10.1109/cvpr52733.2024.02176</a>.","short":"K. Fan, Z. Bai, T. Xiao, T. He, M. Horn, Y. Fu, F. Locatello, Z. Zhang, in:, 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition, IEEE, 2024.","mla":"Fan, Ke, et al. “Adaptive Slot Attention: Object Discovery with Dynamic Slot Number.” <i>2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition</i>, IEEE, 2024, doi:<a href=\"https://doi.org/10.1109/cvpr52733.2024.02176\">10.1109/cvpr52733.2024.02176</a>.","ieee":"K. Fan <i>et al.</i>, “Adaptive slot attention: Object discovery with dynamic slot number,” in <i>2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition</i>, Seattle, WA, United States, 2024.","apa":"Fan, K., Bai, Z., Xiao, T., He, T., Horn, M., Fu, Y., … Zhang, Z. (2024). Adaptive slot attention: Object discovery with dynamic slot number. In <i>2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition</i>. Seattle, WA, United States: IEEE. <a href=\"https://doi.org/10.1109/cvpr52733.2024.02176\">https://doi.org/10.1109/cvpr52733.2024.02176</a>","ista":"Fan K, Bai Z, Xiao T, He T, Horn M, Fu Y, Locatello F, Zhang Z. 2024. Adaptive slot attention: Object discovery with dynamic slot number. 2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition. CVPR: Conference on Computer Vision and Pattern Recognition."},"title":"Adaptive slot attention: Object discovery with dynamic slot number","date_updated":"2026-10-02T08:47:53Z","abstract":[{"lang":"eng","text":"Object-centric learning (OCL) extracts the representation of objects with slots, offering an exceptional blend of flexibility and interpretability for abstracting low-level perceptual features. A widely adopted method within OCL is slot attention, which utilizes attention mechanisms to iteratively refine slot representations. However, a major draw-back of most object-centric models, including slot attention, is their reliance on predefining the number of slots. This not only necessitates prior knowledge of the dataset but also overlooks the inherent variability in the number of objects present in each instance. To overcome this fundamental limitation, we present a novel complexity-aware object auto-encoder framework. Within this framework, we introduce an adaptive slot attention (AdaSlot) mecha-nism that dynamically determines the optimal number of slots based on the content of the data. This is achieved by proposing a discrete slot sampling module that is responsible for selecting an appropriate number of slots from a candidate list. Furthermore, we introduce a masked slot decoder that suppresses unselected slots during the decoding process. Our framework, tested extensively on object discovery tasks with various datasets, shows performance matching or exceeding top fixed-slot models. Moreover, our analysis substantiates that our method exhibits the capability to dynamically adapt the slot number according to each instance's complexity, offering the potential for further exploration in slot attention research. Project will be available at https://kfan21.github.io/AdaSlot/"}],"author":[{"last_name":"Fan","first_name":"Ke","full_name":"Fan, Ke"},{"full_name":"Bai, Zechen","first_name":"Zechen","last_name":"Bai"},{"last_name":"Xiao","first_name":"Tianjun","full_name":"Xiao, Tianjun"},{"last_name":"He","first_name":"Tong","full_name":"He, Tong"},{"full_name":"Horn, Max","last_name":"Horn","first_name":"Max"},{"full_name":"Fu, Yanwei","last_name":"Fu","first_name":"Yanwei"},{"last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","first_name":"Francesco","orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco"},{"full_name":"Zhang, Zheng","last_name":"Zhang","first_name":"Zheng"}],"article_processing_charge":"No","date_created":"2025-01-29T14:27:39Z","year":"2024","acknowledgement":"Yanwei Fu is the corresponding authour. Yanwei Fu is with School of Data Science, Fudan University, Shanghai Key Lab of Intelligent Information Processing, Fudan University, and Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, China.","external_id":{"isi":["001342515506043"],"arxiv":["2406.09196"]},"oa":1,"supplementarymaterial":"no"},{"publisher":"IEEE","type":"conference","conference":{"name":"ICIP: International Conference on Image Processing","location":"Abu Dhabi, United Arab Emirates","end_date":"2024-10-30","start_date":"2024-10-27"},"related_material":{"link":[{"relation":"software","url":"https://github.com/berkerdemirel/decompl"}]},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2303.06439"}],"language":[{"iso":"eng"}],"publication":"2024 IEEE International Conference on Image Processing","publication_status":"published","user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","page":"977-983","isi":1,"_id":"18956","oa_version":"Preprint","month":"11","status":"public","das_tickbox":"0","date_published":"2024-11-01T00:00:00Z","department":[{"_id":"FrLo"}],"OA_place":"repository","fulldoi":"https://doi.org/10.1109/icip51287.2024.10647499","OA_type":"green","doi":"10.1109/icip51287.2024.10647499","publication_identifier":{"eisbn":["9798350349399"],"eissn":["2381-8549"]},"corr_author":"1","quality_controlled":"1","abstract":[{"lang":"eng","text":"Group