Universitätspublikationen
Refine
Year of publication
Document Type
- Article (13448) (remove)
Language
- English (10736)
- German (2260)
- Portuguese (222)
- Spanish (97)
- Italian (53)
- French (36)
- Multiple languages (9)
- Ukrainian (9)
- slo (7)
- Turkish (4)
Has Fulltext
- yes (13448)
Keywords
- inflammation (90)
- COVID-19 (81)
- SARS-CoV-2 (60)
- Adorno (56)
- cancer (43)
- apoptosis (41)
- crystal structure (41)
- Inflammation (39)
- aging (39)
- glioblastoma (38)
Institute
- Medizin (5047)
- Physik (1517)
- Biowissenschaften (1037)
- Biochemie und Chemie (987)
- Gesellschaftswissenschaften (726)
- Frankfurt Institute for Advanced Studies (FIAS) (684)
- Geowissenschaften (508)
- Präsidium (445)
- Philosophie (431)
- Informatik (369)
- Institut für Sozialforschung (IFS) (337)
- Rechtswissenschaft (337)
- Senckenbergische Naturforschende Gesellschaft (330)
- Institut für Ökologie, Evolution und Diversität (321)
- E-Finance Lab e.V. (302)
- Psychologie (283)
- Biochemie, Chemie und Pharmazie (277)
- Biodiversität und Klima Forschungszentrum (BiK-F) (268)
- Neuere Philologien (218)
- Geschichtswissenschaften (213)
- Kulturwissenschaften (190)
- Exzellenzcluster Makromolekulare Komplexe (171)
- Wirtschaftswissenschaften (166)
- Psychologie und Sportwissenschaften (158)
- Pharmazie (156)
- MPI für Biophysik (132)
- Geowissenschaften / Geographie (126)
- Georg-Speyer-Haus (117)
- Sportwissenschaften (112)
- Exzellenzcluster Die Herausbildung normativer Ordnungen (111)
- Sonderforschungsbereiche / Forschungskollegs (108)
- Erziehungswissenschaften (102)
- Zentrum für Biomolekulare Magnetische Resonanz (BMRZ) (102)
- MPI für Hirnforschung (87)
- Zentrum für Arzneimittelforschung, Entwicklung und Sicherheit (ZAFES) (87)
- Geographie (86)
- Buchmann Institut für Molekulare Lebenswissenschaften (BMLS) (63)
- Mathematik (60)
- Informatik und Mathematik (57)
- Deutsches Institut für Internationale Pädagogische Forschung (DIPF) (49)
- Universitätsbibliothek (44)
- Evangelische Theologie (41)
- Sprach- und Kulturwissenschaften (38)
- ELEMENTS (37)
- MPI für empirische Ästhetik (37)
- Sustainable Architecture for Finance in Europe (SAFE) (31)
- Ernst Strüngmann Institut (25)
- Institut für sozial-ökologische Forschung (ISOE) (23)
- Philosophie und Geschichtswissenschaften (22)
- House of Finance (HoF) (20)
- Cornelia Goethe Centrum für Frauenstudien und die Erforschung der Geschlechterverhältnisse (CGC) (19)
- Exzellenzcluster Herz-Lungen-System (18)
- Center for Membrane Proteomics (CMP) (17)
- Fachübergreifend (17)
- Sprachwissenschaften (17)
- Starker Start ins Studium: Qualitätspakt Lehre (17)
- Sigmund-Freud Institut – Forschungsinstitut fur Psychoanalyse und ihre Anwendungen (16)
- Zentrum für Interdisziplinäre Afrikaforschung (ZIAF) (13)
- Extern (12)
- Universität des 3. Lebensalters e.V. (11)
- Katholische Theologie (10)
- Interdisziplinäres Zentrum für Neurowissenschaften Frankfurt (IZNF) (9)
- Institut für Wirtschaft, Arbeit, und Kultur (IWAK) (8)
- Center for Financial Studies (CFS) (7)
- Center for Scientific Computing (CSC) (7)
- Helmholtz International Center for FAIR (7)
- Institute for Monetary and Financial Stability (IMFS) (7)
- LOEWE-Schwerpunkt für Integrative Pilzforschung (7)
- DFG-Forschergruppen (6)
