Pseudoaneurysm Repair With a Septal Occluder

Introduction: New treatment options, like endovascular aortic repair, reduced the mortality rate of patients suffering from complications after an acute type A aortic dissection repair. Nevertheless, initial successful treatment of an aortic dissection does not fully eliminate the risk of later adverse aortic events like anastomotic pseudoaneurysm. Pseudoaneurysm of the anastomosis between the ascending and the arch graft could initiate complications like peripheral embolization, dysphagia or compression of mediastinum organs. Re-operation via re-sternotomy bears enormous morbidity and mortality for these patients. There is a high unmet need for percutaneous therapeutic options to treat pseudoaneurysms. Case Presentation: A 59-year-old-man treated 15 years ago for type A aortic dissection, was hospitalized due to intermittent abdominal pain. A detailed examination revealed 2 pseudoaneurysms: 1 symptomatic at the level of the reimplanted celiac trunk and 1 asymptomatic at the anastomosis between the brachiocephalic trunk and the aortic arch graft. Due to multiple co-morbidities and previous operations, the risk for surgery was considered too high. Both pseudoaneurysm were treated percutaneously, the symptomatic 1 with covered stent and the asymptomatic with Amplatzer septal-occluder. Discussion: We present an alternative percutaneous therapy approach for treatment of pseudoaneurysm using a septaloccluder. A follow-up computed tomography 3 months later showed successfully excluded pseudoaneurysm

Effekte heuristischer Lösungsbeispiele in kooperativen Settings auf mathematische Argumentationskompetenz bei Lehramtsstudierenden

Mathematisches Argumentieren zählt zu den professionellen Anforderungen an angehende Mathematiklehrkräfte. Zur Förderung derartiger komplexer Kompetenzen haben sich heuristische Lösungsbeispiele als geeignet erwiesen. Offen ist, wie dieser Ansatz in kooperativen Settings auf unterschiedliche Kompetenzkomponenten bei Lernenden mit heterogenen Lernvoraussetzungen wirkt. Vorgestellt werden Fragestellungen, Design und Ergebnisse der Interventionsstudien aus dem DFG-Projekt ELK-Math

Symmetries, Safety, and Self-Supervision

Collider searches face the challenge of defining a representation of high-dimensional data such that physical symmetries are manifest, the discriminating features are retained, and the choice of representation is new-physics agnostic. We introduce JetCLR to solve the mapping from low-level data to optimized observables though self-supervised contrastive learning. As an example, we construct a data representation for top and QCD jets using a permutation-invariant transformer-encoder network and visualize its symmetry properties. We compare the JetCLR representation with alternative representations using linear classifier tests and find it to work quite well

Evaluating Data Assimilation Algorithms

Data assimilation leads naturally to a Bayesian formulation in which the posterior probability distribution of the system state, given the observations, plays a central conceptual role. The aim of this paper is to use this Bayesian posterior probability distribution as a gold standard against which to evaluate various commonly used data assimilation algorithms. A key aspect of geophysical data assimilation is the high dimensionality and low predictability of the computational model. With this in mind, yet with the goal of allowing an explicit and accurate computation of the posterior distribution, we study the 2D Navier-Stokes equations in a periodic geometry. We compute the posterior probability distribution by state-of-the-art statistical sampling techniques. The commonly used algorithms that we evaluate against this accurate gold standard, as quantified by comparing the relative error in reproducing its moments, are 4DVAR and a variety of sequential filtering approximations based on 3DVAR and on extended and ensemble Kalman filters. The primary conclusions are that: (i) with appropriate parameter choices, approximate filters can perform well in reproducing the mean of the desired probability distribution; (ii) however they typically perform poorly when attempting to reproduce the covariance; (iii) this poor performance is compounded by the need to modify the covariance, in order to induce stability. Thus, whilst filters can be a useful tool in predicting mean behavior, they should be viewed with caution as predictors of uncertainty. These conclusions are intrinsic to the algorithms and will not change if the model complexity is increased, for example by employing a smaller viscosity, or by using a detailed NWP model

Towards Probing Conformational States of Y2 Receptor Using Hyperpolarized 129Xe NMR

G protein-coupled receptors can adopt many different conformational states, each of them exhibiting different restraints towards downstream signaling pathways. One promising strategy to identify and quantify this conformational landscape is to introduce a cysteine at a receptor site sensitive to different states and label this cysteine with a probe for detection. Here, the application of NMR of hyperpolarized 129Xe for the detection of the conformational states of human neuropeptide Y2 receptor is introduced. The xenon trapping cage molecule cryptophane-A attached to a cysteine in extracellular loop 2 of the receptor facilitates chemical exchange saturation transfer experiments without and in the presence of native ligand neuropeptide Y. High-quality spectra indicative of structural states of the receptor–cage conjugate were obtained. Specifically, five signals could be assigned to the conjugate in the apo form. After the addition of NPY, one additional signal and subtle modifications in the persisting signals could be detected. The correlation of the spectroscopic signals and structural states was achieved with molecular dynamics simulations, suggesting frequent contact between the xenon trapping cage and the receptor surface but a preferred interaction with the bound ligand

Contributions to the Evolution of Blood Pressure Regulation

Peer Reviewe

Study of disease-relevant polymorphisms in the TLR4 and TLR9 genes: a novel method applied to the analysis of the Portuguese population

Toll-like receptors (TLRs) are cellular receptors that mediate recognition of microbial challenges and the subsequent inflammatory response. Genetic variations within these inflammation-associated genes may alter host-pathogen defence mechanisms affecting susceptibility towards infectious diseases. Taking into account the significance of these genes, we developed a simple and rapid method based in the bi-directional PCR amplification of specific alleles (Bi-PASA) for genotyping known sequence variants in TLR4 (Asp299Gly and Thr399Ile) and TLR9 (T-1237C) genes. This method allows genotype determination in a single reaction and is amenable to large-scale analysis. We used Bi-PASA to characterize the distribution of these polymorphisms in the Portuguese population. A total of 388 randomly selected blood donors of Portuguese origin (203 females and 185 males) were genotyped and allele frequencies were determined. Among the tested individuals, 11.1% and 10.8% were heterozygous for Asp299Gly and Thr399Ile, respectively. In what concerns the T-1237C variation in TLR9, the variant allele was present in 19.4% of the individuals tested. Besides confirming the usefulness of the Bi-PASA in polymorphism analysis, the data presented provide valuable information on TLR polymorphisms in the Portuguese population that can be used to stratify risk patients with increased susceptibility to infection.Carvalho A. was financially supported by a fellowship from Fundação para a Ciência e Tecnologia, Portugal (contract SFRH/BD/11837/2003). This study was supported by Fundação para a Ciência e Tecnologia, Portugal (POCI/SAU-ESP/61080/2004)

Optimal Convergence Rates for Tikhonov Regularization in Besov Scales

In this paper we deal with linear inverse problems and convergence rates for Tikhonov regularization. We consider regularization in a scale of Banach spaces, namely the scale of Besov spaces. We show that regularization in Banach scales differs from regularization in Hilbert scales in the sense that it is possible that stronger source conditions may lead to weaker convergence rates and vive versa. Moreover, we present optimal source conditions for regularization in Besov scales