[{"type":"conference","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2207.09239"}],"conference":{"end_date":"2022-12-09","location":"New Orleans, LA, United States","start_date":"2022-11-28","name":"NeurIPS: Neural Information Processing Systems"},"oa":1,"publisher":"Neural Information Processing Systems Foundation","alternative_title":["Advances in Neural Information Processing Systems"],"department":[{"_id":"FrLo"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"ieee":"F. Wenzel <i>et al.</i>, “Assaying out-of-distribution generalization in transfer learning,” in <i>36th Conference on Neural Information Processing Systems</i>, New Orleans, LA, United States, 2022, vol. 35, pp. 7181–7198.","apa":"Wenzel, F., Dittadi, A., Gehler, P. V., Carl-Johann Simon-Gabriel, C.-J. S.-G., Horn, M., Zietlow, D., … Locatello, F. (2022). Assaying out-of-distribution generalization in transfer learning. In <i>36th Conference on Neural Information Processing Systems</i> (Vol. 35, pp. 7181–7198). New Orleans, LA, United States: Neural Information Processing Systems Foundation.","chicago":"Wenzel, Florian, Andrea Dittadi, Peter Vincent Gehler, Carl-Johann Simon-Gabriel Carl-Johann Simon-Gabriel, Max Horn, Dominik Zietlow, David Kernert, et al. “Assaying Out-of-Distribution Generalization in Transfer Learning.” In <i>36th Conference on Neural Information Processing Systems</i>, 35:7181–98. Neural Information Processing Systems Foundation, 2022.","ista":"Wenzel F, Dittadi A, Gehler PV, Carl-Johann Simon-Gabriel C-JS-G, Horn M, Zietlow D, Kernert D, Russell C, Brox T, Schiele B, Schölkopf B, Locatello F. 2022. Assaying out-of-distribution generalization in transfer learning. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, vol. 35, 7181–7198.","mla":"Wenzel, Florian, et al. “Assaying Out-of-Distribution Generalization in Transfer Learning.” <i>36th Conference on Neural Information Processing Systems</i>, vol. 35, Neural Information Processing Systems Foundation, 2022, pp. 7181–98.","short":"F. Wenzel, A. Dittadi, P.V. Gehler, C.-J.S.-G. Carl-Johann Simon-Gabriel, M. Horn, D. Zietlow, D. Kernert, C. Russell, T. Brox, B. Schiele, B. Schölkopf, F. Locatello, in:, 36th Conference on Neural Information Processing Systems, Neural Information Processing Systems Foundation, 2022, pp. 7181–7198.","ama":"Wenzel F, Dittadi A, Gehler PV, et al. Assaying out-of-distribution generalization in transfer learning. In: <i>36th Conference on Neural Information Processing Systems</i>. Vol 35. Neural Information Processing Systems Foundation; 2022:7181-7198."},"article_processing_charge":"No","publication_identifier":{"isbn":["9781713871088"]},"quality_controlled":"1","arxiv":1,"day":"15","intvolume":"        35","date_published":"2022-12-15T00:00:00Z","page":"7181-7198","abstract":[{"text":"Since out-of-distribution generalization is a generally ill-posed problem, various proxy targets (e.g., calibration, adversarial robustness, algorithmic corruptions, invariance across shifts) were studied across different research programs resulting in different recommendations. While sharing the same aspirational goal, these approaches have never been tested under the same\r\nexperimental conditions on real data. In this paper, we take a unified view of previous work, highlighting message discrepancies that we address empirically, and providing recommendations on how to measure the robustness of a model and how to improve it. To this end, we collect 172 publicly available dataset pairs for training and out-of-distribution evaluation of accuracy, calibration error, adversarial attacks, environment invariance, and synthetic corruptions. We fine-tune over 31k networks, from nine different architectures in the many- and\r\nfew-shot setting. Our findings confirm that in- and out-of-distribution accuracies tend to increase jointly, but show that their relation is largely dataset-dependent, and in general more nuanced and more complex than posited by previous, smaller scale studies.","lang":"eng"}],"year":"2022","volume":35,"date_created":"2023-08-22T14:01:13Z","external_id":{"arxiv":["2207.09239"]},"oa_version":"Preprint","language":[{"iso":"eng"}],"publication":"36th Conference on Neural Information Processing Systems","_id":"14173","status":"public","scopus_import":"1","title":"Assaying out-of-distribution generalization in transfer learning","extern":"1","publication_status":"published","date_updated":"2023-09-06T10:34:43Z","author":[{"first_name":"Florian","full_name":"Wenzel, Florian","last_name":"Wenzel"},{"last_name":"Dittadi","first_name":"Andrea","full_name":"Dittadi, Andrea"},{"last_name":"Gehler","full_name":"Gehler, Peter Vincent","first_name":"Peter Vincent"},{"full_name":"Carl-Johann Simon-Gabriel, Carl-Johann Simon-Gabriel","first_name":"Carl-Johann Simon-Gabriel","last_name":"Carl-Johann Simon-Gabriel"},{"last_name":"Horn","first_name":"Max","full_name":"Horn, Max"},{"first_name":"Dominik","full_name":"Zietlow, Dominik","last_name":"Zietlow"},{"first_name":"David","full_name":"Kernert, David","last_name":"Kernert"},{"last_name":"Russell","full_name":"Russell, Chris","first_name":"Chris"},{"last_name":"Brox","full_name":"Brox, Thomas","first_name":"Thomas"},{"last_name":"Schiele","first_name":"Bernt","full_name":"Schiele, Bernt"},{"last_name":"Schölkopf","first_name":"Bernhard","full_name":"Schölkopf, Bernhard"},{"full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","first_name":"Francesco","last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4"}],"month":"12"},{"month":"04","author":[{"full_name":"Dittadi, Andrea","first_name":"Andrea","last_name":"Dittadi"},{"last_name":"Träuble","first_name":"Frederik","full_name":"Träuble, Frederik"},{"last_name":"Wüthrich","first_name":"Manuel","full_name":"Wüthrich, Manuel"},{"last_name":"Widmaier","full_name":"Widmaier, Felix","first_name":"Felix"},{"full_name":"Gehler, Peter","first_name":"Peter","last_name":"Gehler"},{"first_name":"Ole","full_name":"Winther, Ole","last_name":"Winther"},{"last_name":"Locatello","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","full_name":"Locatello, Francesco","orcid":"0000-0002-4850-0683","first_name":"Francesco"},{"first_name":"Olivier","full_name":"Bachem, Olivier","last_name":"Bachem"},{"last_name":"Schölkopf","full_name":"Schölkopf, Bernhard","first_name":"Bernhard"},{"last_name":"Bauer","full_name":"Bauer, Stefan","first_name":"Stefan"}],"date_published":"2022-04-25T00:00:00Z","date_updated":"2023-09-11T09:48:36Z","publication_status":"published","quality_controlled":"1","arxiv":1,"day":"25","title":"The role of pretrained representations for the OOD generalization of  reinforcement learning agents","status":"public","article_processing_charge":"No","extern":"1","publication":"10th International Conference on Learning Representations","language":[{"iso":"eng"}],"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"14174","department":[{"_id":"FrLo"}],"citation":{"short":"A. Dittadi, F. Träuble, M. Wüthrich, F. Widmaier, P. Gehler, O. Winther, F. Locatello, O. Bachem, B. Schölkopf, S. Bauer, in:, 10th International Conference on Learning Representations, 2022.","ama":"Dittadi A, Träuble F, Wüthrich M, et al. The role of pretrained representations for the OOD generalization of  reinforcement learning agents. In: <i>10th International Conference on Learning Representations</i>. ; 2022.","chicago":"Dittadi, Andrea, Frederik Träuble, Manuel Wüthrich, Felix Widmaier, Peter Gehler, Ole Winther, Francesco Locatello, Olivier Bachem, Bernhard Schölkopf, and Stefan Bauer. “The Role of Pretrained Representations for the OOD Generalization of  Reinforcement Learning Agents.” In <i>10th International Conference on Learning Representations</i>, 2022.","apa":"Dittadi, A., Träuble, F., Wüthrich, M., Widmaier, F., Gehler, P., Winther, O., … Bauer, S. (2022). The role of pretrained representations for the OOD generalization of  reinforcement learning agents. In <i>10th International Conference on Learning Representations</i>. Virtual.","ieee":"A. Dittadi <i>et al.</i>, “The role of pretrained representations for the OOD generalization of  reinforcement learning agents,” in <i>10th International Conference on Learning Representations</i>, Virtual, 2022.","ista":"Dittadi A, Träuble F, Wüthrich M, Widmaier F, Gehler P, Winther O, Locatello F, Bachem O, Schölkopf B, Bauer S. 2022. The role of pretrained representations for the OOD generalization of  reinforcement learning agents. 10th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.","mla":"Dittadi, Andrea, et al. “The Role of Pretrained Representations for the OOD Generalization of  Reinforcement Learning Agents.” <i>10th International Conference on Learning Representations</i>, 2022."},"oa_version":"Preprint","date_created":"2023-08-22T14:02:13Z","external_id":{"arxiv":["2107.05686"]},"oa":1,"year":"2022","type":"conference","abstract":[{"lang":"eng","text":"Building sample-efficient agents that generalize out-of-distribution (OOD) in real-world settings remains a fundamental unsolved problem on the path towards achieving higher-level cognition. One particularly promising approach is to begin with low-dimensional, pretrained representations of our world, which should facilitate efficient downstream learning and generalization. By training 240 representations and over 10,000 reinforcement learning (RL) policies on a simulated robotic setup, we evaluate to what extent different properties of\r\npretrained VAE-based representations affect the OOD generalization of downstream agents. We observe that many agents are surprisingly robust to realistic distribution shifts, including the challenging sim-to-real case. In addition, we find that the generalization performance of a simple downstream proxy task reliably predicts the generalization performance of our RL agents\r\nunder a wide range of OOD settings. Such proxy tasks can thus be used to select pretrained representations that will lead to agents that generalize."}],"conference":{"location":"Virtual","end_date":"2022-04-29","name":"ICLR: International Conference on Learning Representations","start_date":"2022-04-25"},"main_file_link":[{"url":" https://doi.org/10.48550/arXiv.2107.05686","open_access":"1"}]},{"title":"You mostly walk alone: Analyzing feature attribution in trajectory prediction","article_processing_charge":"No","status":"public","extern":"1","language":[{"iso":"eng"}],"publication":"10th International Conference on Learning Representations","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"14175","citation":{"apa":"Makansi, O., Kügelgen, J. von, Locatello, F., Gehler, P., Janzing, D., Brox, T., &#38; Schölkopf, B. (2022). You mostly walk alone: Analyzing feature attribution in trajectory prediction. In <i>10th International Conference on Learning Representations</i>. Virtual.","chicago":"Makansi, Osama, Julius von Kügelgen, Francesco Locatello, Peter Gehler, Dominik Janzing, Thomas Brox, and Bernhard Schölkopf. “You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction.” In <i>10th International Conference on Learning Representations</i>, 2022.","ieee":"O. Makansi <i>et al.</i>, “You mostly walk alone: Analyzing feature attribution in trajectory prediction,” in <i>10th International Conference on Learning Representations</i>, Virtual, 2022.","ista":"Makansi O, Kügelgen J von, Locatello F, Gehler P, Janzing D, Brox T, Schölkopf B. 2022. You mostly walk alone: Analyzing feature attribution in trajectory prediction. 10th International Conference on Learning Representations. ICLR: International Conference on Learning Representations.","mla":"Makansi, Osama, et al. “You Mostly Walk Alone: Analyzing Feature Attribution in Trajectory Prediction.” <i>10th International Conference on Learning Representations</i>, 2022.","short":"O. Makansi, J. von Kügelgen, F. Locatello, P. Gehler, D. Janzing, T. Brox, B. Schölkopf, in:, 10th International Conference on Learning Representations, 2022.","ama":"Makansi O, Kügelgen J von, Locatello F, et al. You mostly walk alone: Analyzing feature attribution in trajectory prediction. In: <i>10th International Conference on Learning Representations</i>. ; 2022."