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Discovery of BAY 2666605, a Molecular Glue for PDE3A and SLFN12

ACS MEDICINAL CHEMISTRY LETTERS 2024年第10期15卷 1662-1667页

作者： Lewis, Timothy A. Ellermann, Manuel Kopitz, Charlotte Lange, Martin de Waal, Luc Wu, Xiaoyun Tersteegen, Adrian Denner, Karsten Lienau, Philip Kaulfuss, Stefan Goldoni, Silvia Meyerson, Matthew Greulich, Heidi Gradl, Stefan N. Broad Inst MIT & Harvard Ctr Sci Therapeut Cambridge MA 02142 USA Bayer AG D-13353 Berlin Germany Broad Inst MIT & Harvard Canc Program Cambridge MA 02142 USA Dana Farber Canc Inst Dept Med Oncol Boston MA 01255 USA Bayer Pharmaceut Res & Early Dev Oncol Cambridge MA 02142 USA Bayer AG D-42096 Wuppertal Germany

A subset of phosphodiesterase 3 (PDE3) inhibitors kills cancer cells that express both PDE3A and SLFN12 by inducing a protein-protein interaction between the two, triggering SLFN12 tRNase activity. Following discovery of the prototypical tool compound, DNMDP, an improved compound, BRD9500, was discovered to be potent in cells and active in several tumor models in vivo. More analogs were prepared and tested with the goal of increasing metabolic stability and decreasing PDE3 inhibition while maintaining the cellular activity of BRD9500. This led to the discovery of BAY 2666605, a compound optimized for clinical testing.

关键词： SLFN12 PDE3A melanoma molecularglue velcrin

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Risk factors for cognitive impairment and dementia after stroke: a systematic review and meta-analysis

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LANCET HEALTHY LONGEVITY 2024年第1期5卷 e31-e44页

作者： Filler, Jule Georgakis, Marios K. Dichgans, Martin Ludwig Maximilians Univ Munchen Ludwig Maximilians Univ Hosp Inst Stroke & Dementia Res D-81377 Munich Germany Ludwig Maximilians Univ Munchen Grad Sch Syst Neurosci Munich Germany Broad Inst MIT & Harvard Program Med & Populat Genet Cambridge MA USA Munich Cluster Syst Neurol SyNergy Munich Germany German Ctr Neurodegenerat Dis Munich Germany German Ctr Cardiovasc Res Munich Germany

Background Cognitive impairment and dementia are highly prevalent among stroke survivors and represent a major burden for patients, carers, and health-care systems. We studied the risk factors for post -stroke cognitive impairment (PSCI) and dementia (PSD) beyond the well established risk factors of age and stroke severity. Methods In this systematic review and meta -analysis we conducted a systematic literature search from database inception until Sept 15, 2023. We selected prospective and retrospective cohort studies, post -hoc analyses from randomised controlled trials, and nested case -control studies of patients with acute stroke (ischaemic, haemorrhagic, and transient ischaemic attack), exploring associations between risk factors at baseline and PSCI or PSD over a follow-up period of at least 3 months. Study quality was assessed using the Newcastle -Ottawa quality assessment scale. We calculated pooled relative risks (RRs) with random -effects meta -analyses and performed subgroup, metaregression, and sensitivity analyses. This study was preregistered with PROSPERO, CRD42020164959. Findings We identified 162 eligible articles for our systematic review, of which 113 articles (89 studies, 160 783 patients) were eligible for meta -analysis. Baseline cognitive impairment was the strongest risk factor for PSCI (RR 2 center dot 00, 95% CI 1 center dot 66-2 center dot 40) and PSD (3 center dot 10, 2 center dot 77-3 center dot 47). We identified diabetes (1 center dot 29, 1 center dot 14-1 center dot 45), presence or history of atrial fibrillation (1 center dot 29, 1 center dot 04-1 center dot 60), presence of moderate or severe white matter hyperintensities (WMH;1 center dot 51, 1 center dot 20-1 center dot 91), and WMH severity (1 center dot 30, 1 center dot 10-1 center dot 55, per SD increase) as treatable risk factors for PSCI, independent of age and stroke severity. For PSD, we identified diabetes (1 center dot 38, 1 center dot 10-1 center dot 72), presence of mo