- Institute for Law and Finance (ILF) (6)
- Zentrum für Nordamerika-Forschung (ZENAF) (6)
- Goethe-Zentrum für Wissenschaftliches Rechnen (G-CSC) (5)
- Hessische Stiftung für Friedens- und Konfliktforschung (HSFK) (5)
- Hochschulrechenzentrum (5)
- Forschungszentrum Historische Geisteswissenschaften (FHG) (4)
- Frobenius Institut (4)
- Interdisziplinäres Zentrum für Ostasienstudien (IZO) (4)
- Zentrum für Weiterbildung (4)
- LOEWE-Schwerpunkt Außergerichtliche und gerichtliche Konfliktlösung (3)
- Akademie für Bildungsforschung und Lehrerbildung (bisher: Zentrum für Lehrerbildung und Schul- und Unterrichtsforschung) (2)
- Institut für Bienenkunde (2)
- Institut für Religionsphilosophische Forschung (2)
- keine Angabe Institut (2)
- (1)
- Centre for Drug Research (1)
- Diagnostic Center of Acute Leukemia (1)
- Europäische Akademie der Arbeit in der Universität Frankfurt am Main (1)
- Fachübergreifende Einrichtungen (1)
- SFB 268 (1)
- Wilhelm-Merton-Zentrum (1)
- Zentrale Einrichtung (1)
- studiumdigitale (1)
Background: Reactive oxygen species (ROS) and reactive nitrogen species (RNS) are produced during hemorrhagic shock and resuscitation (H/R), which may contribute to multiple organ failure. The AIM of this study was to test the hypothesis that green tea (Camellia sinenesis) extract containing 85% polyphenols decreases injury after H/R in rats by scavenging ROS and RNS. Method: S: Female Sprague Dawley rats were given 100 mg polyphenol extract/kg body weight or vehicle 2 h prior to hemorrhagic shock. H/R was induced by two protocols: 1) withdrawal of blood to a mean arterial pressure of 40 mm Hg followed by further withdrawals to decrease blood pressure progressively to 28 mm Hg over 1 h (severe), and 2) withdrawal of blood to a sustained hypotension of 40 mm Hg for 1 h (moderate). Rats were then resuscitated over 1 h with 60% of the shed blood volume plus twice the shed blood volume of lactated Ringer's solution. Serum samples were collected at 10 min and 2 h after resuscitation. At 2 or 18 h, livers were harvested for cytokine and 3-nitrotyrosine quantification, immunohistochemical detection of 4-hydroxynonenol (4-HNE) and inducible nitric oxide synthase (iNOS) protein expression. Results: After severe H/R, 18-h survival increased from 20% after vehicle to 70% after polyphenols (p<0.05). After moderate H/R, survival was greater (80%) and not different between vehicle and polyphenols. In moderate H/R, serum alanine aminotransferase (ALT) increased at 10 min and 2 h postresuscitation to 345 and 545 IU/L, respectively. Polyphenol treatment blunted this increase to 153 and 252 IU/L at 10 min and 2 h (p<0.01). Polyphenols also blunted increases in liver homogenates of TNFalpha (7.0 pg/mg with vehicle vs. 4.9 pg/mg with polyphenols, p<0.05), IL-1beta (0.80 vs. 0.37 pg/mg, p<0.05), IL-6 (6.9 vs. 5.1 pg/mg, p<0.05) and nitrotyrosine (1.9 pg/mg vs. 0.6 pg/mg, p<0.05) measured 18 h after H/R. Hepatic 4-HNE immunostaining indicative of lipid peroxidation also decreased from 4.8% after vehicle to 1.5% after polyphenols (p<0.05). By contrast, polyphenols did not block increased iNOS expression at 2 h after H/R. CONCLUSION: Polyphenols decrease ROS/RNS formation and are beneficial after hemorrhagic shock and resuscitation.
