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Feasibility study on integrating morphological and transcriptomic data for identifying teratogenic molecular markers in zebrafish embryo toxicity testing

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compUTATIONAL TOXICOLOGY 2025年 34卷

作者： Wehr, Matthias M. Witters, Hilda Remy, Silvie Schultz, Bruce Jacobs, Marc Escher, Sylvia E. Fraunhofer Inst Toxicol & Expt Med ITEM Hannover Germany VITO Flemish Inst Technol Res NV HLTH Mol Belgium Fraunhofer Inst Algorithms & Sci Comp SCAI St Augustin Germany

To create a resource for the integration of developmental toxicity new approach methodologies (NAM) data, zebrafish embryo toxicity test (ZET) data were curated and the zeTera database was created. To capture observations of the morphological alteration potential of chemicals, the zeTera database contains experimental study designs and morphological observation data from the literature. Observations of alterations recorded in zeTera were mapped to ontologies and terms were harmonized. In addition, public transcriptomics repositories were mined for data on zebrafish embryos under chemically induced stress. The re-analyzed datasets were compiled into the zetOmics database for the identification of biomarkers of teratogenicity. To identify data-rich compounds, an overlap of both databases was formed, and compounds were grouped based on structural similarities. To identify the molecular drivers of teratogenic toxicants, Triadimefon was chosen as model compound for its well-documented teratogenic effects and known mode of action (MOA). We have compiled existing data about Triadimefon from zeTera and conducted additional testing using the ZET, with additional gene expression measurements for data gap filling. From the literature search we identified the adverse outcome pathway (AOP) of triadimefon leading to craniofacial malformations by disruption of retinoic acid metabolism. Transcriptomic response in a concentration dependent manner was observed as early as 24 h post fertilization (hpf) with consistent, statistically significant, differential expression spanning the later timepoints. A set of 5 genes (cyp26a1, dhrs3b, cyp26b1, cthrc1a, and cd248b) were selected for their differential expression pattern across time and concentration. These biomarkers were further confirmed using read across approach including data from related structures.

关键词： Zebrafish embryo toxicity Morphological alteration Teratogenicity Transcriptomics Data mining

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Estimating the causal impact of non-pharmaceutical interventions on COVID-19 spread in seven EU countries via machine learning

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sciENTIFIC REPORTS 2025年第1期15卷 1-16页

作者： Guski, Jannis Botz, Jonas Froehlich, Holger Fraunhofer Inst Algorithms & Sci Comp SCAI Dept Bioinformat D-53757 St Augustin Germany Univ Bonn Bonn Aachen Int Ctr Informat Technol B IT D-53115 Bonn Germany

During the COVID-19 pandemic, Non-Pharmaceutical Interventions (NPIs) were imposed all over Europe with the intent to reduce infection spread. However, reports on the effectiveness of those measures across different European countries are inconclusive up to now. Moreover, attempts to predict the effect of NPIs in a prospective and dynamical manner with the aim to support decision makers in future global health emergencies are largely lacking. Here, we explore causal machine learning to isolate causal effects of NPIs in observational public health data from seven EU countries, taking into account specific challenges like their sequential nature, effect heterogeneity, time-dependent confounding and lack of robustness due to violated assumptions. In a pseudo-prospective scenario planning analysis, we investigate which recommendations our model would have made during the second wave of the pandemic in Germany, demonstrating its capacity to generalize to the near future and identifying effective NPIs. In retrospect, our approach indicates that a wide range of response measures curbed COVID-19 across countries, especially in the early phases of the pandemic. Interestingly, this includes controversial interventions like strict school and border closures, but also recommendation-based policies in Sweden. Finally, we discuss important data- and modeling-related considerations that may optimize causal effect estimation in future pandemics.

关键词： Causal machine learning Policy recommendation Time-dependent confounding

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Thermodynamical and electrochemical model of a PEM electrolyzer plant in the megawatt range with a literature analysis of the fitting parameters

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INTERNATIONAL JOURNAL OF HYDROGEN ENERGY 2025年 104卷 567-583页

作者： Pfennig, Malte Schiffer, Barbara Clees, Tanja Univ Appl Sci Hsch Bonn Rhein Sieg Inst Technol Resource & Energy Efficient Engn TREE Dept Engn & Commun Grantham Allee 20 D-53757 St Augustin Germany Fraunhofer Inst Algorithms & Sci Comp SCAI D-53757 St Augustin Germany

In the coming years, the European Union plans to establish Proton Exchange Membrane (PEM) electrolyzers, each with a 100 MW capacity. However, the selection of their locations has not been systematically optimized to leverage potential benefits, such as utilizing waste heat from large facilities for district heating. Presently, there are hardly any corresponding system models in the literature dynamically simulating a PEM electrolyzer of this size. This paper introduces a first model approach for such systems, drawing on parameters from existing literature. It addresses the inconsistency found in the literature regarding the use of the exchange current density, which varies by a factor of 109. A novel optimization process is developed by using an auxiliary parameter to fit the exchange current density with a newfound condition between the anode and cathode side. The outcome is a comprehensive model of a PEM electrolyzer plant, exemplarily adapted to the Siemens Silyzer 300.