},"department":[{"_id":"FrLo"}],"author":[{"last_name":"Makansi","first_name":"Osama","full_name":"Makansi, Osama"},{"last_name":"Kügelgen","full_name":"Kügelgen, Julius von","first_name":"Julius von"},{"full_name":"Locatello, Francesco","first_name":"Francesco","orcid":"0000-0002-4850-0683","id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello"},{"full_name":"Gehler, Peter","first_name":"Peter","last_name":"Gehler"},{"first_name":"Dominik","full_name":"Janzing, Dominik","last_name":"Janzing"},{"full_name":"Brox, Thomas","first_name":"Thomas","last_name":"Brox"},{"last_name":"Schölkopf","full_name":"Schölkopf, Bernhard","first_name":"Bernhard"}],"month":"04","date_published":"2022-04-25T00:00:00Z","date_updated":"2023-09-11T09:52:20Z","publication_status":"published","quality_controlled":"1","day":"25","arxiv":1,"year":"2022","oa":1,"type":"conference","abstract":[{"text":"Predicting the future trajectory of a moving agent can be easy when the past trajectory continues smoothly but is challenging when complex interactions with other agents are involved. Recent deep learning approaches for trajectory prediction show promising performance and partially attribute this to successful reasoning about agent-agent interactions. However, it remains unclear which features such black-box models actually learn to use for making predictions. This paper proposes a procedure that quantifies the contributions\r\nof different cues to model performance based on a variant of Shapley values. Applying this procedure to state-of-the-art trajectory prediction methods on standard benchmark datasets shows that they are, in fact, unable to reason about interactions. Instead, the past trajectory of the target is the only feature used for predicting its future. For a task with richer social\r\ninteraction patterns, on the other hand, the tested models do pick up such interactions to a certain extent, as quantified by our feature attribution method. We discuss the limits of the proposed method and its links to causality.","lang":"eng"}],"conference":{"start_date":"2022-04-25","name":"ICLR: International Conference on Learning Representations","end_date":"2022-04-29","location":"Virtual"},"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2110.05304"}],"oa_version":"Preprint","external_id":{"arxiv":["2110.05304"]},"date_created":"2023-08-22T14:02:34Z"},{"date_published":"2022-11-04T00:00:00Z","author":[{"full_name":"Rahaman, Nasim","first_name":"Nasim","last_name":"Rahaman"},{"last_name":"Weiss","first_name":"Martin","full_name":"Weiss, Martin"},{"last_name":"Träuble","full_name":"Träuble, Frederik","first_name":"Frederik"},{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","full_name":"Locatello, Francesco","first_name":"Francesco","orcid":"0000-0002-4850-0683"},{"full_name":"Lacoste, Alexandre","first_name":"Alexandre","last_name":"Lacoste"},{"full_name":"Bengio, Yoshua","first_name":"Yoshua","last_name":"Bengio"},{"last_name":"Pal","first_name":"Chris","full_name":"Pal, Chris"},{"last_name":"Li","full_name":"Li, Li Erran","first_name":"Li Erran"},{"last_name":"Schölkopf","first_name":"Bernhard","full_name":"Schölkopf, Bernhard"}],"month":"11","day":"04","arxiv":1,"date_updated":"2023-09-13T09:35:59Z","quality_controlled":"1","publication_status":"submitted","extern":"1","title":"A general purpose neural architecture for geospatial systems","status":"public","article_processing_charge":"No","department":[{"_id":"FrLo"}],"_id":"14215","citation":{"short":"N. Rahaman, M. Weiss, F. Träuble, F. Locatello, A. Lacoste, Y. Bengio, C. Pal, L.E. Li, B. Schölkopf, in:, 36th Conference on Neural Information Processing Systems, n.d.","ama":"Rahaman N, Weiss M, Träuble F, et al. A general purpose neural architecture for geospatial systems. In: <i>36th Conference on Neural Information Processing Systems</i>.","chicago":"Rahaman, Nasim, Martin Weiss, Frederik Träuble, Francesco Locatello, Alexandre Lacoste, Yoshua Bengio, Chris Pal, Li Erran Li, and Bernhard Schölkopf. “A General Purpose Neural Architecture for Geospatial Systems.” In <i>36th Conference on Neural Information Processing Systems</i>, n.d.","apa":"Rahaman, N., Weiss, M., Träuble, F., Locatello, F., Lacoste, A., Bengio, Y., … Schölkopf, B. (n.d.). A general purpose neural architecture for geospatial systems. In <i>36th Conference on Neural Information Processing Systems</i>. New Orleans, LA, United States.","ieee":"N. Rahaman <i>et al.</i>, “A general purpose neural architecture for geospatial systems,” in <i>36th Conference on Neural Information Processing Systems</i>, New Orleans, LA, United States.","ista":"Rahaman N, Weiss M, Träuble F, Locatello F, Lacoste A, Bengio Y, Pal C, Li LE, Schölkopf B. A general purpose neural architecture for geospatial systems. 36th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems.","mla":"Rahaman, Nasim, et al. “A General Purpose Neural Architecture for Geospatial Systems.” <i>36th Conference on Neural Information Processing Systems</i>."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication":"36th Conference on Neural Information Processing Systems","language":[{"iso":"eng"}],"oa_version":"Preprint","date_created":"2023-08-22T14:21:47Z","external_id":{"arxiv":["2211.02348"]},"oa":1,"year":"2022","abstract":[{"lang":"eng","text":"Geospatial Information Systems are used by researchers and Humanitarian Assistance and Disaster Response (HADR) practitioners to support a wide variety of important applications. However, collaboration between these actors is difficult due to the heterogeneous nature of geospatial data modalities (e.g., multi-spectral images of various resolutions, timeseries, weather data) and diversity of tasks (e.g., regression of human activity indicators or detecting forest fires). In this work, we present a roadmap towards the construction of a general-purpose neural architecture (GPNA) with a geospatial inductive bias, pre-trained on large amounts of unlabelled earth observation data in a self-supervised manner. We envision how such a model may facilitate cooperation between members of the community. We show preliminary results on the first step of the roadmap, where we instantiate an architecture that can process a wide variety of geospatial data modalities and demonstrate that it can achieve competitive performance with domain-specific architectures on tasks relating to the U.N.'s Sustainable Development Goals."}],"conference":{"end_date":"2022-12-09","location":"New Orleans, LA, United States","start_date":"2022-11-28","name":"NeurIPS: Neural Information Processing Systems"},"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2211.02348","open_access":"1"}],"type":"conference"},{"abstract":[{"text":"Although reinforcement learning has seen remarkable progress over the last years, solving robust dexterous object-manipulation tasks in multi-object settings remains a challenge. In this paper, we focus on models that can learn manipulation tasks in fixed multi-object settings and extrapolate this skill zero-shot without any drop in performance when the number of objects changes. We consider the generic task of bringing a specific cube out of a set to a goal position. We find that previous approaches, which primarily leverage attention and graph neural network-based architectures, do not generalize their skills when the number of input objects changes while scaling as K2. We propose an alternative plug-and-play module based on relational inductive biases to overcome these limitations. Besides exceeding performances in their training environment, we show that our approach, which scales linearly in K, allows agents to extrapolate and generalize zero-shot to any new object number.","lang":"eng"}],"main_file_link":[{"open_access":"1","url":"https://doi.org/10.48550/arXiv.2201.13388"}],"type":"preprint","year":"2022","oa":1,"doi":"10.48550/arXiv.2201.13388","date_created":"2023-08-22T14:23:16Z","external_id":{"arxiv":["2201.13388"]},"article_number":"2201.13388","oa_version":"Preprint","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"14220","citation":{"apa":"Mambelli, D., Träuble, F., Bauer, S., Schölkopf, B., &#38; Locatello, F. (n.d.). Compositional multi-object reinforcement learning with linear relation networks. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2201.13388\">https://doi.org/10.48550/arXiv.2201.13388</a>","chicago":"Mambelli, Davide, Frederik Träuble, Stefan Bauer, Bernhard Schölkopf, and Francesco Locatello. “Compositional Multi-Object Reinforcement Learning with Linear Relation Networks.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2201.13388\">https://doi.org/10.48550/arXiv.2201.13388</a>.","ieee":"D. Mambelli, F. Träuble, S. Bauer, B. Schölkopf, and F. Locatello, “Compositional multi-object reinforcement learning with linear relation networks,” <i>arXiv</i>. .","ista":"Mambelli D, Träuble F, Bauer S, Schölkopf B, Locatello F. Compositional multi-object reinforcement learning with linear relation networks. arXiv, 2201.13388.","mla":"Mambelli, Davide, et al. “Compositional Multi-Object Reinforcement Learning with Linear Relation Networks.” <i>ArXiv</i>, 2201.13388, doi:<a href=\"https://doi.org/10.48550/arXiv.2201.13388\">10.48550/arXiv.2201.13388</a>.","short":"D. Mambelli, F. Träuble, S. Bauer, B. Schölkopf, F. Locatello, ArXiv (n.d.).","ama":"Mambelli D, Träuble F, Bauer S, Schölkopf B, Locatello F. Compositional multi-object reinforcement learning with linear relation networks. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2201.13388\">10.48550/arXiv.2201.13388</a>"},"department":[{"_id":"FrLo"}],"language":[{"iso":"eng"}],"publication":"arXiv","extern":"1","title":"Compositional multi-object reinforcement learning with linear relation networks","article_processing_charge":"No","status":"public","day":"31","arxiv":1,"date_updated":"2024-10-14T12:27:39Z","publication_status":"submitted","date_published":"2022-01-31T00:00:00Z","month":"01","author":[{"last_name":"Mambelli","full_name":"Mambelli, Davide","first_name":"Davide"},{"last_name":"Träuble","first_name":"Frederik","full_name":"Träuble, Frederik"},{"first_name":"Stefan","full_name":"Bauer, Stefan","last_name":"Bauer"},{"first_name":"Bernhard","full_name":"Schölkopf, Bernhard","last_name":"Schölkopf"},{"id":"26cfd52f-2483-11ee-8040-88983bcc06d4","last_name":"Locatello","first_name":"Francesco","orcid":"0000-0002-4850-0683","full_name":"Locatello, Francesco"}]},{"year":"2022","oa":1,"doi":"10.48550/arXiv.2211.09606","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2211.09606","open_access":"1"}],"abstract":[{"lang":"eng","text":"We show an $(1+\\epsilon)$-approximation algorithm for maintaining maximum $s$-$t$ flow under $m$ edge insertions in $m^{1/2+o(1)} \\epsilon^{-1/2}$ amortized update time for directed, unweighted graphs. This constitutes the first sublinear dynamic maximum flow algorithm in general sparse graphs with arbitrarily good approximation guarantee."}],"type":"preprint","oa_version":"Preprint","external_id":{"arxiv":["2211.09606"]},"date_created":"2023-08-25T15:04:29Z","article_number":"2211.09606","extern":"1","status":"public","article_processing_charge":"No","title":"Incremental approximate maximum flow in m1/2+o(1) update time","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","_id":"14236","citation":{"ama":"Goranci G, Henzinger M. Incremental approximate maximum flow in m1/2+o(1) update time. <i>arXiv</i>. doi:<a href=\"https://doi.org/10.48550/arXiv.2211.09606\">10.48550/arXiv.2211.09606</a>","short":"G. Goranci, M. Henzinger, ArXiv (n.d.).","mla":"Goranci, Gramoz, and Monika Henzinger. “Incremental Approximate Maximum Flow in M1/2+o(1) Update Time.” <i>ArXiv</i>, 2211.09606, doi:<a href=\"https://doi.org/10.48550/arXiv.2211.09606\">10.48550/arXiv.2211.09606</a>.","chicago":"Goranci, Gramoz, and Monika Henzinger. “Incremental Approximate Maximum Flow in M1/2+o(1) Update Time.” <i>ArXiv</i>, n.d. <a href=\"https://doi.org/10.48550/arXiv.2211.09606\">https://doi.org/10.48550/arXiv.2211.09606</a>.","ieee":"G. Goranci and M. Henzinger, “Incremental approximate maximum flow in m1/2+o(1) update time,” <i>arXiv</i>. .","apa":"Goranci, G., &#38; Henzinger, M. (n.d.). Incremental approximate maximum flow in m1/2+o(1) update time. <i>arXiv</i>. <a href=\"https://doi.org/10.48550/arXiv.2211.09606\">https://doi.org/10.48550/arXiv.2211.09606</a>","ista":"Goranci G, Henzinger M. Incremental approximate maximum flow in m1/2+o(1) update time. arXiv, 2211.09606."},"language":[{"iso":"eng"}],"publication":"arXiv","date_published":"2022-11-17T00:00:00Z","month":"11","author":[{"last_name":"Goranci","full_name":"Goranci, Gramoz","first_name":"Gramoz"},{"full_name":"Henzinger, Monika H","first_name":"Monika H","orcid":"0000-0002-5008-6530","id":"540c9bbd-f2de-11ec-812d-d04a5be85630","last_name":"Henzinger"}],"day":"17","arxiv":1,"publication_status":"submitted","date_updated":"2024-11-06T12:01:45Z"},{"intvolume":"         5","date_published":"2022-02-13T00:00:00Z","quality_controlled":"1","day":"13","arxiv":1,"article_processing_charge":"No","publication_identifier":{"issn":["2576-3725"]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"ama":"Holmes D. Affine dimers from characteristic polygons. <i>PUMP Journal of Undergraduate Research</i>. 