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POS0687 INHIBITION OF BONE EROSION, DETERMINED BY HIGH-RESOLUTION PERIPHERAL QUANTITATIVE COMPUTED TOMOGRAPHY (HR-pQCT), IN RHEUMATOID ARTHRITIS PATIENTS RECEIVING A CONVENTIONAL SYNTHETIC DMARD (csDMARD) PLUS DENOSUMAB VS csDMARD THERAPY ALONE: RESULTS OF AN OPEN-LABEL, RANDOMIZED, PARALLEL-GROUP STUDY

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Annals of the Rheumatic Diseases 2022年 81卷 622-623页

作者： N. Iwamoto K. Chiba S. Sato K. Shiraishi K. Watanabe N. Ohki A. Okada T. Koga M. Kobayashi K. Saito N. Okubo A. Kawakami Nagasaki University Graduate School of Biomedical Sciences Department of Immunology and Rheumatology Division of Advanced Preventive Medical Sciences Nagasaki Japan Nagasaki University Graduate School of Biomedical Sciences Department of Orthopedic Surgery Nagasaki Japan Nagasaki University Hospital Clinical Research Center Nagasaki Japan Nagasaki University Graduate School of Biomedical Sciences Department of Radiological Sciences Nagasaki Japan Japanese Red Cross Nagasaki Genbaku Hospital Department of Rheumatology Nagasaki Japan Daiichi Sankyo Co. Ltd. Primary Medical Science Department Medical Affairs Division Tokyo Japan Daiichi Sankyo Co. Ltd. Data Intelligence Department Digital Transformation Management Division Tokyo Japan

Background Denosumab, a human IgG2 monoclonal antibody with high affinity for RANKL, is approved for treatment of bone erosion (ER) in patients with RA, based on the results of clinical trials. However, its effectiveness in combination with conventional therapy in RA patients has not been fully investigated in clinical practice. Objectives This exploratory study aimed to compare, in patients receiving conventional synthetic disease-modifying anti-rheumatic drugs (csDMARD) for treatment of RA, the effectiveness of combined use of csDMARD and denosumab vs csDMARD alone, in terms of inhibition of ER determined by HR-pQCT. Methods Detail protocol of this open-label, randomized, parallel-group study has been published previously. 1 RA patients with moderate or low disease activity and progressive ER were eligible, and were randomly assigned to receive denosumab in addition to the csDMARD (denosumab) group or to continued use of the csDMARD alone (csDMARD) group. Denosumab was administered every 6 months during the 12-month study period. The primary endpoint was change in ER-depth at the second and third metacarpal bones, determined by HR-pQCT at month 6. For the primary endpoint, a linear mixed effect model analysis was performed using treatment group, sex, anti-cyclic citrullinated peptide (CCP) antibody (positive vs negative), and baseline disease activity (DAS28-ESR) as fixed effects, patients as random effects, and baseline values as covariates. For extension data, measurement time-point and the interaction between treatment group and measurement time-point was further added as fixed effects. The adverse events (AEs) were recorded. Results A total of 46 patients were randomized to denosumab and csDMARD groups (both N=23), and baseline characteristics were similar between both groups. Although the difference was not significant, the estimate mean (95%CI) change of ER-depth at month 6 from baseline as the primary endpoint was −0.57 (−1.52, 0.39) in the denosumab group

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A future for the world's children? A WHO–UNICEF–Lancet Commission

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The Lancet 2020年第10224期395卷 605-658页