Activity Recognition (GAR) aims to detect the activity performed by multiple actors in a scene. Prior works model the spatio-temporal features based on the RGB, optical flow or keypoint data types. On the contrary, our hypothesis is that by only using the RGB data without temporality, the performance can be maintained with a negligible loss in accuracy. To that end, we propose a novel GAR technique for volleyball videos, DECOMPL, which consists of two complementary branches. In the visual branch, it extracts the features using attention pooling. In the coordinate branch, it considers the configuration of the players and extracts the spatial information from the box coordinates. Moreover, we analyzed the Volleyball dataset that the recent literature is mostly based on, and systematically reannotated it to emphasize the group concept. Experimental results demonstrated the effectiveness of the proposed model DECOMPL, which delivered the best/second best GAR performance with the reannotations/original annotations among the comparable state-of-the-art methods. Code and new annotations are available at GitHub: https://github.com/berkerdemirel/decompl"}],"author":[{"last_name":"Demirel","id":"8b4bc47f-3200-11ee-973b-8f0e7be21a9f","first_name":"Berker","full_name":"Demirel, Berker"},{"first_name":"Huseyin","last_name":"Ozkan","full_name":"Ozkan, Huseyin"}],"date_updated":"2026-10-02T08:47:17Z","title":"Decompl: Decompositional learning with attention pooling for group activity recognition from a single volleyball image","citation":{"apa":"Demirel, B., &#38; Ozkan, H. (2024). Decompl: Decompositional learning with attention pooling for group activity recognition from a single volleyball image. In <i>2024 IEEE International Conference on Image Processing</i> (pp. 977–983). Abu Dhabi, United Arab Emirates: IEEE. <a href=\"https://doi.org/10.1109/icip51287.2024.10647499\">https://doi.org/10.1109/icip51287.2024.10647499</a>","ieee":"B. Demirel and H. Ozkan, “Decompl: Decompositional learning with attention pooling for group activity recognition from a single volleyball image,” in <i>2024 IEEE International Conference on Image Processing</i>, Abu Dhabi, United Arab Emirates, 2024, pp. 977–983.","ista":"Demirel B, Ozkan H. 2024. Decompl: Decompositional learning with attention pooling for group activity recognition from a single volleyball image. 2024 IEEE International Conference on Image Processing. ICIP: International Conference on Image Processing, 977–983.","chicago":"Demirel, Berker, and Huseyin Ozkan. “Decompl: Decompositional Learning with Attention Pooling for Group Activity Recognition from a Single Volleyball Image.” In <i>2024 IEEE International Conference on Image Processing</i>, 977–83. IEEE, 2024. <a href=\"https://doi.org/10.1109/icip51287.2024.10647499\">https://doi.org/10.1109/icip51287.2024.10647499</a>.","mla":"Demirel, Berker, and Huseyin Ozkan. “Decompl: Decompositional Learning with Attention Pooling for Group Activity Recognition from a Single Volleyball Image.” <i>2024 IEEE International Conference on Image Processing</i>, IEEE, 2024, pp. 977–83, doi:<a href=\"https://doi.org/10.1109/icip51287.2024.10647499\">10.1109/icip51287.2024.10647499</a>.","short":"B. Demirel, H. Ozkan, in:, 2024 IEEE International Conference on Image Processing, IEEE, 2024, pp. 977–983.","ama":"Demirel B, Ozkan H. Decompl: Decompositional learning with attention pooling for group activity recognition from a single volleyball image. In: <i>2024 IEEE International Conference on Image Processing</i>. IEEE; 2024:977-983. doi:<a href=\"https://doi.org/10.1109/icip51287.2024.10647499\">10.1109/icip51287.2024.10647499</a>"},"day":"01","arxiv":1,"researchdata_availability":"yes","supplementarymaterial":"no","oa":1,"external_id":{"arxiv":["2303.06439"],"isi":["001442947000143"]},"year":"2024","date_created":"2025-01-29T12:22:24Z","article_processing_charge":"No"},{"type":"conference","publisher":"Neural Information Processing Systems Foundation","conference":{"location":"Vancouver, Canada","name":"NeurIPS: Neural Information Processing Systems","start_date":"2024-12-16","end_date":"2024-12-16"},"user_id":"317138e5-6ab7-11ef-aa6d-ffef3953e345","publication_status":"published","language":[{"iso":"eng"}],"publication":"38th Conference on Neural Information Processing Systems","scopus_import":"1","_id":"18996","oa_version":"Published