2022;5:24-51.","short":"D. Holmes, PUMP Journal of Undergraduate Research 5 (2022) 24–51.","mla":"Holmes, Daniel. “Affine Dimers from Characteristic Polygons.” <i>PUMP Journal of Undergraduate Research</i>, vol. 5, California State University, 2022, pp. 24–51.","apa":"Holmes, D. (2022). Affine dimers from characteristic polygons. <i>PUMP Journal of Undergraduate Research</i>. California State University.","chicago":"Holmes, Daniel. “Affine Dimers from Characteristic Polygons.” <i>PUMP Journal of Undergraduate Research</i>. California State University, 2022.","ieee":"D. Holmes, “Affine dimers from characteristic polygons,” <i>PUMP Journal of Undergraduate Research</i>, vol. 5. California State University, pp. 24–51, 2022.","ista":"Holmes D. 2022. Affine dimers from characteristic polygons. PUMP Journal of Undergraduate Research. 5, 24–51."},"publisher":"California State University","corr_author":"1","keyword":["dimer model","hyperplane arrangement","torus","lattice polygon"],"oa":1,"type":"journal_article","main_file_link":[{"open_access":"1","url":"https://journals.calstate.edu/pump/article/view/2711"}],"author":[{"last_name":"Holmes","id":"3a443b4c-080d-11ed-979a-feb062bdcee0","first_name":"Daniel","full_name":"Holmes, Daniel"}],"month":"02","date_updated":"2024-10-09T21:06:47Z","publication_status":"published","title":"Affine dimers from characteristic polygons","status":"public","article_type":"original","extern":"1","language":[{"iso":"eng"}],"publication":"PUMP Journal of Undergraduate Research","_id":"14248","oa_version":"Published Version","date_created":"2023-08-29T13:08:09Z","external_id":{"arxiv":["2110.01703"]},"volume":5,"year":"2022","page":"24-51","abstract":[{"lang":"eng","text":"Recent work by Forsgård indicates that not every convex lattice polygon arises as the characteristic polygon of an affine dimer or, equivalently, an admissible oriented line arrangement on the torus in general position. We begin the classication of convex lattice polygons arising as characteristic polygons of affine dimers. We present several general constructions of new affine dimers from old, and an algorithm for finding affine dimers with prescribed polygon.\r\n\r\nWith these tools we prove that all lattice triangles, generalised parallelograms, and polygons of genus at most two admit an affine dimer."}]},{"intvolume":"        24","date_published":"2022-10-01T00:00:00Z","quality_controlled":"1","day":"01","article_processing_charge":"No","publication_identifier":{"issn":["1098-3600"]},"department":[{"_id":"GradSch"}],"citation":{"ama":"Cali E, Lin S-J, Rocca C, et al. A homozygous MED11 C-terminal variant causes a lethal neurodegenerative disease. <i>Genetics in Medicine</i>. 2022;24(10):2194-2203. doi:<a href=\"https://doi.org/10.1016/j.gim.2022.07.013\">10.1016/j.gim.2022.07.013</a>","short":"E. Cali, S.-J. Lin, C. Rocca, Y. Sahin, A. Al Shamsi, S. El Chehadeh, M. Chaabouni, K. Mankad, E. Galanaki, S. Efthymiou, S. Sudhakar, A. Athanasiou-Fragkouli, T. Celik, N. Narli, S. Bianca, D. Murphy, F.M.D.C. Moreira, A. Accogli, C. Petree, K. Huang, K. Monastiri, M. Edizadeh, R. Nardello, M. Ognibene, P. De Marco, M. Ruggieri, F. Zara, P. Striano, Y. Sahin, L. Al-Gazali, M.T.A. Warde, B. Gerard, G. Zifarelli, C. Beetz, S. Fortuna, M. Soler, E.M. Valente, G. Varshney, R. Maroofian, V. Salpietro, H. Houlden, Syn.S. Grp, Genetics in Medicine 24 (2022) 2194–2203.","mla":"Cali, Elisa, et al. “A Homozygous MED11 C-Terminal Variant Causes a Lethal Neurodegenerative Disease.” <i>Genetics in Medicine</i>, vol. 24, no. 10, Elsevier, 2022, pp. 2194–203, doi:<a href=\"https://doi.org/10.1016/j.gim.2022.07.013\">10.1016/j.gim.2022.07.013</a>.","ista":"Cali E, Lin S-J, Rocca C, Sahin Y, Al Shamsi A, El Chehadeh S, Chaabouni M, Mankad K, Galanaki E, Efthymiou S, Sudhakar S, Athanasiou-Fragkouli A, Celik T, Narli N, Bianca S, Murphy D, Moreira FMDC, Accogli A, Petree C, Huang K, Monastiri K, Edizadeh M, Nardello R, Ognibene M, De Marco P, Ruggieri M, Zara F, Striano P, Sahin Y, Al-Gazali L, Warde MTA, Gerard B, Zifarelli G, Beetz C, Fortuna S, Soler M, Valente EM, Varshney G, Maroofian R, Salpietro V, Houlden H, Grp SynS. 2022. A homozygous MED11 C-terminal variant causes a lethal neurodegenerative disease. Genetics in Medicine. 24(10), 2194–2203.","chicago":"Cali, Elisa, Sheng-Jia Lin, Clarissa Rocca, Yavuz Sahin, Aisha Al Shamsi, Salima El Chehadeh, Myriam Chaabouni, et al. “A Homozygous MED11 C-Terminal Variant Causes a Lethal Neurodegenerative Disease.” <i>Genetics in Medicine</i>. Elsevier, 2022. <a href=\"https://doi.org/10.1016/j.gim.2022.07.013\">https://doi.org/10.1016/j.gim.2022.07.013</a>.","apa":"Cali, E., Lin, S.-J., Rocca, C., Sahin, Y., Al Shamsi, A., El Chehadeh, S., … Grp, Syn. S. (2022). A homozygous MED11 C-terminal variant causes a lethal neurodegenerative disease. <i>Genetics in Medicine</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.gim.2022.07.013\">https://doi.org/10.1016/j.gim.2022.07.013</a>","ieee":"E. Cali <i>et al.</i>, “A homozygous MED11 C-terminal variant causes a lethal neurodegenerative disease,” <i>Genetics in Medicine</i>, vol. 24, no. 10. Elsevier, pp. 2194–2203, 2022."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"Elsevier","issue":"10","keyword":["Human mediator complex","MED11","MEDopathies"],"tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"has_accepted_license":"1","doi":"10.1016/j.gim.2022.07.013","oa":1,"file_date_updated":"2023-09-25T08:56:06Z","type":"journal_article","author":[{"last_name":"Cali","full_name":"Cali, Elisa","first_name":"Elisa"},{"last_name":"Lin","first_name":"Sheng-Jia","full_name":"Lin, Sheng-Jia"},{"full_name":"Rocca, Clarissa","first_name":"Clarissa","last_name":"Rocca"},{"first_name":"Yavuz","full_name":"Sahin, Yavuz","last_name":"Sahin"},{"first_name":"Aisha","full_name":"Al Shamsi, Aisha","last_name":"Al Shamsi"},{"full_name":"El Chehadeh, Salima","first_name":"Salima","last_name":"El Chehadeh"},{"last_name":"Chaabouni","first_name":"Myriam","full_name":"Chaabouni, Myriam"},{"last_name":"Mankad","first_name":"Kshitij","full_name":"Mankad, Kshitij"},{"last_name":"Galanaki","first_name":"Evangelia","full_name":"Galanaki, Evangelia"},{"last_name":"Efthymiou","first_name":"Stephanie","full_name":"Efthymiou, Stephanie"},{"full_name":"Sudhakar, Sniya","first_name":"Sniya","last_name":"Sudhakar"},{"full_name":"Athanasiou-Fragkouli, Alkyoni","first_name":"Alkyoni","last_name":"Athanasiou-Fragkouli"},{"first_name":"Tamer","full_name":"Celik, Tamer","last_name":"Celik"},{"last_name":"Narli","full_name":"Narli, Nejat","first_name":"Nejat"},{"last_name":"Bianca","first_name":"Sebastiano","full_name":"Bianca, Sebastiano"},{"first_name":"David","full_name":"Murphy, David","last_name":"Murphy"},{"full_name":"Moreira, Francisco Martins De Carvalho","first_name":"Francisco Martins De Carvalho","last_name":"Moreira"},{"first_name":"Andrea","full_name":"Accogli, Andrea","last_name":"Accogli"},{"first_name":"Cassidy","full_name":"Petree, Cassidy","last_name":"Petree"},{"full_name":"Huang, Kevin","orcid":"0000-0002-2512-7812","first_name":"Kevin","last_name":"Huang","id":"3b3d2888-1ff6-11ee-9fa6-8f209ca91fe3"},{"last_name":"Monastiri","full_name":"Monastiri, Kamel","first_name":"Kamel"},{"first_name":"Masoud","full_name":"Edizadeh, Masoud","last_name":"Edizadeh"},{"last_name":"Nardello","first_name":"Rosaria","full_name":"Nardello, Rosaria"},{"full_name":"Ognibene, Marzia","first_name":"Marzia","last_name":"Ognibene"},{"first_name":"Patrizia","full_name":"De Marco, Patrizia","last_name":"De Marco"},{"first_name":"Martino","full_name":"Ruggieri, Martino","last_name":"Ruggieri"},{"last_name":"Zara","first_name":"Federico","full_name":"Zara, Federico"},{"last_name":"Striano","full_name":"Striano, Pasquale","first_name":"Pasquale"},{"first_name":"Yavuz","full_name":"Sahin, Yavuz","last_name":"Sahin"},{"last_name":"Al-Gazali","first_name":"Lihadh","full_name":"Al-Gazali, Lihadh"},{"full_name":"Warde, Marie Therese Abi","first_name":"Marie Therese Abi","last_name":"Warde"},{"full_name":"Gerard, Benedicte","first_name":"Benedicte","last_name":"Gerard"},{"full_name":"Zifarelli, Giovanni","first_name":"Giovanni","last_name":"Zifarelli"},{"last_name":"Beetz","full_name":"Beetz, Christian","first_name":"Christian"},{"last_name":"Fortuna","first_name":"Sara","full_name":"Fortuna, Sara"},{"last_name":"Soler","first_name":"Miguel","full_name":"Soler, Miguel"},{"full_name":"Valente, Enza Maria","first_name":"Enza Maria","last_name":"Valente"},{"last_name":"Varshney","first_name":"Gaurav","full_name":"Varshney, Gaurav"},{"last_name":"Maroofian","first_name":"Reza","full_name":"Maroofian, Reza"},{"last_name":"Salpietro","full_name":"Salpietro, Vincenzo","first_name":"Vincenzo"},{"first_name":"Henry","full_name":"Houlden, Henry","last_name":"Houlden"},{"first_name":"SYNaPS Study","full_name":"Grp, SYNaPS Study","last_name":"Grp"}],"month":"10","date_updated":"2023-09-25T08:57:07Z","publication_status":"published","ddc":["570"],"title":"A homozygous MED11 C-terminal variant causes a lethal neurodegenerative disease","scopus_import":"1","file":[{"access_level":"open_access","content_type":"application/pdf","relation":"main_file","file_name":"2022_GeneticsMedicine_Calin.pdf","creator":"dernst","file_id":"14371","date_created":"2023-09-25T08:56:06Z","success":1,"date_updated":"2023-09-25T08:56:06Z","checksum":"8117175a89129eb5022d81ffe7625f9f","file_size":1434037}],"status":"public","article_type":"original","extern":"1","publication":"Genetics in Medicine","language":[{"iso":"eng"}],"_id":"14355","oa_version":"Published Version","date_created":"2023-09-20T20:57:18Z","volume":24,"year":"2022","page":"2194-2203","abstract":[{"text":"Purpose: The mediator (MED) multisubunit-complex modulates the activity of the transcriptional machinery, and genetic defects in different MED subunits (17, 20, 27) have been implicated in neurologic diseases. In this study, we identified a recurrent homozygous variant in MED11 (c.325C>T; p.Arg109Ter) in 7 affected individuals from 5 unrelated families. Methods: To investigate the genetic cause of the disease, exome or genome sequencing were performed in 5 unrelated families identified via different research networks and Matchmaker Exchange. Deep clinical and brain imaging evaluations were performed by clinical pediatric neurologists and neuroradiologists. The functional effect of the candidate variant on both MED11 RNA and protein was assessed using reverse transcriptase polymerase chain reaction and western blotting using fibroblast cell lines derived from 1 affected individual and controls and through computational approaches. Knockouts in zebrafish were generated using clustered regularly interspaced short palindromic repeats/Cas9. Results: The disease was characterized by microcephaly, profound neurodevelopmental impairment, exaggerated startle response, myoclonic seizures, progressive widespread neurodegeneration, and premature death. Functional studies on patient-derived fibroblasts did not show a loss of protein function but rather disruption of the C-terminal of MED11, likely impairing binding to other MED subunits. A zebrafish knockout model recapitulates key clinical phenotypes. Conclusion: Loss of the C-terminal of MED subunit 11 may affect its binding efficiency to other MED subunits, thus implicating the MED-complex stability in brain development and neurodegeneration. (C) 2022 The Authors. Published by Elsevier Inc. on behalf of American College of Medical Genetics and Genomics.","lang":"eng"}]},{"has_accepted_license":"1","tmp":{"name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","short":"CC BY (4.0)","image":"/images/cc_by.png","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode"},"keyword":["autosomal recessive","biallelic variants","C","elegans","translation initiation sites","tryptophanyl-tRNA synthetase 1 (WARS1)","WHEP domain","zebrafish"],"type":"journal_article","file_date_updated":"2023-09-25T08:52:54Z","oa":1,"doi":"10.1002/humu.24435","day":"01","quality_controlled":"1","date_published":"2022-10-01T00:00:00Z","intvolume":"        43","publisher":"Wiley","issue":"10","citation":{"ama":"Lin S-J, Vona B, Porter HM, et al. Biallelic variants in WARS1 cause a highly variable neurodevelopmental syndrome and implicate a critical exon for normal auditory function. <i>Human Mutation</i>. 2022;43(10):1472-1489. doi:<a href=\"https://doi.org/10.1002/humu.24435\">10.1002/humu.24435</a>","short":"S.-J. Lin, B. Vona, H.M. Porter, M. Izadi, K. Huang, Y. Lacassie, J.A. Rosenfeld, S. Khan, C. Petree, T.A. Ali, N. Muhammad, S.A. Khan, N. Muhammad, P. Liu, M.-L. Haymon, F. Rueschendorf, I.-K. Kong, L. Schnapp, N. Shur, L. Chorich, L. Layman, T. Haaf, E. Pourkarimi, H.-G. Kim, G.K. Varshney, Human Mutation 43 (2022) 1472–1489.","mla":"Lin, Sheng-Jia, et al. “Biallelic Variants in WARS1 Cause a Highly Variable Neurodevelopmental Syndrome and Implicate a Critical Exon for Normal Auditory Function.” <i>Human Mutation</i>, vol. 43, no. 10, Wiley, 2022, pp. 1472–89, doi:<a href=\"https://doi.org/10.1002/humu.24435\">10.1002/humu.24435</a>.","ista":"Lin S-J, Vona B, Porter HM, Izadi M, Huang K, Lacassie Y, Rosenfeld JA, Khan S, Petree C, Ali TA, Muhammad N, Khan SA, Muhammad N, Liu P, Haymon M-L, Rueschendorf F, Kong I-K, Schnapp L, Shur N, Chorich L, Layman L, Haaf T, Pourkarimi E, Kim H-G, Varshney GK. 2022. Biallelic variants in WARS1 cause a highly variable neurodevelopmental syndrome and implicate a critical exon for normal auditory function. Human Mutation. 