Gamma rhythms and beta rhythms have different synchronization properties

Experimental and modeling efforts suggest that rhythms in the CA1 region of the hippocampus that are in the beta range (12–29 Hz) have a different dynamical structure than that of gamma (30–70 Hz). We use a simplified model to show that the different rhythms employ different dynamical mechanisms to synchronize, based on different ionic currents. The beta frequency is able to synchronize over long conduction delays (corresponding to signals traveling a significant distance in the brain) that apparently cannot be tolerated by gamma rhythms. The synchronization properties are consistent with data suggesting that gamma rhythms are used for relatively local computations whereas beta rhythms are used for higher level interactions involving more distant structures.

Native display of complete foreign protein domains on the surface of hepatitis B virus capsids

The nucleocapsid of hepatitis B virus (HBV), or HBcAg, is a highly symmetric structure formed by multiple dimers of a single core protein that contains potent T helper epitopes in its 183-aa sequence. Both factors make HBcAg an unusually strong immunogen and an attractive candidate as a carrier for foreign epitopes. The immunodominant c/e1 epitope on the capsid has been suggested as a superior location to convey high immunogenicity to a heterologous sequence. Because of its central position, however, any c/e1 insert disrupts the core protein’s primary sequence; hence, only peptides, or rather small protein fragments seemed to be compatible with particle formation. According to recent structural data, the epitope is located at the tips of prominent surface spikes formed by the very stable dimer interfaces. We therefore reasoned that much larger inserts might be tolerated, provided the individual parts of a corresponding fusion protein could fold independently. Using the green fluorescent protein (GFP) as a model insert, we show that the chimeric protein efficiently forms fluorescent particles; hence, all of its structurally important parts must be properly folded. We also demonstrate that the GFP domains are surface-exposed and that the chimeric particles elicit a potent humoral response against native GFP. Hence, proteins of at least up to 238 aa can be natively displayed on the surface of HBV core particles. Such chimeras may not only be useful as vaccines but may also open the way for high resolution structural analyses of nonassembling proteins by electron microscopy.

BodyMap incorporated PCR-based expression profiling data and a gene ranking system

BodyMap is a human and mouse gene expression database that is based on site-directed 3′-expressed sequence tags generated at Osaka University. To date, it contains more than 300 000 tag sequences from 64 human and 39 mouse tissues. For the recent release, the precise anatomical expression patterns for more than half of the human gene entries were generated by introduced amplified fragment length polymorphism (iAFLP), which is a PCR-based high-throughput expression profiling method. The iAFLP data incorporated into BodyMap describe the relative contents of more than 12 000 transcripts across 30 tissue RNAs. In addition, a newly developed gene ranking system helps users obtain lists of genes that have desired expression patterns according to their significance. BodyMap supports complete transfer of unique data sets and provides analysis that is accessible through the WWW at http://bodymap.ims.u-tokyo.ac.jp.

Complete Cytolysis and Neonatal Lethality in Keratin 5 Knockout Mice Reveal Its Fundamental Role in Skin Integrity and in Epidermolysis Bullosa Simplex

In human patients, a wide range of mutations in keratin (K) 5 or K14 lead to the blistering skin disorder epidermolysis bullosa simplex. Given that K14 deficiency does not lead to the ablation of a basal cell cytoskeleton because of a compensatory role of K15, we have investigated the requirement for the keratin cytoskeleton in basal cells by inactivating the K5 gene in mice. We report that the K5−/− mice die shortly after birth, lack keratin filaments in the basal epidermis, and are more severely affected than K14−/− mice. In contrast to the K14−/− mice, we detected a strong induction of the wound-healing keratin K6 in the suprabasal epidermis of cytolyzed areas of postnatal K5−/− mice. In addition, K5 and K14 mice differed with respect to tongue lesions. Moreover, we show that in the absence of K5 and other type II keratins, residual K14 and K15 aggregated along hemidesmosomes, demonstrating that individual keratins without a partner are stable in vivo. Our data indicate that K5 may be the natural partner of K15 and K17. We suggest that K5 null mutations may be lethal in human epidermolysis bullosa simplex patients.

