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91 Publications visible to you, out of a total of 91
Implementation Techniques for SPMD Kernels on CPUs

Abstract

Not specified

Authors: Joachim Meyer, Aksel Alpay, Sebastian Hack, Holger Fröning, Vincent Heuveline

Date Published: 18th Apr 2023

Publication Type: Journal

One Pass to Bind Them: The First Single-Pass SYCL Compiler with Unified Code Representation Across Backends

Abstract

Not specified

Authors: Aksel Alpay, Vincent Heuveline

Date Published: 18th Apr 2023

Publication Type: Journal

ACSEG: AUTOMATED 3D CYTOPLASM SEGMENTATION IN SOFT X-RAY TOMOGRAPHY

Abstract (Expand)

The structure of cells is a key to understanding cellular function, diagnosis of pathological conditions, and development of new treatments. Soft X-ray tomography (SXT) is a unique tool to image cellular … structure without fixation or labeling at high spatial resolution and throughput. Ongoing improvements in faster acquisition times increase demand for accelerated image analysis. Currently, the automatic segmentation of cellular structures is a major bottleneck in the SXT data analysis pipeline. In this paper, we introduce an automated 3D cytoplasm segmentation model - ACSeg - by use of semi-automatically segmented labels and 3D U-Net, implemented in the online platform Biomedisa. The segmentation model is trained on semi-automatically labeled datasets and shows rapid convergence to high-accuracy segmentation, therefore reducing time and labor. ACSeg trained on 43 SXT tomograms of human immune T cells, the model successfully segmented unseen SXT tomograms of human hepatocyte-derived carcinoma cells, mouse microglia, and embryonic fibroblast cells. Furthermore, we could diversify the model by adding only 6 specific SXT tomograms, showing the potential for the development of an optimal experimental design. The ACSeg is published on the open image segmentation platform Biomedisa, enabling high-throughput analysis of cell volume and structure of cytoplasm in diverse cell types. The approach can be expanded for automatic segmentation of other organelles visualized by SXT, providing means for structural analysis of cell remodeling under different pathogens at statistically significant sizes, therefore enabling the development of novel drug treatments.

Authors: Ayse Erozan, Philipp Lösel, Vincent Heuveline, Venera Weinhardt

Date Published: 5th Apr 2023

Publication Type: Journal

A “two-in-one hit” model of shortcut carcinogenesis in MLH1 Lynch syndrome carriers

Abstract

Not specified

Authors: Aysel Ahadova, Albrecht Stenzinger, Toni Seppälä, Robert Hüneburg, Matthias Kloor, Hendrik Bläker, Jan-Niklas Wittemann, Volker Endris, Leonie Gerling, Veit Bertram, Marie Theres Neumuth, Johannes Witt, Sebastian Graf, Glen Kristiansen, Oliver Hommerding, Saskia Haupt, Alexander Zeilmann, Vincent Heuveline, Daniel Kazdal, Johannes Gebert, Magnus von Knebel Doeberitz, Jukka-Pekka Mecklin, Jacob Nattermann

Date Published: 11th Mar 2023

Publication Type: Journal

VTABLE HIJACKING: OBJECT TYPE INTEGRITY FOR RUN- TIME TYPE INFORMATION

Abstract (Expand)

Attackers try to hijack the control-flow of a victim’s process by exploiting a run-time vulnerability. Vtable hijacking is a state-of-the-art technique adversaries use to conduct control-flow hijacking … attacks. It abuses the reliance of language constructs related to polymorphism on dynamic type information. The Control Flow Integrity (CFI) security policy is a well-established solution designed to prevent attacks that corrupt the control-flow. Deployed defense mechanisms based on CFI are often generic, which means that they do not consider high-level programming language semantics. This makes them vulnerable to vtable hijacking attacks. Object Type Integrity (OTI) is an orthogonal security policy that specifically addresses vtable hijacking. CFIXX is a Clang compiler extension that enforces OTI in the context of dynamic dispatch, which prevents vtable hijacking in this setting. However, this extension does not enforce OTI in context of polymorphism. The contribution of this work is a practical implementation to enable OTI in the context of C++’s run-time type information for the dynamic_cast expressions and the typeid operator.