43(10), 1472–1489.","chicago":"Lin, Sheng-Jia, Barbara Vona, Hillary M. Porter, Mahmoud Izadi, Kevin Huang, Yves Lacassie, Jill A. Rosenfeld, et al. “Biallelic Variants in WARS1 Cause a Highly Variable Neurodevelopmental Syndrome and Implicate a Critical Exon for Normal Auditory Function.” <i>Human Mutation</i>. Wiley, 2022. <a href=\"https://doi.org/10.1002/humu.24435\">https://doi.org/10.1002/humu.24435</a>.","apa":"Lin, S.-J., Vona, B., Porter, H. M., Izadi, M., Huang, K., Lacassie, Y., … Varshney, G. K. (2022). Biallelic variants in WARS1 cause a highly variable neurodevelopmental syndrome and implicate a critical exon for normal auditory function. <i>Human Mutation</i>. Wiley. <a href=\"https://doi.org/10.1002/humu.24435\">https://doi.org/10.1002/humu.24435</a>","ieee":"S.-J. Lin <i>et al.</i>, “Biallelic variants in WARS1 cause a highly variable neurodevelopmental syndrome and implicate a critical exon for normal auditory function,” <i>Human Mutation</i>, vol. 43, no. 10. Wiley, pp. 1472–1489, 2022."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publication_identifier":{"issn":["1059-7794"]},"article_processing_charge":"No","date_created":"2023-09-20T20:58:24Z","oa_version":"Published Version","abstract":[{"text":"Aminoacyl-tRNA synthetases (ARSs) are essential enzymes for faithful assignment of amino acids to their cognate tRNA. Variants in ARS genes are frequently associated with clinically heterogeneous phenotypes in humans and follow both autosomal dominant or recessive inheritance patterns in many instances. Variants in tryptophanyl-tRNA synthetase 1 (WARS1) cause autosomal dominantly inherited distal hereditary motor neuropathy and Charcot-Marie-Tooth disease. Presently, only one family with biallelic WARS1 variants has been described. We present three affected individuals from two families with biallelic variants (p.Met1? and p.(Asp419Asn)) in WARS1, showing varying severities of developmental delay and intellectual disability. Hearing impairment and microcephaly, as well as abnormalities of the brain, skeletal system, movement/gait, and behavior were variable features. Phenotyping of knocked down wars-1 in a Caenorhabditis elegans model showed depletion is associated with defects in germ cell development. A wars1 knockout vertebrate model recapitulates the human clinical phenotypes, confirms variant pathogenicity, and uncovers evidence implicating the p.Met1? variant as potentially impacting an exon critical for normal hearing. Together, our findings provide consolidating evidence for biallelic disruption of WARS1 as causal for an autosomal recessive neurodevelopmental syndrome and present a vertebrate model that recapitulates key phenotypes observed in patients.","lang":"eng"}],"page":"1472-1489","year":"2022","volume":43,"ddc":["570"],"publication_status":"published","date_updated":"2023-09-25T08:54:14Z","month":"10","author":[{"last_name":"Lin","first_name":"Sheng-Jia","full_name":"Lin, Sheng-Jia"},{"last_name":"Vona","full_name":"Vona, Barbara","first_name":"Barbara"},{"last_name":"Porter","first_name":"Hillary M.","full_name":"Porter, Hillary M."},{"first_name":"Mahmoud","full_name":"Izadi, Mahmoud","last_name":"Izadi"},{"last_name":"Huang","id":"3b3d2888-1ff6-11ee-9fa6-8f209ca91fe3","full_name":"Huang, Kevin","orcid":"0000-0002-2512-7812","first_name":"Kevin"},{"last_name":"Lacassie","first_name":"Yves","full_name":"Lacassie, Yves"},{"last_name":"Rosenfeld","first_name":"Jill A.","full_name":"Rosenfeld, Jill A."},{"first_name":"Saadullah","full_name":"Khan, Saadullah","last_name":"Khan"},{"first_name":"Cassidy","full_name":"Petree, Cassidy","last_name":"Petree"},{"full_name":"Ali, Tayyiba A.","first_name":"Tayyiba A.","last_name":"Ali"},{"full_name":"Muhammad, Nazif","first_name":"Nazif","last_name":"Muhammad"},{"full_name":"Khan, Sher A.","first_name":"Sher A.","last_name":"Khan"},{"last_name":"Muhammad","full_name":"Muhammad, Noor","first_name":"Noor"},{"full_name":"Liu, Pengfei","first_name":"Pengfei","last_name":"Liu"},{"last_name":"Haymon","first_name":"Marie-Louise","full_name":"Haymon, Marie-Louise"},{"first_name":"Franz","full_name":"Rueschendorf, Franz","last_name":"Rueschendorf"},{"full_name":"Kong, Il-Keun","first_name":"Il-Keun","last_name":"Kong"},{"last_name":"Schnapp","full_name":"Schnapp, Linda","first_name":"Linda"},{"last_name":"Shur","first_name":"Natasha","full_name":"Shur, Natasha"},{"first_name":"Lynn","full_name":"Chorich, Lynn","last_name":"Chorich"},{"last_name":"Layman","full_name":"Layman, Lawrence","first_name":"Lawrence"},{"last_name":"Haaf","first_name":"Thomas","full_name":"Haaf, Thomas"},{"last_name":"Pourkarimi","first_name":"Ehsan","full_name":"Pourkarimi, Ehsan"},{"full_name":"Kim, Hyung-Goo","first_name":"Hyung-Goo","last_name":"Kim"},{"last_name":"Varshney","full_name":"Varshney, Gaurav K.","first_name":"Gaurav K."}],"_id":"14356","language":[{"iso":"eng"}],"publication":"Human Mutation","extern":"1","article_type":"original","scopus_import":"1","status":"public","file":[{"checksum":"74b01d4e4084b2f64c30ed32b18ee928","file_size":12131312,"date_updated":"2023-09-25T08:52:54Z","success":1,"date_created":"2023-09-25T08:52:54Z","file_id":"14370","creator":"dernst","file_name":"2022_HumanMutation_Lin.pdf","relation":"main_file","access_level":"open_access","content_type":"application/pdf"}],"title":"Biallelic variants in WARS1 cause a highly variable neurodevelopmental syndrome and implicate a critical exon for normal auditory function"},{"page":"1454-1471","abstract":[{"text":"Aminoacylation of transfer RNA (tRNA) is a key step in protein biosynthesis, carried out by highly specific aminoacyl-tRNA synthetases (ARSs). ARSs have been implicated in autosomal dominant and autosomal recessive human disorders. Autosomal dominant variants in tryptophanyl-tRNA synthetase 1 (WARS1) are known to cause distal hereditary motor neuropathy and Charcot-Marie-Tooth disease, but a recessively inherited phenotype is yet to be clearly defined. Seryl-tRNA synthetase 1 (SARS1) has rarely been implicated in an autosomal recessive developmental disorder. Here, we report five individuals with biallelic missense variants in WARS1 or SARS1, who presented with an overlapping phenotype of microcephaly, developmental delay, intellectual disability, and brain anomalies. Structural mapping showed that the SARS1 variant is located directly within the enzyme’s active site, most likely diminishing activity, while the WARS1 variant is located in the N-terminal domain. We further characterize the identified WARS1 variant by showing that it negatively impacts protein abundance and is unable to rescue the phenotype of a CRISPR/Cas9 wars1 knockout zebrafish model. In summary, we describe two overlapping autosomal recessive syndromes caused by variants in WARS1 and SARS1, present functional insights into the pathogenesis of the WARS1-related syndrome and define an emerging disease spectrum: ARS-related developmental disorders with or without microcephaly.","lang":"eng"}],"year":"2022","volume":43,"date_created":"2023-09-20T20:59:33Z","external_id":{"pmid":["35790048"]},"oa_version":"Published Version","publication":"Human Mutation","language":[{"iso":"eng"}],"_id":"14357","file":[{"checksum":"c31fc91e0445c35b9da83eb911a9b552","file_size":4863605,"date_updated":"2023-09-25T08:41:23Z","success":1,"date_created":"2023-09-25T08:41:23Z","creator":"dernst","file_id":"14367","file_name":"2022_HumanMutation_Boegershausen.pdf","content_type":"application/pdf","access_level":"open_access","relation":"main_file"}],"scopus_import":"1","status":"public","title":"WARS1 and SARS1: Two tRNA synthetases implicated in autosomal recessive microcephaly","extern":"1","article_type":"original","publication_status":"published","date_updated":"2023-09-25T08:43:06Z","ddc":["570"],"author":[{"full_name":"Boegershausen, Nina","first_name":"Nina","last_name":"Boegershausen"},{"last_name":"Krawczyk","first_name":"Hannah E.","full_name":"Krawczyk, Hannah E."},{"last_name":"Jamra","first_name":"Rami A.","full_name":"Jamra, Rami A."},{"last_name":"Lin","full_name":"Lin, Sheng-Jia","first_name":"Sheng-Jia"},{"last_name":"Yigit","full_name":"Yigit, Goekhan","first_name":"Goekhan"},{"full_name":"Huening, Irina","first_name":"Irina","last_name":"Huening"},{"last_name":"Polo","first_name":"Anna M.","full_name":"Polo, Anna M."},{"full_name":"Vona, Barbara","first_name":"Barbara","last_name":"Vona"},{"last_name":"Huang","id":"3b3d2888-1ff6-11ee-9fa6-8f209ca91fe3","orcid":"0000-0002-2512-7812","first_name":"Kevin","full_name":"Huang, Kevin"},{"last_name":"Schmidt","first_name":"Julia","full_name":"Schmidt, Julia"},{"last_name":"Altmueller","full_name":"Altmueller, Janine","first_name":"Janine"},{"last_name":"Luppe","full_name":"Luppe, Johannes","first_name":"Johannes"},{"last_name":"Platzer","full_name":"Platzer, Konrad","first_name":"Konrad"},{"first_name":"Beate B.","full_name":"Doergeloh, Beate B.","last_name":"Doergeloh"},{"last_name":"Busche","full_name":"Busche, Andreas","first_name":"Andreas"},{"last_name":"Biskup","full_name":"Biskup, Saskia","first_name":"Saskia"},{"last_name":"Mendes, I","first_name":"Marisa","full_name":"Mendes, I, Marisa"},{"last_name":"Smith","first_name":"Desiree E. C.","full_name":"Smith, Desiree E. C."},{"full_name":"Salomons, Gajja S.","first_name":"Gajja S.","last_name":"Salomons"},{"first_name":"Arne","full_name":"Zibat, Arne","last_name":"Zibat"},{"first_name":"Eva","full_name":"Bueltmann, Eva","last_name":"Bueltmann"},{"first_name":"Peter","full_name":"Nuernberg, Peter","last_name":"Nuernberg"},{"first_name":"Malte","full_name":"Spielmann, Malte","last_name":"Spielmann"},{"last_name":"Lemke","first_name":"Johannes R.","full_name":"Lemke, Johannes R."},{"full_name":"Li, Yun","first_name":"Yun","last_name":"Li"},{"full_name":"Zenker, Martin","first_name":"Martin","last_name":"Zenker"},{"first_name":"Gaurav K.","full_name":"Varshney, Gaurav K.","last_name":"Varshney"},{"last_name":"Hillen","full_name":"Hillen, Hauke S.","first_name":"Hauke S."},{"full_name":"Kratz, Christian P.","first_name":"Christian P.","last_name":"Kratz"},{"last_name":"Wollnik","first_name":"Bernd","full_name":"Wollnik, Bernd"}],"month":"10","pmid":1,"type":"journal_article","file_date_updated":"2023-09-25T08:41:23Z","doi":"10.1002/humu.24430","oa":1,"tmp":{"image":"/images/cc_by_nc_nd.png","legal_code_url":"https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode","short":"CC BY-NC-ND (4.0)","name":"Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0)"},"license":"https://creativecommons.org/licenses/by-nc-nd/4.0/","keyword":["aminoacylation","aminoacyl-tRNA synthetase","ARS","CRISPR","Cas9","intellectual disability","microcephaly","SARS1","tRNA","WARS1","zebrafish"],"has_accepted_license":"1","issue":"10","publisher":"Wiley","citation":{"ama":"Boegershausen N, Krawczyk HE, Jamra RA, et al. WARS1 and SARS1: Two tRNA synthetases implicated in autosomal recessive microcephaly. <i>Human Mutation</i>. 2022;43(10):1454-1471. doi:<a href=\"https://doi.org/10.1002/humu.24430\">10.1002/humu.24430</a>","short":"N. Boegershausen, H.E. Krawczyk, R.A. Jamra, S.-J. Lin, G. Yigit, I. Huening, A.M. Polo, B. Vona, K. Huang, J. Schmidt, J. Altmueller, J. Luppe, K. Platzer, B.B. Doergeloh, A. Busche, S. Biskup, M. Mendes, I, D.E.C. Smith, G.S. Salomons, A. Zibat, E. Bueltmann, P. Nuernberg, M. Spielmann, J.R. Lemke, Y. Li, M. Zenker, G.K. Varshney, H.S. Hillen, C.P. Kratz, B. Wollnik, Human Mutation 43 (2022) 1454–1471.","mla":"Boegershausen, Nina, et al. “WARS1 and SARS1: Two TRNA Synthetases Implicated in Autosomal Recessive Microcephaly.” <i>Human Mutation</i>, vol. 43, no. 10, Wiley, 2022, pp. 1454–71, doi:<a href=\"https://doi.org/10.1002/humu.24430\">10.1002/humu.24430</a>.","ista":"Boegershausen N, Krawczyk HE, Jamra RA, Lin S-J, Yigit G, Huening I, Polo AM, Vona B, Huang K, Schmidt J, Altmueller J, Luppe J, Platzer K, Doergeloh BB, Busche A, Biskup S, Mendes, I M, Smith DEC, Salomons GS, Zibat A, Bueltmann E, Nuernberg P, Spielmann M, Lemke JR, Li Y, Zenker M, Varshney GK, Hillen HS, Kratz CP, Wollnik B. 2022. WARS1 and SARS1: Two tRNA synthetases implicated in autosomal recessive microcephaly. Human Mutation. 43(10), 1454–1471.","chicago":"Boegershausen, Nina, Hannah E. Krawczyk, Rami A. Jamra, Sheng-Jia Lin, Goekhan Yigit, Irina Huening, Anna M. Polo, et al. “WARS1 and SARS1: Two TRNA Synthetases Implicated in Autosomal Recessive Microcephaly.” <i>Human Mutation</i>. Wiley, 2022. <a href=\"https://doi.org/10.1002/humu.24430\">https://doi.org/10.1002/humu.24430</a>.","apa":"Boegershausen, N., Krawczyk, H. E., Jamra, R. A., Lin, S.