Role of cardiovascular magnetic resonance in the guidelines of the European Society of Cardiology

BACKGROUND: Despite common enthusiasm for cardiovascular magnetic resonance (CMR), its application in Europe is quite diverse. Restrictions are attributed to a number of factors, like limited access, deficits in training, and incomplete reimbursement. Aim of this study is to perform a systematic summary of the representation of CMR in the guidelines of the European Society of Cardiology (ESC). METHODS: Twenty-nine ESC guidelines were screened for the terms "magnetic", "MRI", "CMR", "MR" and "imaging". As 3 topics were published twice (endocarditis, pulmonary hypertension, NSTEMI), 26 guidelines were finally included. MRI in the context of non-cardiovascular examinations was not recognized. The main CMR-related conclusions and, if available, the level of evidence and the class of recommendation were extracted. RESULTS: Fourteen of the 26 guidelines (53.8 %) contain specific recommendations regarding the use of CMR. Nine guidelines (34.6 %) mention CMR in the text, and 3 (11.5 %) do not mention CMR. The 14 guidelines with recommendations regarding the use of CMR contain 39 class-I recommendations, 12 class-IIa recommendations, 10 class-IIb recommendations and 2 class-III recommendations. Most of the recommendations have evidence level C (41/63; 65.1 %), followed by level B (16/63; 25.4 %) and level A (6/63; 9.5 %). The four guidelines, which absolutely contained most recommendations for CMR, were stable coronary artery disease (n = 14), aortic diseases (n = 9), HCM (n = 7) and myocardial revascularization (n = 7). CONCLUSIONS: CMR is represented in the majority of the ESC guidelines. They contain many recommendations in favour of the use of CMR in specific scenarios. Issues regarding access, training and reimbursement have to be solved to offer CMR to patients in accordance with the ESC guidelines

PySurf:A Framework for Database Accelerated Direct Dynamics

The greatest restriction to the theoretical study of the dynamics of photoinduced processes is computationally expensive electronic structure calculations. Machine learning algorithms have the potential to reduce the number of these computations significantly. Here, PySurf is introduced as an innovative code framework, which is specifically designed for rapid prototyping and development tasks for data science applications in computational chemistry. It comes with powerful Plugin and Workflow engines, which allows intuitive customization for individual tasks. Data is automatically stored through the database framework, which enables additional interpolation of properties in previously evaluated regions of the conformational space. To illustrate the potential of the framework, a code for nonadiabatic surface hopping simulations based on the Landau-Zener algorithm is presented here. Deriving gradients from the interpolated potential energy surfaces allows for full-dimensional nonadiabatic surface hopping simulations using only adiabatic energies (energy only). Simulations of a pyrazine model and ab initio-based calculations of the SO2 molecule show that energy-only calculations with PySurf are able to correctly predict the nonadiabatic dynamics of these prototype systems. The results reveal the degree of sophistication, which can be achieved by the database accelerated energy-only surface hopping simulations being competitive to commonly used semiclassical approaches

Realizability of the Lorentzian (n,1)-Simplex

In a previous article [JHEP 1111 (2011) 072; arXiv:1108.4965] we have developed a Lorentzian version of the Quantum Regge Calculus in which the significant differences between simplices in Lorentzian signature and Euclidean signature are crucial. In this article we extend a central result used in the previous article, regarding the realizability of Lorentzian triangles, to arbitrary dimension. This technical step will be crucial for developing the Lorentzian model in the case of most physical interest: 3+1 dimensions. We first state (and derive in an appendix) the realizability conditions on the edge-lengths of a Lorentzian n-simplex in total dimension n=d+1, where d is the number of space-like dimensions. We then show that in any dimension there is a certain type of simplex which has all of its time-like edge lengths completely unconstrained by any sort of triangle inequality. This result is the d+1 dimensional analogue of the 1+1 dimensional case of the Lorentzian triangle.Comment: V1: 15 pages, 2 figures. V2: Minor clarifications added to Introduction and Discussion sections. 1 reference updated. This version accepted for publication in JHEP. V3: minor updates and clarifications, this version closely corresponds to the version published in JHE

Influence of the Environment on Shaping the Absorption of Monomeric Infrared Fluorescent Proteins

Infrared fluorescent proteins (iRFPs) are potential candidates for deep-tissue in vivo imaging. Here, we provide molecular-level insights into the role of the protein environment in the structural stability of the chromophore within the protein binding pocket through the flexible hydrogen-bonding network using molecular dynamics simulation. Furthermore, we present systematic excited-state analysis to characterize the nature of the first two excited states and the role of the environment in shaping the nature of the chromophore's excited states within the hybrid quantum mechanics/molecular mechanics framework. Our results reveal that the environment red-shifts the absorption of the chromophore by about 0.32 eV compared to the isolated counterpart, and besides the structural stability, the protein environment does not alter the nature of the excited state of the chromophore significantly. Our study contributes to the fundamental understanding of the excited-state processes of iRFPs in a complex environment and provides a design principle for developing iRFPs with desired spectral properties

In vivo myocardial tissue characterization of all four chambers using high-resolution quantitative MRI

