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This document created within the European Coordination and Support Action (CSA) of the EDITH (Ecosystem Digital Twins in Healthcare) project describes the current landscape of formatting and description standards, terminologies and metadata guidelines for virtual human twins (VHTs). It refers to corresponding biomedical data, simulation models and workflows, as well as their metadata relevant for the definition, implementation, and simulation of Digital Twins in Healthcare (DTHs). It comprises both, ISO and community standards and lists the relevant standards and terminologies describing the modelling process, the integration of domain-specific medical research data with routine data from electronic health records, the documentation of data provenance, the validation process for biomedical, physiological, bio-signaling and other healthcare data and models. The document also reveals needs and gaps in the current standards landscape to drive the further development of such standards. Therefore, remarks and comments on how to improve existing standards or on areas for which standards are still missing are very welcome.

Author: Gerhard Mayer, Martin Golebiewski

Date Published: 17th Jan 2024

Publication Type: Tech report

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This document provides a guideline for using and implementing standards, terminologies, and metadata guidelines when setting up, executing, and archiving virtual human twins. It is created within thehe European Coordination and Support Action (CSA) of the EDITH (Ecosystem Digital Twins in Healthcare) project. The aim of this implementation guide is two-fold: First it gives hints to the modelers, which steps they should follow in the model building process and which standards, terminologies, and guidelines (depending on their modelling domain) they should use in defining their biomedical and healthcare models. Second it is intended as a practical guide for implementers giving hints, which standards, terminologies, and guidelines should be supported in the long-term by the simulation environment consisting of the repository, the simulation platform, and the workflow execution engines. Initially it suffices if they support all formats and annotations used by the demonstrator use cases. To get an overview and access information on the standards, terminologies, and metadata guidelines referenced in this document, there also is an EDITH FairSharing collection available: https://fairsharing.org/4787

Author: Gerhard Mayer, Martin Golebiewski

Date Published: 17th Jan 2024

Publication Type: Tech report

Abstract (Expand)

Hydrogen atom transfer (HAT) reactions are important in many biological systems. As these reactions are hard to observe experimentally, it is of high interest to shed light on them using simulations. Here, we present a machine learning model based on graph neural networks for the prediction of energy barriers of HAT reactions in proteins. As input, the model uses exclusively non-optimized structures as obtained from classical simulations. It was trained on more than 17 000 energy barriers calculated using hybrid density functional theory. We built and evaluated the model in the context of HAT in collagen, but we show that the same workflow can easily be applied to HAT reactions in other biological or synthetic polymers. We obtain for relevant reactions (small reaction distances) a model with good predictive power (R2 ∼ 0.9 and mean absolute error of <3 kcal mol−1). As the inference speed is high, this model enables evaluations of dozens of chemical situations within seconds. When combined with molecular dynamics in a kinetic Monte-Carlo scheme, the model paves the way toward reactive simulations.

Authors: Kai Riedmiller, Patrick Reiser, Elizaveta Bobkova, Kiril Maltsev, Ganna Gryn'ova, Pascal Friederich, Frauke Gräter

Date Published: 16th Jan 2024

Publication Type: Journal

Abstract (Expand)

Hydrogen atom transfer (HAT) reactions are important in many biological systems. As these reactions are hard to observe experimentally, it is of high interest to shed light on them using simulations. Here, we present a machine learning model based on graph neural networks for the prediction of energy barriers of HAT reactions in proteins. As input, the model uses exclusively non-optimized structures as obtained from classical simulations. It was trained on more than 17 000 energy barriers calculated using hybrid density functional theory. We built and evaluated the model in the context of HAT in collagen, but we show that the same workflow can easily be applied to HAT reactions in other biological or synthetic polymers. We obtain for relevant reactions (small reaction distances) a model with good predictive power (R2 ∼ 0.9 and mean absolute error of <3 kcal mol−1). As the inference speed is high, this model enables evaluations of dozens of chemical situations within seconds. When combined with molecular dynamics in a kinetic Monte-Carlo scheme, the model paves the way toward reactive simulations.

