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1. Smart Casual Verification of the Confidential Consortium Framework

Author

Howard, Heidi, Kuppe, Markus A., Ashton, Edward, Chamayou, Amaury, and Crooks, Natacha

Subjects
Computer Science - Distributed, Parallel, and Cluster Computing, Computer Science - Formal Languages and Automata Theory, Computer Science - Software Engineering
Abstract

The Confidential Consortium Framework (CCF) is an open-source platform for developing trustworthy and reliable cloud applications. CCF powers Microsoft's Azure Confidential Ledger service and as such it is vital to build confidence in the correctness of CCF's design and implementation. This paper reports our experiences applying smart casual verification to validate the correctness of CCF's novel distributed protocols, focusing on its unique distributed consensus protocol and its custom client consistency model. We use the term smart casual verification to describe our hybrid approach, which combines the rigor of formal specification and model checking with the pragmatism of automated testing, in our case binding the formal specification in TLA+ to the C++ implementation. While traditional formal methods approaches require substantial buy-in and are often one-off efforts by domain experts, we have integrated our smart casual verification approach into CCF's CI pipeline, allowing contributors to continuously validate CCF as it evolves. We describe the challenges we faced in applying smart casual verification to a complex existing codebase and how we overcame them to find six subtle bugs in the design and implementation before they could impact production, Comment: To appear in the 22nd USENIX Symposium on Networked Systems Design and Implementation (NSDI 2025)

Published
2024

2. A small-molecule TNIK inhibitor targets fibrosis in preclinical and clinical models

Author

Ren, Feng, Aliper, Alex, Chen, Jian, Zhao, Heng, Rao, Sujata, Kuppe, Christoph, Ozerov, Ivan V., Zhang, Man, Witte, Klaus, Kruse, Chris, Aladinskiy, Vladimir, Ivanenkov, Yan, Polykovskiy, Daniil, Fu, Yanyun, Babin, Eugene, Qiao, Junwen, Liang, Xing, Mou, Zhenzhen, Wang, Hui, Pun, Frank W., Torres-Ayuso, Pedro, Veviorskiy, Alexander, Song, Dandan, Liu, Sang, Zhang, Bei, Naumov, Vladimir, Ding, Xiaoqiang, Kukharenko, Andrey, Izumchenko, Evgeny, and Zhavoronkov, Alex

Published
2025
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3. Validating Traces of Distributed Programs Against TLA+ Specifications

Author

Cirstea, Horatiu, Kuppe, Markus A., Loillier, Benjamin, Merz, Stephan, Goos, Gerhard, Series Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Madeira, Alexandre, editor, and Knapp, Alexander, editor

Published
2025
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4. Validating Traces of Distributed Programs Against TLA+ Specifications

Author

Cirstea, Horatiu, Kuppe, Markus A., Loillier, Benjamin, and Merz, Stephan

Subjects
Computer Science - Programming Languages, Computer Science - Software Engineering
Abstract

TLA+ is a formal language for specifying systems, including distributed algorithms, that is supported by powerful verification tools. In this work we present a framework for relating traces of distributed programs to high-level specifications written in TLA+. The problem is reduced to a constrained model checking problem, realized using the TLC model checker. Our framework consists of an API for instrumenting Java programs in order to record traces of executions, of a collection of TLA+ operators that are used for relating those traces to specifications, and of scripts for running the model checker. Crucially, traces only contain updates to specification variables rather than full values, and developers may choose to trace only certain variables. We have applied our approach to several distributed programs, detecting discrepancies between the specifications and the implementations in all cases. We discuss reasons for these discrepancies, best practices for instrumenting programs, and how to interpret the verdict produced by TLC.

