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(2020)
Rezension zu: Akremi, Leila, Nina Baur, Hubert Knoblauch und Boris Traue (Hrsg.): Handbuch Interpretativ forschen. Weinheim, Basel: Beltz Juventa 2018. 961 Seiten. ISBN: 978-3-7799-3126-3. Preis: C 49,95.
Human RNF213, which encodes the protein mysterin, is a known susceptibility gene for moyamoya disease (MMD), a cerebrovascular condition with occlusive lesions and compensatory angiogenesis. Mysterin mutations, together with exposure to environmental trigger factors, lead to an elevated stroke risk since childhood. Mysterin is induced during cell stress, to function as cytosolic AAA+ ATPase and ubiquitylation enzyme. Little knowledge exists, in which context mysterin is needed. Here, we found that genetic ablation of several mitochondrial matrix factors, such as the peptidase ClpP, the transcription factor Tfam, as well as the peptidase and AAA+ ATPase Lonp1, potently induces Rnf213 transcript expression in various organs, in parallel with other components of the innate immune system. Mostly in mouse fibroblasts and human endothelial cells, the Rnf213 levels showed prominent upregulation upon Poly(I:C)-triggered TLR3-mediated responses to dsRNA toxicity, as well as upon interferon gamma treatment. Only partial suppression of Rnf213 induction was achieved by C16 as an antagonist of PKR (dsRNA-dependent protein kinase). Since dysfunctional mitochondria were recently reported to release immune-stimulatory dsRNA into the cytosol, our results suggest that mysterin becomes relevant when mitochondrial dysfunction or infections have triggered RNA-dependent inflammation. Thus, MMD has similarities with vasculopathies that involve altered nucleotide processing, such as Aicardi-Goutières syndrome or systemic lupus erythematosus. Furthermore, in MMD, the low penetrance of RNF213 mutations might be modified by dysfunctions in mitochondria or the TLR3 pathway.
Purpose: Neonatal surgery for abdominal wall defects is not performed in a centralized manner in Germany. The aim of this study was to investigate whether treatment for abdominal wall defects in Germany is equally effective compared to international results despite the decentralized care.
Methods: All newborn patients who were clients of the major statutory health insurance company in Germany between 2009 and 2013 and who had a diagnosis of gastroschisis or omphalocele were included. Mortality during the first year of life was analysed.
Results: The 316 patients with gastroschisis were classified as simple (82%) or complex (18%) cases. The main associated anomalies in the 197 patients with omphalocele were trisomy 18/21 (8%), cardiac anomalies (32%) and anomalies of the urinary tract (10%). Overall mortality was 4% for gastroschisis and 16% for omphalocele. Significant factors for non-survival were birth weight below 1500 g for both groups, complex gastroschisis, volvulus and anomalies of the blood supply to the intestine in gastroschisis, and female gender, trisomy 18/21 and lung hypoplasia in omphalocele.
Conclusions: Despite the fact that paediatric surgical care is organized in a decentralized manner in Germany, the mortality rates for gastroschisis and omphalocele are equal to those reported in international data.
A convex body is unconditional if it is symmetric with respect to reflections in all coordinate hyperplanes. We investigate unconditional lattice polytopes with respect to geometric, combinatorial, and algebraic properties. In particular, we characterize unconditional reflexive polytopes in terms of perfect graphs. As a prime example, we study the signed Birkhoff polytope. Moreover, we derive constructions for Gale-dual pairs of polytopes and we explicitly describe Gröbner bases for unconditional reflexive polytopes coming from partially ordered sets.
Purpose of Review: To provide an overview of current surgical peri-implantitis treatment options.
Recent Findings: Surgical procedures for peri-implantitis treatment include two main approaches: non-augmentative and augmentative therapy. Open flap debridement (OFD) and resective treatment are non-augmentative techniques that are indicated in the presence of horizontal bone loss in aesthetically nondemanding areas. Implantoplasty performed adjunctively at supracrestally and buccally exposed rough implant surfaces has been shown to efficiently attenuate soft tissue inflammation compared to control sites. However, this was followed by more pronounced soft tissue recession. Adjunctive augmentative measures are recommended at peri-implantitis sites exhibiting intrabony defects with a minimum depth of 3 mm and in the presence of keratinized mucosa. In more advanced cases with combined defect configurations, a combination of augmentative therapy and implantoplasty at exposed rough implant surfaces beyond the bony envelope is feasible.