Simultaneous assessment of loss of heterozygosity at multiple microsatellite loci using semi-automated fluorescence-based detection: subregional mapping of chromosome 4 in cervical carcinoma.

Detection of loss of heterozygosity (LOH) by comparison of normal and tumor genotypes using PCR-based microsatellite loci provides considerable advantages over traditional Southern blotting-based approaches. However, current methodologies are limited by several factors, including the numbers of loci that can be evaluated for LOH in a single experiment, the discrimination of true alleles versus "stutter bands," and the use of radionucleotides in detecting PCR products. Here we describe methods for high throughput simultaneous assessment of LOH at multiple loci in human tumors; these methods rely on the detection of amplified microsatellite loci by fluorescence-based DNA sequencing technology. Data generated by this approach are processed by several computer software programs that enable the automated linear quantitation and calculation of allelic ratios, allowing rapid ascertainment of LOH. As a test of this approach, genotypes at a series of loci on chromosome 4 were determined for 58 carcinomas of the uterine cervix. The results underscore the efficacy, sensitivity, and remarkable reproducibility of this approach to LOH detection and provide subchromosomal localization of two regions of chromosome 4 commonly altered in cervical tumors.

Pipe3D, a pipeline to analyze integral field spectroscopy DATA: II. Analysis sequence and CALIFA dataproducts

We present PIPE3D, an analysis pipeline based on the FIT3D fitting tool, developed to explore the properties of the stellar populations and ionized gas of integral field spectroscopy (IFS) data. PIPE3D was created to provide coherent, simple to distribute, and comparable dataproducts, independently of the origin of the data, focused on the data of the most recent IFU surveys (e.g., CALIFA, MaNGA, and SAMI), and the last generation IFS instruments (e.g., MUSE). In this article we describe the different steps involved in the analysis of the data, illustrating them by showing the dataproducts derived for NGC 2916, observed by CALIFA and P-MaNGA. As a practical example of the pipeline we present the complete set of dataproducts derived for the 200 datacubes that comprises the V500 setup of the CALIFA Data Release 2 (DR2), making them freely available through the network. Finally, we explore the hypothesis that the properties of the stellar populations and ionized gas of galaxies at the effective radius are representative of the overall average ones, finding that this is indeed the case.

Análise quantitativa de dispersão de vazamentos de substâncias inflamáveis e/ou tóxicas em ambientes com barreiras ou semi confinados.

