Correction
Immunology
Roman David Bulow, Daniel Dimitrov, Peter Boor, Julio Saez-Rodriguez
Summary: A correction to this paper has been published.
SEMINARS IN IMMUNOPATHOLOGY
(2021)
Article
Medicine, General & Internal
Zhenliang Fan, Qiaorui Yang, Hong Xia, Peipei Zhang, Ke Sun, Mengfan Yang, Riping Yin, Dongxue Zhao, Hongzhen Ma, Yiwei Shen, Junfen Fan
Summary: This study developed an AI model to distinguish between IgA nephropathy and diabetic nephropathy by analyzing renal pathology images. The AI model achieved an accuracy of 98.67% in detecting glomeruli and 73.24% in distinguishing the two diseases.
FRONTIERS IN MEDICINE
(2023)
Article
Health Care Sciences & Services
Andrzej Konieczny, Jakub Stojanowski, Magdalena Krajewska, Mariusz Kusztal
Summary: This study focused on evaluating proteinuria remission and kidney function deterioration in patients with IgA nephropathy using various machine learning methods, demonstrating the significant impact of model selection and input features on performance. The tested models accurately classified patients and had low estimation error in regression, showing the importance of careful selection of models and parameters for machine learning applications.
JOURNAL OF PERSONALIZED MEDICINE
(2021)
Article
Biochemical Research Methods
Oezlem Muslu, Charles Tapley Hoyt, Mauricio Lacerda, Martin Hofmann-Apitius, Holger Froehlich
Summary: The study proposes a novel approach, GuiltyTargets, for prioritization of putative targets using attributed network representation learning and positive-unlabeled learning. The evaluation on multiple disease datasets demonstrates its superiority over previous methods and its potential for target repositioning across related diseases.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2022)
Article
Physiology
Xue Zhou, Ning Wang, Yuefeng Zhang, Pei Yu
Summary: By analyzing gene expression profiles, this study identifies CCL2, JUN, and FOS as promising biomarkers for the diagnosis of IgA nephropathy, showing high accuracy in prediction and significantly downregulated expression in IgAN patients.
FRONTIERS IN PHYSIOLOGY
(2022)
Article
Medicine, General & Internal
Ming Xia, Di Liu, Haiyang Liu, Liang Peng, Danyi Yang, Chengyuan Tang, Guochun Chen, Yu Liu, Hong Liu
Summary: This study identified DEGs in the kidney transcriptome of IgAN patients, revealing interesting pathological changes in glomerular compartments. Hub genes (ITGB2, FCER1G, CSF1R) were significantly upregulated in IgAN and related to the severity of renal lesions. Computational drug repurposing suggested tetrandrine as a potential treatment for IgAN, which was validated to reverse mesangial cell proliferation and cell cycle transition.
FRONTIERS IN MEDICINE
(2022)
Article
Urology & Nephrology
Yawen Bai, Yajing Li, Yali Xi, Chunjie Ma
Summary: This study aimed to explore glomerulotubular crosstalk genes and dysregulated pathways relating to the pathogenesis of IgA nephropathy (IgAN). The results showed that immune-related pathways are associated with both glomerular and tubulointerstitial injuries in IgAN, and the glomerulotubular crosstalk might perform a role in the pathogenesis of IgAN.
Review
Biochemistry & Molecular Biology
Claudio Fiocchi
Summary: The recent advancements in technologies like sequencing and mass spectroscopy, combined with artificial intelligence-powered analytic tools, have revolutionized big data research in complex diseases, including inflammatory bowel disease (IBD). This review provides a comprehensive assessment of the current knowledge on omes, omics, and multi-omics in IBD, highlighting their importance in understanding disease mechanisms and potential clinical applications such as biomarker identification and precision medicine. The review also critically analyzes the limitations of current IBD multi-omics studies and suggests ways to optimize the use of multi-omics data for better clinical and therapeutic outcomes. Finally, the review predicts the future incorporation of multi-omics analyses in the routine management of IBD.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Review
Biochemistry & Molecular Biology
Dragan Milenkovic, Tatjana Ruskovska
Summary: Dietary (poly)phenols have been extensively studied for their vasculoprotective effects through genomic and epigenomic mechanisms. The use of omics, multi-omics, and integrative approaches, along with machine learning, can provide insights into the molecular mechanisms of dietary (poly)phenols and their potential in nutrigenomics.
