Publications

What is a Publication?
377 Publications visible to you, out of a total of 377

Abstract

Not specified

Authors: Daniel Moyo, Lynette Beattie, Paul S. Andrews, John W. J. Moore, Jon Timmis, Amy Sawtell, Stefan Hoehme, Adam T. Sampson, Paul M. Kaye

Date Published: 27th Mar 2018

Publication Type: Journal

Abstract (Expand)

Maintenance of tissue extracellular matrix (ECM) and its biomechanical properties for tissue engineering is one of the substantial challenges in the field of decellularization and recellularization. Preservation of the organ-specific biomatrix is crucial for successful recellularization to support cell survival, proliferation, and functionality. However, understanding ECM properties with and without its inhabiting cells as well as the transition between the two states lacks appropriate test methods capable of quantifying bulk viscoelastic parameters in soft tissues. We used compact magnetic resonance elastography (MRE) with 400, 500, and 600 Hz driving frequency to investigate rat liver specimens for quantification of viscoelastic property changes resulting from decellularization. Tissue structures in native and decellularized livers were characterized by collagen and elastin quantification, histological analysis, and scanning electron microscopy. Decellularization did not affect the integrity of microanatomy and structural composition of liver ECM but was found to be associated with increases in the relative amounts of collagen by 83-fold (37.4 +/- 17.5 vs. 0.5 +/- 0.01 mug/mg, p = 0.0002) and elastin by approx. 3-fold (404.1 +/- 139.6 vs. 151.0 +/- 132.3 mug/mg, p = 0.0046). Decellularization reduced storage modulus by approx. 9-fold (from 4.9 +/- 0.8 kPa to 0.5 +/- 0.5 kPa, p < 0.0001) and loss modulus by approx. 7-fold (3.6 kPa to 0.5 kPa, p < 0.0001), indicating a marked loss of global tissue rigidity as well as a property shift from solid towards more fluid tissue behavior (p = 0.0097). Our results suggest that the rigidity of liver tissue is largely determined by cellular components, which are replaced by fluid-filled spaces when cells are removed. This leads to an overall increase in tissue fluidity and a viscous drag within the relatively sparse remaining ECM. Compact MRE is an excellent tool for quantifying the mechanical properties of decellularized biological tissue and a promising candidate for useful applications in tissue engineering.

Authors: H. Everwien, A. Ariza de Schellenberger, N. Haep, H. Tzschatzsch, J. Pratschke, I. M. Sauer, J. Braun, K. H. Hillebrandt, I. Sack

Date Published: 17th Mar 2020

Publication Type: Not specified

Abstract

Not specified

Authors: S Wang, R Feng, X Yuan, F Wandrer, MP Ebert, H Bantel, H Li, S Dooley, HL Weng

Date Published: 2019

Publication Type: Not specified

Abstract (Expand)

Modular Response Analysis (MRA) is a suite of methods that under certain assumptions permits the precise reconstruction of both the directions and strengths of connections between network modules from network responses to perturbations. Standard MRA assumes that modules are insulated, thereby neglecting the existence of inter-modular protein complexes. Such complexes sequester proteins from different modules and propagate perturbations to the protein abundance of a downstream module retroactively to an upstream module. MRA-based network reconstruction detects retroactive, sequestration-induced connections when an enzyme from one module is substantially sequestered by its substrate that belongs to a different module. Moreover, inferred networks may surprisingly depend on the choice of protein abundances that are experimentally perturbed, and also some inferred connections might be false. Here, we extend MRA by introducing a combined computational and experimental approach, which allows for a computational restoration of modular insulation, unmistakable network reconstruction and discrimination between solely regulatory and sequestration-induced connections for a range of signaling pathways. Although not universal, our approach extends MRA methods to signaling networks with retroactive interactions between modules arising from enzyme sequestration effects.

