TY - JOUR A1 - Montellano, Felipe A. A1 - Kluter, Elisabeth J. A1 - Rücker, Viktoria A1 - Ungethüm, Kathrin A1 - Mackenrodt, Daniel A1 - Wiedmann, Silke A1 - Dege, Tassilo A1 - Quilitzsch, Anika A1 - Morbach, Caroline A1 - Frantz, Stefan A1 - Störk, Stefan A1 - Haeusler, Karl Georg A1 - Kleinschnitz, Christoph A1 - Heuschmann, Peter U. T1 - Cardiac dysfunction and high-sensitive C-reactive protein are associated with troponin T elevation in ischemic stroke: insights from the SICFAIL study JF - BMC Neurology N2 - Background Troponin elevation is common in ischemic stroke (IS) patients. The pathomechanisms involved are incompletely understood and comprise coronary and non-coronary causes, e.g. autonomic dysfunction. We investigated determinants of troponin elevation in acute IS patients including markers of autonomic dysfunction, assessed by heart rate variability (HRV) time domain variables. Methods Data were collected within the Stroke Induced Cardiac FAILure (SICFAIL) cohort study. IS patients admitted to the Department of Neurology, Würzburg University Hospital, underwent baseline investigation including cardiac history, physical examination, echocardiography, and blood sampling. Four HRV time domain variables were calculated in patients undergoing electrocardiographic Holter monitoring. Multivariable logistic regression with corresponding odds ratios (OR) and 95% confidence intervals (CI) was used to investigate the determinants of high-sensitive troponin T (hs-TnT) levels ≥14 ng/L. Results We report results from 543 IS patients recruited between 01/2014–02/2017. Of those, 203 (37%) had hs-TnT ≥14 ng/L, which was independently associated with older age (OR per year 1.05; 95% CI 1.02–1.08), male sex (OR 2.65; 95% CI 1.54–4.58), decreasing estimated glomerular filtration rate (OR per 10 mL/min/1.73 m2 0.71; 95% CI 0.61–0.84), systolic dysfunction (OR 2.79; 95% CI 1.22–6.37), diastolic dysfunction (OR 2.29; 95% CI 1.29–4.02), atrial fibrillation (OR 2.30; 95% CI 1.25–4.23), and increasing levels of C-reactive protein (OR 1.48 per log unit; 95% CI 1.22–1.79). We did not identify an independent association of troponin elevation with the investigated HRV variables. Conclusion Cardiac dysfunction and elevated C-reactive protein, but not a reduced HRV as surrogate of autonomic dysfunction, were associated with increased hs-TnT levels in IS patients independent of established cardiovascular risk factors. KW - echocardiography KW - ischemic stroke KW - troponin KW - heart failure KW - biomarkers Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-300119 VL - 22 IS - 1 ER - TY - JOUR A1 - Albert, Judith A1 - Lezius, Susanne A1 - Störk, Stefan A1 - Morbach, Caroline A1 - Güder, Gülmisal A1 - Frantz, Stefan A1 - Wegscheider, Karl A1 - Ertl, Georg A1 - Angermann, Christiane E. T1 - Trajectories of Left Ventricular Ejection Fraction After Acute Decompensation for Systolic Heart Failure: Concomitant Echocardiographic and Systemic Changes, Predictors, and Impact on Clinical Outcomes JF - Journal of the American Heart Association N2 - Prospective longitudinal follow‐up of left ventricular ejection fraction (LVEF) trajectories after acute cardiac decompensation of heart failure is lacking. We investigated changes in LVEF and covariates at 6‐months' follow‐up in patients with a predischarge LVEF ≤40%, and determined predictors and prognostic implications of LVEF changes through 18‐months' follow‐up. Methods and Results Interdisciplinary Network Heart Failure program participants (n=633) were categorized into subgroups based on LVEF at 6‐months' follow‐up: normalized LVEF (>50%; heart failure with normalized ejection fraction, n=147); midrange LVEF (41%–50%; heart failure with midrange ejection fraction, n=195), or persistently reduced LVEF (≤40%; heart failure with persistently reduced LVEF , n=291). All received guideline‐directed medical therapies. At 6‐months' follow‐up, compared with patients with heart failure with persistently reduced LVEF, heart failure with normalized LVEF or heart failure with midrange LVEF subgroups showed greater reductions in LV end‐diastolic/end‐systolic diameters (both P<0.001), and left atrial systolic diameter (P=0.002), more increased septal/posterior end‐diastolic wall‐thickness (both P<0.001), and significantly greater improvement in diastolic