Low-Lying Dirac Eigenmodes, Topological Charge Fluctuations and the Instanton Liquid Model

The local structure of low-lying eigenmodes of the overlap Dirac operator is studied. It is found that these modes cannot be described as linear combinations of 't Hooft "would-be" zeromodes associated with instanton excitations that underly the Instanton Liquid Model. This implies that the instanton liquid scenario for spontaneous chiral symmetry breaking in QCD is not accurate. More generally, our data suggests that the vacuum fluctuations of topological charge are not effectively dominated by localized lumps of unit charge with which the topological "would-be" zeromodes could be associated.Comment: Presented by I. Horvath at the NATO Advanced Research Workshop "Confinement, Topology, and other Non-Perturbative Aspects of QCD", January 21-27, 2002, Stara Lesna, Slovakia. 12 pages, 6 figures, uses crckapb.st

Dirac Equation with Spin Symmetry for the Modified P\"oschl-Teller Potential in DD-dimensions

We present solutions of the Dirac equation with spin symmetry for vector and scalar modified P\"oschl-Teller potential within framework of an approximation of the centrifugal term. The relativistic energy spectrum is obtained using the Nikiforov-Uvarov method and the two-component spinor wavefunctions are obtain are in terms of the Jacobi polynomials. It is found that there exist only positive-energy states for bound states under spin symmetry, and the energy levels increase with the dimension and the potential range parameter $\alpha$.Comment: 9 pages and 1tabl

Recessive Inheritance of Congenital Hydrocephalus With Other Structural Brain Abnormalities Caused by Compound Heterozygous Mutations in ATP1A3

Background: ATP1A3 encodes the α3 subunit of the Na+/K+ ATPase, a fundamental ion-transporting enzyme. Primarily expressed in neurons, ATP1A3 is mutated in several autosomal dominant neurological diseases. To our knowledge, damaging recessive genotypes in ATP1A3 have never been associated with any human disease. Atp1a3 deficiency in zebrafish results in hydrocephalus; however, no known association exists between ATP1A3 and human congenital hydrocephalus (CH). / Methods: We utilized whole-exome sequencing (WES), bioinformatics, and computational modeling to identify and characterize novel ATP1A3 mutations in a patient with CH. We performed immunohistochemical studies using mouse embryonic brain tissues to characterize Atp1a3 expression during brain development. / Results: We identified two germline mutations in ATP1A3 (p. Arg19Cys and p.Arg463Cys), each of which was inherited from one of the patient’s unaffected parents, in a single patient with severe obstructive CH due to aqueductal stenosis, along with open schizencephaly, type 1 Chiari malformation, and dysgenesis of the corpus callosum. Both mutations are predicted to be highly deleterious and impair protein stability. Immunohistochemical studies demonstrate robust Atp1a3 expression in neural stem cells (NSCs), differentiated neurons, and choroid plexus of the mouse embryonic brain. / Conclusion: These data provide the first evidence of a recessive human phenotype associated with mutations in ATP1A3, and implicate impaired Na+/K+ ATPase function in the pathogenesis of CH

A discriminative method for protein remote homology detection and fold recognition combining Top-n-grams and latent semantic analysis

<p>Abstract</p> <p>Background</p> <p>Protein remote homology detection and fold recognition are central problems in bioinformatics. Currently, discriminative methods based on support vector machine (SVM) are the most effective and accurate methods for solving these problems. A key step to improve the performance of the SVM-based methods is to find a suitable representation of protein sequences.</p> <p>Results</p> <p>In this paper, a novel building block of proteins called Top-<it>n</it>-grams is presented, which contains the evolutionary information extracted from the protein sequence frequency profiles. The protein sequence frequency profiles are calculated from the multiple sequence alignments outputted by PSI-BLAST and converted into Top-<it>n</it>-grams. The protein sequences are transformed into fixed-dimension feature vectors by the occurrence times of each Top-<it>n</it>-gram. The training vectors are evaluated by SVM to train classifiers which are then used to classify the test protein sequences. We demonstrate that the prediction performance of remote homology detection and fold recognition can be improved by combining Top-<it>n</it>-grams and latent semantic analysis (LSA), which is an efficient feature extraction technique from natural language processing. When tested on superfamily and fold benchmarks, the method combining Top-<it>n</it>-grams and LSA gives significantly better results compared to related methods.</p> <p>Conclusion</p> <p>The method based on Top-<it>n</it>-grams significantly outperforms the methods based on many other building blocks including N-grams, patterns, motifs and binary profiles. Therefore, Top-<it>n</it>-gram is a good building block of the protein sequences and can be widely used in many tasks of the computational biology, such as the sequence alignment, the prediction of domain boundary, the designation of knowledge-based potentials and the prediction of protein binding sites.</p

Convergence acceleration for multiobjective sparse reconstruction via knowledge transfer