作者： Clark, Helen Coll-Seck, Awa Marie Banerjee, Anshu Peterson, Stefan Dalglish, Sarah L Ameratunga, Shanthi Balabanova, Dina Bhan, Maharaj Kishan Bhutta, Zulfiqar A Borrazzo, John Claeson, Mariam Doherty, Tanya El-Jardali, Fadi George, Asha S Gichaga, Angela Gram, Lu Hipgrave, David B Kwamie, Aku Meng, Qingyue Mercer, Raúl Narain, Sunita Nsungwa-Sabiiti, Jesca Olumide, Adesola O Osrin, David Powell-Jackson, Timothy Rasanathan, Kumanan Rasul, Imran Reid, Papaarangi Requejo, Jennifer Rohde, Sarah S Rollins, Nigel Romedenne, Magali Singh Sachdev, Harshpal Saleh, Rana Shawar, Yusra R Shiffman, Jeremy Simon, Jonathon Sly, Peter D Stenberg, Karin Tomlinson, Mark Ved, Rajani R Costello, Anthony The Helen Clark Foundation Auckland New Zealand Partnership for Maternal Newborn & Child Health Geneva Switzerland Senegal Presidency Dakar Senegal Department of Maternal Newborn Child and Adolescent Health WHO Geneva Switzerland Department of Health Systems Governance and Financing WHO Geneva Switzerland Health Division HIV Data and Analytics Division UNICEF New York NY United States HIV Data and Analytics Division UNICEF New York NY United States Department of International Health Johns Hopkins School of Public Health Baltimore MD United States School of Population Health University of Auckland Auckland New Zealand Department of Global Health and Development London School of Hygiene and Tropical Medicine London United Kingdom Health Systems Transformation Platform Tata Trusts Mumbai India Centre for Global Child Health Hospital for Sick Children Toronto OT Canada Global Financing Facility World Bank Washington DC United States Health Systems Research Unit South African Medical Research Council Cape Town South Africa Department of Health Management and Policy Beirut Lebanon Knowledge to Policy Center American University of Beirut Beirut Lebanon School of Public Health University of Western Cape Bellville South Africa Financing Alliance for Health Nairobi Kenya Institute for Global Health London United Kingdom Department of Economics London United Kingdom University College London London United Kingdom Health Policy and Systems Research Consultant Accra Ghana China Center for Health Development Studies Peking University Beijing China Program of Social Sciences and Health Latin American School of Social Sciences Buenos Aires Argentina Centre for Science and Environment New Delhi India Department of Maternal and Child Health Uganda Ministry of Health Kampala Uganda Institute of Child Health University of Ibadan Ibadan Nigeria Department of Health Systems WHO Phnom Penh Cambodia West and Central Regional Office UNICEF Dakar Senegal P

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Baryon Pasting the Uchuu Lightcone Simulation

arXiv

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arXiv 2024年

作者： Lau, Erwin T. Nagai, Daisuke Farahi, Arya Ishiyama, Tomoaki Miyatake, Hironao Osato, Ken Shirasaki, Masato Center for Astrophysics | Harvard & Smithsonian CambridgeMA02138 United States Department of Physics Yale University New HavenCT06520 United States Department of Statistics and Data Sciences University of Texas at Austin AustinTX78712 United States The NSF-Simons AI Institute for Cosmic Origins University of Texas at Austin AustinTX78712 United States Digital Transformation Enhancement Council Chiba University Chiba263-8522 Japan Nagoya University Nagoya464-8602 Japan Institute for Advanced Research Nagoya University Nagoya464-8601 Japan The University of Tokyo Chiba Kashiwa277-8583 Japan The University of Tokyo Chiba277-8583 Japan Center for Frontier Science Chiba University Chiba263-8522 Japan Department of Physics Graduate School of Science Chiba University Chiba263-8522 Japan National Institutes of Natural Science Tokyo Mitaka181-8588 Japan The Institute of Statistical Mathematics Tokyo Tachikawa190-8562 Japan

We present the Baryon Pasted (BP) X-ray and thermal Sunyaev-Zel’dovich (tSZ) maps derived from the half-sky Uchuu Lightcone simulation. These BP-Uchuu maps are constructed using more than 75 million dark matter halos with masses M500c ≥ 1013M☉ within the redshift range 0 ≤ z ≤ 2. A distinctive feature of our BP-Uchuu Lightcone maps is their capability to assess the influence of both extrinsic and intrinsic scatter caused by triaxial gaseous halos and internal gas characteristics, respectively, at the map level. We show that triaxial gas drives substantial scatter in X-ray luminosities of clusters and groups, accounting for nearly half of the total scatter in core-excised measurements. Additionally, scatter in the thermal pressure and gas density profiles of halos enhances the X-ray and SZ power spectra, leading to biases in cosmological parameter estimates. These findings are statistically robust due to the extensive sky coverage and large halo sample in the BP-Uchuu maps. The BP-Uchuu maps are publicly available online via Globus. Copyright © 2024, The Authors. All rights reserved.