function, biomarkers, symptoms, and health status. Heart failure duration <1 year, female sex, higher predischarge blood pressure, and baseline LVEF were independent predictors of LVEF improvement. Mortality and event‐free survival rates were lower in patients with heart failure with normalized LVEF (P=0.002). Overall, LVEF increased further at 18‐months' follow‐up (P<0.001), while LV end‐diastolic diameter decreased (P=0.048). However, LVEF worsened (P=0.002) and LV end‐diastolic diameter increased (P=0.047) in patients with heart failure with normalized LVEF hospitalized between 6‐months' follow‐up and 18‐months' follow‐up. Conclusions Six‐month survivors of acute cardiac decompensation for systolic heart failure showed variable LVEF trajectories, with >50% showing improvements by ≥1 LVEF category. LVEF changes correlated with various parameters, suggesting multilevel reverse remodeling, were predictable from several baseline characteristics, and were associated with clinical outcomes at 18‐months' follow‐up. Repeat hospitalizations were associated with attenuation of reverse remodeling." KW - acute heart failure KW - left ventricular ejection fraction KW - morbidity KW - mortality KW - natriuretic peptide KW - recovery Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-230210 VL - 10 ER - TY - JOUR A1 - Heuschmann, Peter U. A1 - Montellano, Felipe A. A1 - Ungethüm, Kathrin A1 - Rücker, Viktoria A1 - Wiedmann, Silke A1 - Mackenrodt, Daniel A1 - Quilitzsch, Anika A1 - Ludwig, Timo A1 - Kraft, Peter A1 - Albert, Judith A1 - Morbach, Caroline A1 - Frantz, Stefan A1 - Störk, Stefan A1 - Haeusler, Karl Georg A1 - Kleinschnitz, Christoph T1 - Prevalence and determinants of systolic and diastolic cardiac dysfunction and heart failure in acute ischemic stroke patients: The SICFAIL study JF - ESC Heart Failure N2 - Aims Ischaemic stroke (IS) might induce alterations of cardiac function. Prospective data on frequency of cardiac dysfunction and heart failure (HF) after IS are lacking. We assessed prevalence and determinants of diastolic dysfunction (DD), systolic dysfunction (SD), and HF in patients with acute IS. Methods and results The Stroke‐Induced Cardiac FAILure in mice and men (SICFAIL) study is a prospective, hospital‐based cohort study. Patients with IS underwent a comprehensive assessment of cardiac function in the acute phase (median 4 days after IS) including clinical examination, standardized transthoracic echocardiography by expert sonographers, and determination of blood‐based biomarkers. Information on demographics, lifestyle, risk factors, symptoms suggestive of HF, and medical history was collected by a standardized personal interview. Applying current guidelines, cardiac dysfunction was classified based on echocardiographic criteria into SD (left ventricular ejection fraction < 52% in men or <54% in women) and DD (≥3 signs of DD in patients without SD). Clinically overt HF was classified into HF with reduced, mid‐range, or preserved ejection fraction. Between January 2014 and February 2017, 696 IS patients were enrolled. Of them, patients with sufficient echocardiographic data on SD were included in the analyses {n = 644 patients [median age 71 years (interquartile range 60–78), 61.5% male]}. In these patients, full assessment of DD was feasible in 549 patients without SD (94%). Prevalence of cardiac dysfunction and HF was as follows: SD 9.6% [95% confidence interval (CI) 7.6–12.2%]; DD in patients without SD 23.3% (95% CI 20.0–27.0%); and clinically overt HF 5.4% (95% CI 3.9–7.5%) with subcategories of HF with preserved ejection fraction 4.35%, HF with mid‐range ejection fraction 0.31%, and HF with reduced ejection fraction 0.78%. In multivariable analysis, SD and fulfilment of HF criteria were associated with history of coronary heart disease [SD: odds ratio (OR) 3.87, 95% CI 1.93–7.75, P = 0.0001; HF: OR 2.29, 95% CI 1.04–5.05, P = 0.0406] and high‐sensitive troponin T at baseline (SD: OR 1.78, 95% CI 1.31–2.42, P = 0.0003; HF: OR 1.66, 95% CI 1.17–2.33, P = 0.004); DD was associated with older age (OR 1.08, 95% CI 1.05–1.11, P < 0.0001) and treated hypertension vs. no hypertension (OR 2.84, 95% CI 1.23–6.54, P = 0.0405). Conclusions A substantial proportion of the study population exhibited subclinical and clinical cardiac dysfunction. SICFAIL provides