© Springer Nature Switzerland AG 2019. Multiobjective sparse reconstruction (MOSR) methods can potentially obtain superior reconstruction performance. However, they suffer from high computational cost, especially in high-dimensional reconstruction. Furthermore, they are generally implemented independently without reusing prior knowledge from past experiences, leading to unnecessary computational consumption due to the re-exploration of similar search spaces. To address these problems, we propose a sparse-constraint knowledge transfer operator to accelerate the convergence of MOSR solvers by reusing the knowledge from past problem-solving experiences. Firstly, we introduce the deep nonlinear feature coding method to extract the feature mapping between the search of the current problem and a previously solved MOSR problem. Through this mapping, we learn a set of knowledge-induced solutions which contain the search experience of the past problem. Thereafter, we develop and apply a sparse-constraint strategy to refine these learned solutions to guarantee their sparse characteristics. Finally, we inject the refined solutions into the iteration of the current problem to facilitate the convergence. To validate the efficiency of the proposed operator, comprehensive studies on extensive simulated signal reconstruction are conducted

Corner contributions to holographic entanglement entropy

The entanglement entropy of three-dimensional conformal field theories contains a universal contribution coming from corners in the entangling surface. We study these contributions in a holographic framework and, in particular, we consider the effects of higher curvature interactions in the bulk gravity theory. We find that for all of our holographic models, the corner contribution is only modified by an overall factor but the functional dependence on the opening angle is not modified by the new gravitational interactions. We also compare the dependence of the corner term on the new gravitational couplings to that for a number of other physical quantities, and we show that the ratio of the corner contribution over the central charge appearing in the two-point function of the stress tensor is a universal function for all of the holographic theories studied here. Comparing this holographic result to the analogous functions for free CFT's, we find fairly good agreement across the full range of the opening angle. However, there is a precise match in the limit where the entangling surface becomes smooth, i.e., the angle approaches $\pi$, and we conjecture the corresponding ratio is a universal constant for all three-dimensional conformal field theories. In this paper, we expand on the holographic calculations in our previous letter arXiv:1505.04804, where this conjecture was first introduced.Comment: 62 pages, 6 figures, 1 table; v2: minor modifications to match published version, typos fixe

Biological characteristics and treatment outcomes of metastatic or recurrent neuroendocrine tumors: tumor grade and metastatic site are important for treatment strategy

<p>Abstract</p> <p>Background</p> <p>Studies about the biology, treatment pattern, and treatment outcome of metastatic/recurrent neuroendocrine tumor (NET) have been few.</p> <p>Methods</p> <p>We enrolled patients with metastatic/recurrent NET diagnosed between January 1996 and July 2007 and retrospectively analyzed.</p> <p>Results</p> <p>A total of 103 patients were evaluated. Twenty-six patients (25.2%) had pancreatic NET, 27 (26.2%) had gastrointestinal NET, 2 (1.9%) had lung NET, 28 (27.2%) had NET from other sites, and 20 (19.4%) had NET from unknown origin. The liver was the most common metastatic site (68.9%). Thirty-four patients had grade 1 disease, 1 (1.0%) had grade 2 disease, 15 (14.6%) had grade 3 disease, 9 (8.7%) had large cell disease, and 7 (6.8%) had small cell disease.</p> <p>Sixty-six patients received systemic treatment (interferon, somatostatin analogues or chemotherapy), 64 patients received local treatment (TACE, radiofrequency ablation, metastasectomy, etc.). Thirty-six patients received both systemic and local treatments.</p> <p>Median overall survival (OS) was 29.0 months (95% confidence interval, 25.0-33.0) in the103 patients. OS was significantly influenced by grade (<it>p </it>= .001). OS was 43.0, 23.0, and 29.0 months in patients who received local treatment only, systemic treatment only, and both treatments, respectively (<it>p </it>= .245). The median time-to-progression (TTP) was 6.0 months. Overall response rate was 34.0% and disease-control rate was 64.2%. TTP was influenced by the presence of liver metastasis (<it>p </it>= .011).</p> <p>Conclusions</p> <p>OS of metastatic/recurrent NET was different according to tumor grade. TTP was different according to metastasis site. Therefore, development of optimal treatment strategy based on the characteristics of NET is warranted.</p

A Nonaqueous Approach to the Preparation of Iron Phosphide Nanowires

Previous preparation of iron phosphide nanowires usually employed toxic and unstable iron carbonyl compounds as precursor. In this study, we demonstrate that iron phosphide nanowires can be synthesized via a facile nonaqueous chemical route that utilizes a commonly available iron precursor, iron (III) acetylacetonate. In the synthesis, trioctylphosphine (TOP) and trioctylphosphine oxide (TOPO) have been used as surfactants, and oleylamine has been used as solvent. The crystalline structure and morphology of the as-synthesized products were characterized by powder X-ray diffraction (XRD) and transmission electron microscopy (TEM). The obtained iron phosphide nanowires have a typical width of ~16 nm and a length of several hundred nanometers. Structural and compositional characterization reveals a hexagonal Fe2P crystalline phase. The morphology of as-synthesized products is greatly influenced by the ratio of TOP/TOPO. The presence of TOPO has been found to be essential for the growth of high-quality iron phosphide nanowires. Magnetic measurements reveal ferromagnetic characteristics, and hysteresis behaviors below the blocking temperature have been observed