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arXiv 2023年

作者： Koehler, Gregor Wald, Tassilo Ulrich, Constantin Zimmerer, David Jaeger, Paul F. Franke, Jörg K.H. Kohl, Simon Isensee, Fabian Maier-Hein, Klaus H. Heidelberg Division of Medical Image Computing Germany Helmholtz Information and Data Science School for Health Karlsruhe Heidelberg Germany Helmholtz Imaging DKFZ Germany NCT Heidelberg a partnership between DKFZ University Medical Center Heidelberg Germany Interactive Machine Learning Group DKFZ Applied Computer Vision Lab DKFZ Machine Learning Lab University of Freiburg Freiburg Germany London United Kingdom Pattern Analysis and Learning Group Heidelberg University Hospital Heidelberg Germany

Despite the remarkable success of deep learning systems over the last decade, a key difference still remains between neural network and human decision-making: As humans, we can not only form a decision on the spot, but also ponder, revisiting an initial guess from different angles, distilling relevant information, arriving at a better decision. Here, we propose RecycleNet, a latent feature recycling method, instilling the pondering capability for neural networks to refine initial decisions over a number of recycling steps, where outputs are fed back into earlier network layers in an iterative fashion. This approach makes minimal assumptions about the neural network architecture and thus can be implemented in a wide variety of contexts. Using medical image segmentation as the evaluation environment, we show that latent feature recycling enables the network to iteratively refine initial predictions even beyond the iterations seen during training, converging towards an improved decision. We evaluate this across a variety of segmentation benchmarks and show consistent improvements even compared with top-performing segmentation methods. This allows trading increased computation time for improved performance, which can be beneficial, especially for safety-critical applications. © 2023, CC BY.

关键词： Network layers

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Non-parametric model-based estimation of the effective reproduction number for SARS-CoV-2

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AIP Conference Proceedings 2023年第1期2872卷

作者： Jacques Hermes Marcus Rosenblatt Christian Tönsing Jens Timmer Institute of Physics University of Freiburg Hermann-Herder-Str. 3 79104 Freiburg Germany Freiburg Center for Data Analysis and Modelling (FDM) University of Freiburg Ernst-Zermelo-Str. 1 79104 Freiburg Germany Centre for Integrative Biological Signalling Studies (CIBSS) University of Freiburg Schänzlestr. 18 79104 Freiburg Germany

Viral outbreaks, such as the COVID-19 pandemic, are commonly described by compartmental models by means of ordinary differential equation (ODE) systems. The parameter values of these ODE models are typically unknown and need to be estimated based on accessible data. In order to describe realistic pandemic scenarios with strongly varying situations, these model parameters need to be assumed as time-dependent. While parameter estimation for the typical case of time-constant parameters does not pose larger issues, the determination of time-dependent parameters, e.g. the transition rates of compartmental models, remains notoriously difficult, since the function class of these time-dependent parameters is ***, we propose a combination of an Augmented Kalman Smoother with an Expectation-Maximization algorithm to simultaneously estimate all time-dependent parameters in an SIRD compartmental model. The approach is applicable to general systems of ODEs with time-varying parameters. In particular, it does not require prior knowledge on model parameters or any further assumptions on the function class of the time-dependencies of the ODE. In contrast to other approaches, no assumptions on the parameterization of the serial interval distribution are required for the estimation of SIRD-model parameters. With the presented method, we are able to adequately describe time series of COVID-19 data in Germany including strong fluctuations and multiple waves, and to give non-parametric model-based time course estimates for the effective reproduction number.