reliable data on prevalence and determinants of SD, DD, and clinically overt HF in patients with acute IS according to current guidelines, enabling further clarification of its aetiological and prognostic role. KW - Stroke KW - Heart failure KW - Cardiac dysfunction| Brain natriuretic peptide KW - Troponin Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-225656 VL - 8 IS - 2 ER - TY - THES A1 - Karl, Stefan T1 - Control Centrality in Non-Linear Biological Networks T1 - Kontrollzentralität in nichtlinearen biologischen Netzwerken N2 - Biological systems such as cells or whole organisms are governed by complex regulatory networks of transcription factors, hormones and other regulators which determine the behavior of the system depending on internal and external stimuli. In mathematical models of these networks, genes are represented by interacting “nodes” whose “value” represents the activity of the gene. Control processes in these regulatory networks are challenging to elucidate and quantify. Previous control centrality metrics, which aim to mathematically capture the ability of individual nodes to control biological systems, have been found to suffer from problems regarding biological plausibility. This thesis presents a new approach to control centrality in biological networks. Three types of network control are distinguished: Total control centrality quantifies the impact of gene mutations and identifies potential pharmacological targets such as genes involved in oncogenesis (e.g. zinc finger protein GLI2 or bone morphogenetic proteins in chondrocytes). Dynamic control centrality describes relaying functions as observed in signaling cascades (e.g control in mouse colon stem cells). Value control centrality measures the direct influence of the value of the node on the network (e.g. Indian hedgehog as an essential regulator of proliferation in chondrocytes). Well-defined network manipulations define all three centralities not only for nodes, but also for the interactions between them, enabling detailed insights into network pathways. The calculation of the new metrics is made possible by substantial computational improvements in the simulation algorithms for several widely used mathematical modeling paradigms for genetic regulatory networks, which are implemented in the regulatory network simulation framework Jimena created for this thesis. Applying the new metrics to biological networks and artificial random networks shows how these mathematical concepts correspond to experimentally verified gene functions and signaling pathways in immunity and cell differentiation. In contrast to controversial previous results even from the Barabási group, all results indicate that the ability to control biological networks resides in only few driver nodes characterized by a high number of connections to the rest of the network. Autoregulatory loops strongly increase the controllability of the network, i.e. its ability to control itself, and biological networks are characterized by high controllability in conjunction with high robustness against mutations, a combination that can be achieved best in sparsely connected networks with densities (i.e. connections to nodes ratios) around 2.0 - 3.0. The new concepts are thus considerably narrowing the gap between network science and biology and can be used in various areas such as system modeling, plausibility trials and system analyses. Medical applications discussed in this thesis include the search for oncogenes and pharmacological targets, as well their functional characterization. N2 - Biologische Systeme wie Zellen aber auch ganze Organismen werden durch ein komplexes Netzwerk von Transkriptionsfaktoren, Hormonen und anderen Regulatoren kontrolliert, welche das Verhalten des Systems in Abhängigkeit von internen und externen Einflüssen steuern. In mathematischen Modellen dieser Netzwerke werden Gene durch „Knoten“ repräsentiert, deren „Wert“ die Aktivität des Gens wiederspiegelt. Kontrollvorgänge in diesen Regulationsnetzwerken sind schwierig zu quantifizieren. Existierende Maße für die Kontrollzentralität, d.h. die Fähigkeit einzelner Knoten biologische Systeme zu kontrollieren, zeigen vor allem Probleme mit der biologischen Plausibilität der Ergebnisse. Diese Dissertation stellt eine neue Definition der Kontrollzentralität