Background: Because Endomyocardial Biopsy has low sensitivity of about 20%, it can be performed near to myocardium that presented as Late Gadolinium Enhancement (LGE) in cardiovascular magnetic resonance (CMR). However the important issue of comparing topography of CMR and histological findings has not yet been investigated. Thus the current study was performed using an animal model of myocarditis. Results: In 10 male Lewis rats Experimental Autoimmune myocarditis was induced, 10 rats served as control. On day 21 animals were examined by CMR to compare topographic distribution of LGE to histological inflammation. Sensitivity, specificity, positive and negative predictive values for LGE in diagnosing myocarditis were determined for each segment of myocardium. Latter diagnostic values varied widely depending on topographic distribution of LGE and inflammation as well as on the used CMR sequence. Sensitivity of LGE was up to 76% (left lateral myocardium) and positive predictive values were up to 85% (left lateral myocardium), whereas sensitivity and positive predictive value dropped to 0 - 33% (left inferior myocardium). Conclusions: Topographic distribution of LGE and histological inflammation seem to influence sensitivity, specifity, positive and negative predictive values. Nevertheless, positive predictive value for LGE of up to 85% indicates that Endomyocardial Biopsy should be performed "MR-guided". LGE seems to have greater sensitivity than Endomyocardial Biopsy for the diagnosis of myocarditis.
In diesem Beitrag zur Frage nach dem Ausmaß von Einkommensarmut von Familien stehen zwei Aspekte im Mittelpunkt. – Zum einen ist im Vorfeld von Verteilungsanalysen die Art der Einkommensgewichtung in Mehrpersonenhaushalten zu klären. Nach Abwägung verschiedener Ansätze zur Ableitung einer Äquivalenzskala wurde eine Präferenz für ein institutionell orientiertes Gewichtungsschema, approximiert durch die alte OECD-Skala, begründet. – Zum anderen wurde der Einfluss der Frauenerwerbsbeteiligung auf die Einkommenssituation von Familien mit Kindern empirisch untersucht. Von prekären Einkommensverhältnissen und Einkommensarmut sind vor allem Familien mit geringfügig beschäftigter oder nichterwerbstätiger Partnerin sowie Alleinerziehende – Letztere wiederum bei fehlender Erwerbstätigkeit besonders stark – betroffen, wobei in den neuen Ländern die Situation wesentlich brisanter ist als in den alten Ländern. Bei politischen Maßnahmen sollten Erwerbswünsche der Frauen und Bedürfnisse der Familien berücksichtigt werden. Von daher sind Transfers im Rahmen des Familienleistungsausgleichs und die öffentliche Förderung von Kinderbetreuungseinrichtungen nicht als konkurrierende, sondern eher als komplementäre Konzepte zu diskutieren.
Since the description of sepsis by Schottmüller in 1914, the amount on knowledge available on sepsis and its underlying pathophysiology has substantially increased. Epidemiologic examinations of abdominal septic shock patients show the potential for high risk posed by and the extensive therapy situation in the intensive care unit (ICU) (5). Unfortunately, until now it has not been possible to significantly reduce the mortality rate of septic shock, which is as high as 50-60% worldwide, although PROWESS' results (1) are encouraging. This paper summarizes the main results of the MEDAN project and their medical impacts. Several aspects are already published, see the references. The heterogeneity of patient groups and the variations in therapy strategies is seen as one of the main problems for sepsis trials. In the MEDAN multi-center study of 71 intensive care units in Germany, a group of 382 patients made up exclusively of abdominal septic shock patients who met the consensus criteria for septic shock (3) was analysed. For use within scores or stand-alone experiments variables are often studied as isolated variables, not as a multidimensional whole, e.g. a recent study takes a look at the role thrombocytes play (15). To avoid this limitation, our study compares several established scores (SOFA, APACHE II, SAPS II, MODS) by a multi-dimensional neuronal network analysis. For outcome prediction the data of 382 patients was analysed by using most of the commonly documented vital parameters and doses of medicine (metric variables). Data was collected in German hospitals from 1998 to 2001. The 382 handwritten patient records were transferred to an electronic database giving the amount of 2.5 million data entries. The metric data contained in the database is composed of daily measurements and doses of medicine. We used range and plausibility checks to allow no faulty data in the electronic database. 187 of the 382 patients are deceased (49 %).
Attraction and commercial success of web sites depend heavily on the additional values visitors may find. Here, individual, automatically obtained and maintained user profiles are the key for user satisfaction. This contribution shows for the example of a cooking information site how user profiles might be obtained using category information provided by cooking recipes. It is shown that metrical distance functions and standard clustering procedures lead to erroneous results. Instead, we propose a new mutual information based clustering approach and outline its implications for the example of user profiling.
