Refine
Has Fulltext
- yes (10969) (remove)
Year of publication
Document Type
- Journal article (7621)
- Doctoral Thesis (2795)
- Book article / Book chapter (133)
- Conference Proceeding (107)
- Preprint (107)
- Working Paper (66)
- Review (43)
- Report (27)
- Master Thesis (26)
- Book (19)
Language
- English (10969) (remove)
Keywords
- Toxikologie (119)
- Medizin (99)
- inflammation (91)
- Psychologie (86)
- Biochemie (85)
- cancer (80)
- Organische Chemie (68)
- gene expression (68)
- Anorganische Chemie (66)
- Maus (64)
Institute
- Theodor-Boveri-Institut für Biowissenschaften (1904)
- Graduate School of Life Sciences (794)
- Physikalisches Institut (595)
- Institut für Psychologie (491)
- Neurologische Klinik und Poliklinik (388)
- Medizinische Klinik und Poliklinik II (372)
- Institut für Organische Chemie (366)
- Medizinische Klinik und Poliklinik I (357)
- Institut für Anorganische Chemie (353)
- Institut für Molekulare Infektionsbiologie (353)
Schriftenreihe
- Cultural Animal Studies, Band 3 (24)
- Berichte aus der Informatik (1)
- Deuterocanonical and Cognate Literature Studies (1)
- Deuterocanonical and Cognate Literature Yearbook (1)
- International Archives of the History of Ideas / Archives internationales d’histoire des idées 242 (1)
- Methods in Molecular Biology 2533 (1)
- Methods in Molecular Biology; 2643 (1)
Sonstige beteiligte Institutionen
- VolkswagenStiftung (24)
- Johns Hopkins School of Medicine (17)
- Helmholtz Institute for RNA-based Infection Research (HIRI) (7)
- IZKF Nachwuchsgruppe Geweberegeneration für muskuloskelettale Erkrankungen (7)
- Clinical Trial Center (CTC) / Zentrale für Klinische Studien Würzburg (ZKSW) (5)
- Fraunhofer-Institut für Silicatforschung ISC (5)
- Johns Hopkins University School of Medicine (5)
- Wilhelm-Conrad-Röntgen-Forschungszentrum für komplexe Materialsysteme (5)
- Bernhard-Heine-Centrum für Bewegungsforschung (4)
- Johns Hopkins School of Medicine, Baltimore, MD, U.S. (4)
ResearcherID
- B-1911-2015 (1)
- B-4606-2017 (1)
- C-2593-2016 (1)
- D-1221-2009 (1)
- D-1250-2010 (1)
- I-5818-2014 (1)
- J-8841-2015 (1)
- M-1240-2017 (1)
- N-2030-2015 (1)
- N-3741-2015 (1)
Purpose
Image acquisition and subsequent manual analysis of cardiac cine MRI is time-consuming. The purpose of this study was to train and evaluate a 3D artificial neural network for semantic segmentation of radially undersampled cardiac MRI to accelerate both scan time and postprocessing.
Methods
A database of Cartesian short-axis MR images of the heart (148,500 images, 484 examinations) was assembled from an openly accessible database and radial undersampling was simulated. A 3D U-Net architecture was pretrained for segmentation of undersampled spatiotemporal cine MRI. Transfer learning was then performed using samples from a second database, comprising 108 non-Cartesian radial cine series of the midventricular myocardium to optimize the performance for authentic data. The performance was evaluated for different levels of undersampling by the Dice similarity coefficient (DSC) with respect to reference labels, as well as by deriving ventricular volumes and myocardial masses.
Results
Without transfer learning, the pretrained model performed moderately on true radial data [maximum number of projections tested, P = 196; DSC = 0.87 (left ventricle), DSC = 0.76 (myocardium), and DSC =0.64 (right ventricle)]. After transfer learning with authentic data, the predictions achieved human level even for high undersampling rates (P = 33, DSC = 0.95, 0.87, and 0.93) without significant difference compared with segmentations derived from fully sampled data.