vor. Dabei werden drei Typen der Kontrollzentralität unterschieden: Totale Kontrollzentralität quantifiziert den Einfluss von Mutationen eines Gens und hilft mögliche pharmakologische Ziele wie etwa Onkogene (z. B. das Zinkfingerprotein GLI2 oder Bone Morphogenetic Proteins in Chondrozyten) zu identifizieren. Dynamische Kontrollzentralität beschreibt signalweiterleitende Funktionen in Signalkaskaden (z. B. in Kontrollprozessen in Stammzellen des Mauskolons). Wert-Kontrollzentralität misst den Einfluss des Werts des Knotens (zum Beispiel die Rolle von Indian hedgehog als essentieller Regulator der Chondrozytenproliferation). Durch gezielte Manipulation von Netzwerken können die Zentralitäten nicht nur für Knoten, sondern auch für die Interaktionen zwischen ihnen bestimmt werden, was detaillierte Einblicke in Netzwerkpfade erlaubt. Möglich wird die Berechnung der neuen Maße durch substantielle Verbesserungen der Simulationsalgorithmen mehrerer häufig verwendeter mathematischer Muster für Genregulationsnetzwerke, welche in der für diese Dissertation entwickelten Software Jimena implementiert wurden. Durch die Anwendung der neuen Metriken auf biologische Netzwerke und künstliche Zufallsnetzwerke kann gezeigt werden, dass die mathematischen Konzepte experimentell bestätigte Funktionen von Genen und Signalpfaden im Immunsystem und der Zelldifferenzierung korrekt wiedergeben. Im Gegensatz zu umstrittenen Ergebnissen der Forschungsgruppe Barabási zeigt sich hier, dass die Fähigkeit, biologische Netzwerke zu kontrollieren, in nur wenigen Knoten konzentriert ist, welche sich vor allem durch viele Verbindungen zum Rest des Netzwerks auszeichnen. Knoten, welche ihre eigene Expression beeinflussen, steigern die Fähigkeit eines Netzwerkes sich selbst zu kontrollieren (Kontrollierbarkeit), und biologische Netzwerke zeichnen sich durch hohe Kontrollierbarkeit bei gleichzeitig hoher Resistenz gegenüber Mutationen aus. Diese Kombination kann am besten durch eher schwach verbundene Netzwerke erreicht werden, bei denen auf einen Knoten nur etwa 2 bis 3 Verbindungen kommen. Die neuen Konzepte schlagen so eine Brücke zwischen Netzwerkwissenschaften und Biologie, und sind in einer Vielzahl von Gebieten wie der Modellierung von Systemen sowie der Überprüfung ihrer Plausibilität und ihrer Analyse anwendbar. Medizinische Anwendungen, auf welche in dieser Dissertation eingegangen wird, sind zum Beispiel die Suche nach Onkogenen und pharmakologischen Zielen, aber auch deren funktionelle Analyse. KW - Bioinformatik KW - Genregulation KW - Nichtlineare Differentialgleichung KW - Genetic regulatory networks KW - Control centrality Y1 - 2016 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-150838 ER - TY - JOUR A1 - Stein, Katharina A1 - Coulibaly, Drissa A1 - Balima, Larba Hubert A1 - Goetze, Dethardt A1 - Linsenmair, Karl Eduard A1 - Porembski, Stefan A1 - Stenchly, Kathrin A1 - Theodorou, Panagiotis T1 - Plant-pollinator networks in savannas of Burkina Faso, West Africa JF - Diversity N2 - West African savannas are severely threatened with intensified land use and increasing degradation. Bees are important for terrestrial biodiversity as they provide native plant species with pollination services. However, little information is available regarding their mutualistic interactions with woody plant species. In the first network study from sub-Saharan West Africa, we investigated the effects of land-use intensity and climatic seasonality on plant–bee communities and their interaction networks. In total, we recorded 5686 interactions between 53 flowering woody plant species and 100 bee species. Bee-species richness and the number of interactions were higher in the low compared to medium and high land-use intensity sites. Bee- and plant-species richness and the number of interactions were higher in the dry compared to the rainy season. Plant–bee visitation networks were not strongly affected by land-use intensity; however, climatic seasonality had a strong effect on network architecture. Null-model corrected connectance and nestedness were higher in the dry compared to the rainy season. In addition, network specialization and null-model corrected modularity were lower in the dry compared to the rainy season. Our results suggest that in our study region, seasonal effects on mutualistic network