关键词： Dark Matter

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We are what we experienced before birth: Lessons from epigenetics

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World Allergy Organization Journal 2020年第8期13卷 100361-100361页

作者： Saskia Trump Loreen Thürmann Matthias Klös Tobias Polte Roland Eils Irina Lehmann Charité - Universitätmedizin Berlin and Berlin Institute of Health Molecular Epidemiology Unit Berlin Germany Department of Environmental Immunology Helmholtz Centre for Environmental Research - UFZ Leipzig Germany Charité - Universitätmedizin Berlin and Berlin Institute of Health Center for Digital Health Berlin Germany Heidelberg University Hospital Health Data Science Unit Heidelberg Germany

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6Développement de nouveaux ”endpoints” cliniques à l'aide de biomarqueurs numériques basés sur la voix pour le suivi à distance, en vie réelle, de patients en recherche clinique: exemple de biomarqueurs vocaux pour le suivi du statut symptomatique de patients avec COVID-19

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Revue d'Épidémiologie et de Santé Publique 2022年 70卷 S260-S261页

作者： G. Fagherazzi L. Zhang A. Elbéji M. Pizzimenti P. Nazarov G. Aguayo A. Fischer Deep Digital Phenotyping Research Unit Department of Precision Health Luxembourg Institute of Health Strassen Luxembourg Bioinformatics Platform Luxembourg Institute of Health 1A-B rue Thomas Edison L-1445 Strassen Luxembourg Luxembourg Multiomics Data Science Department of Cancer Research Luxembourg Institute of Health 1A-B rueThomas Edison L-1445 Strassen Luxembourg

Introduction Les opportunités offertes par les nouvelles technologies en santé permettent de repenser la conduite d’études cliniques, afin d'alléger le fardeau de participation des patients, diminuer le nombre de visites sur site, ainsi que d'améliorer le suivi à distance inter-visites. Pour cela, parmi toutes les technologies numériques émergentes, le champ des biomarqueurs vocaux est particulièrement prometteur [1]. Nous proposons ici une méthodologie d'identification et de validation de biomarqueurs vocaux à l'aide de Méthodes d'analyse du signal et d'intelligence artificielle (Fig. 1), que nous illustrons avec des Résultats dans le cadre du suivi de patients avec COVID-19 ou un COVID long pour le suivi du statut symptomatique. Méthodes Nous avons régulièrement collecté des enregistrements audio standardisés pendant les deux premières semaines de suivi en vie réelle de N=272 participants de l’étude de cohorte Predi-COVID [2], tous ayant eu la maladie COVID-19, confirmée par test PCR positif. Des biomarqueurs vocaux ont été entrainés pour prédire le statut symptomatique, défini à partir d'une liste quotidienne des symptômes liés à COVID-19 les plus fréquents. Les audios (lecture d'un texte standardisé de 25 secondes) ont été nettoyés et harmonisés, puis 6473 caractéristiques audio en ont été extraites, afin d'entrainer des modèles de machine learning, dont les performances ont été évaluées à l'aide de métriques habituelles pour la discrimination (AUC, accuracy, precision, recall, F1-score) et le score de Brier pour la calibration. Résultats Au total, 1775 enregistrements ont été analysés (6,5 enregistrements/participant en moyenne). Le modèle de Support Vector Machine a fourni les meilleurs performances (AUC=0.91, accuracy=0,85) avec une bonne calibration (Brier Score=0,11) (Fig. 2). Le biomarqueur vocal dérivé de ces modèles, à partir de la probabilité prédite d’être symptomatique, permettait de discriminer les personnes asymptomatiques des personnes symptomatiqu