Summary: For the time being, no particular surgical protocol or material can be considered as superior in terms of long-term peri-implant tissue stability.
Purpose of Review: Attention deficit hyperactivity disorder (ADHD) shows high heritability in formal genetic studies. In our review article, we provide an overview on common and rare genetic risk variants for ADHD and their link to clinical practice.
Recent findings: The formal heritability of ADHD is about 80% and therefore higher than most other psychiatric diseases. However, recent studies estimate the proportion of heritability based on singlenucleotide variants (SNPs) at 22%. It is a matter of debate which genetic mechanisms explain this huge difference. While frequent variants in first mega-analyses of genome-wideassociation study data containing several thousand patients give the first genome-wide results, explaining only little variance, the methodologically more difficult analyses of rare variants are still in their infancy. Some rare genetic syndromes show higher prevalence for ADHD indicating a potential role for a small number of patients. In contrast, polygenic risk scores (PRS) could potentially be applied to every patient. We give an overview how PRS explain different behavioral phenotypes in ADHD and how they could be used for diagnosis and therapy prediction.
Summary: Knowledge about a patient’s genetic makeup is not yet mandatory for ADHD therapy or diagnosis. PRS however have been introduced successfully in other areas of clinical medicine, and their application in psychiatry will begin within the next years. In order to ensure competent advice for patients, knowledge of the current state of research is useful forpsychiatrists.
Voting advice applications (VAAs) are online tools providing voting advice to their users. This voting advice is based on the match between the answers of the user and the answers of several political parties to a common questionnaire on political attitudes. To visualize this match, VAAs use a wide array of visualisations, most popular of which are the two-dimensional political maps. These maps show the position of both the political parties and the user in the political landscape, allowing the user to understand both their own position and their relation to the political parties. To construct these maps, VAAs require scales that represent the main underlying dimensions of the political space. This makes the correct construction of these scales important if the VAA aims to provide accurate and helpful voting advice. This paper presents three criteria that assess if a VAA achieves this aim. To illustrate their usefulness, these three criteria—unidimensionality, reliability and quality—are used to assess the scales in the cross-national EUVox VAA, a VAA designed for the European Parliament elections of 2014. Using techniques from Mokken scaling analysis and categorical principal component analysis to capture the metrics, I find that most scales show low unidimensionality and reliability. Moreover, even while designers can—and sometimes do—use certain techniques to improve their scales, these improvements are rarely enough to overcome all of the problems regarding unidimensionality, reliability and quality. This leaves certain problems for the designers of VAAs and designers of similar type online surveys.
We explore the phase structure of the 1+1 dimensional Gross-Neveu model at finite number of fermion flavors using lattice field theory. Besides a chirally symmetric phase and a homogeneously broken phase we find evidence for the existence of an inhomogeneous phase, where the condensate is a spatially oscillating function. Our numerical results include a crude μ-T phase diagram.
We use recent results by Bainbridge–Chen–Gendron–Grushevsky–Möller on compactifications of strata of abelian differentials to give a comprehensive solution to the realizability problem for effective tropical canonical divisors in equicharacteristic zero. Given a pair (Γ,D) consisting of a stable tropical curve Γ and a divisor D in the canonical linear system on Γ, we give a purely combinatorial condition to decide whether there is a smooth curve X over a non-Archimedean field whose stable reduction has Γ as its dual tropical curve together with an effective canonical divisor KX that specializes to D.
Inhomogeneous phases in the Gross-Neveu model in 1 + 1 dimensions at finite number of flavors
(2020)
We explore the thermodynamics of the 1+1-dimensional Gross-Neveu (GN) model at a finite number of fermion flavors Nf, finite temperature, and finite chemical potential using lattice field theory. In the limit Nf→∞ the model has been solved analytically in the continuum. In this limit three phases exist: a massive phase, in which a homogeneous chiral condensate breaks chiral symmetry spontaneously; a massless symmetric phase with vanishing condensate; and most interestingly an inhomogeneous phase with a condensate, which oscillates in the spatial direction. In the present work we use chiral lattice fermions (naive fermions and SLAC fermions) to simulate the GN model with 2, 8, and 16 flavors. The results obtained with both discretizations are in agreement. Similarly as for Nf→∞ we find three distinct regimes in the phase diagram, characterized by a qualitatively different behavior of the two-point function of the condensate field. For Nf=8 we map out the phase diagram in detail and obtain an inhomogeneous region smaller as in the limit Nf→∞, where quantum fluctuations are suppressed. We also comment on the existence or absence of Goldstone bosons related to the breaking of translation invariance in 1+1 dimensions.