Authors: D. Lill, O. S. Rukhlenko, A. J. Mc Elwee, E. Kashdan, J. Timmer, B. N. Kholodenko

Date Published: 1st Jun 2019

Publication Type: Not specified

Abstract

Not specified

Authors: Adrien Guillot, Marc Winkler, Milessa Silva Afonso, Abhishek Aggarwal, David Lopez, Hilmar Berger, Marlene S. Kohlhepp, Hanyang Liu, Burcin Özdirik, Johannes Eschrich, Jing Ma, Moritz Peiseler, Felix Heymann, Swetha Pendem, Sangeetha Mahadevan, Bin Gao, Lauri Diehl, Ruchi Gupta, Frank Tacke

Date Published: 2023

Publication Type: Journal

Abstract (Expand)

EXSIMO: EXecutable SImulation MOdel; Data, model and code for executable simulation model of hepatic glucose metabolism Reports: https://matthiaskoenig.github.io/exsimo/ Docker images:: https://hub.docker.com/r/matthiaskoenig/exsimo Github releases: https://github.com/matthiaskoenig/exsimo/releases

Author: Matthias König

Date Published: 2020

Publication Type: Misc

Abstract (Expand)

PK-DB is a database and web interface for pharmacokinetics data and information from clinical trials as well as pre-clinical research. PK-DB allows to curate pharmacokinetics data integrated with the corresponding meta-information. PK-DB is available at https://pk-db.com

Authors: Matthias König, Jan Grzegorzewski

Date Published: 1st Jun 2020

Publication Type: Misc

Abstract

sbmlsim: Python utilities for simulating SBML models available at https://github.com/matthiaskoenig/sbmlsim.

Author: Matthias König

Date Published: 1st Jul 2020

Publication Type: Misc

Abstract

sbmlutils is a collection of python utilities for working with SBML models implemented on top of libSBML and other libraries available from https://github.com/matthiaskoenig/sbmlutils

Author: Matthias König

Date Published: 1st Mar 2020

Publication Type: Misc

Abstract

Not specified

Authors: C. Lieven, M. E. Beber, B. G. Olivier, F. T. Bergmann, M. Ataman, P. Babaei, J. A. Bartell, L. M. Blank, S. Chauhan, K. Correia, C. Diener, A. Drager, B. E. Ebert, J. N. Edirisinghe, J. P. Faria, A. M. Feist, G. Fengos, R. M. T. Fleming, B. Garcia-Jimenez, V. Hatzimanikatis, W. van Helvoirt, C. S. Henry, H. Hermjakob, M. J. Herrgard, A. Kaafarani, H. U. Kim, Z. King, S. Klamt, E. Klipp, J. J. Koehorst, M. Konig, M. Lakshmanan, D. Y. Lee, S. Y. Lee, S. Lee, N. E. Lewis, F. Liu, H. Ma, D. Machado, R. Mahadevan, P. Maia, A. Mardinoglu, G. L. Medlock, J. M. Monk, J. Nielsen, L. K. Nielsen, J. Nogales, I. Nookaew, B. O. Palsson, J. A. Papin, K. R. Patil, M. Poolman, N. D. Price, O. Resendis-Antonio, A. Richelle, I. Rocha, B. J. Sanchez, P. J. Schaap, R. S. Malik Sheriff, S. Shoaie, N. Sonnenschein, B. Teusink, P. Vilaca, J. O. Vik, J. A. H. Wodke, J. C. Xavier, Q. Yuan, M. Zakhartsev, C. Zhang

Date Published: 4th Mar 2020

Publication Type: Journal

Abstract (Expand)

Metabolic reprogramming is a characteristic feature of cancer cells, but there is no unique metabolic program for all tumors. Genetic and gene expression studies have revealed heterogeneous inter- and intratumor patterns of metabolic enzymes and membrane transporters. The functional implications of this heterogeneity remain often elusive. Here, we applied a systems biology approach to gain a comprehensive and quantitative picture of metabolic changes in individual hepatocellular carcinoma (HCC). We used protein intensity profiles determined by mass spectrometry in samples of 10 human HCCs and the adjacent noncancerous tissue to calibrate Hepatokin1, a complex mathematical model of liver metabolism. We computed the 24-h profile of 18 metabolic functions related to carbohydrate, lipid, and nitrogen metabolism. There was a general tendency among the tumors toward downregulated glucose uptake and glucose release albeit with large intertumor variability. This finding calls into question that the Warburg effect dictates the metabolic phenotype of HCC. All tumors comprised elevated beta-oxidation rates. Urea synthesis was found to be consistently downregulated but without compromising the tumor's capacity for ammonia detoxification owing to increased glutamine synthesis. The largest intertumor heterogeneity was found for the uptake and release of lactate and the size of the cellular glycogen content. In line with the observed metabolic heterogeneity, the individual HCCs differed largely in their vulnerability against pharmacological treatment with metformin. Taken together, our approach provided a comprehensive and quantitative characterization of HCC metabolism that may pave the way for a computational a priori assessment of pharmacological therapies targeting metabolic processes of HCC.