Com o atual desenvolvimento industrial e tecnológico da sociedade, a presença de substâncias inflamáveis e/ou tóxicas aumentou significativamente em um grande número de atividades. A possível dispersão de gases perigosos em instalações de armazenamento ou em operações de transporte representam uma grande ameaça à saúde e ao meio ambiente. Portanto, a caracterização de uma nuvem inflamável e/ou tóxica é um ponto crítico na análise quantitativa de riscos. O objetivo principal desta tese foi fornecer novas perspectivas que pudessem auxiliar analistas de risco envolvidos na análise de dispersões em cenários complexos, por exemplo, cenários com barreiras ou semi-confinados. A revisão bibliográfica mostrou que, tradicionalmente, modelos empíricos e integrais são usados na análise de dispersão de substâncias tóxicas / inflamáveis, fornecendo estimativas rápidas e geralmente confiáveis ao descrever cenários simples (por exemplo, dispersão em ambientes sem obstruções sobre terreno plano). No entanto, recentemente, o uso de ferramentas de CFD para simular dispersões aumentou de forma significativa. Estas ferramentas permitem modelar cenários mais complexos, como os que ocorrem em espaços semi-confinados ou com a presença de barreiras físicas. Entre todas as ferramentas CFD disponíveis, consta na bibliografia que o software FLACS® tem bom desempenho na simulação destes cenários. Porém, como outras ferramentas similares, ainda precisa ser totalmente validado. Após a revisão bibliográfica sobre testes de campo já executados ao longo dos anos, alguns testes foram selecionados para realização de um exame preliminar de desempenho da ferramenta CFD utilizado neste estudo. Foram investigadas as possíveis fontes de incertezas em termos de capacidade de reprodutibilidade, de dependência de malha e análise de sensibilidade das variáveis de entrada e parâmetros de simulação. Os principais resultados desta fase foram moldados como princípios práticos a serem utilizados por analistas de risco ao realizar análise de dispersão com a presença de barreiras utilizando ferramentas CFD. Embora a revisão bibliográfica tenha mostrado alguns dados experimentais disponíveis na literatura, nenhuma das fontes encontradas incluem estudos detalhados sobre como realizar simulações de CFD precisas nem fornecem indicadores precisos de desempenho. Portanto, novos testes de campo foram realizados a fim de oferecer novos dados para estudos de validação mais abrangentes. Testes de campo de dispersão de nuvem de propano (com e sem a presença de barreiras obstruindo o fluxo) foram realizados no campo de treinamento da empresa Can Padró Segurança e Proteção (em Barcelona). Quatro testes foram realizados, consistindo em liberações de propano com vazões de até 0,5 kg/s, com duração de 40 segundos em uma área de descarga de 700 m2. Os testes de campo contribuíram para a reavaliação dos pontos críticos mapeados durante as primeiras fases deste estudo e forneceram dados experimentais para serem utilizados pela comunidade internacional no estudo de dispersão e validação de modelos. Simulações feitas utilizando-se a ferramenta CFD foram comparadas com os dados experimentais obtidos nos testes de campo. Em termos gerais, o simulador mostrou bom desempenho em relação às taxas de concentração da nuvem. O simulador reproduziu com sucesso a geometria complexa e seus efeitos sobre a dispersão da nuvem, mostrando claramente o efeito da barreira na distribuição das concentrações. No entanto, as simulações não foram capazes de representar toda a dinâmica da dispersão no que concerne aos efeitos da variação do vento, uma vez que as nuvens simuladas diluíram mais rapidamente do que nuvens experimentais.

3D plane-based egomotion for SLAM on semi-structured environment

Several works deal with 3D data in SLAM problem. Data come from a 3D laser sweeping unit or a stereo camera, both providing a huge amount of data. In this paper, we detail an efficient method to extract planar patches from 3D raw data. Then, we use these patches in an ICP-like method in order to address the SLAM problem. Using ICP with planes is not a trivial task. It needs some adaptation from the original ICP. Some promising results are shown for outdoor environment.

Real-time 3D semi-local surface patch extraction using GPGPU

Feature vectors can be anything from simple surface normals to more complex feature descriptors. Feature extraction is important to solve various computer vision problems: e.g. registration, object recognition and scene understanding. Most of these techniques cannot be computed online due to their complexity and the context where they are applied. Therefore, computing these features in real-time for many points in the scene is impossible. In this work, a hardware-based implementation of 3D feature extraction and 3D object recognition is proposed to accelerate these methods and therefore the entire pipeline of RGBD based computer vision systems where such features are typically used. The use of a GPU as a general purpose processor can achieve considerable speed-ups compared with a CPU implementation. In this work, advantageous results are obtained using the GPU to accelerate the computation of a 3D descriptor based on the calculation of 3D semi-local surface patches of partial views. This allows descriptor computation at several points of a scene in real-time. Benefits of the accelerated descriptor have been demonstrated in object recognition tasks. Source code will be made publicly available as contribution to the Open Source Point Cloud Library.

On stable uniqueness in linear semi-infinite optimization

This paper is intended to provide conditions for the stability of the strong uniqueness of the optimal solution of a given linear semi-infinite optimization (LSIO) problem, in the sense of maintaining the strong uniqueness property under sufficiently small perturbations of all the data. We consider LSIO problems such that the family of gradients of all the constraints is unbounded, extending earlier results of Nürnberger for continuous LSIO problems, and of Helbig and Todorov for LSIO problems with bounded set of gradients. To do this we characterize the absolutely (affinely) stable problems, i.e., those LSIO problems whose feasible set (its affine hull, respectively) remains constant under sufficiently small perturbations.