Conclusion
A 3D U-Net architecture can be used for semantic segmentation of radially undersampled cine acquisitions, achieving a performance comparable with human experts in fully sampled data. This approach can jointly accelerate time-consuming cine image acquisition and cumbersome manual image analysis.
Timing seasonal events, like reproduction or diapause, is crucial for the survival of many species. Global change causes phenologies worldwide to shift, which requires a mechanistic explanation of seasonal time measurement. Day length (photoperiod) is a reliable indicator of winter arrival, but it remains unclear how exactly species measure day length. A reference for time of day could be provided by a circadian clock, by an hourglass clock, or, as some newer models suggest, by a damped circadian clock. However, damping of clock outputs has so far been rarely observed. To study putative clock outputs of Acyrthosiphon pisum aphids, we raised individual nymphs on coloured artificial diet, and measured rhythms in metabolic activity in light-dark illumination cycles of 16:08 hours (LD) and constant conditions (DD). In addition, we kept individuals in a novel monitoring setup and measured locomotor activity. We found that A. pisum is day-active in LD, potentially with a bimodal distribution. In constant darkness rhythmicity of locomotor behaviour persisted in some individuals, but patterns were mostly complex with several predominant periods. Metabolic activity, on the other hand, damped quickly. A damped circadian clock, potentially driven by multiple oscillator populations, is the most likely explanation of our results.
Anticipating where an event will occur enables us to instantaneously respond to events that occur at the expected location. Here we investigated if such spatial anticipations can be triggered by symbolic information that participants cannot consciously see. In two experiments involving a Posner cueing task and a visual search task, a central cue informed participants about the likely location of the next target stimulus. In half of the trials, this cue was rendered invisible by pattern masking. In both experiments, visible cues led to cueing effects, that is, faster responses after valid compared to invalid cues. Importantly, even masked cues caused cueing effects, though to a lesser extent. Additionally, we analyzed effects on attention that persist from one trial to the subsequent trial. We found that spatial anticipations are able to interfere with newly formed spatial anticipations and influence orienting of attention in the subsequent trial. When the preceding cue was visible, the corresponding spatial anticipation persisted to an extent that prevented a noticeable effect of masked cues. The effects of visible cues were likewise modulated by previous spatial anticipations, but were strong enough to also exert an impact on attention themselves. Altogether, the results suggest that spatial anticipations can be formed on the basis of unconscious stimuli, but that interfering influences like still active spatial anticipations can suppress this effect.
Aim
To assess the suitability of several 3D‐printed resins for the manufacturing of tooth replicas for endodontic training in comparison with commercially available replicas by analysing the properties of the materials and comparing them with real teeth during endodontic training.
Methodology
Tooth replicas were 3D‐printed using four resins (NextDent Model, NextDent C&B, V‐Print ee and Vero White Plus) and compared with two commercially available products (VDW and Smile Factory) as well as extracted human teeth. Martens hardness, indentation modulus and radiopacity were investigated on these tooth replicas. Experienced dentists evaluated the suitability of the replicas for endodontic training by comparing them with real teeth in terms of appearance, anatomy, radiopacity, similarity to dentine during access opening, canal gauging and canal instrumentation. Data were analysed using the Kolmogorov–Smirnov and Mann–Whitney U‐test.
Results
The greatest hardness values were recorded for human dentine (P < 0.001), followed by V‐Print ee and the commercial tooth replica of Smile Factory. The greatest radiopacity was associated with VOC and dentine (P < 0.001) in comparison with the other materials tested. The appearance of the in‐house printed tooth replicas was subjectively evaluated by the dentists as being more realistic than the commercially available products. No differences between the replicas was detected during mechanical instrumentation of root canals.
Conclusion
None of the tooth replicas were able to simulate human dentine from the perspectives evaluated. V‐Print ee had radiopacity comparable with dentine, but its hardness was not comparable with dentine.
Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single genes classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single genes classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single genes classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single genes sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single genes classifiers for predicting outcome in breast cancer.
The future of water-derived hydrogen as the “sustainable energy source” straightaway bets on the success of the sluggish oxygen-generating half-reaction. The endeavor to emulate the natural photosystem II for efficient water oxidation has been extended across the spectrum of organic and inorganic combinations. However, the achievement has so far been restricted to homogeneous catalysts rather than their pristine heterogeneous forms. The poor structural understanding and control over the mechanistic pathway often impede the overall development. Herein, we have synthesized a highly crystalline covalent organic framework (COF) for chemical and photochemical water oxidation. The interpenetrated structure assures the catalyst stability, as the catalyst’s performance remains unaltered after several cycles. This COF exhibits the highest ever accomplished catalytic activity for such an organometallic crystalline solid-state material where the rate of oxygen evolution is as high as ∼26,000 μmol L\(^{–1}\) s\(^{–1}\) (second-order rate constant k ≈ 1650 μmol L s\(^{–1}\) g\(^{–2}\)). The catalyst also proves its exceptional activity (k ≈ 1600 μmol L s\(^{–1}\) g\(^{–2}\)) during light-driven water oxidation under very dilute conditions. The cooperative interaction between metal centers in the crystalline network offers 20–30-fold superior activity during chemical as well as photocatalytic water oxidation as compared to its amorphous polymeric counterpart.
Pulsars (in short for Pulsating Stars) are magnetized, fast rotating neutron stars. The basic picture of a pulsar describes it as a neutron star which has a rotation axis that is not aligned with its magnetic field axis. The emission is assumed to be generated near the magnetic poles of the neutron star and emitted along the open magnetic field lines. Consequently, the corresponding beam of photons is emitted along the magnetic field line axis. The non-alignment of both, the rotation and the magnetic field axis, results in the effect that the emission of the pulsar is only seen if its beam points towards the observer.
The emission from a pulsar is therefore perceived as being pulsed although its generation is not. This rather simple geometrical model is commonly referred to as Lighthouse Model and has been widely accepted. However, it does not deliver an explanation of the precise mechanisms behind the emission from pulsars (see below for more details).
Nowadays more than 2000 pulsars are known. They are observed at various wavelengths. Multiwavelength studies have shown that some pulsars are visible only at certain wavelengths while the emission from others can be observed throughout large parts of the electromagnetic spectrum. An example of the latter case is the Crab pulsar which is also the main object of interest in this thesis. Originating from a supernova explosion observed in 1054 A.D. and discovered in 1968, the Crab pulsar has been the central subject of numerous studies. Its pulsed emission is visible throughout the whole electromagnetic spectrum which makes it a key figure in understanding the possible mechanisms of multiwavelength emission from pulsars.
The Crab pulsar is also well known for its radio emission strongly varying on long as well as on short time scales. While long time scale behaviour from a pulsar is usually examined through the use of its average profile (a profile resulting from averaging of a large number of individual pulses resulting from single rotations), short time scale behaviour is examined via its single pulses. The short time scale anomalous behaviour of its radio emission is commonly referred to as Giant Pulses and represents the central topic of this thesis.
While current theoretical approaches place the origin of the radio emission from a pulsar like the Crab near its magnetic poles (Polar Cap Model) as already indicated by the Lighthouse model, its emission at higher frequencies, especially its gamma-ray emission, is assumed to originate further away in the geometrical region surrounding a pulsar which is commonly referred to as a pulsar magnetosphere (Outer Gap Model). Consequently, the respective emission regions are usually assumed not to be connected. However, past observational results from the Crab pulsar represent a contradiction to this assumption.
Radio giant pulses from the Crab pulsar have been observed to emit large amounts of energy on very short time scales implying small emission regions on the surface of the pulsar. Such energetic events might also leave a trace in the gamma-ray emission of the Crab pulsar.
