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64 Publications visible to you, out of a total of 64

Abstract

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Authors: Ghulam A. Qadir, Ying Sun

Date Published: 2025

Publication Type: Journal

Abstract

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Authors: Anne Dropmann, Sophie Alex, Katharina Schorn, Chenhao Tong, Tiziana Caccamo, Patricio Godoy, Iryna Ilkavets, Roman Liebe, Daniela Gonzalez, Jan G. Hengstler, Albrecht Piiper, Luca Quagliata, Matthias S. Matter, Oliver Waidmann, Fabian Finkelmeier, Teng Feng, Thomas S. Weiss, Nuh Rahbari, Emrullah Birgin, Erik Rasbach, Stephanie Roessler, Kai Breuhahn, Marcell Tóth, Matthias P. Ebert, Steven Dooley, Seddik Hammad, Nadja M. Meindl-Beinker

Date Published: 1st Nov 2024

Publication Type: Journal

Abstract

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Authors: Christian Schmithals, Bianca Kakoschky, Dominic Denk, Maike von Harten, Jan Henrik Klug, Edith Hintermann, Anne Dropmann, Eman Hamza, Anne Claire Jacomin, Jens U. Marquardt, Stefan Zeuzem, Peter Schirmacher, Eva Herrmann, Urs Christen, Thomas J. Vogl, Oliver Waidmann, Steven Dooley, Fabian Finkelmeier, Albrecht Piiper

Date Published: 1st Jul 2024

Publication Type: Journal

Abstract (Expand)

Background: When massive necrosis occurs in acute liver failure (ALF), rapid expansion of HSCs called liver progenitor cells (LPCs) in a process called ductular reaction is required for survival. Thetular reaction is required for survival. The underlying mechanisms governing this process are not entirely known to date. In ALF, high levels of retinoic acid (RA), a molecule known for its pleiotropic roles in embryonic development, are secreted by activated HSCs. We hypothesized that RA plays a key role in ductular reaction during ALF. Methods: RNAseq was performed to identify molecular signaling pathways affected by all- trans retinoid acid (atRA) treatment in HepaRG LPCs. Functional assays were performed in HepaRG cells treated with atRA or cocultured with LX-2 cells and in the liver tissue of patients suffering from ALF. Results: Under ALF conditions, activated HSCs secreted RA, inducing RARα nuclear translocation in LPCs. RNAseq data and investigations in HepaRG cells revealed that atRA treatment activated the WNT-β-Catenin pathway, enhanced stemness genes (SOX9, AFP, and others), increased energy storage, and elevated the expression of ATP-binding cassette transporters in a RARα nuclear translocation-dependent manner. Further, atRA treatment–induced pathways were confirmed in a coculture system of HepaRG with LX-2 cells. Patients suffering from ALF who displayed RARα nuclear translocation in the LPCs had significantly better MELD scores than those without. Conclusions: During ALF, RA secreted by activated HSCs promotes LPC activation, a prerequisite for subsequent LPC-mediated liver regeneration.

Authors: Sai Wang, Frederik Link, Stefan Munker, Wenjing Wang, Rilu Feng, Roman Liebe, Yujia Li, Ye Yao, Hui Liu, Chen Shao, Matthias P.A. Ebert, Huiguo Ding, Steven Dooley, Hong-Lei Weng, Shan-Shan Wang

Date Published: 2024

Publication Type: Journal

Abstract (Expand)