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The 2022 report of the Lancet Countdown on health and climate change: health at the mercy of fossil fuels (vol 400, pg 1619, 2022)

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LANCET 2022年第10365期400卷 1766-1766页

作者： Romanello, M. Di Napoli, C. Drummond, P. Institute for Global Health University College London London UK School of Agriculture Policy and Development University of Reading Reading UK Institute for Sustainable Resources University College London London UK Department of Global Health Centre for Health and the Global Environment University of Washington Seattle WA USA UCL Energy Institute University College London London UK Department of Health Sciences University of York York UK Department of Meteorology University of Reading Reading UK Institute for Risk and Disaster Reduction University College London London UK School of Earth and Environment University of Leeds Leeds UK Centre on Climate Change and Planetary Health London School of Hygiene & Tropical Medicine London UK School of Population Health University of Melbourne Melbourne VIC Australia Department of Earth System Science Tsinghua University Beijing China Mercator Research Institute on Global Commons and Climate Change Berlin Germany Department of Environment Climate Change and Health World Health Organization Geneva Switzerland Institute of Environmental Sciences University of Geneva Geneva Switzerland Cardiovascular Epidemiology Unit Department of Public Health & Primary Care University of Cambridge Cambridge UK School of Government University of Birmingham Birmingham UK Economic Analysis of Climate Impacts and Policy Division Centro Euro-Mediterraneo sui Cambiamenti Climatici Venice Italy Institute for Environmental Design and Engineering University College London London UK Natural Resources Institute University of Greenwich London UK Department of Environmental Health Sciences and Yale Center on Climate Change and Health Yale University New Haven CT USA Department of Civil and Environmental Engineering Northeastern University Boston MA USA Department of Fish and Wildlife Conservation Virginia Polytechnic Institute and State University Blacksburg VA USA Department of Geography University College London London UK NU

With advancements in the science of detection and attribution studies, the influence of climate change over many events has now been quantified. Because of the rapidly increasing temperatures, vulnerable populations (adults older than 65 years, and children younger than one year of age) were exposed to 3·7 billion more heatwave days in 2021 than annually in 1986–2005 (indicator 1.1.2), and heat-related deaths increased by 68% between 2000–04 and 2017–21 (indicator 1.1.5), a death toll that was significantly exacerbated by the confluence of the COVID-19 pandemic. Despite the local cooling and overall health benefits of urban greenspaces, only 277 (27%) of 1038 global urban centres were at least moderately green in 2021 (indicator 2.2.3), and the number of households with air conditioning increased by 66% from 2000 to 2020, a maladaptive response that worsens the energy crisis and further increases urban heat, air pollution, and greenhouse gas emissions. [...]millions of people do not have access to the energy needed to keep their homes at healthy temperatures, preserve food and medication, and meet the seventh Sustainable Development Goal (to ensure access to affordable, reliable, sustainable, and modern energy for all). Aggravating this situation even further, governments continue to incentivise fossil fuel production and consumption: 69 (80%) of 86 countries reviewed had net-negative carbon prices (ie, provided a net subsidy to fossil fuels) for a net total of US$400 billion

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Spatial clustering of codeine use and its association with depression: a geospatial analysis of nationally representative South African data

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Journal of Affective Disorders Reports 2022年 10卷 100434-100434页

作者： Nyoni, Princess Cuadros, Diego F. Gibbs, Andrew Tanser, Frank Slotow, Rob Burns, Jonathan K Tomita, Andrew School of Nursing and Public Health Discipline of Public Health Medicine University of KwaZulu-Natal Durban South Africa Health Economics and HIV and AIDS Research Division (HEARD) University of KwaZulu-Natal Durban South Africa Digital Epidemiology Laboratory Digital Futures University of Cincinnati Cincinnati United States Department of Psychology University of Exeter Exeter United Kingdom Gender and Health Research Unit South African Medical Research Council Pretoria South Africa Centre for Rural Health School of Nursing and Public Health University of KwaZulu-Natal Durban South Africa KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP) College of Health Sciences University of KwaZulu-Natal Durban South Africa Centre for Epidemic Response and Innovation (CERI) School of Data Science and Computational Thinking Stellenbosch University Stellenbosch South Africa Centre for the AIDS Programme of Research in South Africa (CAPRISA) Durban South Africa School of Life Sciences University of KwaZulu-Natal Pietermaritzburg South Africa Department of Genetics Evolution and Environment University College London United Kingdom Institute of Health Research University of Exeter Exeter United Kingdom Department of Psychiatry School of Clinical Medicine University of KwaZulu-Natal Durban South Africa