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CSIG-11. TUMOR-CELL INTRINSIC CALCIUM OSCILLATIONS DRIVE BRAIN METASTASIS

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Neuro-Oncology 2024年第SUPPLEMENT_8期26卷 viii65–viii66页

作者： Hebach, Nils R Olshausen, Niels Schlag, Joana S Bang, Severin Kraft, Theresa Mayer, Chanté Linke, Zoe Westphal, Dana Seifert, Michael Timmer, Jens Wick, Wolfgang Winkler, Frank Karreman, Matthia A Clinical Cooperation Unit Neurooncology German Cancer Research Center Heidelberg Germany Neurology Clinic and National Center for Tumor Diseases Heidelberg Germany Institute of Physics University of Freiburg Freiburg Germany Freiburg Center for Data Analysis and Modeling (FDM) Freiburg Germany Institute for Medical Informatics and Biometry (IMB) Carl Gustav Carus Faculty of Medicine Dresden Germany National Center for Tumor Diseases (NCT) Dresden Germany Department of Dermatology Medical Faculty and University Hospital Carl Gustav Carus Dresden Germany

Calcium is a ubiquitous secondary messenger which regulates many cellular processes. Recently, we have shown that a subpopulation of glioblastoma cells can intrinsically generate calcium oscillations which drive proliferative signalling. Here, we set out to investigate whether such cancer cell autonomous oscillations are also present in secondary brain tumours. Employing longitudinal intravital two-photon microscopy in awake mice, we demonstrate that brain metastases of melanoma and lung cancer exhibit spontaneous calcium oscillationsin vivoalong the metastatic cascade. These oscillations are already observed during intravascular arrest and inin vitromonocultures, suggesting a tumour-cell intrinsic origin. We developed a fully automatic image analysis pipeline to accurately quantify calcium oscillations bothin vivoandin vitro. Mathematical modelling of cytosolic and ER calcium stores can predict stable calcium oscillations with similar frequency and peak characteristics as those experimentally observed. We discovered that these oscillations are tightly regulated by an interplay of calcium-induced calcium release and store-operated calcium entry (SOCE). Similarly, SOCE-related ion channels are enriched in tissue from human melanoma brain metastases compared to healthy brain controls and calcium activity can also be observedex vivoin patient-derived brain metastasis resections. Finally, by correlating calcium activity and EdU incorporation we discovered that the presence of calcium oscillations predicts their proliferative potentialin vitro. Importantly, by intravital two-photon microscopy we show that calcium activity correlates with metastasis size in preclinical models, suggesting a potential new therapeutic angle from which to target brain metastases.

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A systematic review of challenges and proposed solutions in modeling multimodal data

arXiv

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arXiv 2025年

作者： Farhadizadeh, Maryam Weymann, Maria Blaß, Michael Kraus, Johann Gundler, Christopher Walter, Sebastian Hempen, Noah Binder, Harald Binder, Nadine Institute of General Practice/Family Medicine Faculty of Medicine Medical Center University of Freiburg Elsässer Straße 2M Freiburg79110 Germany Freiburg Center for Data Analysis Modeling and AI University of Freiburg Ernst-Zermelo-Str. 1 Freiburg79104 Germany Institute of Medical Biometry and Statistics Faculty of Medicine Medical Center University of Freiburg Stefan-Meier-Straße 26 Freiburg79104 Germany Institute for Applied Medical Informatics University Medical Center Hamburg-Eppendorf Martinistraße 52 Hamburg20251 Germany Institute of Medical Systems Biology Ulm University Helmholtzstraße 16 Ulm89081 Germany Department of Computer Science Faculty of Engineering University of Freiburg Georges-Köhler-Allee 051 Freiburg79110 Germany

Multimodal data modeling has emerged as a powerful approach in clinical research, enabling the integration of diverse data types such as imaging, genomics, wearable sensors, and electronic health records. Despite its potential to improve diagnostic accuracy and support personalized care, modeling such heterogeneous data presents significant technical challenges. This systematic review synthesizes findings from 69 studies to identify common obstacles, including missing modalities, limited sample sizes, dimensionality imbalance, interpretability issues, and finding the optimal fusion techniques. We highlight recent methodological advances, such as transfer learning, generative models, attention mechanisms, and neural architecture search that offer promising solutions. By mapping current trends and innovations, this review provides a comprehensive overview of the field and offers practical insights to guide future research and development in multimodal modeling for medical applications. © 2025, CC BY.