Version","month":"09","ddc":["000"],"file_date_updated":"2025-02-04T13:09:08Z","status":"public","date_published":"2024-09-25T00:00:00Z","has_accepted_license":"1","das_tickbox":"0","department":[{"_id":"FrLo"}],"OA_place":"repository","OA_type":"green","publication_identifier":{"eissn":["1049-5258"]},"file":[{"relation":"main_file","success":1,"content_type":"application/pdf","date_created":"2025-02-04T13:09:08Z","file_id":"18997","creator":"dernst","date_updated":"2025-02-04T13:09:08Z","access_level":"open_access","file_name":"2024_NeurIPS_Chen.pdf","file_size":5659119,"checksum":"75c3091e70bd2916cd94afbf40a0c425"}],"quality_controlled":"1","abstract":[{"lang":"eng","text":"We consider the linear causal representation learning setting where we observe a linear mixing of d unknown latent factors, which follow a linear structural causal model. Recent work has shown that it is possible to recover the latent factors as well as the underlying structural causal model over them, up to permutation and scaling, provided that we have at least d environments, each of which corresponds to perfect interventions on a single latent node (factor). After this powerful result, a key open problem faced by the community has been to relax these conditions: allow for coarser than perfect single-node interventions, and allow for fewer than d of them, since the number of latent factors d could be very large. In this work, we consider precisely such a setting, where we allow a smaller than d number of environments, and also allow for very coarse interventions that can very coarsely \\textit{change the entire causal graph over the latent factors}. On the flip side, we relax what we wish to extract to simply the \\textit{list of nodes that have shifted between one or more environments}. We provide a surprising identifiability result that it is indeed possible, under some very mild standard assumptions, to identify the set of shifted nodes. Our identifiability proof moreover is a constructive one: we explicitly provide necessary and sufficient conditions for a node to be a shifted node, and show that we can check these conditions given observed data. Our algorithm lends itself very naturally to the sample setting where instead of just interventional distributions, we are provided datasets of samples from each of these distributions. We corroborate our results on both synthetic experiments as well as an interesting psychometric dataset. The code can be found at https://github.com/TianyuCodings/iLCS."}],"author":[{"full_name":"Chen, Tianyu","first_name":"Tianyu","last_name":"Chen"},{"last_name":"Bello","first_name":"Kevin","full_name":"Bello, Kevin"},{"full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","first_name":"Francesco"},{"first_name":"Bryon","last_name":"Aragam","full_name":"Aragam, Bryon"},{"first_name":"Pradeep Kumar","last_name":"Ravikumar","full_name":"Ravikumar, Pradeep Kumar"}],"date_updated":"2026-10-02T08:49:13Z","title":"Identifying general mechanism shifts in linear causal representations","volume":37,"intvolume":"        37","citation":{"ama":"Chen T, Bello K, Locatello F, Aragam B, Ravikumar PK. Identifying general mechanism shifts in linear causal representations. In: <i>38th Conference on Neural Information Processing Systems</i>. Vol 37. Neural Information Processing Systems Foundation; 2024.","ieee":"T. Chen, K. Bello, F. Locatello, B. Aragam, and P. K. Ravikumar, “Identifying general mechanism shifts in linear causal representations,” in <i>38th Conference on Neural Information Processing Systems</i>, Vancouver, Canada, 2024, vol. 37.","apa":"Chen, T., Bello, K., Locatello, F., Aragam, B., &#38; Ravikumar, P. K. (2024). Identifying general mechanism shifts in linear causal representations. In <i>38th Conference on Neural Information Processing Systems</i> (Vol. 37). Vancouver, Canada: Neural Information Processing Systems Foundation.","ista":"Chen T, Bello K, Locatello F, Aragam B, Ravikumar PK. 2024. Identifying general mechanism shifts in linear causal representations. 38th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 37.","chicago":"Chen, Tianyu, Kevin Bello, Francesco Locatello, Bryon Aragam, and Pradeep Kumar Ravikumar. “Identifying General Mechanism Shifts in Linear Causal Representations.” In <i>38th Conference on Neural Information Processing Systems</i>, Vol. 37. Neural Information Processing Systems Foundation, 2024.","short":"T. Chen, K. Bello, F. Locatello, B. Aragam, P.K. Ravikumar, in:, 38th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2024.","mla":"Chen, Tianyu, et al. “Identifying General Mechanism Shifts in Linear Causal Representations.” <i>38th Conference on Neural Information Processing Systems</i>, vol. 37, Neural Information Processing Systems Foundation, 2024."},"alternative_title":["Advances in Neural Information Processing Systems"],"day":"25","researchdata_availability":"no","arxiv":1,"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)"},"supplementarymaterial":"no","external_id":{"arxiv":["2410.24059"]},"oa":1,"year":"2024","date_created":"2025-02-04T13:09:34Z","article_processing_charge":"No"}]