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Dual-Domain Attention for Image Deblurring 37

Dual-Domain Attention for Image Deblurring

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37th AAAI Conference on Artificial Intelligence (AAAI) / 35th Conference on Innovative Applications of Artificial Intelligence / 13th Symposium on Educational Advances in Artificial Intelligence

作者： Cui, Yuning Tao, Yi Ren, Wenqi Knoll, Alois Techn Univ Munich Munich Germany MIT Univ Village Program Cambridge MA USA Sun Yat Sen Univ Shenzhen Campus Beijing Peoples R China

ISBN: (纸本)9781577358800

As a long-standing and challenging task, image deblurring aims to reconstruct the latent sharp image from its degraded counterpart. In this study, to bridge the gaps between degraded/sharp image pairs in the spatial and frequency domains simultaneously, we develop the dual-domain attention mechanism for image deblurring. Self-attention is widely used in vision tasks, however, due to the quadratic complexity, it is not applicable to image deblurring with high-resolution images. To alleviate this issue, we propose a novel spatial attention module by implementing self-attention in the style of dynamic group convolution for integrating information from the local region, enhancing the representation learning capability and reducing computational burden. Regarding frequency domain learning, many frequency-based deblurring approaches either treat the spectrum as a whole or decompose frequency components in a complicated manner. In this work, we devise a frequency attention module to compactly decouple the spectrum into distinct frequency parts and accentuate the informative part with extremely lightweight learnable parameters. Finally, we incorporate attention modules into a U-shaped network. Extensive comparisons with prior arts on the common benchmarks show that our model, named Dual-Domain Attention Network (DDANet), obtains comparable results with a significantly improved inference speed.

关键词： Frequency domain analysis

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Freshwater Contributions to Decadal Variability of the Indonesian Throughflow

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GEOPHYSICAL RESEARCH LETTERS 2023年第14期50卷 e2023GL103906-e2023GL103906页

作者： Wang, Shouyi Ummenhofer, Caroline C. Oppo, Delia W. Murty, Sujata A. Wagner, Patrick Boening, Claus W. Biastoch, Arne MIT WHOI Joint Program Oceanog Appl Ocean Sci & Engn Woods Hole MA 02543 USA Woods Hole Oceanog Inst Woods Hole MA 02543 USA SUNY Albany Albany NY USA GEOMAR Helmholtz Ctr Ocean Res Kiel Kiel Germany Univ Kiel Kiel Germany

The Makassar Strait, the main passageway of the Indonesian Throughflow (ITF), is an important component of Indo-Pacific climate through its inter-basin redistribution of heat and freshwater. Observational studies suggest that wind-driven freshwater advection from the marginal seas into the Makassar Strait modulates the strait's surface transport. However, direct observations are too short (<15 years) to resolve variability on decadal timescales. Here we use a series of global ocean simulations to assess the advected freshwater contributions to ITF transport across a range of timescales. The simulated seasonal and interannual freshwater dynamics are consistent with previous studies. On decadal timescales, we find that wind-driven advection of South China Sea (SCS) waters into the Makassar Strait modulates upper-ocean ITF transport. Atmospheric circulation changes associated with Pacific decadal variability appear to drive this mechanism via Pacific lower-latitude western boundary current interactions that affect the SCS circulation.

关键词： Advection

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Precurved, Fiber-Reinforced Actuators Enable Pneumatically Efficient Replication of Complex Biological Motions

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SOFT ROBOTICS 2022年第2期9卷 293-308页

作者： Hu, Lucy Gau, Dominik Nixon, James Klein, Melissa Fan, Yiling Menary, Gary Roche, Ellen T. MIT Harvard MIT Program Hlth Sci & Technol 77 Massachusetts Ave Cambridge MA 02139 USA MIT Inst Med Engn & Sci 77 Massachusetts Ave Cambridge MA 02139 USA Tech Univ Munich Dept Mech Engn Munich Germany Queens Univ Sch Mech & Aerosp Engn Belfast Antrim North Ireland MIT Dept Mech Engn Cambridge MA 02139 USA