关键词： Clinical research

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Development of Powerly, unguided mobile app intervention preventing postpartum depression and anxiety & study protocol of randomized clinical trial

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Internet Interventions 2025年 41卷

作者： Marta A. Marciniak Judith Rohde Kenneth S.L. Yuen Harald Binder Henrik Walter Matthias J. Wieser Raffael Kalisch Karin Roelofs Birgit Kleim Department of Psychology Education and Child Studies Erasmus University Rotterdam Rotterdam the Netherlands Healthy Longevity Center University of Zurich Zurich Switzerland Department of Psychology University of Zurich Zurich Switzerland Department of Psychiatry Psychotherapy and Psychosomatics Psychiatric University Hospital Zurich Switzerland Neuroimaging Center (NIC) Focus Program Translational Neuroscience (FTN) Johannes Gutenberg University Medical Center Mainz Germany Leibniz Institute for Resilience Research (LIR) Mainz Germany Institute of Medical Biometry and Statistics Faculty of Medicine and Medical Center University of Freiburg Freiburg Germany Freiburg Center for Data Analysis and Modelling University of Freiburg Freiburg Germany Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin Humboldt-Universität zu Berlin Berlin Institute of Health Berlin Germany Donders Institute for Brain Cognition and Behaviour Radboud University Nijmegen the Netherlands Behavioral Science Institute Radboud University Nijmegen the Netherlands

Background Up to 30 % of pregnant individuals experience high levels of stress. At the same time, 15–20 % of new mothers develop postpartum depression, and 25–35 % experience postpartum anxiety. Mobile applications have the potential to provide an accessible, scalable solution to these mental health challenges. However, previous evidence indicates that none of the commercially available apps for perinatal depression and anxiety have been rigorously evaluated through randomized clinical trials (RCTs), and the quality of these apps remains moderate. In response to this gap, we aim to develop and empirically evaluate Powerly, a mobile app intervention designed to prevent postpartum depression and anxiety. Methods We will conduct a two-arm RCT with 140 healthy pregnant participants to assess the impact of Powerly use compared to care as usual (CAU). Powerly is based on cognitive behavioral therapy techniques and developed in consultation with stakeholders, including healthcare professionals and pregnant individuals. It will offer personalized psychological support tailored to users' needs for four weeks. Self-reported mental health assessments will be collected at baseline, after four weeks of app use, and six weeks postpartum. Discussion We anticipate that participants using Powerly will demonstrate significant improvements in mental health outcomes, including reduced rates of postpartum depression, compared to the CAU group. Additionally, we expect positive changes in emotion regulation, resilience, and mother and child outcomes, such as enhanced maternal bonding and a more positive birth experience. If proved effective, Powerly can offer a scalable, publicly accessible solution for pregnant individuals in need. Trial registration NCT06610552

关键词： Pregnancy Postpartum depression Postpartum anxiety Stress Mobile health Ecological momentary intervention

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Causal inference with multi-state models-estimands and estimators of the population-attributable fraction

arXiv

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arXiv 2019年

作者： Von Cube, Maja Schumacher, Martin Wolkewitz, Martin Institute of Medical Biometry and Statistics Faculty of Medicine and Medical Center University of Freiburg Freiburg Germany Freiburg Center for Data Analysis and Modelling University of Freiburg Freiburg Germany

The population-attributable fraction (PAF) is a popular epidemiological measure for the burden of a harmful exposure within a population. It is often interpreted causally as proportion of preventable cases after an elimination of exposure. Originally, the PAF has been defined for cohort studies of fixed length with a baseline exposure or cross-sectional studies. An extension of the definition to complex time-to-event data is not straightforward. We revise the proposed approaches in literature and provide a clear concept of the PAF for these data situations. The conceptualization is achieved by a proper differentiation between estimands and estimators as well as causal effect measures and measures of association. keywords:Causal effect measure, Competing risks, Excess fraction, Measure of association, Nosocomial infection, Time-dependent exposure. Copyright © 2019, The Authors. All rights reserved.

