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101 Publications visible to you, out of a total of 101
Comparative evaluation of standard machine learning models for liver fibrosis detection

Abstract

Not specified

Authors: Marcus Buchwald, Pascal Memmesheimer, Arash Dooghaie Moghadam, Ines Tuschner, Laura Santamaria Suarez, Timo Itzel, Christoph Antoni, Jimmy Daza, Catharina Gerhards, Michael Neumaier, Christop Brochhausen, Peter R. Galle, Matthias Ebert, Arndt Weinmann, Jürgen Hesser, Vincent Heuveline, Andreas Teufel

Date Published: 10th Jan 2025

Publication Type: Journal

Digital-Tier Strategy Improves Newborn Screening for Glutaric Aciduria Type 1

Abstract (Expand)

Glutaric aciduria type 1 (GA1) is a rare inherited metabolic disease increasingly included in newborn screening (NBS) programs worldwide. Because of the broad biochemical spectrum of individuals with …dividuals with GA1 and the lack of reliable second-tier strategies, NBS for GA1 is still confronted with a high rate of false positives. In this study, we aim to increase the specificity of NBS for GA1 and, hence, to reduce the rate of false positives through machine learning methods. Therefore, we studied NBS profiles from 1,025,953 newborns screened between 2014 and 2023 at the Heidelberg NBS Laboratory, Germany. We identified a significant sex difference, resulting in twice as many false-positives male than female newborns. Moreover, the proposed digital-tier strategy based on logistic regression analysis, ridge regression, and support vector machine reduced the false-positive rate by over 90% compared to regular NBS while identifying all confirmed individuals with GA1 correctly. An in-depth analysis of the profiles revealed that in particular false-positive results with high associated follow-up costs could be reduced significantly. In conclusion, understanding the origin of false-positive NBS and implementing a digital-tier strategy to enhance the specificity of GA1 testing may significantly reduce the burden on newborns and their families from false-positive NBS results.

Authors: Elaine Zaunseder, Julian Teinert, Nikolas Boy, Sven F. Garbade, Saskia Haupt, Patrik Feyh, Georg F. Hoffmann, Stefan Kölker, Ulrike Mütze, Vincent Heuveline

Date Published: 1st Dec 2024

Publication Type: Journal

Dielectrophoretic force-enhanced thermal convection within a horizontal cylindrical annulus

Abstract (Expand)

This study investigates, both experimentally and numerically the flow of a dielectric fluid confined between two concentric, differentially heated, horizontally aligned cylinders subjected to a 200 Hz …ed to a 200 Hz alternating radial electric field. A wide-gap annular setup with a length 20 times larger than the gap size is utilized in this investigation. The study focuses exclusively on the outward heating configuration, meaning the inner cylinder is hotter than the outer one. The electric field, in conjunction with the temperature gradient, triggers thermal electro-hydrodynamic instability caused by the application of dielectrophoretic force. when the applied electric tension exceeds a critical value for specific temperature gradients between the cylinders, the flow symmetry in the gap is disturbed. The instability manifests as periodically oscillating vortices occurring on top of the gap. A notable increase in heat transfer efficiency accompanies the onset of instability. The experimental and numerical results demonstrate quantitative and qualitative agreement.

Authors: M. H. Hamede, J. Roller, A. Meyer, V. Heuveline, C. Egbers

Date Published: 1st Dec 2024

Publication Type: Journal

Dynamic whole-body models for infant metabolism

Abstract (Expand)

1 Abstract Comprehensive, sex-specific whole-body models (WBMs) accounting for organ-specific metabolism have been developed to allow for the simulation of adult and infant metabolism. These WBMs are …nfant metabolism. These WBMs are evaluated daily, giving insights into metabolic flux changes that occur in one day of an infant’s or adult’s life. However, for medical applications, such as in metabolic diseases and their treatment, an evaluation and concentration predictions on a shorter time scale would be beneficial. Therefore, we developed a dynamic infant-WBM that couples metabolite dynamics in short time frames through physiology-based pharma-cokinetic models with the existing infant whole-body models. We then tailored the dynamic infant-WBM enabling the prediction of isovalerylcarnitine (C5), a clinical biomarker used for the inherited metabolic disease isovaleric aciduria (IVA). Our results show that, as expected, the predicted C5 concentrations exceeded the newborn screening thresholds during the time (36 - 72 hours) newborn screening blood samples are taken in the IVA models but not in models simulating healthy infants. We also demonstrate how the dynamic infant-WBMs can be used to test the effect changes in dietary intake have on the biomarker. Since the dynamic infant-WBMs were parametrised with literature-derived experimental or estimated values, we show how uncertainty quantification can be applied to quantify the parameter uncertainties. We found that the fractional unbound plasma needed to be estimated correctly, as this parameter strongly impacted C5 concentration predictions of the dynamic infant-WBMs. Overall, the dynamic infant-WBMs hold promise for personalised medicine, as it enables personalised biomarker concentration predictions of healthy and diseased infant metabolism in various time intervals.

Authors: Elaine Zaunseder, Faiz Khan Mohammad, Ulrike Mütze, Stefan Kölker, Vincent Heuveline, Ines Thiele

Date Published: 26th Nov 2024

Publication Type: Journal

KI-Morph – User-friendly large-scale image analysis & AI on bwHPC systems

Abstract (Expand)

Artificial Intelligence (AI) has become indispensable for analyzing large-scale datasets, particularly in the realm of 3D image volumes. However, effectively harnessing AI for such tasks often requires … advanced algorithms and high-performance computing (HPC) resources, presenting significant challenges for non-technical users. To overcome these barriers, we present KI-Morph, a novel software platform for large-scale image analysis seamlessly integrated with the bwHPC infrastructure. It offers a user-friendly interface, enabling sophisticated AI-driven analysis without requiring technical expertise in either AI or HPC. KI-Morph prioritizes data privacy and sovereignty, ensuring that users retain full control over their data. Additionally, the components developed for the platform support researchers also with science outreach by enabling the creation of interactive online visualizations, for example using the 2D, 3D and augmented reality viewers.

Authors: Vincent Heuveline, Alexander Zeilmann

Date Published: 26th Sep 2024

Publication Type: InProceedings

Personalized metabolic whole-body models for newborns and infants predict growth and biomarkers of inherited metabolic diseases

Abstract

Not specified

Authors: Elaine Zaunseder, Ulrike Mütze, Jürgen G. Okun, Georg F. Hoffmann, Stefan Kölker, Vincent Heuveline, Ines Thiele

Date Published: 1st Aug 2024

Publication Type: Journal

Using CutFEM for solving the linearized Poisson-Boltzmann equation: Introductory application in HiFlow3

Abstract (Expand)

The Poisson-Boltzmann equation(PBE) is a fundamental equation for accurate description of electrostatics in ionic solutions or plasma. Hence, it finds application in a wide variety of fields including … plasma physics, computational biology, colloidal and interface science and chemistry. In this preprint, we describe a first approach for solving it in a linearized setup using the CutFEM method in the software framework HiFlow3. The considered methods are easy to use, but not oriented towards extracting optimal computing time. Forthis purpose,the weak form of the linear PBE is first derived. Then, the CutFEM based numerical method is proposed. Finally, the most important code sections in HiFlow 3 are explained in more details. The electrostatic potential for ubiquitin and the adenovirus virion molecules are calculated and presented in a numerical example at the end of the paper.

Authors: Jonas Roller, Valentin Schmid, Philipp Gerstner, Jakob Nießner, Vincent Heuveline

Date Published: 18th Jul 2024

Publication Type: Journal

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