The aim of this thesis is to search for this connection in the form of a correlation study between radio giant pulses and gamma-photons from the Crab pulsar.
To make such a study possible, a multiwavelength observational campaign was organized for which radio observations were independently applied for, coordinated and carried out with the Effelsberg radio telescope and the Westerbork Synthesis Radio Telescope and gamma-ray observations with the Major Atmospheric Imaging Cherenkov telescopes. The corresponding radio and gamma-ray data sets were reduced and the correlation analysis thereafter consisted of three different approaches:
1) The search for a clustering in the differences of the times of arrival of radio giant pulses and gamma-photons;
2) The search for a linear correlation between radio giant pulses and gamma-photons using the Pearson correlation approach;
3) A search for an increase of the gamma-ray flux around occurring radio giant pulses.
In the last part of the correlation study an increase of the number of gamma-photons centered on a radio giant pulse by about 17% (in contrast with the number of gamma-photons when no radio giant pulse occurs in the same time window) was discovered. This finding suggests that a new theoretical approach for the emission of young pulsars like the Crab pulsar, is necessary.
In previous studies of a genetic isolate, we identified significant linkage of attention deficit hyperactivity disorder (ADHD) to 4q, 5q, 8q, 11q and 17p. The existence of unique large size families linked to multiple regions, and the fact that these families came from an isolated population, we hypothesized that two-locus interaction contributions to ADHD were plausible. Several analytical models converged to show significant interaction between 4q and 11q (P<1 × 10−8) and 11q and 17p (P<1 × 10−6). As we have identified that common variants of the LPHN3 gene were responsible for the 4q linkage signal, we focused on 4q–11q interaction to determine that single-nucleotide polymorphisms (SNPs) harbored in the LPHN3 gene interact with SNPs spanning the 11q region that contains DRD2 and NCAM1 genes, to double the risk of developing ADHD. This interaction not only explains genetic effects much better than taking each of these loci effects by separated but also differences in brain metabolism as depicted by proton magnetic resonance spectroscopy data and pharmacogenetic response to stimulant medication. These findings not only add information about how high order genetic interactions might be implicated in conferring susceptibility to develop ADHD but also show that future studies of the effects of genetic interactions on ADHD clinical information will help to shape predictive models of individual outcome.
This dissertation contributes to the empirical analysis of economic development. The continuing poverty in many Sub-Saharan-African countries as well as the declining trend in growth in the advanced economies that was initiated around the turn of the millennium raises a number of new questions which have received little attention in recent empirical studies. Is culture a decisive factor for economic development? Do larger financial markets trigger positive stimuli with regard to incomes, or is the recent increase in their size in advanced economies detrimental to economic growth? What causes secular stagnation, i.e. the reduction in growth rates of the advanced economies observable over the past 20 years? What is the role of inequality in the growth process, and how do governmental attempts to equalize the income distribution affect economic development? And finally: Is the process of democratization accompanied by an increase in living standards? These are the central questions of this doctoral thesis.
To facilitate the empirical analysis of the determinants of economic growth, this dissertation introduces a new method to compute classifications in the field of social sciences. The approach is based on mathematical algorithms of machine learning and pattern recognition. Whereas the construction of indices typically relies on arbitrary assumptions regarding the aggregation strategy of the underlying attributes, utilization of Support Vector Machines transfers the question of how to aggregate the individual components into a non-linear optimization problem.
Following a brief overview of the theoretical models of economic growth provided in the first chapter, the second chapter illustrates the importance of culture in explaining the differences in incomes across the globe. In particular, if inhabitants have a lower average degree of risk-aversion, the implementation of new technology proceeds much faster compared with countries with a lower tendency towards risk. However, this effect depends on the legal and political framework of the countries, their average level of education, and their stage of development.