Much of the research on bioinspired soft robotics has focused on capturing the interplay of biological form and function. However, existing soft robotic actuators are mostly made with linear or planar fabrication orientations that do not represent the resting geometry of complex biological systems, such as curved musculature. This work introduces the ability to create fiber-reinforced actuators with precurved configurations. By tuning variables such as dimensions and fiber angles, an optimization algorithm can prescribe the mechanical fabrication parameters to create a fiber-reinforced actuator that can generate controlled motion to follow a desired input trajectory. Precurved configurations introduce an additional optimization parameter, the initial bend angle, allowing for a more accurate and robust algorithm and generating a median percent error of <1%. With a customized software tool, we can take existing motion data from biological systems-such as medical imaging-and build soft robotic actuators optimized to replicate these trajectories. We can predict the motion of precurved actuators both analytically and numerically and replicate the motion experimentally, with excellent trajectory matching between the three. In constructing actuators that better match the native forms found within biological systems, we find that precurved actuators are more efficient than their initially straight counterparts. This pneumatic efficiency allows for the use of control systems with lower power and precision, lowering the economic cost of the associated control hardware, while more accurately replicating the biological motion. Taking two examples from biology, that of the human diaphragm during respiration and that of a jellyfish bell during locomotion, we design and generate fiber reinforced actuators to mimic these motions.

关键词： fiber reinforced actuators precurved actuators computational optimization biomimetic motion fabrication design pneumatic efficiency

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Discovery of a structural class of antibiotics with explainable deep learning

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NATURE 2024年第7997期626卷 177-+页

作者： Wong, Felix Zheng, Erica J. Valeri, Jacqueline A. Donghia, Nina M. Anahtar, Melis N. Omori, Satotaka Li, Alicia Cubillos-Ruiz, Andres Krishnan, Aarti Jin, Wengong Manson, Abigail L. Friedrichs, Jens Helbig, Ralf Hajian, Behnoush Fiejtek, Dawid K. Wagner, Florence F. Soutter, Holly H. Earl, Ashlee M. Stokes, Jonathan M. Renner, Lars D. Collins, James J. Broad Inst MIT & Harvard Infect Dis & Microbiome Program Cambridge MA 02142 USA MIT Inst Med Engn & Sci 77 Massachusetts Ave Cambridge MA 02139 USA MIT Dept Biol Engn 77 Massachusetts Ave Cambridge MA 02139 USA Integrated Biosci San Carlos CA USA Harvard Univ Program Chem Biol Cambridge MA 02138 USA Harvard Univ Wyss Inst Biol Inspired Engn Boston MA 02115 USA Broad Inst MIT & Harvard Eric & Wendy Schmidt Ctr Cambridge MA 02142 USA Leibniz Inst Polymer Res Dresden Dresden Germany Max Bergmann Ctr Biomat Dresden Dresden Germany Broad Inst MIT & Harvard Ctr Dev Therapeut Cambridge MA 02142 USA McMaster Univ Michael G DeGroote Inst Infect Dis Res Dept Biochem & Biomed Sci Hamilton ON Canada McMaster Univ David Braley Ctr Antibiot Discovery Hamilton ON Canada

The discovery of novel structural classes of antibiotics is urgently needed to address the ongoing antibiotic resistance crisis(1, 2, 3, 4, 5, 6, 7, 8-9). Deep learning approaches have aided in exploring chemical spaces(1,10, 11, 12, 13, 14-15);these typically use black box models and do not provide chemical insights. Here we reasoned that the chemical substructures associated with antibiotic activity learned by neural network models can be identified and used to predict structural classes of antibiotics. We tested this hypothesis by developing an explainable, substructure-based approach for the efficient, deep learning-guided exploration of chemical spaces. We determined the antibiotic activities and human cell cytotoxicity profiles of 39,312 compounds and applied ensembles of graph neural networks to predict antibiotic activity and cytotoxicity for 12,076,365 compounds. Using explainable graph algorithms, we identified substructure-based rationales for compounds with high predicted antibiotic activity and low predicted cytotoxicity. We empirically tested 283 compounds and found that compounds exhibiting antibiotic activity against Staphylococcus aureus were enriched in putative structural classes arising from rationales. Of these structural classes of compounds, one is selective against methicillin-resistant S. aureus (MRSA) and vancomycin-resistant enterococci, evades substantial resistance, and reduces bacterial titres in mouse models of MRSA skin and systemic thigh infection. Our approach enables the deep learning-guided discovery of structural classes of antibiotics and demonstrates that machine learning models in drug discovery can be explainable, providing insights into the chemical substructures that underlie selective antibiotic activity.