architecture are more pronounced compared to land-use change effects. Nonetheless, the decrease in bee-species richness and the number of plant–bee interactions with an increase in land-use intensity highlights the importance of savanna conservation for maintaining bee diversity and the concomitant provision of ecosystem services. KW - bees KW - community composition KW - connectance KW - land-use intensity KW - modularity KW - mutualism KW - number of interactions KW - seasonality KW - woody plant richness Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-220157 SN - 1424-2818 VL - 13 IS - 1 ER - TY - JOUR A1 - Schlevogt, Bernhard A1 - Boeker, Klaus H. W. A1 - Mauss, Stefan A1 - Klinker, Hartwig A1 - Heyne, Renate A1 - Link, Ralph A1 - Simon, Karl-Georg A1 - Sarrazin, Christoph A1 - Serfert, Yvonne A1 - Manns, Michael P. A1 - Wedemeyer, Heiner T1 - Weight gain after interferon-free treatment of chronic hepatitis C — results from the German Hepatitis C-Registry (DHC-R) JF - Biomedicines N2 - Chronic hepatitis C can be treated very effectively with direct-acting antivirals (DAA) with only minor side effects compared to an interferon-containing treatment regimen. The significance of metabolic comorbidities after HCV cure is not well defined. This study aims to investigate short- and long-term weight change of patients receiving interferon-free antiviral treatment for chronic hepatitis C. The German Hepatitis C-registry (DHC-R) is a national multicenter real-world cohort. A total of 5111 patients were followed prospectively after DAA treatment for up to 3 years. Weight change compared to baseline was analyzed at end of treatment and at years 1, 2, and 3 after completion of antiviral therapy. Regression analysis was performed to identify baseline predictors for weight change. While there was no relevant mean weight change (−0.2 kg, SD 4.3 kg) at the end of antiviral treatment, weight started to increase during long-term follow-up reaching +1.7 kg (SD 8.0 kg, p < 0.001) compared to baseline at 3 years (follow-up year 3, FU3) after completion of antiviral therapy. 48%, 31%, and 22% of patients had a weight gain greater than 1, 3, and 5 kg at FU3, respectively. During follow-up, a body mass index (BMI) <30 proved to be the only consistent predictor for weight gain. DAA treatment is followed by a substantial weight gain (+3 kg or more) in one-third of the patients during long-term follow-up. Non-obese patients seemed to be most vulnerable to weight gain. The body compartment involved in weight gain as well as the mechanism of weight gain remain to be elucidated. KW - chronic hepatitis C KW - direct-acting antivirals KW - interferon-free KW - HCV cure KW - weight gain KW - German Hepatitis C-Registry Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-248476 SN - 2227-9059 VL - 9 IS - 10 ER - TY - JOUR A1 - Karl, Stefan A1 - Dandekar, Thomas T1 - Jimena: Efficient computing and system state identification for genetic regulatory networks JF - BMC Bioinformatics N2 - Background: Boolean networks capture switching behavior of many naturally occurring regulatory networks. For semi-quantitative modeling, interpolation between ON and OFF states is necessary. The high degree polynomial interpolation of Boolean genetic regulatory networks (GRNs) in cellular processes such as apoptosis or proliferation allows for the modeling of a wider range of node interactions than continuous activator-inhibitor models, but suffers from scaling problems for networks which contain nodes with more than ~10 inputs. Many GRNs from literature or new gene expression experiments exceed those limitations and a new approach was developed. Results: (i) As a part of our new GRN simulation framework Jimena we introduce and setup Boolean-tree-based data structures; (ii) corresponding algorithms greatly expedite the calculation of the polynomial interpolation in almost all cases, thereby expanding the range of networks which can be simulated by this model in reasonable time. (iii) Stable states for discrete models are efficiently counted and identified using binary decision diagrams. As application example, we show how system states can now be sampled efficiently in small up to large scale hormone disease networks (Arabidopsis thaliana development and immunity, pathogen Pseudomonas syringae and modulation