Authors: Marco Schröder, Stefan Machmeier, Vincent Heuveline

Date Published: 2nd Mar 2023

Publication Type: Journal

Mortality by age, gene and gender in carriers of pathogenic mismatch repair gene variants receiving surveillance for early cancer diagnosis and treatment: a report from the prospective Lynch syndrome database

Abstract

Not specified

Authors: Mev Dominguez-Valentin, Saskia Haupt, Toni T. Seppälä, Julian R. Sampson, Lone Sunde, Inge Bernstein, Mark A. Jenkins, Christoph Engel, Stefan Aretz, Maartje Nielsen, Gabriel Capella, Francesc Balaguer, Dafydd Gareth Evans, John Burn, Elke Holinski-Feder, Lucio Bertario, Bernardo Bonanni, Annika Lindblom, Zohar Levi, Finlay Macrae, Ingrid Winship, John-Paul Plazzer, Rolf Sijmons, Luigi Laghi, Adriana Della Valle, Karl Heinimann, Tadeusz Dębniak, Robert Fruscio, Francisco Lopez-Koestner, Karin Alvarez-Valenzuela, Lior H. Katz, Ido Laish, Elez Vainer, Carlos Vaccaro, Dirce Maria Carraro, Kevin Monahan, Elizabeth Half, Aine Stakelum, Des Winter, Rory Kennelly, Nathan Gluck, Harsh Sheth, Naim Abu-Freha, Marc Greenblatt, Benedito Mauro Rossi, Mabel Bohorquez, Giulia Martina Cavestro, Leonardo S. Lino-Silva, Karoline Horisberger, Maria Grazia Tibiletti, Ivana do Nascimento, Huw Thomas, Norma Teresa Rossi, Leandro Apolinário da Silva, Attila Zaránd, Juan Ruiz-Bañobre, Vincent Heuveline, Jukka-Pekka Mecklin, Kirsi Pylvänäinen, Laura Renkonen-Sinisalo, Anna Lepistö, Päivi Peltomäki, Christina Therkildsen, Mia Gebauer Madsen, Stefan Kobbelgaard Burgdorf, John L. Hopper, Aung Ko Win, Robert W. Haile, Noralane Lindor, Steven Gallinger, Loïc Le Marchand, Polly A. Newcomb, Jane Figueiredo, Daniel D. Buchanan, Stephen N. Thibodeau, Magnus von Knebel Doeberitz, Markus Loeffler, Nils Rahner, Evelin Schröck, Verena Steinke-Lange, Wolff Schmiegel, Deepak Vangala, Claudia Perne, Robert Hüneburg, Silke Redler, Reinhard Büttner, Jürgen Weitz, Marta Pineda, Nuria Duenas, Joan Brunet Vidal, Leticia Moreira, Ariadna Sánchez, Eivind Hovig, Sigve Nakken, Kate Green, Fiona Lalloo, James Hill, Emma Crosbie, Miriam Mints, Yael Goldberg, Douglas Tjandra, Sanne W. ten Broeke, Revital Kariv, Guy Rosner, Suresh H. Advani, Lidiya Thomas, Pankaj Shah, Mithun Shah, Florencia Neffa, Patricia Esperon, Walter Pavicic, Giovana Tardin Torrezan, Thiago Bassaneze, Claudia Alejandra Martin, Gabriela Moslein, Pål Moller

Date Published: 1st Mar 2023

Publication Type: Journal

Machine Learning Methods Improve Specificity in Newborn Screening for Isovaleric Aciduria

Abstract (Expand)

Isovaleric aciduria (IVA) is a rare disorder of leucine metabolism and part of newborn screening (NBS) programs worldwide. However, NBS for IVA is hampered by, first, the increased birth prevalence due …prevalence due to the identification of individuals with an attenuated disease variant (so-called “mild” IVA) and, second, an increasing number of false positive screening results due to the use of pivmecillinam contained in the medication. Recently, machine learning (ML) methods have been analyzed, analogous to new biomarkers or second-tier methods, in the context of NBS. In this study, we investigated the application of machine learning classification methods to improve IVA classification using an NBS data set containing 2,106,090 newborns screened in Heidelberg, Germany. Therefore, we propose to combine two methods, linear discriminant analysis, and ridge logistic regression as an additional step, a digital-tier, to traditional NBS. Our results show that this reduces the false positive rate by 69.9% from 103 to 31 while maintaining 100% sensitivity in cross-validation. The ML methods were able to classify mild and classic IVA from normal newborns solely based on the NBS data and revealed that besides isovalerylcarnitine (C5), the metabolite concentration of tryptophan (Trp) is important for improved classification. Overall, applying ML methods to improve the specificity of IVA could have a major impact on newborns, as it could reduce the newborns’ and families’ burden of false positives or over-treatment.

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

Date Published: 1st Feb 2023

Publication Type: Journal

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