Published
2024

5. 3DGen: AI-Assisted Generation of Provably Correct Binary Format Parsers

Author

Fakhoury, Sarah, Kuppe, Markus, Lahiri, Shuvendu K., Ramananandro, Tahina, and Swamy, Nikhil

Subjects
Computer Science - Software Engineering
Abstract

Improper parsing of attacker-controlled input is a leading source of software security vulnerabilities, especially when programmers transcribe informal format descriptions in RFCs into efficient parsing logic in low-level, memory unsafe languages. Several researchers have proposed formal specification languages for data formats from which efficient code can be extracted. However, distilling informal requirements into formal specifications is challenging and, despite their benefits, new, formal languages are hard for people to learn and use. In this work, we present 3DGen, a framework that makes use of AI agents to transform mixed informal input, including natural language documents (i.e., RFCs) and example inputs into format specifications in a language called 3D. To support humans in understanding and trusting the generated specifications, 3DGen uses symbolic methods to also synthesize test inputs that can be validated against an external oracle. Symbolic test generation also helps in distinguishing multiple plausible solutions. Through a process of repeated refinement, 3DGen produces a 3D specification that conforms to a test suite, and which yields safe, efficient, provably correct, parsing code in C. We have evaluated 3DGen on 20 Internet standard formats, demonstrating the potential for AI-agents to produce formally verified C code at a non-trivial scale. A key enabler is the use of a domain-specific language to limit AI outputs to a class for which automated, symbolic analysis is tractable.

Published
2024

6. Targeting immune–fibroblast cell communication in heart failure

Author

Amrute, Junedh M., Luo, Xin, Penna, Vinay, Yang, Steven, Yamawaki, Tracy, Hayat, Sikander, Bredemeyer, Andrea, Jung, In-Hyuk, Kadyrov, Farid F., Heo, Gyu Seong, Venkatesan, Rajiu, Shi, Sally Yu, Parvathaneni, Alekhya, Koenig, Andrew L., Kuppe, Christoph, Baker, Candice, Luehmann, Hannah, Jones, Cameran, Kopecky, Benjamin, Zeng, Xue, Bleckwehl, Tore, Ma, Pan, Lee, Paul, Terada, Yuriko, Fu, Angela, Furtado, Milena, Kreisel, Daniel, Kovacs, Atilla, Stitziel, Nathan O., Jackson, Simon, Li, Chi-Ming, Liu, Yongjian, Rosenthal, Nadia A., Kramann, Rafael, Ason, Brandon, and Lavine, Kory J.

Published
2024
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11. Confidential Consortium Framework: Secure Multiparty Applications with Confidentiality, Integrity, and High Availability

Author

Howard, Heidi, Alder, Fritz, Ashton, Edward, Chamayou, Amaury, Clebsch, Sylvan, Costa, Manuel, Delignat-Lavaud, Antoine, Fournet, Cedric, Jeffery, Andrew, Kerner, Matthew, Kounelis, Fotios, Kuppe, Markus A., Maffre, Julien, Russinovich, Mark, and Wintersteiger, Christoph M.

Subjects
Computer Science - Cryptography and Security, Computer Science - Distributed, Parallel, and Cluster Computing
Abstract

Confidentiality, integrity protection, and high availability, abbreviated to CIA, are essential properties for trustworthy data systems. The rise of cloud computing and the growing demand for multiparty applications however means that building modern CIA systems is more challenging than ever. In response, we present the Confidential Consortium Framework (CCF), a general-purpose foundation for developing secure stateful CIA applications. CCF combines centralized compute with decentralized trust, supporting deployment on untrusted cloud infrastructure and transparent governance by mutually untrusted parties. CCF leverages hardware-based trusted execution environments for remotely verifiable confidentiality and code integrity. This is coupled with state machine replication backed by an auditable immutable ledger for data integrity and high availability. CCF enables each service to bring its own application logic, custom multiparty governance model, and deployment scenario, decoupling the operators of nodes from the consortium that governs them. CCF is open-source and available now at https://github.com/microsoft/CCF., Comment: 16 pages, 9 figures. To appear in the Proceedings of the VLDB Endowment, Volume 17

Published
2023

12. Regional-based static and dynamic alterations in Alzheimer disease: a longitudinal study

Author

Kuppe Channappa Usha, Honnenahally Ningappa Suma, and Abhishek Appaji

Subjects
Alzheimer Disease, Magnetic Resonance Imaging, Longitudinal Studies, Cognitive Dysfunction, Biomarkers, Doença de Alzheimer, Imageamento por Ressonância Magnética, Estudos Longitudinais, Disfunção Cognitiva, Biomarcadores, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract

Background Alzheimer disease (AD) leads to cognitive decline and alters functional connectivity (FC) in key brain regions. Resting-state functional magnetic resonance imaging (rs-fMRI) assesses these changes using static-FC for overall correlation and dynamic-FC for temporal variability.