by cytokinins and plant hormones). Conclusions: Jimena simulates currently available GRNs about 10-100 times faster than the previous implementation of the polynomial interpolation model and even greater gains are achieved for large scale-free networks. This speed-up also facilitates a much more thorough sampling of continuous state spaces which may lead to the identification of new stable states. Mutants of large networks can be constructed and analyzed very quickly enabling new insights into network robustness and behavior. KW - Boolean function KW - genetic regulatory network KW - interpolation KW - stable state KW - binary decision diagram KW - Boolean tree Y1 - 2013 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-128671 VL - 14 ER - TY - JOUR A1 - Karl, Stefan A1 - Dandekar, Thomas T1 - Convergence behaviour and control in non-linear biological networks JF - Scientific Reports N2 - Control of genetic regulatory networks is challenging to define and quantify. Previous control centrality metrics, which aim to capture the ability of individual nodes to control the system, have been found to suffer from plausibility and applicability problems. Here we present a new approach to control centrality based on network convergence behaviour, implemented as an extension of our genetic regulatory network simulation framework Jimena (http://stefan-karl.de/jimena). We distinguish three types of network control, and show how these mathematical concepts correspond to experimentally verified node functions and signalling pathways in immunity and cell differentiation: Total control centrality quantifies the impact of node mutations and identifies potential pharmacological targets such as genes involved in oncogenesis (e.g. zinc finger protein GLI2 or bone morphogenetic proteins in chondrocytes). Dynamic control centrality describes relaying functions as observed in signalling cascades (e.g. src kinase or Jak/Stat pathways). Value control centrality measures the direct influence of the value of the node on the network (e.g. Indian hedgehog as an essential regulator of proliferation in chondrocytes). Surveying random scale-free networks and biological networks, we find that control of the network resides in few high degree driver nodes and networks can be controlled best if they are sparsely connected. KW - complex networks KW - control profiles KW - differentiation KW - pathways KW - tumors KW - models KW - centrality KW - chondrosarcoma KW - transcriptional regulation KW - regulatory networks Y1 - 2015 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-148510 VL - 5 IS - 09746 ER - TY - JOUR A1 - Kaltdorf, Martin A1 - Breitenbach, Tim A1 - Karl, Stefan A1 - Fuchs, Maximilian A1 - Kessie, David Komla A1 - Psota, Eric A1 - Prelog, Martina A1 - Sarukhanyan, Edita A1 - Ebert, Regina A1 - Jakob, Franz A1 - Dandekar, Gudrun A1 - Naseem, Muhammad A1 - Liang, Chunguang A1 - Dandekar, Thomas T1 - Software JimenaE allows efficient dynamic simulations of Boolean networks, centrality and system state analysis JF - Scientific Reports N2 - The signal modelling framework JimenaE simulates dynamically Boolean networks. In contrast to SQUAD, there is systematic and not just heuristic calculation of all system states. These specific features are not present in CellNetAnalyzer and BoolNet. JimenaE is an expert extension of Jimena, with new optimized code, network conversion into different formats, rapid convergence both for system state calculation as well as for all three network centralities. It allows higher accuracy in determining network states and allows to dissect networks and identification of network control type and amount for each protein with high accuracy. Biological examples demonstrate this: (i) High plasticity of mesenchymal stromal cells for differentiation into chondrocytes, osteoblasts and adipocytes and differentiation-specific network control focusses on wnt-, TGF-beta and PPAR-gamma signaling. JimenaE allows to study individual proteins, removal or adding interactions (or autocrine loops) and accurately quantifies effects as well as number of system states. (ii) Dynamical modelling of cell–cell interactions of plant Arapidopsis thaliana against Pseudomonas syringae DC3000: We analyze for the first time the pathogen perspective and its interaction with the host. We