关键词： PEM Electrolyzer Hydrogen Thermal energy Modeling

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comparing scientific Machine Learning With Population Pharmacokinetic and Classical Machine Learning Approaches for Prediction of Drug Concentrations

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CPT-PHARMACOMETRICS & SYSTEMS PHARMACOLOGY 2025年第4期14卷 759-769页

作者： Valderrama, Diego Teplytska, Olga Koltermann, Luca Marie Trunz, Elena Schmulenson, Eduard Fritsch, Achim Jaehde, Ulrich Froehlich, Holger Fraunhofer Inst Algorithms & Sci Comp SCAI Dept Bioinformat St Augustin Germany Univ Bonn Inst Pharm Dept Clin Pharm Bonn Germany Univ Bonn Inst Comp Sci 2 Visual Comp Bonn Germany Univ Bonn Bonn Aachen Int Ctr Informat Technol B IT Bonn Germany

A variety of classical machine learning (ML) approaches has been developed over the past decade aiming to individualize drug dosages based on measured plasma concentrations. However, the interpretability of these models is challenging as they do not incorporate information on pharmacokinetic (PK) drug disposition. In this work we compare drug plasma concentraton predictions of well-known population PK (PopPK) modeling with classical machine learning models and a newly proposed scientific machine learning (MMPK-sciML) framework. MMPK-sciML allows to estimate PopPK parameters and their inter-individual variability (IIV) using multimodal covariate data of each patient and does not require assumptions about the underlying covariate relationships. A dataset of 541 fluorouracil (5FU) plasma concentrations as example for an intravenously administered drug and a dataset of 302 sunitinib and its active metabolite concentrations each as example for an orally administered drug were used for analysis. Whereas classical ML models were not able to describe the data sufficiently, MMPK-sciML allowed us to obtain accurate drug plasma concentration predictions for test patients. In case of 5FU, goodness-of-fit shows that the MMPK-sciML approach predicts drug plasma concentrations more accurately than PopPK models. For sunitinib, we observed slightly less accurate drug concentration predictions compared to PopPK. Overall, MMPK-sciML has shown promising results and should therefore be further investigated as a valuable alternative to classical PopPK modeling, provided there is sufficient training data.

关键词： concentration prediction drug therapy machine learning oncology pharmacokinetics scientific machine learning

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Predictive modeling to uncover Parkinson's disease characteristics that delay diagnosis

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NPJ PARKINSONS DISEASE 2025年第1期11卷 1-7页

作者： Haehnel, Tom Raschka, Tamara Klucken, Jochen Glaab, Enrico Corvol, Jean-Christophe Falkenburger, Bjoern H. Froehlich, Holger Fraunhofer Inst Algorithms & Sci Comp SCAI Dept Bioinformat St Augustin Germany TUD Dresden Univ Technol Med Fac Dept Neurol Dresden Germany TUD Dresden Univ Technol Univ Hosp Carl Gustav Carus Dresden Germany Univ Bonn Bonn Aachen Int Ctr IT Bonn Germany Univ Luxembourg Luxembourg Ctr Syst Biomed LCSB Biomed Data Sci Esch Sur Alzette Luxembourg Luxembourg Inst Hlth LIH Strassen Luxembourg Ctr Hosp Luxembourg CHL Esch Sur Alzette Luxembourg Sorbonne Univ Pitie Salpetriere Hosp AP HP Paris Brain Inst ICMCNRSInsermDept Neurol Paris France German Ctr Neurodegenerat Dis DZNE Dresden Germany

PD patients present with diverse symptoms, complicating timely diagnosis. We analyzed 1124 PD trajectories using a novel model-based approach to estimate whether diagnosis was early or late compared to cohort averages. Higher age, specific non-motor symptoms, and fast disease progression were linked to later diagnosis, while gait impairment led to earlier diagnosis. Our findings are in line with a biological definition of PD that extends beyond classical motor symptoms.

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STATISTICAL ANALYSIS AND ROBUST OPTIMIZATION OF FORMING PROCESSES AND FORMING-TO-CRASH PROCESS CHAINS

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INTERNATIONAL JOURNAL OF MATERIAL FORMING 2010年第1期3卷 45-48页

作者： Clees, T. Steffes-Iai, D. Helbig, M. Sun, D. -Z. Fraunhofer Inst Algorithms & Sci Comp SCAI Aachen Germany Fraunhofer Inst Mech Mat IWM Aachen Germany

In this paper, a novel strategy for statistical analysis and multi-objective robust design-parameter optimization of forming processes as well as forming-to-crash process chains is discussed and results presented for a ZStE340 metal blank of a B-pillar. The strategy comprises both physical experiments and numerical simulation and is built upon a novel material and damage model as well as several software tools which allow for an efficient sensitivity, stability and robustness analysis, even for simulation results on highly resolved grids.