Published
2024
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13. Specification and Verification with the TLA+ Trifecta: TLC, Apalache, and TLAPS

Author

Konnov, Igor, Kuppe, Markus, and Merz, Stephan

Subjects
Computer Science - Logic in Computer Science
Abstract

Using an algorithm due to Safra for distributed termination detection as a running example, we present the main tools for verifying specifications written in TLA+. Examining their complementary strengths and weaknesses, we suggest a workflow that supports different types of analysis and that can be adapted to the desired degree of confidence.

Published
2022
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14. Understanding Inconsistency in Azure Cosmos DB with TLA+

Author

Hackett, A. Finn, Rowe, Joshua, and Kuppe, Markus Alexander

Subjects
Computer Science - Software Engineering
Abstract

Beyond implementation correctness of a distributed system, it is equally important to understand exactly what users should expect to see from that system. Even if the system itself works as designed, insufficient understanding of its user-visible semantics can cause bugs in its dependencies. By focusing a formal specification effort on precisely defining the expected user-facing behaviors of the Azure Cosmos DB service at Microsoft, we were able to write a formal specification of the database that was significantly smaller and conceptually simpler than any other specification of Cosmos DB, while representing a wider range of valid user-observable behaviors than existing more detailed specifications. Many of the additional behaviors we documented were previously poorly understood outside of the Cosmos DB development team, even informally, leading to data consistency errors in Microsoft products that depend on it. Using this model, we were able to raise two key issues in Cosmos DB's public-facing documentation, which have since been addressed. We were also able to offer a fundamental solution to a previous high-impact outage within another Azure service that depends on Cosmos DB.

Published
2022

15. A novel thiol-saccharide mucolytic for the treatment of muco-obstructive lung diseases

Author

Addante, Annalisa, Raymond, Wilfred, Gitlin, Irina, Charbit, Annabelle, Orain, Xavier, Scheffler, Aaron Wolfe, Kuppe, Aditi, Duerr, Julia, Daniltchenko, Maria, Drescher, Marika, Graeber, Simon Y, Healy, Anne-Marie, Oscarson, Stefan, Fahy, John V, and Mall, Marcus A

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Lung, Cystic Fibrosis, Rare Diseases, Orphan Drug, Clinical Research, 5.1 Pharmaceuticals, Respiratory, Good Health and Well Being, Adult, Humans, Mice, Animals, Expectorants, Sulfhydryl Compounds, Acetylcysteine, Sputum, Lung Diseases, Obstructive, Inflammation, Carbohydrates, Medical and Health Sciences, Respiratory System, Cardiovascular medicine and haematology
Abstract

BackgroundMucin disulfide cross-links mediate pathologic mucus formation in muco-obstructive lung diseases. MUC-031, a novel thiol-modified carbohydrate compound, cleaves disulfides to cause mucolysis. The aim of this study was to determine the mucolytic and therapeutic effects of MUC-031 in sputum from patients with cystic fibrosis (CF) and mice with muco-obstructive lung disease (βENaC-Tg mice).MethodsWe compared the mucolytic efficacy of MUC-031 and existing mucolytics (N-acetylcysteine (NAC) and recombinant human deoxyribonuclease I (rhDNase)) using rheology to measure the elastic modulus (G') of CF sputum, and we tested effects of MUC-031 on airway mucus plugging, inflammation and survival in βENaC-Tg mice to determine its mucolytic efficacy in vivo.ResultsIn CF sputum, compared to the effects of rhDNase and NAC, MUC-031 caused a larger decrease in sputum G', was faster in decreasing sputum G' by 50% and caused mucolysis of a larger proportion of sputum samples within 15 min of drug addition. Compared to vehicle control, three treatments with MUC-031 in 1 day in adult βENaC-Tg mice decreased airway mucus content (16.8±3.2 versus 7.5±1.2 nL·mm-2, p

Published
2023

17. Harnessing Artificial Intelligence for Enhanced Renal Analysis: Automated Detection of Hydronephrosis and Precise Kidney Segmentation