Data driven automatic model selection and parameter adaptation – a case study for septic shock
(2004)
In bioinformatics, biochemical pathways can be modeled by many differential equations. It is still an open problem how to fit the huge amount of parameters of the equations to the available data. Here, the approach of systematically learning the parameters is necessary. This paper propose as model selection criterion the least complex description of the observed data by the model, the minimum description length. For the small, but important example of inflammation modeling the performance of the approach is evaluated.
In bioinformatics, biochemical signal pathways can be modeled by many differential equations. It is still an open problem how to fit the huge amount of parameters of the equations to the available data. Here, the approach of systematically obtaining the most appropriate model and learning its parameters is extremely interesting. One of the most often used approaches for model selection is to choose the least complex model which “fits the needs”. For noisy measurements, the model which has the smallest mean squared error of the observed data results in a model which fits too accurately to the data – it is overfitting. Such a model will perform good on the training data, but worse on unknown data. This paper propose as model selection criterion the least complex description of the observed data by the model, the minimum description length. For the small, but important example of inflammation modeling the performance of the approach is evaluated. Keywords: biochemical pathways, differential equations, septic shock, parameter estimation, overfitting, minimum description length.
In bioinformatics, biochemical pathways can be modeled by many differential equations. It is still an open problem how to fit the huge amount of parameters of the equations to the available data. Here, the approach of systematically learning the parameters is necessary. In this paper, for the small, important example of inflammation modeling a network is constructed and different learning algorithms are proposed. It turned out that due to the nonlinear dynamics evolutionary approaches are necessary to fit the parameters for sparse, given data. Proceedings of the 15th IEEE International Conference on Tools with Artificial Intelligence - ICTAI 2003
In bioinformatics, biochemical pathways can be modeled by many differential equations. It is still an open problem how to fit the huge amount of parameters of the equations to the available data. Here, the approach of systematically learning the parameters is necessary. In this paper, for the small, important example of inflammation modeling a network is constructed and different learning algorithms are proposed. It turned out that due to the nonlinear dynamics evolutionary approaches are necessary to fit the parameters for sparse, given data. Keywords: model parameter adaption, septic shock. coupled differential equations, genetic algorithm.
In contrast to the symbolic approach, neural networks seldom are designed to explain what they have learned. This is a major obstacle for its use in everyday life. With the appearance of neuro-fuzzy systems which use vague, human-like categories the situation has changed. Based on the well-known mechanisms of learning for RBF networks, a special neuro-fuzzy interface is proposed in this paper. It is especially useful in medical applications, using the notation and habits of physicians and other medically trained people. As an example, a liver disease diagnosis system is presented.
The prevention of credit card fraud is an important application for prediction techniques. One major obstacle for using neural network training techniques is the high necessary diagnostic quality: Since only one financial transaction of a thousand is invalid no prediction success less than 99.9% is acceptable. Due to these credit card transaction proportions complete new concepts had to be developed and tested on real credit card data. This paper shows how advanced data mining techniques and neural network algorithm can be combined successfully to obtain a high fraud coverage combined with a low false alarm rate.
This paper describes the use of a Radial Basis Function (RBF) neural network in the approximation of process parameters for the extrusion of a rubber profile in tyre production. After introducing the rubber industry problem, the RBF network model and the RBF net learning algorithm are developed, which uses a growing number of RBF units to compensate the approximation error up to the desired error limit. Its performance is shown for simple analytic examples. Then the paper describes the modelling of the industrial problem. Simulations show good results, even when using only a few training samples. The paper is concluded by a discussion of possible systematic error influences, improvements and potential generalisation benefits. Keywords: Adaptive process control; Parameter estimation; RBF-nets; Rubber extrusion
Diese Arbeit plädiert für eine rationale Behandlung von Patientendaten und untersucht dazu die Analyse der Daten mit Hilfe neuronale Netze etwas näher. Erfolgreiche Beispielanwendungen zeigen, daß die menschlichen Diagnosefähigkeiten deutlich schlechter sind als neuronale Diagnosesysteme. Für das Beispiel der neueren Architektur mit RBF-Netzen wird die Funktionalität näher erläutert und gezeigt, wie menschliche und neuronale Expertise miteinander gekoppelt werden kann. Der Ausblick deutet Anwendungen und Praxisproblematik derartiger Systeme an.