Background: There is an alarming trend in sub-Saharan Africa in the use of codeine-containing pharmaceuticals, but its risk of common comorbidities, such as mental health, remains unquantified at a national-level. We investigated the relationship between codeine use and onset of depression in South Africa at a population-level. Methods: We used nationally representative panel data from the South Africa National Income Dynamic Study to investigate the relationship between exposure to codeine use in the community (i.e. residing in a codeine hotspot) and onset of depression. Geographical hotspots of codeine use were identified using Kulldorff spatial scan statistic in SaTScan. We quantified depression onset at Wave 5 (year 2017) between individuals residing inside and outside a codeine hotspot who were depression-free at enrolment (Wave 4: 2015) using generalised estimating equation (GEE) regression models. Results: We identified four statistically significant hotspots of codeine use, mostly located at the northern part of the country. Among 13,020 participants who were depression-free at enrolment, residing within a codeine use hotspot was significantly associated with higher subsequent onset of depression (aRR=1.21, 95% CI:1.08-1.44). Limitations: data on diagnosis of depressive disorder were not available. Conclusion: South Africa, a resource scarce nation with chronically limited mental health services, is not spared from the global opioid epidemic and its impact on depression. Targeted scale-up access to agonist therapy to effectively treat (opioid) addiction in communities at risk for high exposure to codeine use could reduce the risk of subsequent mental health challenges. © 2022

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Citizen science’s transformative impact on science, citizen empowerment and socio-political processes

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Socio-Ecological Practice research 2023年第1期5卷 11-33页

作者： von Gönner, Julia Herrmann, Thora M. Bruckermann, Till Eichinger, Michael Hecker, Susanne Klan, Friederike Lorke, Julia Richter, Anett Sturm, Ulrike Voigt-Heucke, Silke Brink, Wiebke Liedtke, Christin Premke-Kraus, Matthias Altmann, Carolin Bauhus, Wilhelm Bengtsson, Luiza Büermann, Andrea Dietrich, Peter Dörler, Daniel Eich-Brod, Regina Ferschinger, Laura Freyberg, Linda Grützner, Agnes Hammel, Gertrud Heigl, Florian Heyen, Nils B. Hölker, Franz Johannsen, Carolin Kluß, Thorsten Kluttig, Thekla Knobloch, Jörn Munke, Martin Mortega, Kim Pathe, Carsten Soßdorf, Anna Stämpfli, Tiina Thiel, Christian Tönsmann, Susanne Valentin, Anke Wagenknecht, Katherin Wegener, Robert Woll, Silvia Bonn, Aletta Department of Ecosystem Services Helmholtz Centre for Environmental Research - UFZ Permoserstr. 15 Leipzig 04318 Germany Institute of Biodiversity Friedrich Schiller University Jena Dornburgerstr. 159 Jena 07743 Germany German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig Puschstr. 4 Leipzig 04103 Germany Institute of Education Leibniz University Hannover Schloßwenderstr. 1 Hannover 30159 Germany Center for Preventive Medicine and Digital Health Medical Faculty Mannheim Heidelberg University Ludolf-Krehl-Str. 7-11 Mannheim 68167 Germany Institute of Medical Biostatistics Epidemiology and Informatics University Medical Center of the Johannes Gutenberg University Mainz Obere Zahlbacher Str. 69 Mainz 55131 Germany Leibniz Institute for Evolution and Biodiversity Science Museum Für Naturkunde Berlin Invalidenstr. 43 Berlin 10115 Germany Institute of Data Science German Aerospace Center (DLR) Mälzerstr. 3-5 Jena 07745 Germany Leibniz Institute for Science and Mathematics Education Olshausenstr. 62 Kiel 24118 Germany Thünen-Institute of Biodiversity Bundesallee 65 Brunswick 38116 Germany Wissenschaft Im Dialog Charlottenstr. 80 Berlin 10117 Germany Helmholtz Association Berlin Head Office Anna-Louisa-Karsch-Str. 2 Berlin 10178 Germany Leibniz Association Berlin Head Office Chausseestr.111 Berlin 10115 Germany Research Transfer Office University of Münster Robert-Koch-Str.40 Münster 48149 Germany Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association Robert-Rössle-Str.10 Berlin 13125 Germany Department of Monitoring and Exploration Technologies Helmholtz Centre for Environmental Research - UFZ Permoserstr. 15 Leipzig 04318 Germany Institute of Zoology University of Natural Resources and Life Sciences Vienna Gregor-Mendel-Str. 33 Vienna 1180 Austria Institute for Energy and Climate Research IEK8 Forschungszentrum Jülich GmbH Jülich 52425 Germany Heinrich Heine University Duesseldorf Universitä

