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94 Publications visible to you, out of a total of 94

Abstract

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Authors: Stefan Hoehme, Seddik Hammad, Jan Boettger, Brigitte Begher-Tibbe, Petru Bucur, Eric Vibert, Rolf Gebhardt, Jan G. Hengstler, Dirk Drasdo

Date Published: 2023

Publication Type: Journal

Abstract

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Authors: Le Tao, Guangyue Yang, Tiantian Sun, Jie Tao, Chan Zhu, Huimin Yu, Yalan Cheng, Zongguo Yang, Mingyi Xu, Yuefeng Jiang, Wei Zhang, Zhiyi Wang, Wenting Ma, Liu Wu, Dongying Xue, Dongxue Wang, Wentao Yang, Yongjuan Zhao, Shane Horsefield, Bostjan Kobe, Zhe Zhang, Zongxiang Tang, Qigen Li, Qiwei Zhai, Steven Dooley, Ekihiro Seki, Ping Liu, Jianrong Xu, Hongzhuan Chen, Cheng Liu

Date Published: 2023

Publication Type: Journal

Abstract

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Authors: Rilu Feng, Kejia Kan, Carsten Sticht, Yujia Li, Shanshan Wang, Hui Liu, Chen Shao, Stefan Munker, Hanno Niess, Sai Wang, Christoph Meyer, Roman Liebe, Matthias P. Ebert, Steven Dooley, Huiguo Ding, Honglei Weng

Date Published: 1st Dec 2022

Publication Type: Journal

Abstract (Expand)

MOTIVATION: Over the last decades, image processing and analysis have become one of the key technologies in systems biology and medicine. The quantification of anatomical structures and dynamic processes in living systems is essential for understanding the complex underlying mechanisms and allows, i.e. the construction of spatio-temporal models that illuminate the interplay between architecture and function. Recently, deep learning significantly improved the performance of traditional image analysis in cases where imaging techniques provide large amounts of data. However, if only a few images are available or qualified annotations are expensive to produce, the applicability of deep learning is still limited. RESULTS: We present a novel approach that combines machine learning-based interactive image segmentation using supervoxels with a clustering method for the automated identification of similarly colored images in large image sets which enables a guided reuse of interactively trained classifiers. Our approach solves the problem of deteriorated segmentation and quantification accuracy when reusing trained classifiers which is due to significant color variability prevalent and often unavoidable in biological and medical images. This increase in efficiency improves the suitability of interactive segmentation for larger image sets, enabling efficient quantification or the rapid generation of training data for deep learning with minimal effort. The presented methods are applicable for almost any image type and represent a useful tool for image analysis tasks in general. AVAILABILITY AND IMPLEMENTATION: The presented methods are implemented in our image processing software TiQuant which is freely available at tiquant.hoehme.com. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Authors: A. Friebel, T. Johann, D. Drasdo, S. Hoehme

Date Published: 30th Sep 2022

Publication Type: Journal

Abstract (Expand)

Erythropoietin (Epo) ensures survival and proliferation of colony-forming unit erythroid (CFU-E) progenitor cells and their differentiation to hemoglobin-containing mature erythrocytes. A lack of Epo-induced responses causes embryonic lethality, but mechanisms regulating the dynamic communication of cellular alterations to the organismal level remain unresolved. By time-resolved transcriptomics and proteomics, we show that Epo induces in CFU-E cells a gradual transition from proliferation signature proteins to proteins indicative for differentiation, including heme-synthesis enzymes. In the absence of the Epo receptor (EpoR) in embryos, we observe a lack of hemoglobin in CFU-E cells and massive iron overload of the fetal liver pointing to a miscommunication between liver and placenta. A reduction of iron-sulfur cluster-containing proteins involved in oxidative phosphorylation in these embryos leads to a metabolic shift toward glycolysis. This link connecting erythropoiesis with the regulation of iron homeostasis and metabolic reprogramming suggests that balancing these interactions is crucial for protection from iron intoxication and for survival.