Author

Radu Alexa, Jennifer Kranz, Rafael Kramann, Christoph Kuppe, Ritabrata Sanyal, Sikander Hayat, Luis Felipe Casas Murillo, Turkan Hajili, Marco Hoffmann, and Matthias Saar

Subjects
Hydronephrosis, Artificial intelligence, Segmentation, Neuronal networks, Diseases of the genitourinary system. Urology, RC870-923, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282
Abstract

Background and objective: Hydronephrosis is essential in the diagnosis of renal colic. We automated the detection of hydronephrosis from ultrasound images to standardize the therapy and reduce the misdiagnosis of renal colic. Methods: Anonymously collected ultrasound images of human kidneys, both normal and hydronephrotic, were preprocessed for neural networks. Six “state of the art” models were trained and cross-validated for the detection of hydronephrosis, and two convolutional networks were used for kidney segmentation. In the testing phase, performance metrics included true positives, true negatives, false positives, false negatives, accuracy, and F1 score, while the evaluation of the segmentation task involved accuracy, precision, dice, jaccard, recall, and ASSD. Key findings and limitations: A total of 523 sonographic kidney images (423 nonhydronephrotic and 100 hydronephrotic) were collected from three different ultrasound devices. After training on this dataset, all models were used to evaluate 200 new ultrasound kidney images (142 nonhydronephrotic and 58 hydronephrotic kidneys). The highest validation accuracy (98.5%) was achieved by the AlexNet model (GoogLeNet 97%, AlexNet_v2 96%, ResNet50 96%, ResNet101 97.5%, and ResNet152 95%). The deeplabv3_resnet50 and deeplabv3_resnet101 reached a dice coefficient of 94.74% and 94.48%, respectively, on the task of automated kidney segmentation. The study is limited by analyzing only hydronephrosis, but this specific focus enabled high detection accuracy. Conclusions and clinical implications: We show that our automated ultrasound deep learning model can be trained and used to interpret and segmentate ultrasound images from different sources with high accuracy. This method will serve as an automated tool in the diagnostic algorithm of acute renal failure in the future. Patient summary: Hydronephrosis is crucial in the diagnosis of renal colic. Recent advances in artificial intelligence allow automated detection of hydronephrosis in ultrasound images with high accuracy. These methods will help standardize the diagnosis and treatment renal colic.

Published
2024
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19. Abstract 4140393: Targeting Immune-Fibroblast Crosstalk in Myocardial Infarction and Cardiac Fibrosis

Author

Amrute, Junedh, Luo, Xin, Penna, Vinay, Yang, Steven, Yamawaki, Tracy, Hayat, Sikander, Bredemeyer, Andrea, Jung, In-hyuk, Kadyrov, Farid, Heo, Gyu Seong, VENKATESAN, RAJIU, Shi, Sally, Parvathaneni, Alekhya, Koenig, Andrew, Kuppe, Christoph, Baker, Candice, Luehmann, Hannah, Jones, Cameran, Kopecky, Benjamin, Zeng, Xue, Blekwehl, Tore, Ma, Pan, Lee, Paul, Terada, Yuriko, Fu, Angela, Furtado, Milena, KREISEL, DANIEL, Kovacs, Attila, Stitziel, Nathan, Jackson, Simon, Li, Chi-Ming, Liu, Yongjian, Rosenthal, Nadia, Kramann, Rafael, Ason, Brandon, and Lavine, Kory

Published
2024
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24. Deep learning-based bias transfer for overcoming laboratory differences of microscopic images

Author

Thebille, Ann-Katrin, Dietrich, Esther, Klaus, Martin, Gernhold, Lukas, Lennartz, Maximilian, Kuppe, Christoph, Kramann, Rafael, Huber, Tobias B., Sauter, Guido, Puelles, Victor G., Zimmermann, Marina, and Bonn, Stefan

Subjects
Electrical Engineering and Systems Science - Image and Video Processing, Computer Science - Computer Vision and Pattern Recognition, Computer Science - Machine Learning
Abstract