Background and Aims: Transforming growth factor-β1 (TGF-β1) plays important roles in chronic liver diseases, including metabolic dysfunction-associated steatotic liver disease (MASLD). MASLD involvesSLD involves various biological processes including dysfunctional cholesterol metabolism and contributes to progression to metabolic dysfunction-associated steatohepatitis (MASH) and hepatocellular carcinoma (HCC). However, the reciprocal regulation of TGF-β1 signaling and cholesterol metabolism in MASLD is yet unknown. Methods: Changes in transcription of genes associated with cholesterol metabolism were assessed by RNA-Seq of murine hepatocyte cell line (AML12) and mouse primary hepatocytes (MPH) treated with TGF-β1. Functional assays were performed on AML12 cells (untreated, TGF-β1 treated, or subjected to cholesterol enrichment (CE) or depletion (CD)), and on mice injected with adeno-associated virus 8 (AAV8)-Control/TGF-β1. Results: TGF-β1 inhibited mRNA expression of several cholesterol metabolism regulatory genes, including rate-limiting enzymes of cholesterol biosynthesis in AML12 cells, MPHs, and AAV8-TGF-β1-treated mice. Total cholesterol levels and lipid droplet accumulation in AML12 cells and liver tissue were also reduced upon TGF-β1 treatment. Smad2/3 phosphorylation following 2 h TGF-β1 treatment persisted after CE or CD and was mildly increased following CD, while TGF-β1-mediated AKT phosphorylation (30 min) was inhibited by CE. Furthermore, CE protected AML12 cells from several effects mediated by 72 h incubation with TGF-β1, including EMT, actin polymerization, and apoptosis. CD mimicked the outcome of long term TGF- β1 administration, an effect that was blocked by an inhibitor of the type I TGF-β receptor. Additionally, the supernatant of CE- or CD-treated AML12 cells inhibited or promoted, respectively, the activation of LX-2 hepatic stellate cells. Conclusions: TGF-β1 inhibits cholesterol metabolism while cholesterol attenuates TGF-β1 downstream effects in hepatocytes.

Authors: Sai Wang, Frederik Link, Mei Han, Roohi Chaudhary, Anastasia Asimakopoulos, Roman Liebe, Ye Yao, Seddik Hammad, Anne Dropmann, Marinela Krizanac, Claudia Rubie, Laura Kim Feiner, Matthias Glanemann, Matthias Ebert, Ralf Weiskirchen, Yoav I Henis, Marcelo Ehrlich, Steven Dooley

Date Published: 15th Aug 2023

Publication Type: Journal

Abstract (Expand)

ional workflows describe the complex multi-step methods that are used for data collection, data preparation, analytics, predictive modelling, and simulation that lead to new data products. They can inherently contribute to the FAIR data principles: by processing data according to established metadata; by creating metadata themselves during the processing of data; and by tracking and recording data provenance. These properties aid data quality assessment and contribute to secondary data usage. Moreover, workflows are digital objects in their own right. This paper argues that FAIR principles for workflows need to address their specific nature in terms of their composition of executable software steps, their provenance, and their development.

Authors: Carole Goble, Sarah Cohen-Boulakia, Stian Soiland-Reyes, Daniel Garijo, Yolanda Gil, Michael R. Crusoe, Kristian Peters, Daniel Schober

Date Published: 2020

Publication Type: Journal

Abstract (Expand)

Life science researchers use computational models to articulate and test hypotheses about the behavior of biological systems. Semantic annotation is a critical component for enhancing the interoperability and reusability of such models as well as for the integration of the data needed for model parameterization and validation. Encoded as machine-readable links to knowledge resource terms, semantic annotations describe the computational or biological meaning of what models and data represent. These annotations help researchers find and repurpose models, accelerate model composition and enable knowledge integration across model repositories and experimental data stores. However, realizing the potential benefits of semantic annotation requires the development of model annotation standards that adhere to a community-based annotation protocol. Without such standards, tool developers must account for a variety of annotation formats and approaches, a situation that can become prohibitively cumbersome and which can defeat the purpose of linking model elements to controlled knowledge resource terms. Currently, no consensus protocol for semantic annotation exists among the larger biological modeling community. Here, we report on the landscape of current annotation practices among the COmputational Modeling in BIology NEtwork community and provide a set of recommendations for building a consensus approach to semantic annotation.

Authors: M. L. Neal, M. Konig, D. Nickerson, G. Misirli, R. Kalbasi, A. Drager, K. Atalag, V. Chelliah, M. T. Cooling, D. L. Cook, S. Crook, M. de Alba, S. H. Friedman, A. Garny, J. H. Gennari, P. Gleeson, M. Golebiewski, M. Hucka, N. Juty, C. Myers, B. G. Olivier, H. M. Sauro, M. Scharm, J. L. Snoep, V. Toure, A. Wipat, O. Wolkenhauer, D. Waltemath

Date Published: 22nd Mar 2019

Publication Type: InBook

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