关键词： Risk assessment

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Chemoproteomik-basierte Identifikation von 4-Oxo-β-lactamen als Inhibitoren der Dipeptidylpeptidasen 8 und 9

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Angewandte Chemie 2022年第47期134卷

作者： Dr. Luís A. R. Carvalho Dr. Breyan Ross Lorenz Fehr Oguz Bolgi Svenja Wöhrle Dr. Kenneth M. Lum David Podlesainski Andreia C. Vieira Dr. Reiner Kiefersauer Rita Félix Dr. Tiago Rodrigues Dr. Susana D. Lucas Prof. Dr. Olaf Groß Dr. Ruth Geiss-Friedlander Prof. Dr. Benjamin F. Cravatt Prof. Dr. Robert Huber Prof. Dr. Markus Kaiser Prof. Dr. Rui Moreira Department of Pharmaceutical Sciences and Medicines Research Institute for Medicines (iMed.ULisboa) Faculdade de Farmácia Universidade de Lisboa Lisboa Av. Prof. Gama Pinto 1649-003 Lisboa Portugal Department of Chemistry The Scripps Research Institute La Jolla California 92037 USA Diese Autoren haben zu gleichen Teilen zu der Arbeit beigetragen. Contribution: Conceptualization (supporting) Data curation (equal) Formal analysis (equal) Investigation (equal) Writing - original draft (equal) Writing - review & editing (equal) Max-Planck Institut für Biochemie 82152 Planegg Deutschland Proteros Biostructures GmbH 82152 Planegg Deutschland Fakultät für Biologie Zentrum für Medizinische Biotechnologie Universität Duisburg-Essen 45117 Essen Deutschland Center of Biochemistry and Molecular Cell Research Albert-Ludwigs-Universität 79104 Freiburg Deutschland Contribution: Data curation (supporting) Formal analysis (supporting) Investigation (supporting) Institut für Neuropathologie Universitätsklinikum Freiburg 79106 Freiburg Deutschland Contribution: Data curation (supporting) Formal analysis (supporting) Investigation (supporting) Writing - review & editing (supporting) Contribution: Conceptualization (supporting) Data curation (supporting) Formal analysis (supporting) Supervision (supporting) Signalling Research Centres BIOSS and CIBSS University of Freiburg 79104 Freiburg Deutschland Contribution: Data curation (supporting) Formal analysis (supporting) Supervision (supporting) Contribution: Conceptualization (supporting) Data curation (supporting) Formal analysis (supporting) Supervision (supporting) Writing - original draft (supporting) Writing - review & editing (supporting) Contribution: Data curation (supporting) Formal analysis (equal) Supervision (supporting) Validation (equal) Fakultät für Chemie Technische Universität München 85747 Garching Deutschland Contribution: Conceptualization (supporting) Data curation (supporting) Formal analysis (equal) Supe

Die Dipeptidylpeptidasen 8 und 9 (DPP8/9) sind aufgrund ihrer wichtigen Rolle in biologischen Prozessen wie der Immunität und Tumorgenese in den letzten Jahren in den Fokus der Wirkstoffforschung gerückt. Der individuelle Beitrag der jeweiligen Protease innerhalb dieser Prozesse ist bisher jedoch meistens noch unbekannt. Die Untersuchung ihrer individuellen Funktion kann dabei von der Verfügbarkeit Protease-selektiver und chemisch-diverser Hemmstoffe profitieren. In dieser Arbeit stellen wir die durch Anwendung von Aktivitäts-basiertem Protein-Profiling (ABPP) entdeckten 4-Oxo-β-lactame als potente, nicht-Substrat-abgeleitete, nanomolare DPP8/9-Inhibitoren vor. Röntgenkristallographische Untersuchungen von Liganden-DPP-Komplexen offenbarten dabei unterschiedliche Ligandenbindungsmodi für DPP8 und DPP9, einschließlich einer neuartigen Adressierung einer erweiterten S2′ (eS2′)-Bindetasche in DPP8. Zusätzliche Assays bestätigten ihre Hemmwirkung sowohl auf biochemischer als auch auf zellulärer Ebene. Zusammenfassend führte unser kombinierter Ansatz aus chemischer Proteomik und strukturbasiertem Design somit zu der Entwicklung neuartiger DPP8/9-Inhibitoren mit einem alternativem molekularen Hemmmechanismus und einem bisher nicht erreichten Selektivitätsindex.