The automated analysis of medical images is currently limited by technical and biological noise and bias. The same source tissue can be represented by vastly different images if the image acquisition or processing protocols vary. For an image analysis pipeline, it is crucial to compensate such biases to avoid misinterpretations. Here, we evaluate, compare, and improve existing generative model architectures to overcome domain shifts for immunofluorescence (IF) and Hematoxylin and Eosin (H&E) stained microscopy images. To determine the performance of the generative models, the original and transformed images were segmented or classified by deep neural networks that were trained only on images of the target bias. In the scope of our analysis, U-Net cycleGANs trained with an additional identity and an MS-SSIM-based loss and Fixed-Point GANs trained with an additional structure loss led to the best results for the IF and H&E stained samples, respectively. Adapting the bias of the samples significantly improved the pixel-level segmentation for human kidney glomeruli and podocytes and improved the classification accuracy for human prostate biopsies by up to 14%., Comment: Accepted as a regular conference paper at MIUA 2021

Published
2021
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26. Increased levels of a mycophenolic acid metabolite in patients with kidney failure negatively affect cardiomyocyte health

Author

Eva Harlacher, Corinna Schulte, Sonja Vondenhoff, Philippe Schmitt-Kopplin, Philippe Diederich, Christian Hemmers, Julia Moellmann, Julia Wollenhaupt, Rogier Veltrop, Erik Biessen, Michael Lehrke, Björn Peters, Georg Schlieper, Christoph Kuppe, Jürgen Floege, Vera Jankowski, Nikolaus Marx, Joachim Jankowski, and Heidi Noels

Subjects
chronic kidney disease, cardiovascular disease, uremic toxin, cardiomyocyte, drug metabolite, mycophenolate mofetil, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Chronic kidney disease (CKD) significantly increases cardiovascular risk and mortality, and the accumulation of uremic toxins in the circulation upon kidney failure contributes to this increased risk. We thus performed a screening for potential novel mediators of reduced cardiovascular health starting from dialysate obtained after hemodialysis of patients with CKD. The dialysate was gradually fractionated to increased purity using orthogonal chromatography steps, with each fraction screened for a potential negative impact on the metabolic activity of cardiomyocytes using a high-throughput MTT-assay, until ultimately a highly purified fraction with strong effects on cardiomyocyte health was retained. Mass spectrometry and nuclear magnetic resonance identified the metabolite mycophenolic acid-β-glucuronide (MPA-G) as a responsible substance. MPA-G is the main metabolite from the immunosuppressive agent MPA that is supplied in the form of mycophenolate mofetil (MMF) to patients in preparation for and after transplantation or for treatment of autoimmune and non-transplant kidney diseases. The adverse effect of MPA-G on cardiomyocytes was confirmed in vitro, reducing the overall metabolic activity and cellular respiration while increasing mitochondrial reactive oxygen species production in cardiomyocytes at concentrations detected in MMF-treated patients with failing kidney function. This study draws attention to the potential adverse effects of long-term high MMF dosing, specifically in patients with severely reduced kidney function already displaying a highly increased cardiovascular risk.

Published
2024
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29. The TLA Debugger

Author

Kuppe, Markus A., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Masci, Paolo, editor, Bernardeschi, Cinzia, editor, Graziani, Pierluigi, editor, Koddenbrock, Mario, editor, and Palmieri, Maurizio, editor

Published
2023
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33. Expansion-enhanced super-resolution radial fluctuations enable nanoscale molecular profiling of pathology specimens

Author

Kylies, Dominik, Zimmermann, Marina, Haas, Fabian, Schwerk, Maria, Kuehl, Malte, Brehler, Michael, Czogalla, Jan, Hernandez, Lola C., Konczalla, Leonie, Okabayashi, Yusuke, Menzel, Julia, Edenhofer, Ilka, Mezher, Sam, Aypek, Hande, Dumoulin, Bernhard, Wu, Hui, Hofmann, Smilla, Kretz, Oliver, Wanner, Nicola, Tomas, Nicola M., Krasemann, Susanne, Glatzel, Markus, Kuppe, Christoph, Kramann, Rafael, Banjanin, Bella, Schneider, Rebekka K., Urbschat, Christopher, Arck, Petra, Gagliani, Nicola, van Zandvoort, Marc, Wiech, Thorsten, Grahammer, Florian, Sáez, Pablo J., Wong, Milagros N., Bonn, Stefan, Huber, Tobias B., and Puelles, Victor G.