-J., Yigit, G., Huening, I., … Wollnik, B. (2022). WARS1 and SARS1: Two tRNA synthetases implicated in autosomal recessive microcephaly. <i>Human Mutation</i>. Wiley. <a href=\"https://doi.org/10.1002/humu.24430\">https://doi.org/10.1002/humu.24430</a>","ieee":"N. Boegershausen <i>et al.</i>, “WARS1 and SARS1: Two tRNA synthetases implicated in autosomal recessive microcephaly,” <i>Human Mutation</i>, vol. 43, no. 10. Wiley, pp. 1454–1471, 2022."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","publication_identifier":{"issn":["1059-7794"]},"quality_controlled":"1","day":"01","intvolume":"        43","date_published":"2022-10-01T00:00:00Z"},{"title":"Reversed conductance decay of 1D topological insulators by tight-binding analysis","status":"public","scopus_import":"1","article_type":"original","extern":"1","language":[{"iso":"eng"}],"publication":"The Journal of Physical Chemistry Letters","_id":"17868","author":[{"last_name":"Li","first_name":"Liang","full_name":"Li, Liang"},{"first_name":"Suman","full_name":"Gunasekaran, Suman","last_name":"Gunasekaran"},{"last_name":"Wei","full_name":"Wei, Yujing","first_name":"Yujing"},{"last_name":"Nuckolls","full_name":"Nuckolls, Colin","first_name":"Colin"},{"id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","last_name":"Venkataraman","first_name":"Latha","orcid":"0000-0002-6957-6089","full_name":"Venkataraman, Latha"}],"month":"10","date_updated":"2024-12-10T09:21:49Z","publication_status":"published","OA_type":"green","volume":13,"year":"2022","page":"9703-9710","abstract":[{"lang":"eng","text":"Reversed conductance decay describes increasing conductance of a molecular chain series with increasing chain length. Realizing reversed conductance decay is an important step toward making long and highly conducting molecular wires. Recent work has shown that one-dimensional topological insulators (1D TIs) can exhibit reversed conductance decay due to their nontrivial edge states. The Su–Schrieffer–Heeger (SSH) model for 1D TIs relates to the electronic structure of these isolated molecules but not their electron transport properties as single-molecule junctions. Herein, we use a tight-binding approach to demonstrate that polyacetylene and other diradicaloid 1D TIs show a reversed conductance decay at the short chain limit. We explain these conductance trends by analyzing the impact of the edge states in these 1D systems on the single-molecule junction transmission. Additionally, we discuss how the self-energy from the electrode-molecule coupling and the on-site energy of the edge sites can be tuned to create longer wires with reversed conductance decays."}],"oa_version":"Preprint","external_id":{"pmid":["36219846"]},"date_created":"2024-09-06T13:02:46Z","article_processing_charge":"No","publication_identifier":{"issn":["1948-7185"]},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"mla":"Li, Liang, et al. “Reversed Conductance Decay of 1D Topological Insulators by Tight-Binding Analysis.” <i>The Journal of Physical Chemistry Letters</i>, vol. 13, no. 41, American Chemical Society, 2022, pp. 9703–10, doi:<a href=\"https://doi.org/10.1021/acs.jpclett.2c02812\">10.1021/acs.jpclett.2c02812</a>.","ista":"Li L, Gunasekaran S, Wei Y, Nuckolls C, Venkataraman L. 2022. Reversed conductance decay of 1D topological insulators by tight-binding analysis. The Journal of Physical Chemistry Letters. 13(41), 9703–9710.","chicago":"Li, Liang, Suman Gunasekaran, Yujing Wei, Colin Nuckolls, and Latha Venkataraman. “Reversed Conductance Decay of 1D Topological Insulators by Tight-Binding Analysis.” <i>The Journal of Physical Chemistry Letters</i>. American Chemical Society, 2022. <a href=\"https://doi.org/10.1021/acs.jpclett.2c02812\">https://doi.org/10.1021/acs.jpclett.2c02812</a>.","apa":"Li, L., Gunasekaran, S., Wei, Y., Nuckolls, C., &#38; Venkataraman, L. (2022). Reversed conductance decay of 1D topological insulators by tight-binding analysis. <i>The Journal of Physical Chemistry Letters</i>. American Chemical Society. <a href=\"https://doi.org/10.1021/acs.jpclett.2c02812\">https://doi.org/10.1021/acs.jpclett.2c02812</a>","ieee":"L. Li, S. Gunasekaran, Y. Wei, C. Nuckolls, and L. Venkataraman, “Reversed conductance decay of 1D topological insulators by tight-binding analysis,” <i>The Journal of Physical Chemistry Letters</i>, vol. 13, no. 41. American Chemical Society, pp. 9703–9710, 2022.","ama":"Li L, Gunasekaran S, Wei Y, Nuckolls C, Venkataraman L. Reversed conductance decay of 1D topological insulators by tight-binding analysis. <i>The Journal of Physical Chemistry Letters</i>. 2022;13(41):9703-9710. doi:<a href=\"https://doi.org/10.1021/acs.jpclett.2c02812\">10.1021/acs.jpclett.2c02812</a>","short":"L. Li, S. Gunasekaran, Y. Wei, C. Nuckolls, L. Venkataraman, The Journal of Physical Chemistry Letters 13 (2022) 9703–9710."},"publisher":"American Chemical Society","issue":"41","OA_place":"repository","intvolume":"        13","date_published":"2022-10-11T00:00:00Z","quality_controlled":"1","day":"11","doi":"10.1021/acs.jpclett.2c02812","oa":1,"pmid":1,"type":"journal_article","main_file_link":[{"url":"https://doi.org/10.26434/chemrxiv-2022-b1fh9-v3","open_access":"1"}]},{"issue":"90","publisher":"Royal Society of Chemistry","citation":{"ama":"Orchanian NM, Guizzo S, Steigerwald ML, Nuckolls C, Venkataraman L. Electric-field-induced coupling of aryl iodides with a nickel(0) complex. <i>Chemical Communications</i>. 2022;58(90):12556-12559. doi:<a href=\"https://doi.org/10.1039/d2cc03671a\">10.1039/d2cc03671a</a>","short":"N.M. Orchanian, S. Guizzo, M.L. Steigerwald, C. Nuckolls, L. Venkataraman, Chemical Communications 58 (2022) 12556–12559.","mla":"Orchanian, Nicholas M., et al. “Electric-Field-Induced Coupling of Aryl Iodides with a Nickel(0) Complex.” <i>Chemical Communications</i>, vol. 58, no. 90, Royal Society of Chemistry, 2022, pp. 12556–59, doi:<a href=\"https://doi.org/10.1039/d2cc03671a\">10.1039/d2cc03671a</a>.","ista":"Orchanian NM, Guizzo S, Steigerwald ML, Nuckolls C, Venkataraman L. 2022. Electric-field-induced coupling of aryl iodides with a nickel(0) complex. Chemical Communications. 58(90), 12556–12559.","ieee":"N. M. Orchanian, S. Guizzo, M. L. Steigerwald, C. Nuckolls, and L. Venkataraman, “Electric-field-induced coupling of aryl iodides with a nickel(0) complex,” <i>Chemical Communications</i>, vol. 58, no. 90. Royal Society of Chemistry, pp. 12556–12559, 2022.","apa":"Orchanian, N. M., Guizzo, S., Steigerwald, M. L., Nuckolls, C., &#38; Venkataraman, L. (2022). Electric-field-induced coupling of aryl iodides with a nickel(0) complex. <i>Chemical Communications</i>. Royal Society of Chemistry. <a href=\"https://doi.org/10.1039/d2cc03671a\">https://doi.org/10.1039/d2cc03671a</a>","chicago":"Orchanian, Nicholas M., Sophia Guizzo, Michael L. Steigerwald, Colin Nuckolls, and Latha Venkataraman. “Electric-Field-Induced Coupling of Aryl Iodides with a Nickel(0) Complex.” <i>Chemical Communications</i>. Royal Society of Chemistry, 2022. <a href=\"https://doi.org/10.1039/d2cc03671a\">https://doi.org/10.1039/d2cc03671a</a>."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","article_processing_charge":"No","publication_identifier":{"eissn":["1364-548X"],"issn":["1359-7345"]},"quality_controlled":"1","day":"10","intvolume":"        58","OA_place":"repository","date_published":"2022-10-10T00:00:00Z","pmid":1,"type":"journal_article","main_file_link":[{"url":"https://doi.org/10.26434/chemrxiv-2022-lfnw1","open_access":"1"}],"doi":"10.1039/d2cc03671a","oa":1,"publication":"Chemical Communications","language":[{"iso":"eng"}],"_id":"17869","status":"public","scopus_import":"1","title":"Electric-field-induced coupling of aryl iodides with a nickel(0) complex","extern":"1","article_type":"letter_note","publication_status":"published","date_updated":"2024-12-10T09:27:04Z","OA_type":"green","month":"10","author":[{"first_name":"Nicholas M.","full_name":"Orchanian, Nicholas M.","last_name":"Orchanian"},{"last_name":"Guizzo","full_name":"Guizzo, Sophia","first_name":"Sophia"},{"last_name":"Steigerwald","first_name":"Michael L.","full_name":"Steigerwald, Michael L."},{"full_name":"Nuckolls, Colin","first_name":"Colin","last_name":"Nuckolls"},{"full_name":"Venkataraman, Latha","first_name":"Latha","orcid":"0000-0002-6957-6089","id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","last_name":"Venkataraman"}],"page":"12556-12559","abstract":[{"text":"The formation of carbon–carbon bonds with transition metal reagents serves as a cornerstone of organic synthesis. Here, we show that the reactivity of an otherwise kinetically inert transition metal complex can be induced by an external electric field to affect a coupling reaction. These results highlight the importance of electric field effects in reaction chemistry and offers a new strategy to modulate organometallic reactivity.","lang":"eng"}],"year":"2022","volume":58,"related_material":{"link":[{"url":"https://doi.org/10.1039/d2cc03671a","relation":"erratum"}]},"external_id":{"pmid":["36245392"]},"date_created":"2024-09-06T13:03:38Z","oa_version":"Preprint"},{"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"short":"I.B. Stone, R.L. Starr, N. Hoffmann, X. Wang, A.M. Evans, C. Nuckolls, T.H. Lambert, M.L. Steigerwald, T.C. Berkelbach, X. Roy, L. Venkataraman, Chemical Science 13 (2022) 10798–10805.","ama":"Stone IB, Starr RL, Hoffmann N, et al. Interfacial electric fields catalyze Ullmann coupling reactions on gold surfaces. <i>Chemical Science</i>. 2022;13(36):10798-10805. doi:<a href=\"https://doi.org/10.1039/d2sc03780g\">10.1039/d2sc03780g</a>","apa":"Stone, I. B., Starr, R. L., Hoffmann, N., Wang, X., Evans, A. M., Nuckolls, C., … Venkataraman, L. (2022). Interfacial electric fields catalyze Ullmann coupling reactions on gold surfaces. <i>Chemical Science</i>. Royal Society of Chemistry. <a href=\"https://doi.org/10.1039/d2sc03780g\">https://doi.org/10.1039/d2sc03780g</a>","ieee":"I. B. Stone <i>et al.</i>, “Interfacial electric fields catalyze Ullmann coupling reactions on gold surfaces,” <i>Chemical Science</i>, vol. 13, no. 36. Royal Society of Chemistry, pp. 10798–10805, 2022.","chicago":"Stone, Ilana B., Rachel L. Starr, Norah Hoffmann, Xiao Wang, Austin M. Evans, Colin Nuckolls, Tristan H. Lambert, et al. “Interfacial Electric Fields Catalyze Ullmann Coupling Reactions on Gold Surfaces.” <i>Chemical Science</i>. Royal Society of Chemistry, 2022. <a href=\"https://doi.org/10.1039/d2sc03780g\">https://doi.org/10.1039/d2sc03780g</a>.","ista":"Stone IB, Starr RL, Hoffmann N, Wang X, Evans AM, Nuckolls C, Lambert TH, Steigerwald ML, Berkelbach TC, Roy X, Venkataraman L. 2022. Interfacial electric fields catalyze Ullmann coupling reactions on gold surfaces. Chemical Science. 13(36), 10798–10805.","mla":"Stone, Ilana B., et al. “Interfacial Electric Fields Catalyze Ullmann Coupling Reactions on Gold Surfaces.” <i>Chemical Science</i>, vol. 13, no. 36, Royal Society of Chemistry, 2022, pp. 10798–805, doi:<a href=\"https://doi.org/10.1039/d2sc03780g\">10.1039/d2sc03780g</a>."},"issue":"36","publisher":"Royal Society of Chemistry","publication_identifier":{"issn":["2041-6520"],"eissn":["2041-6539"]},"article_processing_charge":"Yes","DOAJ_listed":"1","day":"01","quality_controlled":"1","date_published":"2022-09-01T00:00:00Z","OA_place":"publisher","intvolume":"        13","main_file_link":[{"url":"https://doi.org/10.1039/D2SC03780G","open_access":"1"}],"type":"journal_article","oa":1,"doi":"10.1039/d2sc03780g","tmp":{"image":"/images/cc_by_nc.png","legal_code_url":"https://creativecommons.org/licenses/by-nc/3.0/legalcode","name":"Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)","short":"CC BY-NC (3.0)"},"license":"https://creativecommons.org/licenses/by-nc/3.0/","_id":"17870","publication":"Chemical Science","language":[{"iso":"eng"}],"article_type":"original","extern":"1","title":"Interfacial electric fields catalyze Ullmann coupling reactions on gold surfaces","scopus_import":"1","status":"public","OA_type":"gold","date_updated":"2024-12-10T09:29:53Z","publication_status":"published","month":"09","author":[{"last_name":"Stone","full_name":"Stone, Ilana B.","first_name":"Ilana B."},{"first_name":"Rachel L.","full_name":"Starr, Rachel L.","last_name":"Starr"},{"first_name":"Norah","full_name":"Hoffmann, Norah","last_name":"Hoffmann"},{"full_name":"Wang, Xiao","first_name":"Xiao","last_name":"Wang"},{"last_name":"Evans","first_name":"Austin M.","full_name":"Evans, Austin M."},{"last_name":"Nuckolls","full_name":"Nuckolls, Colin","first_name":"Colin"},{"first_name":"Tristan H.","full_name":"Lambert, Tristan H.","last_name":"Lambert"},{"last_name":"Steigerwald","first_name":"Michael L.","full_name":"Steigerwald, Michael L."