Authors: Kai Riedmiller, Patrick Reiser, Elizaveta Bobkova, Kiril Maltsev, Ganna Gryn’ova, Pascal Friederich, Frauke Gräter

Date Published: 16th Jan 2024

Publication Type: Journal

Abstract (Expand)

Abstract The dominant mechanism forming multiple stellar systems in the high-mass regime ( M *  ≳ 8  M ⊙ ) remained unknown because direct imaging of multiple protostellar systems at early phases of ⊙ ) remained unknown because direct imaging of multiple protostellar systems at early phases of high-mass star formation is very challenging. High-mass stars are expected to form in clustered environments containing binaries and higher-order multiplicity systems. So far only a few high-mass protobinary systems, and no definitive higher-order multiples, have been detected. Here we report the discovery of one quintuple, one quadruple, one triple and four binary protostellar systems simultaneously forming in a single high-mass protocluster, G333.23–0.06, using Atacama Large Millimeter/submillimeter Array high-resolution observations. We present a new example of a group of gravitationally bound binary and higher-order multiples during their early formation phases in a protocluster. This provides the clearest direct measurement of the initial configuration of primordial high-order multiple systems, with implications for the in situ multiplicity and its origin. We find that the binary and higher-order multiple systems, and their parent cores, show no obvious sign of disk-like kinematic structure. We conclude that the observed fragmentation into binary and higher-order multiple systems can be explained by core fragmentation, indicating its crucial role in establishing the multiplicity during high-mass star cluster formation.

Authors: Shanghuo Li, Patricio Sanhueza, Henrik Beuther, Huei-Ru Vivien Chen, Rolf Kuiper, Fernando A. Olguin, Ralph E. Pudritz, Ian W. Stephens, Qizhou Zhang, Fumitaka Nakamura, Xing Lu, Rajika L. Kuruwita, Takeshi Sakai, Thomas Henning, Kotomi Taniguchi, Fei Li

Date Published: 15th Jan 2024

Publication Type: Journal

Abstract (Expand)

The merger of a white dwarf (WD) and a neutron star (NS) is a relatively common event that will produce an observable electromagnetic signal. Furthermore, the compactness of these stellar objects makes them an interesting candidate for gravitational wave (GW) astronomy, potentially being in the frequency range of LISA and other missions. To date, three-dimensional simulations of these mergers have not fully modelled the WD disruption, or have used lower resolutions and have not included magnetic fields even though they potentially shape the evolution of the merger remnant. In this work, we simulate the merger of a 1.4M_⊙NS with a 1M_⊙carbon oxygen WD in the magnetohydrodynamic moving mesh code \AREPO. We find that the disruption of the WD forms an accretion disk around the NS, and the subsequent accretion by the NS powers the launch of strongly magnetized, mildly relativistic jets perpendicular to the orbital plane. Although the exact properties of the jets could be altered by unresolved physics around the NS, the event could result in a transient with a larger luminosity than kilonovae. We discuss possible connections to fast blue optical transients (FBOTs) and long-duration gamma-ray bursts. We find that the frequency of GWs released during the merger is too high to be detectable by the LISA mission, but suitable for deci-hertz observatories such as LGWA, BBO or DECIGO.

Authors: J. Moran-Fraile, F. K. Roepke, R. Pakmor, M. A. Aloy, S. T. Ohlmann, F. R. N. Schneider, G. Leidi

Date Published: 5th Jan 2024

Publication Type: Journal

Abstract (Expand)

Small Ubiquitin-related modifiers of the SUMO family regulate thousands of proteins in eukaryotic cells. Many SUMO substrates, effectors and enzymes carry short motifs (SIMs) that mediate low affinity interactions with SUMO proteins. This raises the question how specificity is achieved in target selection, SUMO paralogue choice and SUMO-dependent interactions. A unique but poorly understood feature of SUMO proteins is their intrinsically disordered N-terminus. We reveal a function for N-termini of human, C. elegans, and yeast SUMO proteins as intramolecular inhibitors of SUMO-SIM interactions. Mutational analyses, NMR spectroscopy, and Molecular Dynamics simulations indicate that SUMO's N-terminus can inhibit SIM binding by fast and fuzzy interactions with SUMO‘s core. Deletion of the C. elegans SUMO1 N-terminus leads to p53-dependent apoptosis during germline development, indicating an important role of SUMO's N-termini in DNA damage repair. Our findings reveal a mechanism of disorder-based autoinhibition that contributes to the specificity of SUMOylation and SUMO-dependent interactions.

Authors: Stefan Richter, Fan Jin, Tobias Ritterhoff, Aleksandra Fergin, Eric Maurer, Andrea Frank, Alex Hajnal, Rachel Klevit, Frauke Gräter, Annette Flotho, Frauke Melchior

Date Published: 5th Jan 2024

Publication Type: Journal

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