Published
2023
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34. Defining cardiac functional recovery in end-stage heart failure at single-cell resolution

Author

Amrute, Junedh M., Lai, Lulu, Ma, Pan, Koenig, Andrew L., Kamimoto, Kenji, Bredemeyer, Andrea, Shankar, Thirupura S., Kuppe, Christoph, Kadyrov, Farid F., Schulte, Linda J., Stoutenburg, Dylan, Kopecky, Benjamin J., Navankasattusas, Sutip, Visker, Joseph, Morris, Samantha A., Kramann, Rafael, Leuschner, Florian, Mann, Douglas L., Drakos, Stavros G., and Lavine, Kory J.

Published
2023
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36. The TLA+ Toolbox

Author

Kuppe, Markus Alexander, Lamport, Leslie, and Ricketts, Daniel

Subjects
Computer Science - Software Engineering, Computer Science - Logic in Computer Science
Abstract

We discuss the workflows supported by the TLA+ Toolbox to write and verify specifications. We focus on features that are useful in industry because its users are primarily engineers. Two features are novel in the scope of formal IDEs: CloudTLC connects the Toolbox with cloud computing to scale up model checking. A Profiler helps to debug inefficient expressions and to pinpoint the source of state space explosion. For those who wish to contribute to the Toolbox or learn from its flaws, we present its technical architecture., Comment: In Proceedings F-IDE 2019, arXiv:1912.09611

Published
2019
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37. A previously uncharacterized Factor Associated with Metabolism and Energy (FAME/C14orf105/CCDC198/1700011H14Rik) is related to evolutionary adaptation, energy balance, and kidney physiology

Author

Julian Petersen, Lukas Englmaier, Artem V. Artemov, Irina Poverennaya, Ruba Mahmoud, Thibault Bouderlique, Marketa Tesarova, Ruslan Deviatiiarov, Anett Szilvásy-Szabó, Evgeny E. Akkuratov, David Pajuelo Reguera, Hugo Zeberg, Marketa Kaucka, Maria Eleni Kastriti, Jan Krivanek, Tomasz Radaszkiewicz, Kristína Gömöryová, Sarah Knauth, David Potesil, Zbynek Zdrahal, Ranjani Sri Ganji, Anna Grabowski, Miriam E. Buhl, Tomas Zikmund, Michaela Kavkova, Håkan Axelson, David Lindgren, Rafael Kramann, Christoph Kuppe, Ferenc Erdélyi, Zoltán Máté, Gábor Szabó, Till Koehne, Tibor Harkany, Kaj Fried, Jozef Kaiser, Peter Boor, Csaba Fekete, Jan Rozman, Petr Kasparek, Jan Prochazka, Radislav Sedlacek, Vitezslav Bryja, Oleg Gusev, and Igor Adameyko

Subjects
Science
Abstract

Abstract In this study we use comparative genomics to uncover a gene with uncharacterized function (1700011H14Rik/C14orf105/CCDC198), which we hereby name FAME (Factor Associated with Metabolism and Energy). We observe that FAME shows an unusually high evolutionary divergence in birds and mammals. Through the comparison of single nucleotide polymorphisms, we identify gene flow of FAME from Neandertals into modern humans. We conduct knockout experiments on animals and observe altered body weight and decreased energy expenditure in Fame knockout animals, corresponding to genome-wide association studies linking FAME with higher body mass index in humans. Gene expression and subcellular localization analyses reveal that FAME is a membrane-bound protein enriched in the kidneys. Although the gene knockout results in structurally normal kidneys, we detect higher albumin in urine and lowered ferritin in the blood. Through experimental validation, we confirm interactions between FAME and ferritin and show co-localization in vesicular and plasma membranes.

Published
2023
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39. Dynamic partitioning of branched-chain amino acids-derived nitrogen supports renal cancer progression

Author

Marco Sciacovelli, Aurelien Dugourd, Lorea Valcarcel Jimenez, Ming Yang, Efterpi Nikitopoulou, Ana S. H. Costa, Laura Tronci, Veronica Caraffini, Paulo Rodrigues, Christina Schmidt, Dylan Gerard Ryan, Timothy Young, Vincent R. Zecchini, Sabrina H. Rossi, Charlie Massie, Caroline Lohoff, Maria Masid, Vassily Hatzimanikatis, Christoph Kuppe, Alex Von Kriegsheim, Rafael Kramann, Vincent Gnanapragasam, Anne Y. Warren, Grant D. Stewart, Ayelet Erez, Sakari Vanharanta, Julio Saez-Rodriguez, and Christian Frezza

Subjects
Science
Abstract

Primary and metastatic tumours have different metabolic phenotypes due to changes in nutrient availability. Here the authors perform multi-omic analyses of primary and metastatic renal cancer cells grown in a physiological medium and show that the reprogramming of the branched-chain amino acid catabolism and urea cycle through re-expression of ASS1 allows metabolic flexibility during renal cancer progression.