In this paper we regard first the situation where parallel channels are disturbed by noise. With the goal of maximal information conservation we deduce the conditions for a transform which "immunizes" the channels against noise influence before the signals are used in later operations. It shows up that the signals have to be decorrelated and normalized by the filter which corresponds for the case of one channel to the classical result of Shannon. Additional simulations for image encoding and decoding show that this constitutes an efficient approach for noise suppression. Furthermore, by a corresponding objective function we deduce the stochastic and deterministic learning rules for a neural network that implements the data orthonormalization. In comparison with other already existing normalization networks our network shows approximately the same in the stochastic case but, by its generic deduction ensures the convergence and enables the use as independent building block in other contexts, e.g. whitening for independent component analysis. Keywords: information conservation, whitening filter, data orthonormalization network, image encoding, noise suppression.
Im Zeitraum 1. 11. 1993 bis 30. 3. 1997 wurden 1149 allgemeinchirurgische Intensivpatienten prospektiv erfaßt, von denen 114 die Kriterien des septischen Schocks erfüllten. Die Letalität der Patienten mit einem septischen Schock betrug 47,3%. Nach Training eines neuronalen Netzes mit 91 (von insgesamt n = 114) Patienten ergab die Testung bei den verbleibenden 23 Patienten bei der Berücksichtigung von Parameterveränderungen vom 1. auf den 2. Tag des septischen Schocks folgendes Ergebnis: Alle 10 verstorbenen Patienten wurden korrekt als nicht überlebend vorhergesagt, von den 13 Überlebenden wurden 12 korrekt als überlebend vorhergesagt (Sensitivität 100%; Spezifität 92,3%).
This paper describes the use of a radial basis function (RBF) neural network. It approximates the process parameters for the extrusion of a rubber profile used in tyre production. After introducing the problem, we describe the RBF net algorithm and the modeling of the industrial problem. The algorithm shows good results even using only a few training samples. It turns out that the „curse of dimensions“ plays an important role in the model. The paper concludes by a discussion of possible systematic error influences and improvements.
The paper focuses on the division of the sensor field into subsets of sensor events and proposes the linear transformation with the smallest achievable error for reproduction: the transform coding approach using the principal component analysis (PCA). For the implementation of the PCA, this paper introduces a new symmetrical, lateral inhibited neural network model, proposes an objective function for it and deduces the corresponding learning rules. The necessary conditions for the learning rate and the inhibition parameter for balancing the crosscorrelations vs. the autocorrelations are computed. The simulation reveals that an increasing inhibition can speed up the convergence process in the beginning slightly. In the remaining paper, the application of the network in picture encoding is discussed. Here, the use of non-completely connected networks for the self-organized formation of templates in cellular neural networks is shown. It turns out that the self-organizing Kohonen map is just the non-linear, first order approximation of a general self-organizing scheme. Hereby, the classical transform picture coding is changed to a parallel, local model of linear transformation by locally changing sets of self-organized eigenvector projections with overlapping input receptive fields. This approach favors an effective, cheap implementation of sensor encoding directly on the sensor chip. Keywords: Transform coding, Principal component analysis, Lateral inhibited network, Cellular neural network, Kohonen map, Self-organized eigenvector jets.
After a short introduction into traditional image transform coding, multirate systems and multiscale signal coding the paper focuses on the subject of image encoding by a neural network. Taking also noise into account a network model is proposed which not only learns the optimal localized basis functions for the transform but also learns to implement a whitening filter by multi-resolution encoding. A simulation showing the multi-resolution capabilitys concludes the contribution.
We present a framework for the self-organized formation of high level learning by a statistical preprocessing of features. The paper focuses first on the formation of the features in the context of layers of feature processing units as a kind of resource-restricted associative multiresolution learning We clame that such an architecture must reach maturity by basic statistical proportions, optimizing the information processing capabilities of each layer. The final symbolic output is learned by pure association of features of different levels and kind of sensorial input. Finally, we also show that common error-correction learning for motor skills can be accomplished also by non-specific associative learning. Keywords: feedforward network layers, maximal information gain, restricted Hebbian learning, cellular neural nets, evolutionary associative learning