Authors: N. Berndt, J. Eckstein, N. Heucke, T. Wuensch, R. Gajowski, M. Stockmann, D. Meierhofer, H. G. Holzhutter

Date Published: 8th Oct 2020

Publication Type: Journal

Abstract (Expand)

MicroRNA (miRNA)-mediated gene regulation contributes to liver pathophysiology, including hepatic stellate cell (HSC) activation and fibrosis progression. Here, we investigated the role of miR-942 in human liver fibrosis. The expression of miR-942, HSC activation markers, transforming growth factor-beta pseudoreceptor BMP and activin membrane-bound inhibitor (BAMBI), as well as collagen deposition, were investigated in 100 liver specimens from patients with varying degree of hepatitis B virus (HBV)-related fibrosis. Human primary HSCs and the immortalized cell line (LX2 cells) were used for functional studies. We found that miR-942 expression was upregulated in activated HSCs and correlated inversely with BAMBI expression in liver fibrosis progression. Transforming growth factor beta (TGF-beta) and lipopolyssacharide (LPS), two major drivers of liver fibrosis and inflammation, induce miR-942 expression in HSCs via Smad2/3 respective NF-kappaB/p50 binding to the miR-942 promoter. Mechanistically, the induced miR-942 degrades BAMBI mRNA in HSCs, thereby sensitizing the cells for fibrogenic TGF-beta signaling and also partly mediates LPS-induced proinflammatory HSC fate. In conclusion, the TGF-beta and LPS-induced miR-942 mediates HSC activation through downregulation of BAMBI in human liver fibrosis. Our study provides new insights on the molecular mechanism of HSC activation and fibrosis.

Authors: L. Tao, D. Xue, D. Shen, W. Ma, J. Zhang, X. Wang, W. Zhang, L. Wu, K. Pan, Y. Yang, Z. C. Nwosu, S. Dooley, E. Seki, C. Liu

Date Published: 12th Aug 2018

Publication Type: Not specified

Abstract (Expand)

IL-6 is a central mediator of the immediate induction of hepatic acute phase proteins (APP) in the liver during infection and after injury, but increased IL-6 activity has been associated with multiple pathological conditions. In hepatocytes, IL-6 activates JAK1-STAT3 signaling that induces the negative feedback regulator SOCS3 and expression of APPs. While different inhibitors of IL-6-induced JAK1-STAT3-signaling have been developed, understanding their precise impact on signaling dynamics requires a systems biology approach. Here we present a mathematical model of IL-6-induced JAK1-STAT3 signaling that quantitatively links physiological IL-6 concentrations to the dynamics of IL-6-induced signal transduction and expression of target genes in hepatocytes. The mathematical model consists of coupled ordinary differential equations (ODE) and the model parameters were estimated by a maximum likelihood approach, whereas identifiability of the dynamic model parameters was ensured by the Profile Likelihood. Using model simulations coupled with experimental validation we could optimize the long-term impact of the JAK-inhibitor Ruxolitinib, a therapeutic compound that is quickly metabolized. Model-predicted doses and timing of treatments helps to improve the reduction of inflammatory APP gene expression in primary mouse hepatocytes close to levels observed during regenerative conditions. The concept of improved efficacy of the inhibitor through multiple treatments at optimized time intervals was confirmed in primary human hepatocytes. Thus, combining quantitative data generation with mathematical modeling suggests that repetitive treatment with Ruxolitinib is required to effectively target excessive inflammatory responses without exceeding doses recommended by the clinical guidelines.