},{"full_name":"Berkelbach, Timothy C.","first_name":"Timothy C.","last_name":"Berkelbach"},{"full_name":"Roy, Xavier","first_name":"Xavier","last_name":"Roy"},{"id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","last_name":"Venkataraman","full_name":"Venkataraman, Latha","first_name":"Latha","orcid":"0000-0002-6957-6089"}],"abstract":[{"text":"The electric fields created at solid–liquid interfaces are important in heterogeneous catalysis. Here we describe the Ullmann coupling of aryl iodides on rough gold surfaces, which we monitor in situ using the scanning tunneling microscope-based break junction (STM-BJ) and ex situ using mass spectrometry and fluorescence spectroscopy. We find that this Ullmann coupling reaction occurs only on rough gold surfaces in polar solvents, the latter of which implicates interfacial electric fields. These experimental observations are supported by density functional theory calculations that elucidate the roles of surface roughness and local electric fields on the reaction. More broadly, this touchstone study offers a facile method to access and probe in real time an increasingly prominent yet incompletely understood mode of catalysis.","lang":"eng"}],"page":"10798-10805","volume":13,"year":"2022","date_created":"2024-09-06T13:04:27Z","oa_version":"Published Version"},{"article_number":"2106629","doi":"10.1002/adma.202106629","oa":1,"type":"journal_article","pmid":1,"main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/2108.09998"}],"OA_place":"repository","intvolume":"        34","date_published":"2022-04-01T00:00:00Z","quality_controlled":"1","arxiv":1,"day":"01","article_processing_charge":"No","publication_identifier":{"issn":["0935-9648","1521-4095"]},"citation":{"ama":"Evers F, Aharony A, Bar‐Gill N, et al. Theory of chirality induced spin selectivity: Progress and challenges. <i>Advanced Materials</i>. 2022;34(13). doi:<a href=\"https://doi.org/10.1002/adma.202106629\">10.1002/adma.202106629</a>","short":"F. Evers, A. Aharony, N. Bar‐Gill, O. Entin‐Wohlman, P. Hedegård, O. Hod, P. Jelinek, G. Kamieniarz, M. Lemeshko, K. Michaeli, V. Mujica, R. Naaman, Y. Paltiel, S. Refaely‐Abramson, O. Tal, J. Thijssen, M. Thoss, J.M. van Ruitenbeek, L. Venkataraman, D.H. Waldeck, B. Yan, L. Kronik, Advanced Materials 34 (2022).","mla":"Evers, Ferdinand, et al. “Theory of Chirality Induced Spin Selectivity: Progress and Challenges.” <i>Advanced Materials</i>, vol. 34, no. 13, 2106629, Wiley, 2022, doi:<a href=\"https://doi.org/10.1002/adma.202106629\">10.1002/adma.202106629</a>.","apa":"Evers, F., Aharony, A., Bar‐Gill, N., Entin‐Wohlman, O., Hedegård, P., Hod, O., … Kronik, L. (2022). Theory of chirality induced spin selectivity: Progress and challenges. <i>Advanced Materials</i>. Wiley. <a href=\"https://doi.org/10.1002/adma.202106629\">https://doi.org/10.1002/adma.202106629</a>","chicago":"Evers, Ferdinand, Amnon Aharony, Nir Bar‐Gill, Ora Entin‐Wohlman, Per Hedegård, Oded Hod, Pavel Jelinek, et al. “Theory of Chirality Induced Spin Selectivity: Progress and Challenges.” <i>Advanced Materials</i>. Wiley, 2022. <a href=\"https://doi.org/10.1002/adma.202106629\">https://doi.org/10.1002/adma.202106629</a>.","ieee":"F. Evers <i>et al.</i>, “Theory of chirality induced spin selectivity: Progress and challenges,” <i>Advanced Materials</i>, vol. 34, no. 13. Wiley, 2022.","ista":"Evers F, Aharony A, Bar‐Gill N, Entin‐Wohlman O, Hedegård P, Hod O, Jelinek P, Kamieniarz G, Lemeshko M, Michaeli K, Mujica V, Naaman R, Paltiel Y, Refaely‐Abramson S, Tal O, Thijssen J, Thoss M, van Ruitenbeek JM, Venkataraman L, Waldeck DH, Yan B, Kronik L. 2022. Theory of chirality induced spin selectivity: Progress and challenges. Advanced Materials. 34(13), 2106629."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","issue":"13","publisher":"Wiley","oa_version":"Preprint","external_id":{"arxiv":["2108.09998"],"pmid":["35064943"]},"date_created":"2024-09-06T13:07:43Z","volume":34,"year":"2022","abstract":[{"text":"<jats:title>Abstract</jats:title><jats:p>A critical overview of the theory of the chirality‐induced spin selectivity (CISS) effect, that is, phenomena in which the chirality of molecular species imparts significant spin selectivity to various electron processes, is provided. Based on discussions in a recently held workshop, and further work published since, the status of CISS effects—in electron transmission, electron transport, and chemical reactions—is reviewed. For each, a detailed discussion of the state‐of‐the‐art in theoretical understanding is provided and remaining challenges and research opportunities are identified.</jats:p>","lang":"eng"}],"month":"04","author":[{"full_name":"Evers, Ferdinand","first_name":"Ferdinand","last_name":"Evers"},{"last_name":"Aharony","first_name":"Amnon","full_name":"Aharony, Amnon"},{"full_name":"Bar‐Gill, Nir","first_name":"Nir","last_name":"Bar‐Gill"},{"last_name":"Entin‐Wohlman","first_name":"Ora","full_name":"Entin‐Wohlman, Ora"},{"last_name":"Hedegård","first_name":"Per","full_name":"Hedegård, Per"},{"last_name":"Hod","full_name":"Hod, Oded","first_name":"Oded"},{"first_name":"Pavel","full_name":"Jelinek, Pavel","last_name":"Jelinek"},{"full_name":"Kamieniarz, Grzegorz","first_name":"Grzegorz","last_name":"Kamieniarz"},{"first_name":"Mikhail","full_name":"Lemeshko, Mikhail","last_name":"Lemeshko"},{"last_name":"Michaeli","first_name":"Karen","full_name":"Michaeli, Karen"},{"last_name":"Mujica","first_name":"Vladimiro","full_name":"Mujica, Vladimiro"},{"last_name":"Naaman","first_name":"Ron","full_name":"Naaman, Ron"},{"last_name":"Paltiel","first_name":"Yossi","full_name":"Paltiel, Yossi"},{"last_name":"Refaely‐Abramson","full_name":"Refaely‐Abramson, Sivan","first_name":"Sivan"},{"full_name":"Tal, Oren","first_name":"Oren","last_name":"Tal"},{"last_name":"Thijssen","first_name":"Jos","full_name":"Thijssen, Jos"},{"last_name":"Thoss","first_name":"Michael","full_name":"Thoss, Michael"},{"last_name":"van Ruitenbeek","first_name":"Jan M.","full_name":"van Ruitenbeek, Jan M."},{"orcid":"0000-0002-6957-6089","first_name":"Latha","full_name":"Venkataraman, Latha","last_name":"Venkataraman","id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf"},{"first_name":"David H.","full_name":"Waldeck, David H.","last_name":"Waldeck"},{"first_name":"Binghai","full_name":"Yan, Binghai","last_name":"Yan"},{"last_name":"Kronik","full_name":"Kronik, Leeor","first_name":"Leeor"}],"date_updated":"2024-12-10T09:43:10Z","publication_status":"published","OA_type":"green","title":"Theory of chirality induced spin selectivity: Progress and challenges","scopus_import":"1","status":"public","article_type":"review","extern":"1","publication":"Advanced Materials","language":[{"iso":"eng"}],"_id":"17873"},{"year":"2022","volume":13,"abstract":[{"lang":"eng","text":"Redox-active two-dimensional polymers (RA-2DPs) are promising lithium battery organic cathode materials due to their regular porosities and high chemical stabilities. However, weak electrical conductivities inherent to the non-conjugated molecular motifs used thus far limit device performance and the practical relevance of these materials. We herein address this problem by developing a modular approach to construct π-conjugated RA-2DPs with a new polycyclic aromatic redox-active building block PDI-DA. Efficient imine-condensation between PDI-DA and two polyfunctional amine nodes followed by quantitative alkyl chain removal produced RA-2DPs TAPPy-PDI and TAPB-PDI as conjugated, porous, polycrystalline networks. In-plane conjugation and permanent porosity endow these materials with high electrical conductivity and high ion diffusion rates. As such, both RA-2DPs function as organic cathode materials with good rate performance and excellent cycling stability. Importantly, the improved design enables higher areal mass-loadings than were previously available, which drives a practical demonstration of TAPPy-PDI as the power source for a series of LED lights. Collectively, this investigation discloses viable synthetic methodologies and design principles for the realization of high-performance organic cathode materials."}],"page":"3533-3538","oa_version":"Published Version","date_created":"2024-09-06T13:08:38Z","extern":"1","article_type":"original","scopus_import":"1","status":"public","title":"π-Conjugated redox-active two-dimensional polymers as organic cathode materials","_id":"17874","language":[{"iso":"eng"}],"publication":"Chemical Science","month":"03","author":[{"full_name":"Jin, Zexin","first_name":"Zexin","last_name":"Jin"},{"last_name":"Cheng","first_name":"Qian","full_name":"Cheng, Qian"},{"full_name":"Evans, Austin M.","first_name":"Austin M.","last_name":"Evans"},{"last_name":"Gray","full_name":"Gray, Jesse","first_name":"Jesse"},{"last_name":"Zhang","first_name":"Ruiwen","full_name":"Zhang, Ruiwen"},{"first_name":"Si Tong","full_name":"Bao, Si Tong","last_name":"Bao"},{"first_name":"Fengkai","full_name":"Wei, Fengkai","last_name":"Wei"},{"id":"9ebb78a5-cc0d-11ee-8322-fae086a32caf","last_name":"Venkataraman","full_name":"Venkataraman, Latha","first_name":"Latha","orcid":"0000-0002-6957-6089"},{"first_name":"Yuan","full_name":"Yang, Yuan","last_name":"Yang"},{"first_name":"Colin","full_name":"Nuckolls, Colin","last_name":"Nuckolls"}],"OA_type":"gold","publication_status":"published","date_updated":"2024-12-10T09:54:17Z","oa":1,"doi":"10.1039/d1sc07157b","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1039/D1SC07157B"}],"type":"journal_article","tmp":{"image":"/images/cc_by_nc.png","legal_code_url":"https://creativecommons.org/licenses/by-nc/3.0/legalcode","name":"Creative Commons Attribution-NonCommercial 3.0 Unported (CC BY-NC 3.0)","short":"CC BY-NC (3.0)"},"publication_identifier":{"eissn":["2041-6539"],"issn":["2041-6520"]},"article_processing_charge":"Yes","publisher":"Royal Society of Chemistry","issue":"12","citation":{"ama":"Jin Z, Cheng Q, Evans AM, et al. π-Conjugated redox-active two-dimensional polymers as organic cathode materials. <i>Chemical Science</i>. 2022;13(12):3533-3538. doi:<a href=\"https://doi.org/10.1039/d1sc07157b\">10.1039/d1sc07157b</a>","short":"Z. Jin, Q. Cheng, A.M. Evans, J. Gray, R. Zhang, S.T. Bao, F. Wei, L. Venkataraman, Y. Yang, C. Nuckolls, Chemical Science 13 (2022) 3533–3538.","mla":"Jin, Zexin, et al. “π-Conjugated Redox-Active Two-Dimensional Polymers as Organic Cathode Materials.” <i>Chemical Science</i>, vol. 13, no. 12, Royal Society of Chemistry, 2022, pp. 3533–38, doi:<a href=\"https://doi.org/10.1039/d1sc07157b\">10.1039/d1sc07157b</a>.","apa":"Jin, Z., Cheng, Q., Evans, A. M., Gray, J., Zhang, R., Bao, S. T., … Nuckolls, C. (2022). π-Conjugated redox-active two-dimensional polymers as organic cathode materials. <i>Chemical Science</i>. Royal Society of Chemistry. <a href=\"https://doi.org/10.1039/d1sc07157b\">https://doi.org/10.1039/d1sc07157b</a>","chicago":"Jin, Zexin, Qian Cheng, Austin M. Evans, Jesse Gray, Ruiwen Zhang, Si Tong Bao, Fengkai Wei, Latha Venkataraman, Yuan Yang, and Colin Nuckolls. “π-Conjugated Redox-Active Two-Dimensional Polymers as Organic Cathode Materials.” <i>Chemical Science</i>. Royal Society of Chemistry, 2022. <a href=\"https://doi.org/10.1039/d1sc07157b\">https://doi.org/10.1039/d1sc07157b</a>.","ieee":"Z. Jin <i>et al.</i>, “π-Conjugated redox-active two-dimensional polymers as organic cathode materials,” <i>Chemical Science</i>, vol. 13, no. 12. Royal Society of Chemistry, pp. 3533–3538, 2022.","ista":"Jin Z, Cheng Q, Evans AM, Gray J, Zhang R, Bao ST, Wei F, Venkataraman L, Yang Y, Nuckolls C. 2022. π-Conjugated redox-active two-dimensional polymers as organic cathode materials. Chemical Science. 13(12), 3533–3538."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_published":"2022-03-08T00:00:00Z","intvolume":"        13","OA_place":"publisher","day":"08","DOAJ_listed":"1","quality_controlled":"1"},{"extern":"1","article_type":"original","scopus_import":"1","status":"public","title":"Scalable Hamiltonian learning for large-scale out-of-equilibrium quantum dynamics","_id":"18191","publication":"Physical Review A","language":[{"iso":"eng"}],"month":"02","author":[{"first_name":"Agnes","full_name":"Valenti, Agnes","last_name":"Valenti"},{"last_name":"Jin","full_name":"Jin, Guliuxin","first_name":"Guliuxin"},{"last_name":"Leonard","id":"b75b3f45-7995-11ef-9bfd-9a9cd02c3577","full_name":"Leonard, Julian","first_name":"Julian"},{"last_name":"Huber","first_name":"Sebastian D.","full_name":"Huber, Sebastian D."