关键词： Antibiotics Bacterial systems biology Computational science Drug discovery Networks and systems biology

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Deglacial increase of seasonal temperature variability in the tropical ocean

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NATURE 2022年第7938期612卷 88-+页

作者： Woermer, Lars Wendt, Jenny Boehman, Brenna Haug, Gerald H. Hinrichs, Kai-Uwe Univ Bremen MARUM Ctr Marine Environm Sci Bremen Germany Max Planck Inst Chem Mainz Germany Swiss Fed Inst Technol Dept Earth Sci Zurich Switzerland MIT WHOI Joint Program Oceanog Appl Ocean Sci & En Cambridge MA USA MIT WHOI Joint Program Oceanog Appl Ocean Sci & En Woods Hole MA USA

The relatively stable Holocene climate was preceded by a pronounced event of abrupt warming in the Northern Hemisphere, the termination of the Younger Dryas (YD) cold period(1,2). Although this transition has been intensively studied, its imprint on low-latitude ocean temperature is still controversial and its effects on sub-annual to decadal climate variability remain poorly understood(1,3,4). Sea surface temperature (SST) variability at these timescales in the tropical Atlantic is expected to intensify under current and future global warming and has considerable consequences for environmental conditions in Africa and South America, and for tropical Pacific climate(5-8). Here we present a 100-mu m-resolution record obtained by mass spectrometry imaging (MSI) of long-chain alkenones in sediments from the Cariaco Basin(9-11) and find that annually averaged SST remained stable during the transition into the Holocene. However, seasonality increased more than twofold and approached modern values of 1.6 & DEG;C, probably driven by the position and/or annual range of the Intertropical Convergence Zone (ITCZ). We further observe that interannual variability intensified during the early Holocene. Our results demonstrate that sub-decadal-scale SST variability in the tropical Atlantic is sensitive to abrupt changes in climate background, such as those witnessed during the most recent glacial to interglacial transition.

关键词： Palaeoceanography Palaeoclimate Palaeoecology

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SELECTIVE FREQUENCY NETWORK FOR IMAGE RESTORATION 11

SELECTIVE FREQUENCY NETWORK FOR IMAGE RESTORATION

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11th International Conference on Learning Representations, ICLR 2023

作者： Cui, Yuning Tao, Yi Bing, Zhenshan Ren, Wenqi Gao, Xinwei Cao, Xiaochun Huang, Kai Knoll, Alois Technical University of Munich Germany MIT Universal Village Program United States Sun Yat-sen University China Tencent China Chinese Academy of Sciences China

Image restoration aims to reconstruct the latent sharp image from its corrupted *** dealing with this long-standing task in the spatial domain, a few approaches seek solutions in the frequency domain in consideration of the large discrepancy between spectra of sharp/degraded image ***, these works commonly utilize transformation tools, e.g., wavelet transform, to split features into several frequency parts, which is not flexible enough to select the most informative frequency component to *** this paper, we exploit a multi-branch and content-aware module to decompose features into separate frequency subbands dynamically and locally, and then accentuate the useful ones via channel-wise attention *** addition, to handle large-scale degradation blurs, we propose an extremely simple decoupling and modulation module to enlarge the receptive field via global and window-based average *** two developed modules into a U-Net backbone, the proposed Selective Frequency Network (SFNet) performs favorably against state-of-the-art algorithms on five image restoration tasks, including single-image defocus deblurring, image dehazing, image motion deblurring, image desnowing, and image deraining. © 2023 11th International Conference on Learning Representations, ICLR 2023. All rights reserved.