Authors: S. Sobotta, A. Raue, X. Huang, J. Vanlier, A. Junger, S. Bohl, U. Albrecht, M. J. Hahnel, S. Wolf, N. S. Mueller, L. A. D'Alessandro, S. Mueller-Bohl, M. E. Boehm, P. Lucarelli, S. Bonefas, G. Damm, D. Seehofer, W. D. Lehmann, S. Rose-John, F. van der Hoeven, N. Gretz, F. J. Theis, C. Ehlting, J. G. Bode, J. Timmer, M. Schilling, U. Klingmuller

Date Published: 9th Oct 2017

Publication Type: Not specified

Abstract (Expand)

Numerical modeling of biological systems has become an important assistance for understanding and predicting hepatic diseases like non‐alcoholic fatty liver disease (NAFLD) or the detoxification of drugs and toxines by the liver. We developed a model for the simulation of hepatic function‐perfusion processes using a multiscale and multiphase approach. Here, the liver lobules are described using a homogenization approach with a coupled set of partial differential equations (PDE) based on the Theory of Porous Media (TPM) to describe the coupled blood transport and tissue deformation. For the description of metabolic processes on cellular scale ordinary differential equations (ODE) are used. For many practical and clinical applications, e.g. optimization procedures or uncertainty quantification, a fast but reliable computation is required. Thus, we use a non‐linear model order reduction (MOR) based on an artificial neural network (ANN) for the prediction of simulation results. The practicability of this approach is shown in a comparison between the high fidelity numerical simulation of a NAFLD and the predicted results by the ANN.

Authors: Lena Lambers, Tim Ricken, Matthias König

Date Published: 1st Nov 2019

Publication Type: Journal

Abstract

Not specified

Authors: Stefan Hoehme, Francois Bertaux, William Weens, Bettina Grasl-Kraupp, Jan G. Hengstler, Dirk Drasdo

Date Published: 28th Dec 2017

Publication Type: Not specified

Abstract

Not specified

Authors: Stefan Hoehme, Rolf Gebhardt, JG Hengstler, D. Drasdo

Date Published: 18th May 2020

Publication Type: Misc

Abstract (Expand)

Drug-induced liver injury (DILI) has become a major problem for patients and for clinicians, academics and the pharmaceutical industry. To date, existing hepatotoxicity test systems are only poorly predictive and the underlying mechanisms are still unclear. One of the factors known to amplify hepatotoxicity is the tumor necrosis factor alpha (TNFalpha), especially due to its synergy with commonly used drugs such as diclofenac. However, the exact mechanism of how diclofenac in combination with TNFalpha induces liver injury remains elusive. Here, we combined time-resolved immunoblotting and live-cell imaging data of HepG2 cells and primary human hepatocytes (PHH) with dynamic pathway modeling using ordinary differential equations (ODEs) to describe the complex structure of TNFalpha-induced NFkappaB signal transduction and integrated the perturbations of the pathway caused by diclofenac. The resulting mathematical model was used to systematically identify parameters affected by diclofenac. These analyses showed that more than one regulatory module of TNFalpha-induced NFkappaB signal transduction is affected by diclofenac, suggesting that hepatotoxicity is the integrated consequence of multiple changes in hepatocytes and that multiple factors define toxicity thresholds. Applying our mathematical modeling approach to other DILI-causing compounds representing different putative DILI mechanism classes enabled us to quantify their impact on pathway activation, highlighting the potential of the dynamic pathway model as a quantitative tool for the analysis of DILI compounds.

Authors: A. Oppelt, D. Kaschek, S. Huppelschoten, R. Sison-Young, F. Zhang, M. Buck-Wiese, F. Herrmann, S. Malkusch, C. L. Kruger, M. Meub, B. Merkt, L. Zimmermann, A. Schofield, R. P. Jones, H. Malik, M. Schilling, M. Heilemann, B. van de Water, C. E. Goldring, B. K. Park, J. Timmer, U. Klingmuller

Date Published: 15th Jun 2018

Publication Type: Not specified

Abstract (Expand)