},{"full_name":"Greplova, Eliska","first_name":"Eliska","last_name":"Greplova"}],"publication_status":"published","date_updated":"2024-10-08T10:00:23Z","year":"2022","volume":105,"abstract":[{"text":"Large-scale quantum devices provide insights beyond the reach of classical simulations. However, for a reliable and verifiable quantum simulation, the building blocks of the quantum device require exquisite benchmarking. This benchmarking of large-scale dynamical quantum systems represents a major challenge due to lack of efficient tools for their simulation. Here, we present a scalable algorithm based on neural networks for Hamiltonian tomography in out-of-equilibrium quantum systems. We illustrate our approach using a model for a forefront quantum simulation platform: ultracold atoms in optical lattices. Specifically, we show that our algorithm is able to reconstruct the Hamiltonian of an arbitrary sized bosonic ladder system using an accessible amount of experimental measurements. We are able to significantly increase the previously known parameter precision.","lang":"eng"}],"oa_version":"Preprint","external_id":{"arxiv":["2103.01240"]},"date_created":"2024-10-07T11:46:53Z","publication_identifier":{"issn":["2469-9926"],"eissn":["2469-9934"]},"article_processing_charge":"No","issue":"2","publisher":"American Physical Society","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"mla":"Valenti, Agnes, et al. “Scalable Hamiltonian Learning for Large-Scale out-of-Equilibrium Quantum Dynamics.” <i>Physical Review A</i>, vol. 105, no. 2, 023302, American Physical Society, 2022, doi:<a href=\"https://doi.org/10.1103/physreva.105.023302\">10.1103/physreva.105.023302</a>.","ista":"Valenti A, Jin G, Leonard J, Huber SD, Greplova E. 2022. Scalable Hamiltonian learning for large-scale out-of-equilibrium quantum dynamics. Physical Review A. 105(2), 023302.","apa":"Valenti, A., Jin, G., Leonard, J., Huber, S. D., &#38; Greplova, E. (2022). Scalable Hamiltonian learning for large-scale out-of-equilibrium quantum dynamics. <i>Physical Review A</i>. American Physical Society. <a href=\"https://doi.org/10.1103/physreva.105.023302\">https://doi.org/10.1103/physreva.105.023302</a>","chicago":"Valenti, Agnes, Guliuxin Jin, Julian Leonard, Sebastian D. Huber, and Eliska Greplova. “Scalable Hamiltonian Learning for Large-Scale out-of-Equilibrium Quantum Dynamics.” <i>Physical Review A</i>. American Physical Society, 2022. <a href=\"https://doi.org/10.1103/physreva.105.023302\">https://doi.org/10.1103/physreva.105.023302</a>.","ieee":"A. Valenti, G. Jin, J. Leonard, S. D. Huber, and E. Greplova, “Scalable Hamiltonian learning for large-scale out-of-equilibrium quantum dynamics,” <i>Physical Review A</i>, vol. 105, no. 2. American Physical Society, 2022.","ama":"Valenti A, Jin G, Leonard J, Huber SD, Greplova E. Scalable Hamiltonian learning for large-scale out-of-equilibrium quantum dynamics. <i>Physical Review A</i>. 2022;105(2). doi:<a href=\"https://doi.org/10.1103/physreva.105.023302\">10.1103/physreva.105.023302</a>","short":"A. Valenti, G. Jin, J. Leonard, S.D. Huber, E. Greplova, Physical Review A 105 (2022)."},"date_published":"2022-02-01T00:00:00Z","intvolume":"       105","day":"01","arxiv":1,"quality_controlled":"1","oa":1,"doi":"10.1103/physreva.105.023302","main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2103.01240","open_access":"1"}],"type":"journal_article","article_number":"023302"},{"author":[{"last_name":"Ackerman-Schraier","full_name":"Ackerman-Schraier, Linor","first_name":"Linor"},{"last_name":"Rosenberg","first_name":"Aviv A.","full_name":"Rosenberg, Aviv A."},{"full_name":"Marx, Ailie","first_name":"Ailie","last_name":"Marx"},{"last_name":"Bronstein","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","orcid":"0000-0001-9699-8730","first_name":"Alexander","full_name":"Bronstein, Alexander"}],"month":"12","OA_type":"gold","date_updated":"2024-10-14T09:46:06Z","publication_status":"published","article_type":"original","extern":"1","title":"Machine learning approaches demonstrate that protein structures carry information about their genetic coding","status":"public","scopus_import":"1","_id":"18220","publication":"Scientific Reports","language":[{"iso":"eng"}],"oa_version":"Published Version","external_id":{"pmid":["36539476"]},"date_created":"2024-10-08T12:52:29Z","volume":12,"year":"2022","abstract":[{"lang":"eng","text":"Synonymous codons translate into the same amino acid. Although the identity of synonymous codons is often considered inconsequential to the final protein structure, there is mounting evidence for an association between the two. Our study examined this association using regression and classification models, finding that codon sequences predict protein backbone dihedral angles with a lower error than amino acid sequences, and that models trained with true dihedral angles have better classification of synonymous codons given structural information than models trained with random dihedral angles. Using this classification approach, we investigated local codon–codon dependencies and tested whether synonymous codon identity can be predicted more accurately from codon context than amino acid context alone, and most specifically which codon context position carries the most predictive power."}],"date_published":"2022-12-20T00:00:00Z","OA_place":"publisher","intvolume":"        12","DOAJ_listed":"1","day":"20","quality_controlled":"1","publication_identifier":{"issn":["2045-2322"]},"article_processing_charge":"Yes","citation":{"ama":"Ackerman-Schraier L, Rosenberg AA, Marx A, Bronstein AM. Machine learning approaches demonstrate that protein structures carry information about their genetic coding. <i>Scientific Reports</i>. 2022;12. doi:<a href=\"https://doi.org/10.1038/s41598-022-25874-z\">10.1038/s41598-022-25874-z</a>","short":"L. Ackerman-Schraier, A.A. Rosenberg, A. Marx, A.M. Bronstein, Scientific Reports 12 (2022).","mla":"Ackerman-Schraier, Linor, et al. “Machine Learning Approaches Demonstrate That Protein Structures Carry Information about Their Genetic Coding.” <i>Scientific Reports</i>, vol. 12, 21968, Springer Nature, 2022, doi:<a href=\"https://doi.org/10.1038/s41598-022-25874-z\">10.1038/s41598-022-25874-z</a>.","apa":"Ackerman-Schraier, L., Rosenberg, A. A., Marx, A., &#38; Bronstein, A. M. (2022). Machine learning approaches demonstrate that protein structures carry information about their genetic coding. <i>Scientific Reports</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41598-022-25874-z\">https://doi.org/10.1038/s41598-022-25874-z</a>","chicago":"Ackerman-Schraier, Linor, Aviv A. Rosenberg, Ailie Marx, and Alex M. Bronstein. “Machine Learning Approaches Demonstrate That Protein Structures Carry Information about Their Genetic Coding.” <i>Scientific Reports</i>. Springer Nature, 2022. <a href=\"https://doi.org/10.1038/s41598-022-25874-z\">https://doi.org/10.1038/s41598-022-25874-z</a>.","ieee":"L. Ackerman-Schraier, A. A. Rosenberg, A. Marx, and A. M. Bronstein, “Machine learning approaches demonstrate that protein structures carry information about their genetic coding,” <i>Scientific Reports</i>, vol. 12. Springer Nature, 2022.","ista":"Ackerman-Schraier L, Rosenberg AA, Marx A, Bronstein AM. 2022. Machine learning approaches demonstrate that protein structures carry information about their genetic coding. Scientific Reports. 12, 21968."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","publisher":"Springer Nature","article_number":"21968","oa":1,"doi":"10.1038/s41598-022-25874-z","main_file_link":[{"url":"https://doi.org/10.1038/s41598-022-25874-z","open_access":"1"}],"pmid":1,"type":"journal_article"},{"year":"2022","volume":13,"abstract":[{"lang":"eng","text":"Synonymous codons translate into chemically identical amino acids. Once considered inconsequential to the formation of the protein product, there is evidence to suggest that codon usage affects co-translational protein folding and the final structure of the expressed protein. Here we develop a method for computing and comparing codon-specific Ramachandran plots and demonstrate that the backbone dihedral angle distributions of some synonymous codons are distinguishable with statistical significance for some secondary structures. This shows that there exists a dependence between codon identity and backbone torsion of the translated amino acid. Although these findings cannot pinpoint the causal direction of this dependence, we discuss the vast biological implications should coding be shown to directly shape protein conformation and demonstrate the usefulness of this method as a tool for probing associations between codon usage and protein structure. Finally, we urge for the inclusion of exact genetic information into structural databases."}],"oa_version":"Published Version","date_created":"2024-10-08T12:53:01Z","external_id":{"pmid":["35595777"]},"extern":"1","article_type":"original","scopus_import":"1","status":"public","title":"Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon","_id":"18221","publication":"Nature Communications","language":[{"iso":"eng"}],"author":[{"full_name":"Rosenberg, Aviv A.","first_name":"Aviv A.","last_name":"Rosenberg"},{"full_name":"Marx, Ailie","first_name":"Ailie","last_name":"Marx"},{"orcid":"0000-0001-9699-8730","first_name":"Alexander","full_name":"Bronstein, Alexander","last_name":"Bronstein","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6"}],"month":"05","OA_type":"gold","publication_status":"published","date_updated":"2024-10-14T09:49:02Z","oa":1,"doi":"10.1038/s41467-022-30390-9","main_file_link":[{"url":"https://doi.org/10.1038/s41467-022-30390-9","open_access":"1"}],"type":"journal_article","pmid":1,"article_number":"2815","publication_identifier":{"issn":["2041-1723"]},"article_processing_charge":"Yes","publisher":"Springer Nature","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","citation":{"ista":"Rosenberg AA, Marx A, Bronstein AM. 2022. Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon. Nature Communications. 13, 2815.","chicago":"Rosenberg, Aviv A., Ailie Marx, and Alex M. Bronstein. “Codon-Specific Ramachandran Plots Show Amino Acid Backbone Conformation Depends on Identity of the Translated Codon.” <i>Nature Communications</i>. Springer Nature, 2022. <a href=\"https://doi.org/10.1038/s41467-022-30390-9\">https://doi.org/10.1038/s41467-022-30390-9</a>.","apa":"Rosenberg, A. A., Marx, A., &#38; Bronstein, A. M. (2022). Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon. <i>Nature Communications</i>. Springer Nature. <a href=\"https://doi.org/10.1038/s41467-022-30390-9\">https://doi.org/10.1038/s41467-022-30390-9</a>","ieee":"A. A. Rosenberg, A. Marx, and A. M. Bronstein, “Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon,” <i>Nature Communications</i>, vol. 13. Springer Nature, 2022.","mla":"Rosenberg, Aviv A., et al. “Codon-Specific Ramachandran Plots Show Amino Acid Backbone Conformation Depends on Identity of the Translated Codon.” <i>Nature Communications</i>, vol. 13, 2815, Springer Nature, 2022, doi:<a href=\"https://doi.org/10.1038/s41467-022-30390-9\">10.1038/s41467-022-30390-9</a>.","short":"A.A. Rosenberg, A. Marx, A.M. Bronstein, Nature Communications 13 (2022).","ama":"Rosenberg AA, Marx A, Bronstein AM. Codon-specific Ramachandran plots show amino acid backbone conformation depends on identity of the translated codon. <i>Nature Communications</i>. 2022;13. doi:<a href=\"https://doi.org/10.1038/s41467-022-30390-9\">10.1038/s41467-022-30390-9</a>"},"date_published":"2022-05-20T00:00:00Z","intvolume":"        13","OA_place":"publisher","DOAJ_listed":"1","day":"20","quality_controlled":"1"},{"type":"journal_article","main_file_link":[{"open_access":"1","url":"https://doi.org/10.1093/humrep/deac171"}],"doi":"10.1093/humrep/deac171","oa":1,"quality_controlled":"1","day":"01","OA_place":"publisher","intvolume":"        37","date_published":"2022-10-01T00:00:00Z","citation":{"ama":"Fordham DE, Rosentraub D, Polsky AL, et al. Embryologist agreement when assessing blastocyst implantation probability: Is data-driven prediction the solution to embryo assessment subjectivity? <i>Human Reproduction</i>. 2022;37(10):2275-2290. doi:<a href=\"https://doi.org/10.1093/humrep/deac171\">10.1093/humrep/deac171</a>","short":"D.E. Fordham, D. Rosentraub, A.L. Polsky, T. Aviram, Y. Wolf, O. Perl, A. Devir, S. Rosentraub, D.H. Silver, Y. Gold Zamir, A.M. Bronstein, M. Lara Lara, J. Ben Nagi, A. Alvarez, S. Munné, Human Reproduction 37 (2022) 2275–2290.","mla":"Fordham, Daniel E., et al. “Embryologist Agreement When Assessing Blastocyst Implantation Probability: Is Data-Driven Prediction the Solution to Embryo Assessment Subjectivity?” <i>Human Reproduction</i>, vol. 37, no. 10, Oxford University Press, 2022, pp. 2275–90, doi:<a href=\"https://doi.org/10.1093/humrep/deac171\">10.1093/humrep/deac171</a>.","ista":"Fordham DE, Rosentraub D, Polsky AL, Aviram T, Wolf Y, Perl O, Devir A, Rosentraub S, Silver DH, Gold Zamir Y, Bronstein AM, Lara Lara M, Ben Nagi J, Alvarez A, Munné S. 2022. Embryologist agreement when assessing blastocyst implantation probability: Is data-driven prediction the solution to embryo assessment subjectivity? Human Reproduction. 