关键词： 4-Oxo-β-lactame Aktivitäts-basiertes Protein Profiling (ABPP) Dipeptidylpeptidasen 8/9 Proteomics Röntgenstrukturanalyse

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A magnetic avalanche as the central engine powering a solar flare

arXiv

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arXiv 2025年

作者： Chitta, L.P. Pontin, D.I. Priest, E.R. Berghmans, D. Kraaikamp, E. Rodriguez, L. Verbeeck, C. Zhukov, A.N. Krucker, S. Cuadrado, R. Aznar Calchetti, D. Hirzberger, J. Peter, H. Schühle, U. Solanki, S.K. Teriaca, L. Giunta, A.S. Auchère, F. Harra, L. Müller, D. Max-Planck-Institut für Sonnensystemforschung Göttingen37077 Germany School of Information and Physical Sciences University of Newcastle CallaghanNSW2308 Australia School of Mathematics and Statistics University of St Andrews St AndrewsKY16 9SS United Kingdom Solar-Terrestrial Centre of Excellence Solar Influences Data analysis Centre Royal Observatory of Belgium Brussels1180 Belgium Skobeltsyn Institute of Nuclear Physics Moscow State University Moscow119991 Russia Space Sciences Laboratory University of California BerkeleyCA94720 United States University of Applied Sciences and Arts Northwestern Switzerland WindischCH-5210 Switzerland Georges-Köhler-Allee 401a Freiburg79110 Germany RAL Space UKRI STFC Rutherford Appleton Laboratory DidcotOX11 0QX United Kingdom University of Catania Astrophysics Section Dept. of Physics and Astronomy Via S. Sofia 78 Catania95123 Italy Université Paris-Saclay CNRS Institut d’astrophysique spatiale Orsay91405 France Physikalisch-Meteorologisches Observatorium Davos World Radiation Center Davos Dorf7260 Switzerland Die Eidgenössische Technische Hochschule Zürich Zürich8093 Switzerland PO Box 299 Noordwijk2200 AG Netherlands

Solar flares are the most powerful, magnetically-driven, explosions in the heliosphere. The nature of magnetic energy release in the solar corona that heats the plasma and accelerates particles in a flare, however, remains poorly understood. Here, we report high-resolution coronal observations of a flare (SOL2024-09-30T23:47) by the Solar Orbiter mission that reveal initially weaker but rapid reconnection events, on timescales of at most a few seconds, leading to a more prominent activity of similar nature that explosively cause a flare. Signatures of this process are further imprinted on the widespread raining plasma blobs with short lifetimes, giving rise to the characteristic ribbon-like emission pattern associated with the flare. Our novel observations unveil the central engine of a flare and emphasize the crucial role of an avalanche-like magnetic energy release mechanism at work. Copyright © 2025, The Authors. All rights reserved.

关键词： Electric corona

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The population-attributable fraction for time-dependent exposures using dynamic prediction and landmarking

arXiv

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arXiv 2019年

作者： von Cube, Maja Schumacher, Martin Putter, Hein Timsit, Jéan-François de Velde, Cornelis van Wolkewitz, Martin Institute of Medical Biometry and Statistics Faculty of Medicine and Medical Center University of Freiburg Freiburg Germany Freiburg Center for Data Analysis and Modelling University of Freiburg Freiburg Germany Leiden University Medical Centre Department of Medical Statistics and Bioinformatics UMR 1137 IAME Inserm Université Paris Diderot Paris France APHP Medical and Infectious Diseases ICU Bichat Hospital Paris France Leiden University Medical Centre Department of Surgery Leiden Netherlands