next provide a detailed analysis on how plant hormonal regulation stimulates specific proteins and who and which protein has which type and amount of network control including a detailed heatmap of the A.thaliana response distinguishing between two states of the immune response. (iii) In an immune response network of dendritic cells confronted with Aspergillus fumigatus, JimenaE calculates now accurately the specific values for centralities and protein-specific network control including chemokine and pattern recognition receptors. KW - cellular signalling networks KW - computer modelling Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-313303 VL - 13 ER - TY - JOUR A1 - Rauch, Bernhard A1 - Salzwedel, Annett A1 - Bjarnason-Wehrens, Birna A1 - Albus, Christian A1 - Meng, Karin A1 - Schmid, Jean-Paul A1 - Benzer, Werner A1 - Hackbusch, Matthes A1 - Jensen, Katrin A1 - Schwaab, Bernhard A1 - Altenberger, Johann A1 - Benjamin, Nicola A1 - Bestehorn, Kurt A1 - Bongarth, Christa A1 - Dörr, Gesine A1 - Eichler, Sarah A1 - Einwang, Hans-Peter A1 - Falk, Johannes A1 - Glatz, Johannes A1 - Gielen, Stephan A1 - Grilli, Maurizio A1 - Grünig, Ekkehard A1 - Guha, Manju A1 - Hermann, Matthias A1 - Hoberg, Eike A1 - Höfer, Stefan A1 - Kaemmerer, Harald A1 - Ladwig, Karl-Heinz A1 - Mayer-Berger, Wolfgang A1 - Metzendorf, Maria-Inti A1 - Nebel, Roland A1 - Neidenbach, Rhoia Clara A1 - Niebauer, Josef A1 - Nixdorff, Uwe A1 - Oberhoffer, Renate A1 - Reibis, Rona A1 - Reiss, Nils A1 - Saure, Daniel A1 - Schlitt, Axel A1 - Völler, Heinz A1 - Känel, Roland von A1 - Weinbrenner, Susanne A1 - Westphal, Ronja T1 - Cardiac rehabilitation in German speaking countries of Europe — evidence-based guidelines from Germany, Austria and Switzerland LLKardReha-DACH — Part 1 JF - Journal of Clinical Medicine N2 - Background: Although cardiovascular rehabilitation (CR) is well accepted in general, CR-attendance and delivery still considerably vary between the European countries. Moreover, clinical and prognostic effects of CR are not well established for a variety of cardiovascular diseases. Methods: The guidelines address all aspects of CR including indications, contents and delivery. By processing the guidelines, every step was externally supervised and moderated by independent members of the “Association of the Scientific Medical Societies in Germany” (AWMF). Four meta-analyses were performed to evaluate the prognostic effect of CR after acute coronary syndrome (ACS), after coronary bypass grafting (CABG), in patients with severe chronic systolic heart failure (HFrEF), and to define the effect of psychological interventions during CR. All other indications for CR-delivery were based on a predefined semi-structured literature search and recommendations were established by a formal consenting process including all medical societies involved in guideline generation. Results: Multidisciplinary CR is associated with a significant reduction in all-cause mortality in patients after ACS and after CABG, whereas HFrEF-patients (left ventricular ejection fraction <40%) especially benefit in terms of exercise capacity and health-related quality of life. Patients with other cardiovascular diseases also benefit from CR-participation, but the scientific evidence is less clear. There is increasing evidence that the beneficial effect of CR strongly depends on “treatment intensity” including medical supervision, treatment of cardiovascular risk factors, information and education, and a minimum of individually adapted exercise volume. Additional psychologic interventions should be performed on the basis of individual needs. Conclusions: These guidelines reinforce the substantial benefit of CR in specific clinical indications, but also describe remaining deficits in CR-delivery in clinical practice as well as in CR-science with respect to methodology and presentation. KW - cardiac rehabilitation standards KW - scientific guidelines KW - secondary prevention KW - coronary artery disease KW - chronic heart failure KW - heart valve repair KW - ICD-CRT KW - ventricular assist device KW - heart transplantation KW - peripheral artery disease KW - pulmonary hypertension KW - myocarditis KW - adults with congenital heart disease Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-239709 SN - 2077-0383 VL - 10 IS - 10 ER -