Authors: S. Chakraborty, G. Andrieux, P. Kastl, L. Adlung, S. Altamura, M. E. Boehm, L. E. Schwarzmuller, Y. Abdullah, M. C. Wagner, B. Helm, H. J. Grone, W. D. Lehmann, M. Boerries, H. Busch, M. U. Muckenthaler, M. Schilling, U. Klingmuller

Date Published: 20th Sep 2022

Publication Type: Journal

Abstract (Expand)

Objectives. We assessed the potential of glial cell line-derived neurotrophic factor (GDNF) as a useful biomarker to predict cirrhosis in chronic hepatitis B (CHB) patients. Methods. A total of 735nts. Methods. A total of 735 patients from two medical centers (385 CHB patients and 350 healthy controls) were included to determine the association of serum and tissue GDNF levels with biopsy-proven cirrhosis. The diagnostic accuracy of serum GDNF (sGDNF) was estimated and compared with other indices of cirrhosis. Results. We showed significantly higher levels of sGDNF in CHB patients with fibrosis (28.4 pg/ml vs. 11.6 pg/ml in patients without) and patients with cirrhosis (33.8 pg/ml vs. 23.5 pg/ml in patients without). The areas under receiver operating curve (AUROCs) of sGDNF were 0.83 (95% confidence interval (CI): 0.80–0.87) for predicting liver fibrosis and 0.84 (95% CI: 0.79–0.89) for cirrhosis. Findings from the serum protein level and hepatic mRNA expression were consistent. Using the best cutoff to predict cirrhosis, we categorized the patients into sGDNF-high and sGDNF-low groups. The sGDNF-high group had significantly larger Masson’s trichrome and reticulin staining-positive area, higher Scheuer score, and METAVIR fibrosis stage (all p < 0.001 ) but not steatosis. On multivariable regression, sGDNF was independently associated with cirrhosis with an odds ratio of 6.98 (95% CI: 1.10–17.94). Finally, we demonstrated that sGDNF outperformed AST to platelet ratio index, FIB-4, fibroscore, forn index, and fibrometer in differentiating F4 vs. F3. Conclusion. Using serum, tissue mRNA, and biopsy data, our study revealed a significant potential of sGDNF as a novel noninvasive biomarker for cirrhosis in CHB patients.

Authors: Guangyue Yang, Liping Zhuang, Tiantian Sun, Yee Hui Yeo, Le Tao, Wei Zhang, Wenting Ma, Liu Wu, Zongguo Yang, Yanqin Yang, Dongying Xue, Jie Zhang, Rilu Feng, Ebert Matthias P., Steven Dooley, Ekihiro Seki, Ping Liu, Cheng Liu

Date Published: 9th Jul 2022

Publication Type: Journal

Abstract (Expand)

The hepatic Na+-taurocholate cotransporting polypeptide NTCP/SLC10A1 is important for the uptake of bile salts and selected drugs. Its inhibition results in increased systemic bile salt concentrations.oncentrations. NTCP is also the entry receptor for the hepatitis B/D virus. We investigated interindividual hepatic SLC10A1/NTCP expression using various omics technologies. SLC10A1/NTCP mRNA expression/protein abundance was quantified in well-characterized 143 human livers by real-time PCR and LC-MS/MS-based targeted proteomics. Genome-wide SNP arrays and SLC10A1 next-generation sequencing were used for genomic analyses. SLC10A1 DNA methylation was assessed through MALDI-TOF MS. Transcriptomics and untargeted metabolomics (UHPLC-Q-TOF-MS) were correlated to identify NTCP-related metabolic pathways. SLC10A1 mRNA and NTCP protein levels varied 44-fold and 10.4-fold, respectively. Non-genetic factors (e.g., smoking, alcohol consumption) influenced significantly NTCP expression. Genetic variants in SLC10A1 or other genes do not explain expression variability which was validated in livers (n = 50) from The Cancer Genome Atlas. The identified two missense SLC10A1 variants did not impair transport function in transfectants. Specific CpG sites in SLC10A1 as well as single metabolic alterations and pathways (e.g., peroxisomal and bile acid synthesis) were significantly associated with expression. Inter-individual variability of NTCP expression is multifactorial with the contribution of clinical factors, DNA methylation, transcriptional regulation as well as hepatic metabolism, but not genetic variation.

Authors: Roman Tremmel, Anne T. Nies, Barbara A. C. van Eijck, Niklas Handin, Mathias Haag, Stefan Winter, Florian A. Büttner, Charlotte Kölz, Franziska Klein, Pascale Mazzola, Ute Hofmann, Kathrin Klein, Per Hoffmann, Markus M. Nöthen, Fabienne Z. Gaugaz, Per Artursson, Matthias Schwab, Elke Schaeffeler

Date Published: 1st Jul 2022

Publication Type: Journal

Abstract (Expand)

In health and disease, liver cells are continuously exposed to cytokines and growth factors. While individual signal transduction pathways induced by these factors were studied in great detail, the cellular responses induced by repeated or combined stimulations are complex and less understood. Growth factor receptors on the cell surface of hepatocytes were shown to be regulated by receptor interactions, receptor trafficking and feedback regulation. Here, we exemplify how mechanistic mathematical modelling based on quantitative data can be employed to disentangle these interactions at the molecular level. Crucial is the analysis at a mechanistic level based on quantitative longitudinal data within a mathematical framework. In such multi-layered information, step-wise mathematical modelling using submodules is of advantage, which is fostered by sharing of standardized experimental data and mathematical models. Integration of signal transduction with metabolic regulation in the liver and mechanistic links to translational approaches promise to provide predictive tools for biology and personalized medicine.