The public health impact of a harmful exposure can be quantified by the population-attributable fraction (PAF). The PAF describes the attributable risk due to an exposure and is often interpreted as the proportion of preventable cases if the exposure could be extinct. Difficulties in the definition and interpretation of the PAF arise when the exposure of interest depends on time. Then, the definition of exposed and unexposed individuals is not straightforward. We propose dynamic prediction and landmarking to define and estimate a PAF in this data situation. Two estimands are discussed which are based on two hypothetical interventions that could prevent the exposure in different ways. Considering the first estimand, at each landmark the estimation problem is reduced to a time-independent setting. Then, estimation is simply performed by using a generalized-linear model accounting for the current exposure state and further (time-varying) covariates. The second estimand is based on counterfactual outcomes, estimation can be performed using pseudo-values or inverse-probability weights. The approach is explored in a simulation study and applied on two data examples. First, we study a large French database of intensive care unit patients to estimate the population-benefit of a pathogen-specific intervention that could prevent ventilator-associated pneumonia caused by the pathogen Pseudomonas aeruginosa. Moreover, we quantify the population-attributable burden of locoregional and distant recurrence in breast cancer patients. Copyright © 2019, The Authors. All rights reserved.

关键词： Intensive care units

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Coronal hole picoflare jets are progenitors of both fast and Alfvénic slow solar wind

arXiv

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arXiv 2024年

作者： Chitta, L.P. Huang, Z. D’Amicis, R. Calchetti, D. Zhukov, A.N. Kraaikamp, E. Verbeeck, C. Cuadrado, R. Aznar Hirzberger, J. Berghmans, D. Horbury, T.S. Solanki, S.K. Owen, C.J. Harra, L. Peter, H. Schühle, U. Teriaca, L. Louarn, P. Livi, S. Giunta, A.S. Hassler, D.M. Wang, Y.-M. Max-Planck-Institut für Sonnensystemforschung Göttingen37077 Germany Via Fosso del Cavaliere 100 Rome00133 Italy Solar-Terrestrial Centre of Excellence Solar Influences Data analysis Centre Royal Observatory of Belgium Brussels1180 Belgium Skobeltsyn Institute of Nuclear Physics Moscow State University Moscow119991 Russia Department of Physics Imperial College London LondonSW7 2AZ United Kingdom Mullard Space Science Laboratory Holmbury St MaryRH5 6NT United Kingdom Physikalisch-Meteorologisches Observatorium Davos World Radiation Center Davos Dorf7260 Switzerland Die Eidgenössische Technische Hochschule Zürich Zürich8093 Switzerland Georges-Köhler-Allee 401a Freiburg79110 Germany Institut de Recherche en Astrophysique et Planétologie CNRS Université de Toulouse CNES Toulouse France Southwest Research Institute San AntonioTX78238 United States RAL Space UKRI STFC Rutherford Appleton Laboratory DidcotOX11 0QX United Kingdom Southwest Research Institute BoulderCO80302 United States Space Science Division Naval Research Laboratory WashingtonDC20375 United States

Solar wind, classified by its bulk speed and the Alfvénic nature of its fluctuations, generates the heliosphere. The elusive physical processes responsible for the generation of the different types of this wind are a topic of active debate. Recent observations reveal intermittent jets, with kinetic energy in the picoflare range, emerging from dark areas of a polar coronal hole threaded by open magnetic field lines. These could substantially contribute to solar wind. However, their ubiquity and direct links to solar wind have not been established. Here, we report a unique set of remote-sensing and in situ observations from the Solar Orbiter spacecraft that establish a unified picture of fast and Alfvénic slow wind, connected to the similar widespread picoflare jet activity in two coronal holes. Radial expansion of coronal holes ultimately regulates the speed of the emerging wind. Copyright © 2024, The Authors. All rights reserved.

关键词： Solar wind

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