MOLECULAR ASPECTS OF MEDICINE
(2023)
Article
Computer Science, Information Systems
Richard Lupat, Rashindrie Perera, Sherene Loi, Jason Li
Summary: Cancer subtyping provides valuable insights and is an essential step toward personalized medicine. However, recent studies have highlighted inconsistencies in breast cancer subtype classifications, indicating the need for optimization. We propose a deep-learning-based algorithm, Moanna, that integrates multi-omics data to predict breast cancer subtypes. Evaluation results show high accuracy and improved correlation with patient survival compared to existing methods.
Review
Biochemistry & Molecular Biology
Somayah Albaradei, Maha Thafar, Asim Alsaedi, Christophe Van Neste, Takashi Gojobori, Magbubah Essack, Xin Gao
Summary: Metastasis, the primary cause of cancer-related deaths, has been the focus of research utilizing technologies like high-throughput sequencing to unravel cellular processes. Machine learning and deep learning methods have been used to predict metastasis onset, enhancing diagnostic and disease treatment outcomes.
COMPUTATIONAL AND STRUCTURAL BIOTECHNOLOGY JOURNAL
(2021)
Review
Medicine, Research & Experimental
Ajay Vikram Singh, Vaisali Chandrasekar, Namuna Paudel, Peter Laux, Andreas Luch, Donato Gemmati, Veronica Tisato, Kirti S. Prabhu, Shahab Uddin, Sarada Prasad Dakua
Summary: More information about genetic makeup, drug response, multi-omics response, and genomic response is now available, leading to personalized treatment. Non-animal testing and computational toxicogenomics are becoming integral parts of risk assessment. Artificial intelligence (AI) has the potential to analyze patient data, predict treatment outcomes, and expedite data processing in personalized medicine and toxicogenomics. This article explores the current trends, future perspectives, challenges, and limitations in personalized medicine, toxicogenomics, and AI.
BIOMEDICINE & PHARMACOTHERAPY
(2023)
Article
Nanoscience & Nanotechnology
Yanan Xue, Cheng Chen, Rong Tan, Jingyu Zhang, Qin Fang, Rui Jin, Xiangyu Mi, Danying Sun, Yinan Xue, Yue Wang, Rong Xiong, Haojian Lu, Weiqiang Tan
Summary: Diabetic wounds pose significant challenges in clinical treatments. In this study, by using artificial intelligence and bioinformatics, a potential therapeutic agent TSA and a potential target HDAC4 for diabetic wound healing were identified. Furthermore, a microneedle-mediated patch loaded with TSA was developed to reduce injection-caused secondary damage and showed promising results in reducing inflammation and promoting tissue regeneration.
ACS APPLIED MATERIALS & INTERFACES
(2022)
Article
Multidisciplinary Sciences
Maria Agustina Ricci Lara, Rodrigo Echeveste, Enzo Ferrante
Summary: AI systems in the field of medical imaging can exhibit unfair biases, and it is important to address the meaning of fairness and potential sources of biases, as well as implement strategies to mitigate them. An analysis of the current state of the field reveals strengths and areas for improvement, along with challenges and opportunities.
NATURE COMMUNICATIONS
(2022)
Article
Materials Science, Multidisciplinary
Mohd Zaki, Amreen Jan, N. M. Anoop Krishnan, John C. Mauro
Summary: Glass science has made rapid progress in recent decades, thanks to advanced experimental techniques, simulation methods, and computing capabilities. Glassomics, inspired by the omics approach in biological science, provides a holistic way to study glasses. By utilizing artificial intelligence, experiments, and simulations, glassomics allows high-throughput screening of glasses based on the entire periodic table. This approach offers a comprehensive understanding of the composition, structure, process, and properties of glasses through simulations, machine learning, and natural language processing.