The initial wealth of individuals is often not sufficient to cover the cost of investments in both education and new technologies. By providing loans, a developed financial sector may help to overcome this shortage. However, the investigations in the third chapter show that this mechanism is dependent on the development levels of the economies. In poor countries, growth of the financial sector leads to better education and higher investment levels. This effect diminishes along the development process, as intermediary activity is increasingly replaced by speculative transactions. Particularly in times of low technological innovation, an increasing financial sector has a negative impact on economic development. In fact, the world economy is currently in a phase of this kind. Since the turn of the millennium, growth rates in the advanced economies have experienced a multi-national decline, leading to an intense debate about "secular stagnation" initiated at the beginning of 2015. The fourth chapter deals with this phenomenon and shows that the growth potentials of new technologies have been gradually declining since the beginning of the 2000s.
If incomes are unequally distributed, some individuals can invest less in education and technological innovations, which is why the fifth chapter identifies an overall negative effect of inequality on growth. This influence, however, depends on the development level of countries. While the negative effect is strongly pronounced in poor economies with a low degree of equality of opportunity, this influence disappears during the development process. Accordingly, redistributive polices of governments exert a growth-promoting effect in developing countries, while in advanced economies, the fostering of equal opportunities is much more decisive.
The sixth chapter analyzes the growth effect of the political environment and shows that the ambiguity of earlier studies is mainly due to unsophisticated measurement of the degree of democratization. To solve this problem, the chapter introduces a new method based on mathematical algorithms of machine learning and pattern recognition. While the approach can be used for various classification problems in the field of social sciences, in this dissertation it is applied for the problem of democracy measurement. Based on different country examples, the chapter shows that the resulting SVMDI is superior to other indices in modeling the level of democracy. The subsequent empirical analysis emphasizes a significantly positive growth effect of democracy measured via SVMDI.
Semi-arid tree covers, in both high and coppice growth forms, play an essential role in protecting water and soil resources and provides multiple ecosystem services across fragile ecosystems. Thus, they require continuous inventories. Quantification of forest structure in these tree covers provides important measures for their management and biodiversity conservation. We present a framework, based on consumer-grade UAV photogrammetry, to separately estimate primary variables of tree height (H) and crown area (A) across diverse coppice and high stands dominated by Quercus brantii Lindl. along the latitudinal gradient of Zagros mountains of western Iran. Then, multivariate linear regressions were parametrized with H and A to estimate the diameter at breast height (DBH) of high trees because of its importance to accelerate the existing practical DBH inventories across Zagros Forests. The estimated variables were finally applied to a model tree aboveground biomass (AGB) for both vegetative growth forms by local allometric equations and Random Forest models. In each step, the estimated variables were evaluated against the field reference values, indicating practically high accuracies reaching root mean square error (RMSE) of 0.68 m and 4.74 cm for H and DBH, as well as relative RMSE < 10% for AGB estimates. The results generally suggest an effective framework for single tree-based attribute estimation over mountainous, semi-arid coppice, and high stands.
We present a supersymmetric left-right model which predicts gauge coupling unification close to the string scale and extra vector bosons at the TeV scale. The subtleties in constructing a model which is in agreement with the measured quark masses and mixing for such a low left-right breaking scale are discussed. It is shown that in the constrained version of this model radiative breaking of the gauge symmetries is possible and a SM-like Higgs is obtained. Additional CP-even scalars of a similar mass or even much lighter are possible. The expected mass hierarchies for the supersymmetric states differ clearly from those of the constrained MSSM. In particular, the lightest down-type squark, which is a mixture of the sbottom and extra vector-like states, is always lighter than the stop. We also comment on the model’s capability to explain current anomalies observed at the LHC.
We derive a multi-species BGK model with velocity-dependent collision frequency for a non-reactive, multi-component gas mixture. The model is derived by minimizing a weighted entropy under the constraint that the number of particles of each species, total momentum, and total energy are conserved. We prove that this minimization problem admits a unique solution for very general collision frequencies. Moreover, we prove that the model satisfies an H-Theorem and characterize the form of equilibrium.