Quantitative native T(1) Mapping of the myocardium without the application of contrast agents can be used to detect fibrosis in the left ventricle. Spatial resolution of standard native T(1) mapping is limited by cardiac motion and hence is not sufficient to resolve small myocardial structures, such as the right ventricle and the atria. Here, we present a novel MR approach which provides cardiac motion information and native T(1) maps from the same data. Motion information is utilized to optimize data selection for T(1) mapping and a model-based iterative reconstruction scheme ensures high-resolution T(1) maps for the entire heart. Feasibility of the approach was demonstrated in three healthy volunteers. In the T(1) maps, the myocardium of all four chambers can be visualized and T(1) values of the left atrium and right chambers were comparable to left ventricular T(1) values

HOAX: A Hyperparameter Optimization Algorithm Explorer for Neural Networks

Computational chemistry has become an important tool to predict and understand molecular properties and reactions. Even though recent years have seen a significant growth in new algorithms and computational methods that speed up quantum chemical calculations, the bottleneck for trajectory-based methods to study photoinduced processes is still the huge number of electronic structure calculations. In this work, we present an innovative solution, in which the amount of electronic structure calculations is drastically reduced, by employing machine learning algorithms and methods borrowed from the realm of artificial intelligence. However, applying these algorithms effectively requires finding optimal hyperparameters, which remains a challenge itself. Here we present an automated user-friendly framework, HOAX, to perform the hyperparameter optimization for neural networks, which bypasses the need for a lengthy manual process. The neural network generated potential energy surfaces (PESs) reduces the computational costs compared to the ab initio-based PESs. We perform a comparative investigation on the performance of different hyperparameter optimiziation algorithms, namely grid search, simulated annealing, genetic algorithm, and bayesian optimizer in finding the optimal hyperparameters necessary for constructing the well-performing neural network in order to fit the PESs of small organic molecules. Our results show that this automated toolkit not only facilitate a straightforward way to perform the hyperparameter optimization but also the resulting neural networks-based generated PESs are in reasonable agreement with the ab initio-based PESs.Comment: 18 page

(Quantum) Space-Time as a Statistical Geometry of Fuzzy Lumps and the Connection with Random Metric Spaces

We develop a kind of pregeometry consisting of a web of overlapping fuzzy lumps which interact with each other. The individual lumps are understood as certain closely entangled subgraphs (cliques) in a dynamically evolving network which, in a certain approximation, can be visualized as a time-dependent random graph. This strand of ideas is merged with another one, deriving from ideas, developed some time ago by Menger et al, that is, the concept of probabilistic- or random metric spaces, representing a natural extension of the metrical continuum into a more microscopic regime. It is our general goal to find a better adapted geometric environment for the description of microphysics. In this sense one may it also view as a dynamical randomisation of the causal-set framework developed by e.g. Sorkin et al. In doing this we incorporate, as a perhaps new aspect, various concepts from fuzzy set theory.Comment: 25 pages, Latex, no figures, some references added, some minor changes added relating to previous wor

Speaking up for the lost voices: representation and inclusion of people with communication impairment in brain tumour research

Brain tumours and their associated treatments can lead to progressive impairments of communication, adversely affecting quality-of-life. This commentary explores our concerns that people with speech, language, and communication needs face barriers to representation and inclusion in brain tumour research; we then offer possible solutions to support their participation. Our main concerns are that there is currently poor recognition of the nature of communication difficulties following brain tumours, limited focus on the psychosocial impact, and lack of transparency on why people with speech, language, and communication needs were excluded from research or how they were supported to take part. We propose solutions focusing on working towards more accurate reporting of symptoms and the impact of impairment, using innovative qualitative methods to collect data on the lived experiences of speech, language, and communication needs, and empowering speech and language therapists to become part of research teams as experts and advocates for this population. These solutions would support the accurate representation and inclusion of people with communication needs after brain tumour in research, allowing healthcare professionals to learn more about their priorities and needs

Singlet fission in tetracene:An excited state analysis

Singlet fission is a potential mechanism to enhance the performance of current solar cells. However, the actual mechanism is still a matter of debate, with charge transfer states believed to play an essential role. The probability of the overall process can be related to the electronic coupling between the electronic states. Here, we explore the excited states of three pairs of tetracene with different relative orientation in the crystal structure showing different electronic couplings and identify the role of charge transfer states. First, a suitable theoretical method for the study of the tetracene pairs is determined by comparing time-dependent density functional theory with wave function-based methods in terms of excitation energies, so-called exciton descriptors, and graphical tools such as electron-hole correlation plots and natural transition orbitals. The results show the presence of low-lying charge transfer states in those tetracene pairs with non-zero electronic coupling, suggesting a superexchange-mediated mechanism, and high-lying charge resonance states for the pair with zero electronic coupling. Finally, the lower electron-hole correlation coefficients for pairs with non-zero coupling speak in favour of the superexchange-mediated mechanism, as a weaker Coulombic attraction due to the mixing with charge transfer states further facilitates the formation of the (Formula presented.) state from the photoexcited molecule