Article
Pathology
Nassim Bouteldja, David Laurin Hoelscher, Barbara Mara Klinkhammer, Roman David Buelow, Johannes Lotz, Nick Weiss, Christoph Daniel, Kerstin Amann, Peter Boor
Summary: This research proposes a novel concept of stain augmentation to develop stain-independent CNNs for digital pathology. It outperforms state-of-the-art techniques and enables segmentation on immunohistochemical stainings without additional annotations, achieving performance comparable to the annotated stain. Examples of application in inflammation and fibrosis quantification are presented, indicating the effectiveness of stain augmentation in deep-learning segmentation algorithms.
AMERICAN JOURNAL OF PATHOLOGY
(2023)
Article
Peripheral Vascular Disease
Christopher Werlein, Maximilian Ackermann, Helge Stark, Harshit R. Shah, Alexandar Tzankov, Jasmin Dinonne Haslbauer, Saskia von Stillfried, Roman David Buelow, Ali El-Armouche, Stephan Kuenzel, Jan Lukas Robertus, Marius Reichardt, Axel Haverich, Anne Hoefer, Lavinia Neubert, Edith Plucinski, Peter Braubach, Stijn Verleden, Tim Salditt, Nikolaus Marx, Tobias Welte, Johann Bauersachs, Hans-Heinrich Kreipe, Steven J. Mentzer, Peter Boor, Stephen M. Black, Florian Laenger, Mark Kuehnel, Danny Jonigk
Summary: In this multicentre study, researchers performed a comprehensive analysis of heart samples from autopsies of COVID-19 patients and discovered that cardiac involvement in COVID-19 is a macrophage-driven inflammatory process that is distinct from the typical anti-viral inflammatory responses. The study also found the presence of intussusceptive angiogenesis in the affected hearts, which is a key characteristic of vascular remodeling in COVID-19 pneumonia.
Article
Multidisciplinary Sciences
David L. Hoelscher, Nassim Bouteldja, Mehdi Joodaki, Maria L. Russo, Yu-Chia Lan, Alireza Vafaei Sadr, Mingbo Cheng, Vladimir Tesar, Saskia V. Stillfried, Barbara M. Klinkhammer, Jonathan Barratt, Juergen Floege, Ian S. D. Roberts, Rosanna Coppo, Ivan G. Costa, Roman D. Buelow, Peter Boor
Summary: Pathology diagnostics still rely on tissue morphology assessment by trained experts. Here, the authors perform deep-learning-based segmentation followed by large-scale feature extraction of histological images, i.e., next-generation morphometry, to enable outcome-relevant and disease-specific pathomics analysis of non-tumor kidney pathology.
NATURE COMMUNICATIONS
(2023)
Letter
Critical Care Medicine
Daniel Gagiannis, Carsten Hackenbroch, Wilhelm Bloch, Fabian Zech, Frank Kirchhoff, Sonja Djudjaj, Saskia von Stillfried, Roman Buelow, Peter Boor, Konrad Steinestel
AMERICAN JOURNAL OF RESPIRATORY AND CRITICAL CARE MEDICINE
(2023)
Editorial Material
Biochemistry & Molecular Biology
Maria Polychronidou, Jingyi Hou, M. Madan Babu, Prisca Liberali, Ido Amit, Bart Deplancke, Galit Lahav, Shalev Itzkovitz, Matthias Mann, Julio Saez-Rodriguez, Fabian Theis, Roland Eils
Summary: In this Editorial, our Chief Editor and members of our Advisory Editorial Board discuss the recent breakthroughs, current challenges, and emerging opportunities in single-cell biology, and share their vision for the future of the field.
MOLECULAR SYSTEMS BIOLOGY
(2023)
Letter
Biotechnology & Applied Microbiology
Sebastian Lobentanzer, Patrick Aloy, Jan Baumbach, Balazs Bohar, Vincent J. Carey, Pornpimol Charoentong, Katharina Danhauser, Tunca Dogan, Johann Dreo, Ian Dunham, Elias Farr, Adria Fernandez-Torras, Benjamin M. Gyori, Michael Hartung, Charles Tapley Hoyt, Christoph Klein, Tamas Korcsmaros, Andreas Maier, Matthias Mann, David Ochoa, Elena Pareja-Lorente, Ferdinand Popp, Martin Preusse, Niklas Probul, Benno Schwikowski, Buenyamin Sen, Maximilian T. Strauss, Denes Turei, Erva Ulusoy, Dagmar Waltemath, Judith A. H. Wodke, Julio Saez-Rodriguez
NATURE BIOTECHNOLOGY
(2023)
Article
Medicine, General & Internal
Jan D. Lanzer, Alberto Valdeolivas, Mark Pepin, Hauke Hund, Johannes Backs, Norbert Frey, Hans-Christoph Friederich, Jobst-Hendrik Schultz, Julio Saez-Rodriguez, Rebecca T. Levinson
Summary: Using systems medicine approaches, we analyzed comorbidity profiles of heart failure patients and identified distinct profiles for HFpEF and HFrEF. This can improve diagnosis and treatment for HFpEF patients.