Authors: Lorenza A. D’Alessandro, Ursula Klingmüller, Marcel Schilling

Date Published: 30th Jun 2022

Publication Type: Journal

Abstract (Expand)

The Hedgehog signaling pathway regulates many processes during embryogenesis and the homeostasis of adult organs. Recent data suggest that central metabolic processes and signaling cascades in the liver are controlled by the Hedgehog pathway and that changes in hepatic Hedgehog activity also affect peripheral tissues, such as the reproductive organs in females. Here, we show that hepatocyte-specific deletion of the Hedgehog pathway is associated with the dramatic expansion of adipose tissue in mice, the overall phenotype of which does not correspond to the classical outcome of insulin resistance-associated diabetes type 2 obesity. Rather, we show that alterations in the Hedgehog signaling pathway in the liver lead to a metabolic phenotype that is resembling metabolically healthy obesity. Mechanistically, we identified an indirect influence on the hepatic secretion of the fibroblast growth factor 21, which is regulated by a series of signaling cascades that are directly transcriptionally linked to the activity of the Hedgehog transcription factor GLI1. The results of this study impressively show that the metabolic balance of the entire organism is maintained via the activity of morphogenic signaling pathways, such as the Hedgehog cascade. Obviously, several pathways are orchestrated to facilitate liver metabolic status to peripheral organs, such as adipose tissue.

Authors: F. Ott, C. Korner, K. Werner, M. Gericke, I. Liebscher, D. Lobsien, S. Radrezza, A. Shevchenko, U. Hofmann, J. Kratzsch, R. Gebhardt, T. Berg, M. Matz-Soja

Date Published: 18th May 2022

Publication Type: Journal

Abstract (Expand)

Objective Multidrug resistance protein 2 (MRP2) is a bottleneck in bilirubin excretion. Its loss is sufficient to induce hyperbilirubinaemia, a prevailing characteristic of acute liver failure (ALF) characteristic of acute liver failure (ALF) that is closely associated with clinical outcome. This study scrutinises the transcriptional regulation of MRP2 under different pathophysiological conditions. Design Hepatic MRP2, farnesoid X receptor (FXR) and Forkhead box A2 (FOXA2) expression and clinicopathologic associations were examined by immunohistochemistry in 14 patients with cirrhosis and 22 patients with ALF. MRP2 regulatory mechanisms were investigated in primary hepatocytes, Fxr −/− mice and lipopolysaccharide (LPS)-treated mice. Results Physiologically, homeostatic MRP2 transcription is mediated by the nuclear receptor FXR/retinoid X receptor complex. Fxr −/− mice lack apical MRP2 expression and rapidly progress into hyperbilirubinaemia. In patients with ALF, hepatic FXR expression is undetectable, however, patients without infection maintain apical MRP2 expression and do not suffer from hyperbilirubinaemia. These patients express FOXA2 in hepatocytes. FOXA2 upregulates MRP2 transcription through binding to its promoter. Physiologically, nuclear FOXA2 translocation is inhibited by insulin. In ALF, high levels of glucagon and tumour necrosis factor α induce FOXA2 expression and nuclear translocation in hepatocytes. Impressively, ALF patients with sepsis express low levels of FOXA2, lose MRP2 expression and develop severe hyperbilirubinaemia. In this case, LPS inhibits FXR expression, induces FOXA2 nuclear exclusion and thus abrogates the compensatory MRP2 upregulation. In both Fxr −/− and LPS-treated mice, ectopic FOXA2 expression restored apical MRP2 expression and normalised serum bilirubin levels. Conclusion FOXA2 replaces FXR to maintain MRP2 expression in ALF without sepsis. Ectopic FOXA2 expression to maintain MRP2 represents a potential strategy to prevent hyperbilirubinaemia in septic ALF.