Erratum for: Cyclic AMP induces transactivation of the receptors for epidermal growth factor and nerve growth factor, thereby modulating activation of MAP kinase, Akt, and neurite outgrowth in PC12 cells.Journal of biological chemistry, 2002 Nov 15;277(46):43623-30. doi: 10.1074/jbc.M203926200. Epub 2002 Sep 5.
Type-II multiferroic materials, in which ferroelectric polarization is induced by inversion non-symmetric magnetic order, promise new and highly efficient multifunctional applications based on mutual control of magnetic and electric properties. However, to date this phenomenon is limited to low temperatures. Here we report giant pressure-dependence of the multiferroic critical temperature in CuBr2: at 4.5 GPa it is enhanced from 73.5 to 162 K, to our knowledge the highest TC ever reported for non-oxide type-II multiferroics. This growth shows no sign of saturating and the dielectric loss remains small under these high pressures. We establish the structure under pressure and demonstrate a 60\% increase in the two-magnon Raman energy scale up to 3.6 GPa. First-principles structural and magnetic energy calculations provide a quantitative explanation in terms of dramatically pressure-enhanced interactions between CuBr2 chains. These large, pressure-tuned magnetic interactions motivate structural control in cuprous halides as a route to applied high-temperature multiferroicity.
Recurrent cortical network dynamics plays a crucial role for sequential information processing in the brain. While the theoretical framework of reservoir computing provides a conceptual basis for the understanding of recurrent neural computation, it often requires manual adjustments of global network parameters, in particular of the spectral radius of the recurrent synaptic weight matrix. Being a mathematical and relatively complex quantity, the spectral radius is not readily accessible to biological neural networks, which generally adhere to the principle that information about the network state should either be encoded in local intrinsic dynamical quantities (e.g. membrane potentials), or transmitted via synaptic connectivity. We present two synaptic scaling rules for echo state networks that solely rely on locally accessible variables. Both rules work online, in the presence of a continuous stream of input signals. The first rule, termed flow control, is based on a local comparison between the mean squared recurrent membrane potential and the mean squared activity of the neuron itself. It is derived from a global scaling condition on the dynamic flow of neural activities and requires the separability of external and recurrent input currents. We gained further insight into the adaptation dynamics of flow control by using a mean field approximation on the variances of neural activities that allowed us to describe the interplay between network activity and adaptation as a two-dimensional dynamical system. The second rule that we considered, variance control, directly regulates the variance of neural activities by locally scaling the recurrent synaptic weights. The target set point of this homeostatic mechanism is dynamically determined as a function of the variance of the locally measured external input. This functional relation was derived from the same mean-field approach that was used to describe the approximate dynamics of flow control.
The effectiveness of the presented mechanisms was tested numerically using different external input protocols. The network performance after adaptation was evaluated by training the network to perform a time delayed XOR operation on binary sequences. As our main result, we found that flow control can reliably regulate the spectral radius under different input statistics, but precise tuning is negatively affected by interneural correlations. Furthermore, flow control showed a consistent task performance over a wide range of input strengths/variances. Variance control, on the other side, did not yield the desired spectral radii with the same precision. Moreover, task performance was less consistent across different input strengths.
Given the better performance and simpler mathematical form of flow control, we concluded that a local control of the spectral radius via an implicit adaptation scheme is a realistic alternative to approaches using classical “set point” homeostatic feedback controls of neural firing.
