Deep nested level sets: Fully automated segmentation of cardiac MR images in patients with pulmonary hypertension

In this paper we introduce a novel and accurate optimisation method for segmentation of cardiac MR (CMR) images in patients with pulmonary hypertension (PH). The proposed method explicitly takes into account the image features learned from a deep neural network. To this end, we estimate simultaneous probability maps over region and edge locations in CMR images using a fully convolutional network. Due to the distinct morphology of the heart in patients with PH, these probability maps can then be incorporated in a single nested level set optimisation framework to achieve multi-region segmentation with high efficiency. The proposed method uses an automatic way for level set initialisation and thus the whole optimisation is fully automated. We demonstrate that the proposed deep nested level set (DNLS) method outperforms existing state-of-the-art methods for CMR segmentation in PH patients

Universal Quantum Computation with the Exchange Interaction

Experimental implementations of quantum computer architectures are now being investigated in many different physical settings. The full set of requirements that must be met to make quantum computing a reality in the laboratory [1] is daunting, involving capabilities well beyond the present state of the art. In this report we develop a significant simplification of these requirements that can be applied in many recent solid-state approaches, using quantum dots [2], and using donor-atom nuclear spins [3] or electron spins [4]. In these approaches, the basic two-qubit quantum gate is generated by a tunable Heisenberg interaction (the Hamiltonian is $H_{ij}=J(t){\vec S}_i\cdot{\vec S}_j$ between spins $i$ and $j$), while the one-qubit gates require the control of a local Zeeman field. Compared to the Heisenberg operation, the one-qubit operations are significantly slower and require substantially greater materials and device complexity, which may also contribute to increasing the decoherence rate. Here we introduce an explicit scheme in which the Heisenberg interaction alone suffices to exactly implement any quantum computer circuit, at a price of a factor of three in additional qubits and about a factor of ten in additional two-qubit operations. Even at this cost, the ability to eliminate the complexity of one-qubit operations should accelerate progress towards these solid-state implementations of quantum computation.Comment: revtex, 2 figures, this version appeared in Natur

Microtubules gate tau condensation to spatially regulate microtubule functions.

Tau is an abundant microtubule-associated protein in neurons. Tau aggregation into insoluble fibrils is a hallmark of Alzheimer's disease and other types of dementia1, yet the physiological state of tau molecules within cells remains unclear. Using single-molecule imaging, we directly observe that the microtubule lattice regulates reversible tau self-association, leading to localized, dynamic condensation of tau molecules on the microtubule surface. Tau condensates form selectively permissible barriers, spatially regulating the activity of microtubule-severing enzymes and the movement of molecular motors through their boundaries. We propose that reversible self-association of tau molecules, gated by the microtubule lattice, is an important mechanism of the biological functions of tau, and that oligomerization of tau is a common property shared between the physiological and disease-associated forms of the molecule

SNPs in the FCER1A Gene Region Show No Association with Allergic Rhinitis in a Han Chinese Population

Background: Immunoglobulin E (IgE) is a central player in the allergic response, and raised total IgE levels are considered as an indicator of atopy or potential development of atopy. A recent genome-wide scan in a German population-based cohort of adults identified the gene encoding the alpha chain of the high affinity receptor for IgE (FCER1A) as a susceptibility locus influencing total serum IgE levels. The aim of this study was to investigate whether the polymorphisms in the FCER1A gene are associated with allergic rhinitis (AR) in a Han Chinese population. Methodology/Principal Findings: A population of 378 patients with AR and 288 healthy controls was studied. Precise phenotyping of patients was accomplished by means of a questionnaire and clinical examination. Blood was drawn for DNA extraction and total serum immunoglobulin E (IgE) measurement. A total of 16 single nucleotide polymorphisms (SNPs) in FCER1A were selected and individually genotyped. None of the SNPs in the FCER1A showed an association with AR. Similarly, the lack of association was also evident in subgroup analysis for the presence of different allergen sensitivities. None of the selected SNPs in FCER1A was associated with total IgE level. Conclusions: Although FCER1A presents itself as a good candidate for contributing to total serum IgE, this study failed t

Nodal dynamics, not degree distributions, determine the structural controllability of complex networks

Structural controllability has been proposed as an analytical framework for making predictions regarding the control of complex networks across myriad disciplines in the physical and life sciences (Liu et al., Nature:473(7346):167-173, 2011). Although the integration of control theory and network analysis is important, we argue that the application of the structural controllability framework to most if not all real-world networks leads to the conclusion that a single control input, applied to the power dominating set (PDS), is all that is needed for structural controllability. This result is consistent with the well-known fact that controllability and its dual observability are generic properties of systems. We argue that more important than issues of structural controllability are the questions of whether a system is almost uncontrollable, whether it is almost unobservable, and whether it possesses almost pole-zero cancellations.Comment: 1 Figures, 6 page

Explainable anatomical shape analysis through deep hierarchical generative models.