关键词： simulation material modeling process chains random fields robust design sensitivity optimization

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Petri and how he saw the world

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SOFTWARE AND SYSTEMS MODELING 2015年第2期14卷 727-733页

作者： Smith, Einar Fraunhofer Inst Algorithms & Sci Comp SCAI Schloss Birlinghoven D-53754 St Augustin Germany

This article is a short summary and explanation of the scientific work of Carl Adam Petri. The very basics of net theory are sufficient to understand it.

关键词： Petri Nets Concurrency Asynchronous systems Discrete density Measuring theory

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Decomposition of ordinary differential equations

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BULLETIN OF MATHEMATICAL sciENCES 2017年第3期7卷 575-613页

作者： Schwarz, Fritz Fraunhofer Inst Algorithms & Sci Comp SCAI D-53754 St Augustin Germany

Decompositions of linear ordinary differential equations (ode's) into components of lower order have successfully been employed for determining their solutions. Here this approach is generalized to nonlinear ode's. It is not based on the existence of Lie symmetries, in that it is a genuine extension of the usual solution algorithms. If an equation allows a Lie symmetry, the proposed decompositions are usually more efficient and often lead to simpler expressions for the solution. For the vast majority of equations without a Lie symmetry decomposition is the only available systematic solution procedure. Criteria for the existence of diverse decomposition types and algorithms for applying them are discussed in detail and many examples are given. The collection of Kamke of solved equations, and a tremendeous compilation of random equations are applied as a benchmark test for comparison of various solution procedures. Extensions of these proceedings for more general types of ode's and also partial differential equations are suggested.

关键词： Ordinary differential equations Decomposition Exact solutions

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Flexible docking under pharmacophore type constraints

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JOURNAL OF compUTER-AIDED MOLECULAR DESIGN 2002年第2期16卷 129-149页

作者： Hindle, SA Rarey, M Buning, C Lengauer, T Fraunhofer Inst Algorithms & Sci Comp FhI SCAI Schloss Birlinghoven D-53754 St Augustin Germany

FlexX-Pharm, an extended version of the flexible docking tool FlexX, allows the incorporation of information about important characteristics of protein-ligand binding modes into a docking calculation. This information is introduced as a simple set of constraints derived from receptor-based type pharmacophore features. The constraints are determined by selected FlexX interactions and inclusion volumes in the receptor active site. They guide the docking process to produce a set of docking solutions with particular properties. By applying a series of look-ahead checks during the flexible construction of ligand fragments within the active site, FlexX-Pharm determines which partially built docking solutions can potentially obey the constraints. Solutions that will not obey the constraints are deleted as early as possible, often decreasing the calculation time and enabling new docking solutions to emerge. FlexX-Pharm was evaluated on various individual protein-ligand complexes where the top docking solutions generated by FlexX had high root mean square deviations (RMSD) from the experimentally observed binding modes. FlexX-Pharm showed an improvement in the RMSD of the top solutions in most cases, along with a reduction in run time. We also tested FlexX-Pharm as a database screening tool on a small dataset of molecules for three target proteins. In two cases, FlexX-Pharm missed one or two of the active molecules due to the constraints selected. However, in general FlexX-Pharm maintained or improved the enrichment shown with FlexX, while completing the screen in considerably less run time.

关键词： constraint flexible docking molecular modeling pharmacophore protein-ligand interaction virtual screening

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Linking factors between groundstate p_c in 2D iso- and anisotropic ±J Ising models

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PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 2006年第1-4期359卷 399-414页

作者： Bendisch, J Fraunhofer Inst Algorithms & Sci Computat SCAI D-53754 St Augustin Germany

For honeycomb, square and triangular lattices we consider the groundstate threshold p(c) of spontaneous absolute magnetization in iso- and anisotropic random +/- J Ising models from so-called uniform classes HCz, SQ(z), TRz,. The class index z(>= 1) gives a fixed number of so-called PAF-bonds on the plaquette perimeter. A PAF-bond is a bond which has a positive (P) probability p to be antiferromagnetic (AF) and the probability 1 - p to be ferromagnetic where p has the same value for all the PAF-bonds in a considered lattice. The non-PAF-bonds in the lattice are ferromagnetic. In [Achilles et al., Physica A 275 (2000) 178], for each of the uniform classes HC1,..., HC6, SQ(1),..., SQ(4), TR1,..., TR3 we proposed a so-called basic minimal (maximal) model to obtain the minimal (maximal) p(c)-value in the underlying class. Moreover, Supported by estimates from simulations, concerning these basic models, we gave presumably exact values for the minimal (maximal) p(c). Here we show that the predicted p(c)-values are linked by meaningful factors. To this end, in essence, z-values (1, 2,..., 6) and coordination numbers (Delta(hc) = 3, Delta(sq) = 4, Delta(tr) = 6) are used. Typical factors are (Delta(sq) - 1)/(Delta(hc) - 1) or z(1)/z(2)>= 1. Especially, the minimal model case, with its 13 basic models fits in very well. Furthermore, for in-between-models of a uniform class, p, is approximated by linear interpolation between p(c,min) and p(c,max) from basic minimal and maximal models. (c) 2005 Elsevier B.V. All rights reserved.

关键词： random 2D king spin glasses groundstate phase transitions minimal matchings of frustrated plaquettes

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