Citizen science (CS) can foster transformative impact for science, citizen empowerment and socio-political processes. To unleash this impact, a clearer understanding of its current status and challenges for its development is needed. Using quantitative indicators developed in a collaborative stakeholder process, our study provides a comprehensive overview of the current status of CS in Germany, Austria and Switzerland. Our online survey with 340 responses focused on CS impact through (1) scientific practices, (2) participant learning and empowerment, and (3) socio-political processes. With regard to scientific impact, we found that data quality control is an established component of CS practice, while publication of CS data and results has not yet been achieved by all project coordinators (55%). Key benefits for citizen scientists were the experience of collective impact (“making a difference together with others”) as well as gaining new knowledge. For the citizen scientists’ learning outcomes, different forms of social learning, such as systematic feedback or personal mentoring, were essential. While the majority of respondents attributed an important value to CS for decision-making, only few were confident that CS data were indeed utilized as evidence by decision-makers. Based on these results, we recommend (1) that project coordinators and researchers strengthen scientific impact by fostering data management and publications, (2) that project coordinators and citizen scientists enhance participant impact by promoting social learning opportunities and (3) that project initiators and CS networks foster socio-political impact through early engagement with decision-makers and alignment with ongoing policy processes. In this way, CS can evolve its transformative impact. © 2023, The Author(s).

关键词： data quality Participatory research Political uptake Recognition research data management Social learning

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Leveraging implicit knowledge in neural networks for functional dissection and engineering of proteins (vol 1, pg 225, 2019)

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NATURE MACHINE INTELLIGENCE 2019年第6期1卷 290-290页