Quantification of anatomical shape changes currently relies on scalar global indexes which are largely insensitive to regional or asymmetric modifications. Accurate assessment of pathology-driven anatomical remodeling is a crucial step for the diagnosis and treatment of many conditions. Deep learning approaches have recently achieved wide success in the analysis of medical images, but they lack interpretability in the feature extraction and decision processes. In this work, we propose a new interpretable deep learning model for shape analysis. In particular, we exploit deep generative networks to model a population of anatomical segmentations through a hierarchy of conditional latent variables. At the highest level of this hierarchy, a two-dimensional latent space is simultaneously optimised to discriminate distinct clinical conditions, enabling the direct visualisation of the classification space. Moreover, the anatomical variability encoded by this discriminative latent space can be visualised in the segmentation space thanks to the generative properties of the model, making the classification task transparent. This approach yielded high accuracy in the categorisation of healthy and remodelled left ventricles when tested on unseen segmentations from our own multi-centre dataset as well as in an external validation set, and on hippocampi from healthy controls and patients with Alzheimer's disease when tested on ADNI data. More importantly, it enabled the visualisation in three-dimensions of both global and regional anatomical features which better discriminate between the conditions under exam. The proposed approach scales effectively to large populations, facilitating highthroughput analysis of normal anatomy and pathology in largescale studies of volumetric imaging

Construction loads using a shoring-clearing-striking process

[EN] This paper presents the results of tests carried out during the construction of a block of flats with reinforced concrete slab floors in Madrid, Spain, using the shoring, clearing and striking (SCS) process. Loads on shores were recorded during the different construction stages of Floor Slabs 1 to 6. The experimental results were used to analyse load transmission between slabs and shores during the construction of the building. The results of the analysis showed that slab-shore load transmission differed according to the position of the span analysed and also that variations in the construction process had a significant effect on the expected loads. The paper includes the evolving calculation developed by a non-linear numerical model to simulate the building s behaviour during the different construction phases and variations in the concrete properties with time. The experimental and numerical FEM results were compared with those obtained applying simplified methods that consider the real stiffness of the shoring.Gasch, I.; Alvarado Vargas, YA.; Calderón García, PA.; Ivorra Chorro, S. (2014). Construction loads using a shoring-clearing-striking process. Proceedings of the ICE - Structures and Buildings. 167(4):217-229. doi:10.1680/stbu.12.00006S217229167

New chemolysis for urological calcium phosphate calculi – a study in vitro

BACKGROUND: Advances in techniques have left very few indications for open surgical extraction of urinary stones currently. These advances notwithstanding, the search continues for medical approaches to urinary stone management. In this study, we perform an in vitro study analyzing the efficiency and prospect of two new complex solutions in urological calcium phosphate calculi dissolution. METHODS: Eighteen stones composed mainly of calcium phosphates were taken from patients who underwent kidney stone surgery. These stones were large enough (weight range 0.514–0.928 g) to be fragmented and matched equally into six groups. Chemolysis of phosphate stones was done with six different solvents and was repeated 3 times with 6 stones for each solution. At 24, 48 and 72 h, reduction in weight, percentage weight change, and dissolution rate; the dissolution rates at pH 5.0, 7.0 and 8.5 for each solution, using different cations (Na(+), K(+ )or Ca(2+)), according to different dilutions (1:1, 1:2, 1:3, 1:4) of S1 and S2 were simultaneously determined. RESULTS: Calcium phosphate calculi were poorly dissolved by Phys and Art, and they had a low dissolution rate in pH 8.5 EDTA. The most effective solutions were S1, S2 and R, with 72 h mean dissolution rates: 5.75 ± 0.44 mg/hr (S1), 5.2 ± 0.63 mg/hr (S2), 4.55 ± 0.46 mg/hr (R) ([Image: see text] ± s, p < 0.01 R, S1 and S2 vs Phys, Art and EDTA; p < 0.05, S1 vs R, LSD-test). The mean percentage weight loss at 72 h was: 52.1 ± 15.75 % (S1), 44.4 ± 7.37 % (S2) and 40.5 ± 3.67 % (R) ([Image: see text] ± s, p < 0.01 R, S1 and S2 vs Phys, Art and EDTA, LSD-test). Diluted twice, S1 and S2 had even better effectiveness than their initial solution. The additive of Na(+), K(+ )or Ca(2+ )greatly reduced the dissolution rates of S1, S2. CONCLUSION: Our data indicate that test solutions S1 and S2 are effective solvents in the chemolysis of calcium phosphate stones. At twice dilutions, these solutions are even more useful in the treatment of stone disease

Two-orbital SU(N) magnetism with ultracold alkaline-earth atoms

Fermionic alkaline-earth atoms have unique properties that make them attractive candidates for the realization of novel atomic clocks and degenerate quantum gases. At the same time, they are attracting considerable theoretical attention in the context of quantum information processing. Here we demonstrate that when such atoms are loaded in optical lattices, they can be used as quantum simulators of unique many-body phenomena. In particular, we show that the decoupling of the nuclear spin from the electronic angular momentum can be used to implement many-body systems with an unprecedented degree of symmetry, characterized by the SU(N) group with N as large as 10. Moreover, the interplay of the nuclear spin with the electronic degree of freedom provided by a stable optically excited state allows for the study of spin-orbital physics. Such systems may provide valuable insights into strongly correlated physics of transition metal oxides, heavy fermion materials, and spin liquid phases.Comment: 15 pages, 10 figures. V2: extended experimental accessibility and Kondo sections in the main text (including new Fig. 5b) and in the Methods; reorganized other parts; added reference