The HIV-1 Vif protein is essential for viral fitness and pathogenicity. Vif decreases expression of cellular restriction factors APOBEC3G (A3G), A3F, A3D and A3H, which inhibit HIV-1 replication by inducing hypermutation during reverse transcription. Vif counteracts A3G at several levels (transcription, translation, and protein degradation) that altogether reduce the levels of A3G in cells and prevent its incorporation into viral particles. How Vif affects A3G translation remains unclear. Here, we uncovered the importance of a short conserved uORF (upstream ORF) located within two critical stem-loop structures of the 5′ untranslated region (5′-UTR) of A3G mRNA for this process. A3G translation occurs through a combination of leaky scanning and translation re-initiation and the presence of an intact uORF decreases the extent of global A3G translation under normal conditions. Interestingly, the uORF is also absolutely required for Vif-mediated translation inhibition and redirection of A3G mRNA into stress granules. Overall, we discovered that A3G translation is regulated by a small uORF conserved in the human population and that Vif uses this specific feature to repress its translation.
A remarkable feature of many small non-coding RNAs (sRNAs) of Escherichia coli and Salmonella is their accumulation in the stationary phase of bacterial growth. Several stress response regulators and sigma factors have been reported to direct the transcription of stationary phase-specific sRNAs, but a widely conserved sRNA gene that is controlled by the major stationary phase and stress sigma factor, Sigma(S) (RpoS), has remained elusive. We have studied in Salmonella the conserved SdsR sRNA, previously known as RyeB, one of the most abundant stationary phase-specific sRNAs in E. coli. Alignments of the sdsR promoter region and genetic analysis strongly suggest that this sRNA gene is selectively transcribed by Sigma(S). We show that SdsR down-regulates the synthesis of the major Salmonella porin OmpD by Hfq-dependent base pairing; SdsR thus represents the fourth sRNA to regulate this major outer membrane porin. Similar to the InvR, MicC and RybB sRNAs, SdsR recognizes the ompD mRNA in the coding sequence, suggesting that this mRNA may be primarily targeted downstream of the start codon. The SdsR-binding site in ompD was localized by 3'-RACE, an experimental approach that promises to be of use in predicting other sRNA-target interactions in bacteria.
The human ubiquitin ligase HUWE1 has key roles in tumorigenesis, yet it is unkown how its activity is regulated. We present the crystal structure of a C-terminal part of HUWE1, including the catalytic domain, and reveal an asymmetric auto-inhibited dimer. We show that HUWE1 dimerizes in solution and self-associates in cells, and that both occurs through the crystallographic dimer interface. We demonstrate that HUWE1 is inhibited in cells and that it can be activated by disruption of the dimer interface. We identify a conserved segment in HUWE1 that counteracts dimer formation by associating with the dimerization region intramolecularly. Our studies reveal, intriguingly, that the tumor suppressor p14ARF binds to this segment and may thus shift the conformational equilibrium of HUWE1 toward the inactive state. We propose a model, in which the activity of HUWE1 underlies conformational control in response to physiological cues—a mechanism that may be exploited for cancer therapy.
We investigate transport measurements on all II-VI semiconductor resonant tunneling diodes (RTDs). Being very versatile, the dilute magnetic semiconductor (DMS) system (Zn,Be,Mn,Cd)Se is a perfect testbed for various spintronic device designs, as it allows for separate control of electrical and magnetic properties. In contrast to the ferromagnetic semiconductor (Ga,Mn)As, doping ZnSe with Mn impurities does not alter the electrical properties of the semiconductor, as the magnetic dopant is isoelectric in the ZnSe host.