BACKGROUND & AIMS: Recently, spatial-temporal/metabolic mathematical models have been established that allow the simulation of metabolic processes in tissues. We applied these models to decipherer ammonia detoxification mechanisms in the liver. METHODS: An integrated metabolic-spatial-temporal model was used to generate hypotheses of ammonia metabolism. Predicted mechanisms were validated using time-resolved analyses of nitrogen metabolism, activity analyses, immunostaining and gene expression after induction of liver damage in mice. Moreover, blood from the portal vein, liver vein and mixed venous blood was analyzed in a time dependent manner. RESULTS: Modeling revealed an underestimation of ammonia consumption after liver damage when only the currently established mechanisms of ammonia detoxification were simulated. By iterative cycles of modeling and experiments, the reductive amidation of alpha-ketoglutarate (α-KG) via glutamate dehydrogenase (GDH) was identified as the lacking component. GDH is released from damaged hepatocytes into the blood where it consumes ammonia to generate glutamate, thereby providing systemic protection against hyperammonemia. This mechanism was exploited therapeutically in a mouse model of hyperammonemia by injecting GDH together with optimized doses of cofactors. Intravenous injection of GDH (720 U/kg), α-KG (280 mg/kg) and NADPH (180 mg/kg) reduced the elevated blood ammonia concentrations (>200 μM) to levels close to normal within only 15 min. CONCLUSION: If successfully translated to patients the GDH-based therapy might provide a less aggressive therapeutic alternative for patients with severe hyperammonemia.

Authors: Ahmed Ghallab, Géraldine Cellière, Sebastian G. Henkel, Dominik Driesch, Stefan Hoehme, Ute Hofmann, Sebastian Zellmer, Patricio Godoy, Agapios Sachinidis, Meinolf Blaszkewicz, Raymond Reif, Rosemarie Marchan, Lars Kuepfer, Dieter Häussinger, Dirk Drasdo, Rolf Gebhardt, Jan G. Hengstler

Date Published: 1st Apr 2016

Publication Type: Not specified

Abstract (Expand)

The metabolization and excretion of drugs in the liver are spatially heterogeneous processes. This is due to the spatial variability of physiological processes at different length scales of biological organization in healthy individuals, while many liver diseases further contribute to the heterogeneity. Classical, well-stirred pharmacokinetic models do not represent this heterogeneity, and various modeling approaches capable of representing heterogeneity have been developed recently. These approaches range from mechanistic and physio-geometrically realistic models focusing on specific spatial scales, via continuum models using homogenized physiological and metabolic properties, to integrative multiscale models. Such models could become essential research tools for simulations involving drugs with notable first-pass effects, fast-acting drugs or tracers, and diseased livers.

Authors: Lars Ole Schwen, Lars Kuepfer, Tobias Preusser

Date Published: 29th Nov 2017

Publication Type: Not specified

Abstract (Expand)

Lipidomes undergo permanent extensive remodeling, but how the turnover rate differs between lipid classes and molecular species is poorly understood. We employed metabolic (15)N labeling and shotgun ultra-high-resolution mass spectrometry (sUHR) to quantify the absolute (molar) abundance and determine the turnover rate of glycerophospholipids and sphingolipids by direct analysis of total lipid extracts. sUHR performed on a commercial Orbitrap Elite instrument at the mass resolution of 1.35 x 10(6) (m/z 200) baseline resolved peaks of (13)C isotopes of unlabeled and monoisotopic peaks of (15)N labeled lipids (Deltam = 0.0063 Da). Therefore, the rate of metabolic (15)N labeling of individual lipid species could be determined without compromising the scope, accuracy, and dynamic range of full-lipidome quantitative shotgun profiling. As a proof of concept, we employed sUHR to determine the lipidome composition and fluxes of 62 nitrogen-containing membrane lipids in human hepatoma HepG2 cells.

Authors: K. Schuhmann, K. Srzentic, K. O. Nagornov, H. Thomas, T. Gutmann, U. Coskun, Y. O. Tsybin, A. Shevchenko

Date Published: 5th Dec 2017

Publication Type: Not specified

Abstract

Not specified

Authors: Alaa Hammad, Seddik Hammad, Kerry Gould, Matthias P. Ebert, Steven Dooley, Anne Dropmann

Date Published: 2023

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

Abstract

Not specified

Authors: Pia Erdoesi, Maren Buettner, Matthias Meyer-Bender, Rizqah Kamies, IoannisK. Deligiannis, MichaelP. Menden, Steven Dooley, CeliaP. Martinez-Jimenez, Christoph Ogris, Seddik Hammad

Date Published: 2022

Publication Type: Journal

Abstract (Expand)