37(10), 2275–2290.","apa":"Fordham, D. E., Rosentraub, D., Polsky, A. L., Aviram, T., Wolf, Y., Perl, O., … Munné, S. (2022). Embryologist agreement when assessing blastocyst implantation probability: Is data-driven prediction the solution to embryo assessment subjectivity? <i>Human Reproduction</i>. Oxford University Press. <a href=\"https://doi.org/10.1093/humrep/deac171\">https://doi.org/10.1093/humrep/deac171</a>","chicago":"Fordham, Daniel E, Dror Rosentraub, Avital L Polsky, Talia Aviram, Yotam Wolf, Oriel Perl, Asnat Devir, et al. “Embryologist Agreement When Assessing Blastocyst Implantation Probability: Is Data-Driven Prediction the Solution to Embryo Assessment Subjectivity?” <i>Human Reproduction</i>. Oxford University Press, 2022. <a href=\"https://doi.org/10.1093/humrep/deac171\">https://doi.org/10.1093/humrep/deac171</a>.","ieee":"D. E. Fordham <i>et al.</i>, “Embryologist agreement when assessing blastocyst implantation probability: Is data-driven prediction the solution to embryo assessment subjectivity?,” <i>Human Reproduction</i>, vol. 37, no. 10. Oxford University Press, pp. 2275–2290, 2022."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","issue":"10","publisher":"Oxford University Press","article_processing_charge":"No","publication_identifier":{"issn":["0268-1161"],"eissn":["1460-2350"]},"date_created":"2024-10-08T12:53:20Z","oa_version":"Published Version","page":"2275-2290","abstract":[{"lang":"eng","text":"STUDY QUESTION: What is the accuracy and agreement of embryologists when assessing the implantation probability of blastocysts using time-lapse imaging (TLI), and can it be improved with a data-driven algorithm?\r\n\r\nSUMMARY ANSWER: The overall interobserver agreement of a large panel of embryologists was moderate and prediction accuracy was modest, while the purpose-built artificial intelligence model generally resulted in higher performance metrics.\r\n\r\nWHAT IS KNOWN ALREADY: Previous studies have demonstrated significant interobserver variability amongst embryologists when assessing embryo quality. However, data concerning embryologists’ ability to predict implantation probability using TLI is still lacking. Emerging technologies based on data-driven tools have shown great promise for improving embryo selection and predicting clinical outcomes.\r\n\r\nSTUDY DESIGN, SIZE, DURATION: TLI video files of 136 embryos with known implantation data were retrospectively collected from two clinical sites between 2018 and 2019 for the performance assessment of 36 embryologists and comparison with a deep neural network (DNN).\r\n\r\nPARTICIPANTS/MATERIALS, SETTING, METHODS: We recruited 39 embryologists from 13 different countries. All participants were blinded to clinical outcomes. A total of 136 TLI videos of embryos that reached the blastocyst stage were used for this experiment. Each embryo’s likelihood of successfully implanting was assessed by 36 embryologists, providing implantation probability grades (IPGs) from 1 to 5, where 1 indicates a very low likelihood of implantation and 5 indicates a very high likelihood. Subsequently, three embryologists with over 5 years of experience provided Gardner scores. All 136 blastocysts were categorized into three quality groups based on their Gardner scores. Embryologist predictions were then converted into predictions of implantation (IPG ≥ 3) and no implantation (IPG ≤ 2). Embryologists’ performance and agreement were assessed using Fleiss kappa coefficient. A 10-fold cross-validation DNN was developed to provide IPGs for TLI video files. The model’s performance was compared to that of the embryologists.\r\n\r\nMAIN RESULTS AND THE ROLE OF CHANCE: Logistic regression was employed for the following confounding variables: country of residence, academic level, embryo scoring system, log years of experience and experience using TLI. None were found to have a statistically significant impact on embryologist performance at α = 0.05. The average implantation prediction accuracy for the embryologists was 51.9% for all embryos (N = 136). The average accuracy of the embryologists when assessing top quality and poor quality embryos (according to the Gardner score categorizations) was 57.5% and 57.4%, respectively, and 44.6% for fair quality embryos. Overall interobserver agreement was moderate (κ = 0.56, N = 136). The best agreement was achieved in the poor + top quality group (κ = 0.65, N = 77), while the agreement in the fair quality group was lower (κ = 0.25, N = 59). The DNN showed an overall accuracy rate of 62.5%, with accuracies of 62.2%, 61% and 65.6% for the poor, fair and top quality groups, respectively. The AUC for the DNN was higher than that of the embryologists overall (0.70 DNN vs 0.61 embryologists) as well as in all of the Gardner groups (DNN vs embryologists—Poor: 0.69 vs 0.62; Fair: 0.67 vs 0.53; Top: 0.77 vs 0.54).\r\n\r\nLIMITATIONS, REASONS FOR CAUTION: Blastocyst assessment was performed using video files acquired from time-lapse incubators, where each video contained data from a single focal plane. Clinical data regarding the underlying cause of infertility and endometrial thickness before the transfer was not available, yet may explain implantation failure and lower accuracy of IPGs. Implantation was defined as the presence of a gestational sac, whereas the detection of fetal heartbeat is a more robust marker of embryo viability. The raw data were anonymized to the extent that it was not possible to quantify the number of unique patients and cycles included in the study, potentially masking the effect of bias from a limited patient pool. Furthermore, the lack of demographic data makes it difficult to draw conclusions on how representative the dataset was of the wider population. Finally, embryologists were required to assess the implantation potential, not embryo quality. Although this is not the traditional approach to embryo evaluation, morphology/morphokinetics as a means of assessing embryo quality is believed to be strongly correlated with viability and, for some methods, implantation potential.\r\n\r\nWIDER IMPLICATIONS OF THE FINDINGS: Embryo selection is a key element in IVF success and continues to be a challenge. Improving the predictive ability could assist in optimizing implantation success rates and other clinical outcomes and could minimize the financial and emotional burden on the patient. This study demonstrates moderate agreement rates between embryologists, likely due to the subjective nature of embryo assessment. In particular, we found that average embryologist accuracy and agreement were significantly lower for fair quality embryos when compared with that for top and poor quality embryos. Using data-driven algorithms as an assistive tool may help IVF professionals increase success rates and promote much needed standardization in the IVF clinic. Our results indicate a need for further research regarding technological advancement in this field."}],"volume":37,"year":"2022","date_updated":"2024-10-14T09:54:40Z","publication_status":"published","OA_type":"free access","author":[{"first_name":"Daniel E","full_name":"Fordham, Daniel E","last_name":"Fordham"},{"full_name":"Rosentraub, Dror","first_name":"Dror","last_name":"Rosentraub"},{"full_name":"Polsky, Avital L","first_name":"Avital L","last_name":"Polsky"},{"first_name":"Talia","full_name":"Aviram, Talia","last_name":"Aviram"},{"full_name":"Wolf, Yotam","first_name":"Yotam","last_name":"Wolf"},{"last_name":"Perl","full_name":"Perl, Oriel","first_name":"Oriel"},{"full_name":"Devir, Asnat","first_name":"Asnat","last_name":"Devir"},{"first_name":"Shahar","full_name":"Rosentraub, Shahar","last_name":"Rosentraub"},{"last_name":"Silver","first_name":"David H","full_name":"Silver, David H"},{"first_name":"Yael","full_name":"Gold Zamir, Yael","last_name":"Gold Zamir"},{"last_name":"Bronstein","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","full_name":"Bronstein, Alexander","orcid":"0000-0001-9699-8730","first_name":"Alexander"},{"full_name":"Lara Lara, Miguel","first_name":"Miguel","last_name":"Lara Lara"},{"last_name":"Ben Nagi","first_name":"Jara","full_name":"Ben Nagi, Jara"},{"last_name":"Alvarez","first_name":"Adrian","full_name":"Alvarez, Adrian"},{"last_name":"Munné","first_name":"Santiago","full_name":"Munné, Santiago"}],"month":"10","publication":"Human Reproduction","language":[{"iso":"eng"}],"_id":"18222","title":"Embryologist agreement when assessing blastocyst implantation probability: Is data-driven prediction the solution to embryo assessment subjectivity?","scopus_import":"1","status":"public","article_type":"original","extern":"1"},{"status":"public","scopus_import":"1","title":"Baby steps towards few-shot learning with multiple semantics","extern":"1","article_type":"original","language":[{"iso":"eng"}],"publication":"Pattern Recognition Letters","_id":"18224","author":[{"last_name":"Schwartz","full_name":"Schwartz, Eli","first_name":"Eli"},{"full_name":"Karlinsky, Leonid","first_name":"Leonid","last_name":"Karlinsky"},{"last_name":"Feris","first_name":"Rogerio","full_name":"Feris, Rogerio"},{"full_name":"Giryes, Raja","first_name":"Raja","last_name":"Giryes"},{"orcid":"0000-0001-9699-8730","first_name":"Alexander","full_name":"Bronstein, Alexander","last_name":"Bronstein","id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6"}],"month":"08","publication_status":"published","date_updated":"2024-10-14T10:58:20Z","year":"2022","volume":160,"page":"142-147","abstract":[{"text":"Learning from one or few visual examples is one of the key capabilities of humans since early infancy, but is still a significant challenge for modern AI systems. While considerable progress has been achieved in few-shot learning from a few image examples, much less attention has been given to the verbal descriptions that are usually provided to infants when they are presented with a new object. In this paper, we focus on the role of additional semantics that can significantly facilitate few-shot visual learning. Building upon recent advances in few-shot learning with additional semantic information, we demonstrate that further improvements are possible by combining multiple and richer semantics (category labels, attributes, and natural language descriptions). Using these ideas, we offer the community new results on the popular miniImageNet and CUB few-shot benchmarks, comparing favorably to the previous state-of-the-art results for both visual only and visual plus semantics-based approaches. We also performed an ablation study investigating the components and design choices of our approach. Code available on github.com/EliSchwartz/mutiple-semantics.","lang":"eng"}],"oa_version":"Preprint","external_id":{"arxiv":["1906.01905"]},"date_created":"2024-10-08T12:54:03Z","article_processing_charge":"No","publication_identifier":{"issn":["0167-8655"]},"publisher":"Elsevier","citation":{"short":"E. Schwartz, L. Karlinsky, R. Feris, R. Giryes, A.M. Bronstein, Pattern Recognition Letters 160 (2022) 142–147.","ama":"Schwartz E, Karlinsky L, Feris R, Giryes R, Bronstein AM. Baby steps towards few-shot learning with multiple semantics. <i>Pattern Recognition Letters</i>. 2022;160:142-147. doi:<a href=\"https://doi.org/10.1016/j.patrec.2022.06.012\">10.1016/j.patrec.2022.06.012</a>","ista":"Schwartz E, Karlinsky L, Feris R, Giryes R, Bronstein AM. 2022. Baby steps towards few-shot learning with multiple semantics. Pattern Recognition Letters. 160, 142–147.","chicago":"Schwartz, Eli, Leonid Karlinsky, Rogerio Feris, Raja Giryes, and Alex M. Bronstein. “Baby Steps towards Few-Shot Learning with Multiple Semantics.” <i>Pattern Recognition Letters</i>. Elsevier, 2022. <a href=\"https://doi.org/10.1016/j.patrec.2022.06.012\">https://doi.org/10.1016/j.patrec.2022.06.012</a>.","apa":"Schwartz, E., Karlinsky, L., Feris, R., Giryes, R., &#38; Bronstein, A. M. (2022). Baby steps towards few-shot learning with multiple semantics. <i>Pattern Recognition Letters</i>. Elsevier. <a href=\"https://doi.org/10.1016/j.patrec.2022.06.012\">https://doi.org/10.1016/j.patrec.2022.06.012</a>","ieee":"E. Schwartz, L. Karlinsky, R. Feris, R. Giryes, and A. M. Bronstein, “Baby steps towards few-shot learning with multiple semantics,” <i>Pattern Recognition Letters</i>, vol. 160. Elsevier, pp. 142–147, 2022.","mla":"Schwartz, Eli, et al. “Baby Steps towards Few-Shot Learning with Multiple Semantics.” <i>Pattern Recognition Letters</i>, vol. 160, Elsevier, 2022, pp. 142–47, doi:<a href=\"https://doi.org/10.1016/j.patrec.2022.06.012\">10.1016/j.patrec.2022.06.012</a>."},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","OA_place":"repository","intvolume":"       160","date_published":"2022-08-01T00:00:00Z","quality_controlled":"1","arxiv":1,"day":"01","doi":"10.1016/j.patrec.2022.06.012","oa":1,"type":"journal_article","main_file_link":[{"open_access":"1","url":"https://arxiv.org/abs/1906.01905"}]}]