关键词： Image reconstruction

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Strip Attention for Image Restoration 32

Strip Attention for Image Restoration

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32nd International Joint Conference on Artificial Intelligence (IJCAI)

作者： Cui, Yuning Tao, Yi Jing, Luoxi Knoll, Alois Tech Univ Munich Sch Computat Informat & Technol Munich Germany MIT Univ Village Program Cambridge MA USA Peking Univ Sch Comp Sci Beijing Peoples R China

ISBN: (纸本)9781956792034

As a long-standing task, image restoration aims to recover the latent sharp image from its degraded counterpart. In recent years, owing to the strong ability of self-attention in capturing long-range dependencies, Transformer based methods have achieved promising performance on multifarious image restoration tasks. However, the canonical self-attention leads to quadratic complexity with respect to input size, hindering its further applications in image restoration. In this paper, we propose a Strip Attention Network (SANet) for image restoration to integrate information in a more efficient and effective manner. Specifically, a strip attention unit is proposed to harvest the contextual information for each pixel from its adjacent pixels in the same row or column. By employing this operation in different directions, each location can perceive information from an expanded region. Furthermore, we apply various receptive fields in different feature groups to enhance representation learning. Incorporating these designs into a U-shaped backbone, our SANet performs favorably against state-of-the-art algorithms on several image restoration tasks. The code is available at https://***/c-yn/SANet.

关键词： Image reconstruction

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Larval dispersal and recruitment of benthic invertebrates in the Arctic Ocean

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PROGRESS IN OCEANOGRAPHY 2022年 203卷 102776-102776页

作者： Meyer-Kaiser, Kirstin S. Schrage, Kharis R. Von Appen, Wilken-Jon Hoppmann, Mario Lochthofen, Normen Sundfjord, Arild Soltwedel, Thomas Woods Hole Oceanog Inst 266 Woods Hole Rd Woods Hole MA 02543 USA Alfred Wegener Inst Helmholtz Zentrum Polar & Meeresforsch Handelshafen 12 D-27570 Bremerhaven Germany Framsenteret Norsk Polarinst N-9296 Tromso Norway MIT WHOI Joint Program Oceanog Appl Ocean Sci & E Cambridge MA USA MIT WHOI Joint Program Oceanog Appl Ocean Sci & E Woods Hole MA USA

Larval dispersal is a fundamental process responsible for colonization and connectivity of benthic invertebrate populations. It is difficult to study larval dispersal in polar environments because weather and climate conditions restrict sample collection to certain seasons. In this study, we leveraged oceanographic moorings as long-term scientific platforms for collecting larvae and recruits of benthic invertebrate species in the Fram Strait and along the continental slope north of Svalbard in 2017-2021. Larval traps and fouling panels were deployed at various depths on 15 moorings at 8 locations, and additional specimens of biofouling were obtained opportunistically from moored instruments. Our results showed a significant difference in species composition between samples collected in Atlantic Water in the West Spitsbergen Current (WSC) and samples collected in Arctic Water near the seafloor and in the East Greenland Current (EGC) in the western part of the Fram Strait. There was also a stark difference between Atlantic Water species in the Fram Strait and on the north Svalbard slope. Most specimens collected in the WSC belonged to species with long-duration planktotrophic larvae, such as the ubiquitous bivalve Hiatella arctica, the bryozoan Alcyonidium mamillatum, and two nudibranchs. Samplers exposed primarily to Arctic water at their given depth and location were dominated by hydrozoans. We observed medusae budding off of the hydroids Stegopoma plicatile and Rhizoragium roseum. Our study demonstrates that the WSC is an important vector for larval dispersal into the central Arctic Ocean. Integration of biological samplers on oceanographic moorings holds great promise for monitoring efforts as climate change progresses, especially in environments where research is challenging and seasonally limited, such as the Arctic.

关键词： Larval settlement Biofouling LTER HAUSGARTEN Fram Strait West Spitsbergen Current East Greenland Current

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