OBJECTIVES: The aim of this study was to noninvasively evaluate changes in renal stiffness, diffusion, and oxygenation in patients with chronic, advanced stage immunoglobulin A nephropathy (IgAN) by multiparametric magnetic resonance imaging using tomoelastography, diffusion-weighted imaging (DWI), and blood oxygen level-dependent (BOLD) imaging. MATERIALS AND METHODS: In this prospective study, 32 subjects (16 patients with biopsy-proven IgAN and 16 age- and sex-matched healthy controls) underwent multifrequency magnetic resonance elastography with tomoelastography postprocessing at 4 frequencies from 40 to 70 Hz to generate shear wave speed (meter per second) maps reflecting tissue stiffness. In addition, DWI and BOLD imaging were performed to determine the apparent diffusion coefficient in square millimeter per second and T2* relaxation time in milliseconds, respectively. Regions including the entire renal parenchyma of both kidneys were analyzed. Areas under the receiver operating characteristic (AUCs) curve were calculated to test diagnostic performance. Clinical parameters such as estimated glomerular filtration rate and protein-to-creatinine ratio were determined and correlated with imaging findings. RESULTS: Success rates of tomoelastography, DWI, and BOLD imaging regarding both kidneys were 100%, 91%, and 87%, respectively. Shear wave speed was decreased in IgAN (-21%, P < 0.0001), accompanied by lower apparent diffusion coefficient values (-12%, P = 0.004). BOLD imaging was not sensitive to IgAN (P = 0.12). Tomoelastography detected IgAN with higher diagnostic accuracy than DWI (area under the curve = 0.9 vs 0.8) and positively correlated with estimated glomerular filtration rate (r = 0.66, P = 0.006). CONCLUSIONS: Chronic, advanced stage IgAN is associated with renal softening and restricted water diffusion. Tomoelastography is superior to DWI and BOLD imaging in detecting IgAN.

Authors: S. T. Lang, J. Guo, A. Bruns, M. Durr, J. Braun, B. Hamm, I. Sack, S. R. Marticorena Garcia

Date Published: 2nd Jul 2019

Publication Type: Not specified

Abstract (Expand)

The Hedgehog (Hh) and Wnt/β-Catenin (Wnt) cascades are morphogen pathways whose pronounced influence on adult liver metabolism has been identified in recent years. How both pathways communicate and control liver metabolic functions are largely unknown. Detecting core components of Wnt and Hh signaling and mathematical modeling showed that both pathways in healthy liver act largely complementary to each other in the pericentral (Wnt) and the periportal zone (Hh) and communicate mainly by mutual repression. The Wnt/Hh module inversely controls the spatiotemporal operation of various liver metabolic pathways, as revealed by transcriptome, proteome, and metabolome analyses. Shifting the balance to Wnt (activation) or Hh (inhibition) causes pericentralization and periportalization of liver functions, respectively. Thus, homeostasis of the Wnt/Hh module is essential for maintaining proper liver metabolism and to avoid the development of certain metabolic diseases. With caution due to minor species-specific differences, these conclusions may hold for human liver as well.

Authors: Erik Kolbe, Susanne Aleithe, Christiane Rennert, Luise Spormann, Fritzi Ott, David Meierhofer, Robert Gajowski, Claus Stöpel, Stefan Hoehme, Michael Kücken, Lutz Brusch, Michael Seifert, Witigo von Schoenfels, Clemens Schafmayer, Mario Brosch, Ute Hofmann, Georg Damm, Daniel Seehofer, Jochen Hampe, Rolf Gebhardt, Madlen Matz-Soja

Date Published: 1st Dec 2019

Publication Type: Not specified

Abstract

Not specified

Authors: Astrid Ruiz-Margáin, Alessandra Pohlmann, Silke Lanzerath, Melanie Langheinrich, Alejandro Campos-Murguía, Berenice M. Román-Calleja, Robert Schierwagen, Sabine Klein, Frank Erhard Uschner, Maximilian Joseph Brol, Aldo Torre-Delgadillo, Nayelli C. Flores-García, Michael Praktiknjo, Ricardo U. Macías Rodríguez, Jonel Trebicka

Date Published: 1st Aug 2023

Publication Type: Journal

Powered by
(v.1.14.2)
Copyright © 2008 - 2023 The University of Manchester and HITS gGmbH