Author summary How can a neural network control its recurrent synaptic strengths such that network dynamics are optimal for sequential information processing? An important quantity in this respect, the spectral radius of the recurrent synaptic weight matrix, is a non-local quantity. Therefore, a direct calculation of the spectral radius is not feasible for biological networks. However, we show that there exist a local and biologically plausible adaptation mechanism, flow control, which allows to control the recurrent weight spectral radius while the network is operating under the influence of external inputs. Flow control is based on a theorem of random matrix theory, which is applicable if inter-synaptic correlations are weak. We apply the new adaption rule to echo-state networks having the task to perform a time-delayed XOR operation on random binary input sequences. We find that flow-controlled networks can adapt to a wide range of input strengths while retaining essentially constant task performance.
Recurrent cortical network dynamics plays a crucial role for sequential information processing in the brain. While the theoretical framework of reservoir computing provides a conceptual basis for the understanding of recurrent neural computation, it often requires manual adjustments of global network parameters, in particular of the spectral radius of the recurrent synaptic weight matrix. Being a mathematical and relatively complex quantity, the spectral radius is not readily accessible to biological neural networks, which generally adhere to the principle that information about the network state should either be encoded in local intrinsic dynamical quantities (e.g. membrane potentials), or transmitted via synaptic connectivity. We present two synaptic scaling rules for echo state networks that solely rely on locally accessible variables. Both rules work online, in the presence of a continuous stream of input signals. The first rule, termed flow control, is based on a local comparison between the mean squared recurrent membrane potential and the mean squared activity of the neuron itself. It is derived from a global scaling condition on the dynamic flow of neural activities and requires the separability of external and recurrent input currents. We gained further insight into the adaptation dynamics of flow control by using a mean field approximation on the variances of neural activities that allowed us to describe the interplay between network activity and adaptation as a two-dimensional dynamical system. The second rule that we considered, variance control, directly regulates the variance of neural activities by locally scaling the recurrent synaptic weights. The target set point of this homeostatic mechanism is dynamically determined as a function of the variance of the locally measured external input. This functional relation was derived from the same mean-field approach that was used to describe the approximate dynamics of flow control.
The effectiveness of the presented mechanisms was tested numerically using different external input protocols. The network performance after adaptation was evaluated by training the network to perform a time delayed XOR operation on binary sequences. As our main result, we found that flow control can reliably regulate the spectral radius under different input statistics, but precise tuning is negatively affected by interneural correlations. Furthermore, flow control showed a consistent task performance over a wide range of input strengths/variances. Variance control, on the other side, did not yield the desired spectral radii with the same precision. Moreover, task performance was less consistent across different input strengths.
Given the better performance and simpler mathematical form of flow control, we concluded that a local control of the spectral radius via an implicit adaptation scheme is a realistic alternative to approaches using classical “set point” homeostatic feedback controls of neural firing.
Author summary How can a neural network control its recurrent synaptic strengths such that network dynamics are optimal for sequential information processing? An important quantity in this respect, the spectral radius of the recurrent synaptic weight matrix, is a non-local quantity. Therefore, a direct calculation of the spectral radius is not feasible for biological networks. However, we show that there exist a local and biologically plausible adaptation mechanism, flow control, which allows to control the recurrent weight spectral radius while the network is operating under the influence of external inputs. Flow control is based on a theorem of random matrix theory, which is applicable if inter-synaptic correlations are weak. We apply the new adaption rule to echo-state networks having the task to perform a time-delayed XOR operation on random binary input sequences. We find that flow-controlled networks can adapt to a wide range of input strengths while retaining essentially constant task performance.
Evolution of nematic fluctuations in CaK(Fe1−xNix)4As4 with spin-vortex crystal magnetic order
(2020)
The CaK(Fe1−xNix)4As4 superconductors resemble the archetypal 122-type iron-based materials but have a crystal structure with distinctly lower symmetry. This family hosts one of the few examples of the so-called spin-vortex crystal magnetic order, a non-collinear magnetic configuration that preserves tetragonal symmetry, in contrast to the orthorhombic collinear stripe-type magnetic configuration common to the 122-type systems. Thus, nematic order is completely absent from its phase diagram. To investigate the evolution of nematic fluctuations in such a case, we present elastoresistance and elastic modulus measurements in CaK(Fe1−xNix)4As4 (x=0−0.05) combined with phenomenological modeling and density functional theory. We find clear experimental signatures of considerable nematic fluctuations, including softening of the Young's modulus Y[110] and a Curie-Weiss type divergence of the B2g elastoresistance coefficient in CaK(Fe0.951Ni0.049)4As4. Overall, nematic fluctuations within this series bear strong similarities to the hole-doped Ba1−xKxFe2As2 series, including a substitution-induced sign change. Our theoretical analysis addresses the effect of the specific crystal symmetry of the 1144-type structure in determining its magnetic ground state and on the nematic fluctuations.