Published
2022
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41. Platelet-instructed SPP1+ macrophages drive myofibroblast activation in fibrosis in a CXCL4-dependent manner

Author

Hoeft, Konrad, Schaefer, Gideon J.L., Kim, Hyojin, Schumacher, David, Bleckwehl, Tore, Long, Qingqing, Klinkhammer, Barbara Mara, Peisker, Fabian, Koch, Lars, Nagai, James, Halder, Maurice, Ziegler, Susanne, Liehn, Elisa, Kuppe, Christoph, Kranz, Jennifer, Menzel, Sylvia, Costa, Ivan, Wahida, Adam, Boor, Peter, Schneider, Rebekka K., Hayat, Sikander, and Kramann, Rafael

Published
2023
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42. Adult human kidney organoids originate from CD24+ cells and represent an advanced model for adult polycystic kidney disease

Author

Xu, Yaoxian, Kuppe, Christoph, Perales-Patón, Javier, Hayat, Sikander, Kranz, Jennifer, Abdallah, Ali T., Nagai, James, Li, Zhijian, Peisker, Fabian, Saritas, Turgay, Halder, Maurice, Menzel, Sylvia, Hoeft, Konrad, Kenter, Annegien, Kim, Hyojin, van Roeyen, Claudia R. C., Lehrke, Michael, Moellmann, Julia, Speer, Thimoteus, Buhl, Eva M., Hoogenboezem, Remco, Boor, Peter, Jansen, Jitske, Knopp, Cordula, Kurth, Ingo, Smeets, Bart, Bindels, Eric, Reinders, Marlies E. J., Baan, Carla, Gribnau, Joost, Hoorn, Ewout J., Steffens, Joachim, Huber, Tobias B., Costa, Ivan, Floege, Jürgen, Schneider, Rebekka K., Saez-Rodriguez, Julio, Freedman, Benjamin S., and Kramann, Rafael

Published
2022
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44. Spatial multi-omic map of human myocardial infarction

Author

Kuppe, Christoph, Ramirez Flores, Ricardo O., Li, Zhijian, Hayat, Sikander, Levinson, Rebecca T., Liao, Xian, Hannani, Monica T., Tanevski, Jovan, Wünnemann, Florian, Nagai, James S., Halder, Maurice, Schumacher, David, Menzel, Sylvia, Schäfer, Gideon, Hoeft, Konrad, Cheng, Mingbo, Ziegler, Susanne, Zhang, Xiaoting, Peisker, Fabian, Kaesler, Nadine, Saritas, Turgay, Xu, Yaoxian, Kassner, Astrid, Gummert, Jan, Morshuis, Michiel, Amrute, Junedh, Veltrop, Rogier J. A., Boor, Peter, Klingel, Karin, Van Laake, Linda W., Vink, Aryan, Hoogenboezem, Remco M., Bindels, Eric M. J., Schurgers, Leon, Sattler, Susanne, Schapiro, Denis, Schneider, Rebekka K., Lavine, Kory, Milting, Hendrik, Costa, Ivan G., Saez-Rodriguez, Julio, and Kramann, Rafael

Published
2022
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47. Chirality in diffractive plasmonic nanostructures

