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19 Publications visible to you, out of a total of 19
Deep Learning and Explainable Artificial Intelligence for Improving Specificity and Detecting Metabolic Patterns in Newborn Screening

Abstract

Not specified

Authors: Elaine Zaunseder, Ulrike Mütze, Sven F. Garbade, Saskia Haupt, Stefan Kölker, Vincent Heuveline

Date Published: 5th Dec 2023

Publication Type: Journal

Explainable Artificial Intelligence for Improving a Session-Based Malware Traffic Classification with Deep Learning

Abstract

Not specified

Authors: Stefan Machmeier, Maximilian Hoecker, Vincent Heuveline

Date Published: 5th Dec 2023

Publication Type: Journal

Dominantly inherited micro-satellite instable cancer – the four Lynch syndromes - an EHTG, PLSD position statement

Abstract (Expand)

Abstract The recognition of dominantly inherited micro-satellite instable (MSI) cancers caused by pathogenic variants in one of the four mismatch repair ( MMR ) genes MSH2, MLH1, MSH6 and PMS2 has … MMR ) genes MSH2, MLH1, MSH6 and PMS2 has modified our understanding of carcinogenesis. Inherited loss of function variants in each of these MMR genes cause four dominantly inherited cancer syndromes with different penetrance and expressivities: the four Lynch syndromes. No person has an “average sex “or a pathogenic variant in an “average Lynch syndrome gene” and results that are not stratified by gene and sex will be valid for no one. Carcinogenesis may be a linear process from increased cellular division to localized cancer to metastasis. In addition, in the Lynch syndromes (LS) we now recognize a dynamic balance between two stochastic processes: MSI producing abnormal cells, and the host’s adaptive immune system’s ability to remove them. The latter may explain why colonoscopy surveillance does not reduce the incidence of colorectal cancer in LS, while it may improve the prognosis. Most early onset colon, endometrial and ovarian cancers in LS are now cured and most cancer related deaths are after subsequent cancers in other organs. Aspirin reduces the incidence of colorectal and other cancers in LS. Immunotherapy increases the host immune system’s capability to destroy MSI cancers. Colonoscopy surveillance, aspirin prevention and immunotherapy represent major steps forward in personalized precision medicine to prevent and cure inherited MSI cancer.

Authors: Pal Møller, Toni T. Seppälä, Aysel Ahadova, Emma J. Crosbie, Elke Holinski-Feder, Rodney Scott, Saskia Haupt, Gabriela Möslein, Ingrid Winship, Sanne W. Bajwa-ten Broeke, Kelly E. Kohut, Neil Ryan, Peter Bauerfeind, Laura E. Thomas, D. Gareth Evans, Stefan Aretz, Rolf H. Sijmons, Elizabeth Half, Karl Heinimann, Karoline Horisberger, Kevin Monahan, Christoph Engel, Giulia Martina Cavestro, Robert Fruscio, Naim Abu-Freha, Levi Zohar, Luigi Laghi, Lucio Bertario, Bernardo Bonanni, Maria Grazia Tibiletti, Leonardo S. Lino-Silva, Carlos Vaccaro, Adriana Della Valle, Benedito Mauro Rossi, Leandro Apolinário da Silva, Ivana Lucia de Oliveira Nascimento, Norma Teresa Rossi, Tadeusz Dębniak, Jukka-Pekka Mecklin, Inge Bernstein, Annika Lindblom, Lone Sunde, Sigve Nakken, Vincent Heuveline, John Burn, Eivind Hovig, Matthias Kloor, Julian R. Sampson, Mev Dominguez-Valentin

Date Published: 1st Dec 2023

Publication Type: Journal

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

Abstract (Expand)

Abstract Extensive whole-body models (WBMs) accounting for organ-specific dynamics have been developed to simulate adult metabolism. However, there is currently a lack of models representing infant …ls representing infant metabolism taking into consideration its special requirements in energy balance, nutrition, and growth. Here, we present a resource of organ-resolved, sex-specific, anatomically accurate models of newborn and infant metabolism, referred to as infant-whole-body models (infant-WBMs), spanning the first 180 days of life. These infant-WBMs were parameterised to represent the distinct metabolic characteristics of newborns and infants accurately. In particular, we adjusted the changes in organ weights, the energy requirements of brain development, heart function, and thermoregulation, as well as dietary requirements and energy requirements for physical activity. Subsequently, we validated the accuracy of the infant-WBMs by showing that the predicted neonatal and infant growth was consistent with the recommended growth by the World Health Organisation. We assessed the infant-WBMs’ reliability and capabilities for personalisation by simulating 10,000 newborn models, personalised with blood concentration measurements from newborn screening and birth weight. Moreover, we demonstrate that the models can accurately predict changes over time in known blood biomarkers in inherited metabolic diseases. By this, the infant-WBM resource can provide valuable insights into infant metabolism on an organ-resolved level and enable a holistic view of the metabolic processes occurring in infants, considering the unique energy and dietary requirements as well as growth patterns specific to this population. As such, the infant-WBM resource holds promise for personalised medicine, as the infant-WBMs could be a first step to digital metabolic twins for newborn and infant metabolism for personalised systematic simulations and treatment planning.

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

Date Published: 23rd Oct 2023

Publication Type: Journal

A Generalizable Approach for Network Flow Image Representation for Deep Learning

Abstract

Not specified

Authors: Stefan Machmeier, Manuel Trageser, Marcus Buchwald, Vincent Heuveline

Date Published: 16th Oct 2023

Publication Type: Journal

Finite element approximation of dielectrophoretic force driven flow problems

Abstract (Expand)

In this paper, we propose a full discretization scheme for the instationary thermal-electro-hydrodynamic (TEHD) Boussinesq equations. These equations model the dynamics of a non-isothermal, dielectric …f a non-isothermal, dielectric fluid under the influence of a dielectrophoretic (DEP) force. Our scheme combines an H 1 -conformal finite element method for spatial discretization with a backward differentiation formula (BDF) for time stepping. The resulting scheme allows for a decoupled solution of the individual parts of this multi-physics system. Moreover, we derive a priori convergence rates that are of first and second order in time, depending on how the individual ingredients of the BDF scheme are chosen and of optimal order in space. In doing so, special care is taken of modeling the DEP force, since its original form is a cubic term. The obtained error estimates are verified by numerical experiments.

Authors: Philipp Gerstner, Vincent Heuveline

Date Published: 1st May 2023

Publication Type: Journal

Multi-view-AE: A Python package for multi-view autoencoder models

Abstract

Not specified

Authors: Ana Lawry Aguila, Alejandra Jayme, Nina Montaña-Brown, Vincent Heuveline, Andre Altmann

Date Published: 1st May 2023

Publication Type: Journal

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