Deconfinement of Mott localized electrons into topological and spin–orbit-coupled Dirac fermions
(2020)
The interplay of electronic correlations, spin–orbit coupling and topology holds promise for the realization of exotic states of quantum matter. Models of strongly interacting electrons on honeycomb lattices have revealed rich phase diagrams featuring unconventional quantum states including chiral superconductivity and correlated quantum spin Hall insulators intertwining with complex magnetic order. Material realizations of these electronic states are, however, scarce or inexistent. In this work, we propose and show that stacking 1T-TaSe2 into bilayers can deconfine electrons from a deep Mott insulating state in the monolayer to a system of correlated Dirac fermions subject to sizable spin–orbit coupling in the bilayer. 1T-TaSe2 develops a Star-of-David charge density wave pattern in each layer. When the Star-of-David centers belonging to two adyacent layers are stacked in a honeycomb pattern, the system realizes a generalized Kane–Mele–Hubbard model in a regime where Dirac semimetallic states are subject to significant Mott–Hubbard interactions and spin–orbit coupling. At charge neutrality, the system is close to a quantum phase transition between a quantum spin Hall and an antiferromagnetic insulator. We identify a perpendicular electric field and the twisting angle as two knobs to control topology and spin–orbit coupling in the system. Their combination can drive it across hitherto unexplored grounds of correlated electron physics, including a quantum tricritical point and an exotic first-order topological phase transition.
Cancer‐associated venous thromboembolism (VTE) is a frequent, potentially life‐threatening event that complicates cancer management. Anticoagulants are the cornerstone of therapy for the treatment and prevention of cancer‐associated thrombosis (CAT); factor Xa–inhibiting direct oral anticoagulants (DOACs; apixaban, edoxaban, and rivaroxaban), which have long been recommended for the treatment of VTE in patients without cancer, have been investigated in this setting. The first randomized comparisons of DOACs against low‐molecular‐weight heparin for the treatment of CAT indicated that DOACs are efficacious in this setting, with findings reflected in recent updates to published guidance on CAT treatment. However, the higher risk of bleeding events (particularly in the gastrointestinal tract) with DOACs highlights the need for appropriate patient selection. Further insights will be gained from additional studies that are ongoing or awaiting publication. The efficacy and safety of DOAC thromboprophylaxis in ambulatory patients with cancer at a high risk of VTE have also been assessed in placebo‐controlled randomized controlled trials of apixaban and rivaroxaban. Both studies showed efficacy benefits with DOACs, but both studies also showed a nonsignificant increase in major bleeding events while on treatment. This review summarizes the evidence base for rivaroxaban use in CAT, the patient profile potentially most suited to DOAC use, and ongoing controversies under investigation. We also describe ongoing studies from the CALLISTO (Cancer Associated thrombosis—expLoring soLutions for patients through Treatment and Prevention with RivarOxaban) program, which comprises several randomized clinical trials and real‐world evidence studies, including investigator‐initiated research.
The study of (anti-)deuteron production in pp collisions has proven to be a powerful tool to investigate the formation mechanism of loosely bound states in high energy hadronic collisions. In this paper the production of (anti-)deuterons is studied as a function of the charged particle multiplicity in inelastic pp collisions at s√=13 TeV using the ALICE experiment. Thanks to the large accumulated integrated luminosity, it has been possible to measure (anti-)deuteron production in pp collisions up to the same charged particle multiplicity (dNch/dη∼26) as measured in p-Pb collisions at similar centre-of-mass energies. Within the uncertainties, the deuteron yield in pp collisions resembles the one in p-Pb interactions, suggesting a common formation mechanism behind the production of light nuclei in hadronic interactions. In this context the measurements are compared with the expectations of coalescence and Statistical Hadronisation Models (SHM).