作者： zu Belzen, Julius Upmeier Buergel, Thore Holderbach, Stefan Bubeck, Felix Adam, Lukas Gandor, Catharina Klein, Marita Mathony, Jan Pfuderer, Pauline Platz, Lukas Przybilla, Moritz Schwendemann, Max Heid, Daniel Hoffmann, Mareike Daniela Jendrusch, Michael Schmelas, Carolin Waldhauer, Max Lehmann, Irina Niopek, Dominik Eils, Roland University of Heidelberg Synthetic Biology Group Institute for Pharmacy and Molecular Biotechnology and Center for Quantitative Analysis of Molecular and Cellular Biosystems Heidelberg Germany (GRID:grid.7700.0) (ISNI:0000 0001 2190 4373) Digital Health Center Berlin Institute of Health (BIH) and Charité University Medicine Berlin Germany (GRID:grid.6363.0) (ISNI:0000 0001 2218 4662) University of Heidelberg Synthetic Biology Group Institute for Pharmacy and Molecular Biotechnology and Center for Quantitative Analysis of Molecular and Cellular Biosystems Heidelberg Germany (GRID:grid.7700.0) (ISNI:0000 0001 2190 4373) University of Heidelberg Synthetic Biology Group Institute for Pharmacy and Molecular Biotechnology and Center for Quantitative Analysis of Molecular and Cellular Biosystems Heidelberg Germany (GRID:grid.7700.0) (ISNI:0000 0001 2190 4373) German Cancer Research Center (DKFZ) Department of Theoretical Bioinformatics Heidelberg Germany (GRID:grid.7497.d) (ISNI:0000 0004 0492 0584) University Hospital Heidelberg Department of Infectious Diseases Virology Heidelberg Germany (GRID:grid.5253.1) (ISNI:0000 0001 0328 4908) BioQuant Center and Cluster of Excellence CellNetworks at Heidelberg University Heidelberg Germany (GRID:grid.7700.0) (ISNI:0000 0001 2190 4373) Berlin Institute of Health (BIH) and Charité University Medicine Molecular Epidemiology Unit Berlin Germany (GRID:grid.484013.a) University of Heidelberg Synthetic Biology Group Institute for Pharmacy and Molecular Biotechnology and Center for Quantitative Analysis of Molecular and Cellular Biosystems Heidelberg Germany (GRID:grid.7700.0) (ISNI:0000 0001 2190 4373) University Hospital Heidelberg Health Data Science Unit Heidelberg Germany (GRID:grid.5253.1) (ISNI:0000 0001 0328 4908) Digital Health Center Berlin Institute of Health (BIH) and Charité University Medicine Berlin Germany (GRID:grid.6363.0) (ISNI:0000 0001 2218 4662) University Hospital Heidelberg Health Data Science Unit Heidelberg Germany (GRI

Proteins are nature’s most versatile molecular machines. Deep neural networks trained on large protein datasets have recently been used to tackle the unmet complexity of protein sequence–function relationships. The implicit knowledge contained in these networks represents a powerful, but thus far inaccessible, resource for understanding protein biology. Here, we show that occlusion-based sensitivity analysis can leverage the knowledge present in deep-neural-network-based protein sequence classifiers to identify functionally relevant parts of proteins. We first validated our approach by successfully predicting positions that mediate small molecule binding or catalytic activity across different protein classes. Next, we inferred the impact of point mutations on the activity of ERK and HRas, signalling factors frequently deregulated in cancer. Finally, we used our approach to identify engineering hotspots in CRISPR–Cas9 and anti-CRISPR protein AcrIIA4. Our work demonstrates how implicit knowledge in neural networks can be harnessed for protein functional dissection and protein *** neural networks are a powerful tool for predicting protein function, but identifying the specific parts of a protein sequence that are relevant to its functions remains a challenge. An occlusion-based sensitivity technique helps interpret these deep neural networks, and can guide protein engineering by locating functionally relevant protein positions.

关键词： Proteins

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WS05.03 Pharmacological improvement of CFTR function rescues airway epithelial homeostasis and host defense in children with cystic fibrosis

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Journal of Cystic Fibrosis 2024年 23卷 S9-S10页

作者： J. Loske M. Völler S. Lukassen L. Thürmann A. Seegebarth J. Röhmel S. Wisniewski M. Messingschlager S. Lorenz S. Klages R. Eils I. Lehmann M.A. Mall S. Trump S.Y. Graeber Berlin Institute of Health at Charité – Universitätsmedizin Berlin Center of Digital Health Molecular Epidemiology Unit Berlin Germany Freie Universität Berlin Department of Biology Berlin Germany Charité - Universitätsmedizin Berlin Department of Pediatric Respiratory Medicine Immunology and Critical Care Medicine Berlin Germany Berlin Institute of Health at Charité – Universitätsmedizin Berlin Center of Digital Health Berlin Germany Berlin Institute of Health at Charité - Universitätsmedizin Berlin Berlin Germany German Centre for Lung Research (DZL) Associated Partner Site Berlin Germany Max Planck Institute for Molecular Genetics Berlin Germany Heidelberg University Hospital and BioQuant Health Data Science Unit Heidelberg Germany Freie Universität Berlin Department of Mathematics and Computer Science Berlin Germany

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