Author

Kuppe, Christian, Valev, Ventsislav, and Wadsworth, William

Subjects
530
Abstract

Historically, chirality was mostly studied in molecules over which control is naturally limited. However, the ability to produce artificial, chiral structures with feature sizes smaller than the wavelength of light, allows to execute hitherto unseen control over geometrical parameters which govern the emergence and evolution of the research around chirality. The presence of chirality in molecules can be measured with light. However, the resulting chiral optical response is typically very weak. Interestingly, it is possible to combine artificially created nanostructures and chiral molecules to enhance the chiral optical response of the latter. Nanostructures which are specifically tailored to enhance the response of a certain molecule are therefore needed. However, such nanostructures also present a predicament: If the nanostructures themselves are chiral, they will overshadow the chiral optical response of the molecule. If the nanostructures are achiral (non-chiral) they cannot be spectrally tailored to the molecule as they do not yield any chiral optical response in the far-field. A promising solution is offered by diffractive nanostructures which have been shown to yield extremely large responses. However, previous studies have been limited in scale and a physical explanation for the observed behaviour is still elusive. Developing an experimental apparatus to optically characterise various nanogratings, supported by numerical simulations and mathematical models, this thesis provides both an explanation and the means for chiral sensing in diffracted beams. The apparatus enables the detection of chirality through circular intensity measurements of the light diffracted by such nanogratings. Starting with a proof-of-principle study of higher-order diffraction spectroscopy, various nanograting designs and their far-field responses are investigated. Consequently, the potential of such nanogratings to enhance the response of chiral molecules is demonstrated. Of special interest are racemic nanogratings, i.e. consisting of an equal number of both chiral configurations. The reason for this lies in the fact that racemic nanogratings yield no net chiral optical response but, by means of diffraction spectroscopy, it is possible to unveil such a behaviour in the far-field which is the first time this has been reported. Although the far-field chiral optical response of a racemic nanograting accumulates to a net zero, individual diffracted beams do yield non-zero values and hence can now be spectrally tailored to that of the molecules. The results of a proof-of-principle study with chiral molecules demonstrate the potential of artificially created nanogratings to become a platform to detect chirality in molecular films with light. The presented findings contribute to the advancement in the design and characterisation of chiral materials.

Published
2019

48. Impact of sucroferric oxyhydroxide on the oral and intestinal microbiome in hemodialysis patients

Author

Mohamed M. H. Abdelbary, Christoph Kuppe, Sareh Said-Yekta Michael, Thilo Krüger, Jürgen Floege, and Georg Conrads

Subjects
Medicine, Science
Abstract

Abstract Hyperphosphatemia is a consequence of chronic kidney disease associated with mineral/bone impairment, increased cardiovascular events and mortality. Therapeutically, most dialysis patients have to take phosphate binders. Here, we investigated effects of the Fe(3+)-based phosphate binder sucroferric oxyhydroxide (SFOH) on the oral and gastrointestinal microbiome of 11 hemodialysis patients. Saliva, dental plaque and stool were collected at baseline, one and four weeks of SFOH intake and subjected to 16S rRNA gene (V3-V4 region) directed Illumina MiSeq-based analysis. Total Fe, Fe(2+) and Fe(3+) were determined in stool and saliva. Overall, the microbiome did not change significantly. However, some patient-, sample- and taxon-specific differences were noted, which allowed patients to be divided into those with a shift in their microbiome (6/11) and those without a shift (5/11). Total Fe and Fe(2+) were highest after one week of SFOH, particularly in patients who exhibited a shift in microbiome composition. Eight bacterial taxa showed significant unidirectional changes during treatment. In-depth microbiome analysis revealed that taxa that significantly benefited from iron plethora had no iron-binding siderophores or alternatives, which was in contrast to taxa that significantly declined under iron plethora. Patients with microbiome-shift were significantly younger and had higher serum phosphate concentrations. In conclusion, this study sheds light on the impact of iron on the microbiome of hemodialysis patients.

Published
2022
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50. Mapping the cardiac vascular niche in heart failure

Author

Fabian Peisker, Maurice Halder, James Nagai, Susanne Ziegler, Nadine Kaesler, Konrad Hoeft, Ronghui Li, Eric M. J. Bindels, Christoph Kuppe, Julia Moellmann, Michael Lehrke, Christian Stoppe, Michael T. Schaub, Rebekka K. Schneider, Ivan Costa, and Rafael Kramann

Subjects
Science
Abstract

The cardiac vascular niche is of major importance in homeostasis and disease, but knowledge of its complexity in response to injury remains limited. Here we combine lineage tracing with single cell RNA sequencing to show alterations in fibroblasts, endothelial and mural cells in hypertrophic remodeling.

Published
2022
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