Authors: Sai Wang, Rilu Feng, Shan Shan Wang, Hui Liu, Chen Shao, Yujia Li, Frederik Link, Stefan Munker, Roman Liebe, Christoph Meyer, Elke Burgermeister, Matthias Ebert, Steven Dooley, Huiguo Ding, Honglei Weng

Date Published: 20th Apr 2022

Publication Type: Journal

Abstract

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Authors: Yujia Li, Weiguo Fan, Frederik Link, Sai Wang, Steven Dooley

Date Published: 1st Feb 2022

Publication Type: Journal

Abstract

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Authors: Steven Dooley, Jonel Trebicka, Sebastian Mueller

Date Published: 18th Jan 2022

Publication Type: Journal

Abstract (Expand)

Abstract Chronic alcohol consumption induces stress and damage in alcohol metabolising hepatocytes, which leads to inflammatory and fibrogenic responses. Besides these direct effects, alcohol disruptsffects, alcohol disrupts intestinal barrier functions and induces gut microbial dysbiosis, causing translocation of bacteria or microbial products through the gut mucosa to the liver and, which induce inflammation indirectly. Inflammation is one of the key drivers of alcohol-associated liver disease progression from steatosis to severe alcoholic hepatitis. The current standard of care for the treatment of severe alcoholic hepatitis is prednisolone, aiming to reduce inflammation. Prednisolone, however improves only short-term but not long-term survival rates in those patients, and even increases the risk for bacterial infections. Thus, recent studies focus on the exploration of more specific inflammatory targets for the treatment of severe alcoholic hepatitis. These comprise, among others interference with inflammatory cytokines, modulation of macrophage phenotypes or targeting of immune cell communication, as summarized in the present overview. Although several approaches give promising results in preclinical studies, data robustness and ability to transfer experimental results to human disease is still not sufficient for effective clinical translation.

Authors: Sophie Lotersztajn, Antonio Riva, Sai Wang, Steven Dooley, Shilpa Chokshi, Bin Gao

Date Published: 18th Jan 2022

Publication Type: Journal

Abstract (Expand)

Abstract Alcohol-related liver disease (ALD) impacts millions of patients worldwide each year and the numbers are increasing. Disease stages range from steatosis via steatohepatitis and fibrosis toepatitis and fibrosis to cirrhosis, severe alcohol-associated hepatitis and liver cancer. ALD is usually diagnosed at an advanced stage of progression with no effective therapies. A major research goal is to improve diagnosis, prognosis and also treatments for early ALD. This however needs prioritization of this disease for financial investment in basic and clinical research to more deeply investigate mechanisms and identify biomarkers and therapeutic targets for early detection and intervention. Topics of interest are communication of the liver with other organs of the body, especially the gut microbiome, the individual genetic constitution, systemic and liver innate inflammation, including bacterial infections, as well as fate and number of hepatic stellate cells and the composition of the extracellular matrix in the liver. Additionally, mechanical forces and damaging stresses towards the sophisticated vessel system of the liver, including the especially equipped sinusoidal endothelium and the biliary tract, work together to mediate hepatocytic import and export of nutritional and toxic substances, adapting to chronic liver disease by morphological and functional changes. All the aforementioned parameters contribute to the outcome of alcohol use disorder and the risk to develop advanced disease stages including cirrhosis, severe alcoholic hepatitis and liver cancer. In the present collection, we summarize current knowledge on these alcohol-related liver disease parameters, excluding the aspect of inflammation, which is presented in the accompanying review article by Lotersztajn and colleagues.

Authors: Bernd Schnabl, Gavin E. Arteel, Felix Stickel, Jan Hengstler, Nachiket Vartak, Ahmed Ghallab, Steven Dooley, Yujia Li, Robert F. Schwabe

Date Published: 18th Jan 2022

Publication Type: Journal

Abstract (Expand)

Abstract Summary Mass spectrometry-based proteomics is increasingly employed in biology and medicine. To generate reliable information from large datasets and ensure comparability of results, it isrge datasets and ensure comparability of results, it is crucial to implement and standardize the quality control of the raw data, the data processing steps and the statistical analyses. MSPypeline provides a platform for importing MaxQuant output tables, generating quality control reports, data preprocessing including normalization and performing exploratory analyses by statistical inference plots. These standardized steps assess data quality, provide customizable figures and enable the identification of differentially expressed proteins to reach biologically relevant conclusions. Availability and implementation The source code is available under the MIT license at https://github.com/siheming/mspypeline with documentation at https://mspypeline.readthedocs.io. Benchmark mass spectrometry data are available on ProteomeXchange (PXD025792). Supplementary information Supplementary data are available at Bioinformatics Advances online.

Authors: Simon Heming, Pauline Hansen, Artyom Vlasov, Florian Schwörer, Stephen Schaumann, Paulina Frolovaitė, Wolf-Dieter Lehmann, Jens Timmer, Marcel Schilling, Barbara Helm, Ursula Klingmüller

Date Published: 2022

Publication Type: Journal

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