Article
Computer Science, Interdisciplinary Applications
Isaac Shiri, Behrooz Razeghi, Alireza Vafaei Sadr, Mehdi Amini, Yazdan Salimi, Sohrab Ferdowsi, Peter Boor, Deniz Guenduez, Slava Voloshynovskiy, Habib Zaidi
Summary: A federated learning (FL) framework was developed for multi-institutional PET/CT image segmentation. The FL algorithms showed comparable performance to centralized learning methods and outperformed the single center-based baseline. The results have promising implications for HN tumor segmentation from PET/CT images.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Urology & Nephrology
Masaomi Nangaku, A. Richard Kitching, Peter Boor, Alessia Fornoni, Jurgen Floege, P. Toby Coates, Jonathan Himmelfarb, Rachel Lennon, Hans-Joachim Anders, Benjamin D. Humphreys, Fergus J. Caskey, Agnes B. Fogo
Summary: The International Society of Nephrology organized the TRANSFORM meeting to provide guidance on translational animal studies for new drug development in kidney disease. The meeting covered various themes such as disease model selection, pharmacokinetics, interventions, choice of animal, statistical power, organoids and organ-on-a-chip models, and reporting of results. These recommendations aim to accelerate the development of new drugs for efficacious diseases.
KIDNEY INTERNATIONAL
(2023)
Review
Biochemistry & Molecular Biology
Theodore Alexandrov, Julio Saez-Rodriguez, Sinem K. Saka
Summary: Spatial omics is a rapidly growing field that integrates imaging and omics to obtain spatially resolved information. It has opened up new opportunities and challenges for method developers and provides a new window into spatial biology.
MOLECULAR SYSTEMS BIOLOGY
(2023)
Article
Mathematical & Computational Biology
Roman D. Buelow, David L. Hoelscher, Ivan G. Costa, Peter Boor
NPJ SYSTEMS BIOLOGY AND APPLICATIONS
(2023)
Article
Immunology
Patricia Sole, Jun Yamanouchi, Josep Garnica, Muhammad Myn Uddin, Robert Clarke, Joel Moro, Nahir Garabatos, Shari Thiessen, Mireia Ortega, Santiswarup Singha, Debajyoti Mondal, Cesar Fandos, Julio Saez-Rodriguez, Yang Yang, Pau Serra, Pere Santamaria
Summary: Chronic antigenic stimulation can induce the differentiation of CD4(+) T cells into T regulatory type 1 (TR1) cells, which produce interleukin-10 and do not express FOXP3. The progenitors and transcriptional regulators of this T-cell subset are still unknown.
CELLULAR & MOLECULAR IMMUNOLOGY
(2023)
Article
Surgery
Alton B. Farris, Mariam P. Alexander, Ulysses G. J. Balis, Laura Barisoni, Peter Boor, Roman D. Bulow, Lynn D. Cornell, Anthony J. Demetris, Evan Farkash, Meyke Hermsen, Julien Hogan, Renate Kain, Jesper Kers, Jun Kong, Richard M. Levenson, Alexandre Loupy, Maarten Naesens, Pinaki Sarder, John E. Tomaszewski, Jeroen van der Laak, Dominique van Midden, Yukako Yagi, Kim Solez
Summary: The Banff Digital Pathology Working Group aims to establish a digital pathology repository and promote collaborations through the development, validation, and sharing of image analysis models, as well as regular videoconferencing. AI-based support systems for transplantation pathology were presented during the discussions, and potential collaborations in competitions/trials on AI applied to kidney transplant specimens were also discussed.
TRANSPLANT INTERNATIONAL
(2023)