Robust linear semi-infinite programming duality under uncertainty

In this paper, we propose a duality theory for semi-infinite linear programming problems under uncertainty in the constraint functions, the objective function, or both, within the framework of robust optimization. We present robust duality by establishing strong duality between the robust counterpart of an uncertain semi-infinite linear program and the optimistic counterpart of its uncertain Lagrangian dual. We show that robust duality holds whenever a robust moment cone is closed and convex. We then establish that the closed-convex robust moment cone condition in the case of constraint-wise uncertainty is in fact necessary and sufficient for robust duality. In other words, the robust moment cone is closed and convex if and only if robust duality holds for every linear objective function of the program. In the case of uncertain problems with affinely parameterized data uncertainty, we establish that robust duality is easily satisfied under a Slater type constraint qualification. Consequently, we derive robust forms of the Farkas lemma for systems of uncertain semi-infinite linear inequalities.

Calmness modulus of linear semi-infinite programs

Our main goal is to compute or estimate the calmness modulus of the argmin mapping of linear semi-infinite optimization problems under canonical perturbations, i.e., perturbations of the objective function together with continuous perturbations of the right-hand side of the constraint system (with respect to an index ranging in a compact Hausdorff space). Specifically, we provide a lower bound on the calmness modulus for semi-infinite programs with unique optimal solution which turns out to be the exact modulus when the problem is finitely constrained. The relationship between the calmness of the argmin mapping and the same property for the (sub)level set mapping (with respect to the objective function), for semi-infinite programs and without requiring the uniqueness of the nominal solution, is explored, too, providing an upper bound on the calmness modulus of the argmin mapping. When confined to finitely constrained problems, we also provide a computable upper bound as it only relies on the nominal data and parameters, not involving elements in a neighborhood. Illustrative examples are provided.

Enrichment of the Phenotypic and Genotypic Data Warehouse analysis using Question Answering systems to facilitate the decision making process in cereal breeding programs

Currently there are an overwhelming number of scientific publications in Life Sciences, especially in Genetics and Biotechnology. This huge amount of information is structured in corporate Data Warehouses (DW) or in Biological Databases (e.g. UniProt, RCSB Protein Data Bank, CEREALAB or GenBank), whose main drawback is its cost of updating that makes it obsolete easily. However, these Databases are the main tool for enterprises when they want to update their internal information, for example when a plant breeder enterprise needs to enrich its genetic information (internal structured Database) with recently discovered genes related to specific phenotypic traits (external unstructured data) in order to choose the desired parentals for breeding programs. In this paper, we propose to complement the internal information with external data from the Web using Question Answering (QA) techniques. We go a step further by providing a complete framework for integrating unstructured and structured information by combining traditional Databases and DW architectures with QA systems. The great advantage of our framework is that decision makers can compare instantaneously internal data with external data from competitors, thereby allowing taking quick strategic decisions based on richer data.

Constraint qualifications in linear vector semi-infinite optimization

Linear vector semi-infinite optimization deals with the simultaneous minimization of finitely many linear scalar functions subject to infinitely many linear constraints. This paper provides characterizations of the weakly efficient, efficient, properly efficient and strongly efficient points in terms of cones involving the data and Karush–Kuhn–Tucker conditions. The latter characterizations rely on different local and global constraint qualifications. The global constraint qualifications are illustrated on a collection of selected applications.

Constraint qualifications in convex vector semi-infinite optimization

Convex vector (or multi-objective) semi-infinite optimization deals with the simultaneous minimization of finitely many convex scalar functions subject to infinitely many convex constraints. This paper provides characterizations of the weakly efficient, efficient and properly efficient points in terms of cones involving the data and Karush–Kuhn–Tucker conditions. The latter characterizations rely on different local and global constraint qualifications. The results in this paper generalize those obtained by the same authors on linear vector semi-infinite optimization problems.