A Comprehensive Review on the Interplay between Neisseria spp. and Host Sphingolipid Metabolites
(2021)
Sphingolipids represent a class of structural related lipids involved in membrane biology and various cellular processes including cell growth, apoptosis, inflammation and migration. Over the past decade, sphingolipids have become the focus of intensive studies regarding their involvement in infectious diseases. Pathogens can manipulate the sphingolipid metabolism resulting in cell membrane reorganization and receptor recruitment to facilitate their entry. They may recruit specific host sphingolipid metabolites to establish a favorable niche for intracellular survival and proliferation. In contrast, some sphingolipid metabolites can also act as a first line defense against bacteria based on their antimicrobial activity. In this review, we will focus on the strategies employed by pathogenic Neisseria spp. to modulate the sphingolipid metabolism and hijack the sphingolipid balance in the host to promote cellular colonization, invasion and intracellular survival. Novel techniques and innovative approaches will be highlighted that allow imaging of sphingolipid derivatives in the host cell as well as in the pathogen.
A comprehensive approach for currency crises theories stressing the role of the anchor country
(2008)
The approach is based on the finding that new generations of currency crises theories always had developed ex post after popular currency crises. Discussing the main theories of currency crises shows their disparity: The First Generation of currency crises models argues based on the assumption of a chronic budget deficit that is being monetized by the domestic central bank. The result is a trade-off between an expansionary monetary policy that is focused on the internal economic balance and a fixed exchange rate which is depending on the rules of interest parity and purchasing power parity. This imbalance inevitably results in a currency crisis. Altogether, this theory argues with a disrupted external balance on the foreign exchange market. Second Generation currency crises models on the other side focus on the internal macroeconomic balance. The stability of a fixed exchange rate is depending on the economic benefit of the exchange rate system in relation to the social costs of maintaining it. As soon as social costs are increasing and showing up in deteriorating fundamentals, this leads to a speculative attack on the fixed exchange rate system. The term Third Generation of currency crises finally summarizes a variety of currency crises theories. These are also arguing psychologically to explain phenomena as contagion and spill-over effects to rationalize crises detached from the fundamental situation. Apart from the apparent inconsistency of the main theories of currency crises, a further observation is that these explanations focus on the crisis country only while international monetary transmission effects are left out of consideration. These however are a central parameter for the stability of fixed exchange rate systems, in exchange rate theory as well as in empirical observations. Altogether, these findings provide the motivation for developing a theoretical approach which integrates the main elements of the different generations of currency crises theories and which integrates international monetary transmission. Therefore a macroeconomic approach is chosen applying the concept of the Monetary Conditions Index (MCI), a linear combination of the real interest rate and the real exchange rate. This index firstly is extended for international monetary influences and called MCIfix. MCIfix illustrates the monetary conditions required for the stability of a fixed exchange rate system. The central assumption of this concept is that the uncovered interest parity is maintained. The main conclusion is that the MCIfix only depends on exogenous parameters. In a second step, the analysis integrates the monetary policy requirements for achieving an internal macroeconomic stability. By minimizing a loss function of social welfare, a MCI is derived which pictures the economically optimal monetary policy MCIopt. Instability in a fixed exchange rate system occurs as soon as the monetary conditions for an internal and external balance are deviating. For discussing macroeconomic imbalances, the central parameters determining the MCIfix (and therefore the relation of MCIfix to MCIopt) are discussed: the real interest rate of the anchor country, the real effective exchange rate and a risk premium. Applying this theory framework, four constellations are discussed where MCIfix and MCIopt fall apart in order to show the central bank’s possibilities for reacting and the consequences of that behaviour. The discussion shows that the integrative approach manages to incorporate the central elements of traditional currency crises theories and that it includes international monetary transmission instead of reducing the discussion on an inconsistent domestic monetary policy. The theory framework for fixed exchange rates is finally applied in four case studies: the currency crises in Argentina, the crisis in the Czech Republic, the Asian currency crisis and the crisis of the European Monetary System. The case studies show that the developed monetary framework achieves integration of different generations of crises theories and that the monetary policy of the anchor country plays a decisive role in destabilising fixed exchange rate systems.