Transient down-regulation of beta1 integrin subtypes on kidney carcinoma cells is induced by mechanical contact with endothelial cell membranes

Adhesion molecules of the integrin beta1 family are thought to be involved in the malignant progression renal cell carcinoma (RCC). Still, it is not clear how they contribute to this process. Since the hematogenous phase of tumour dissemination is the rate-limiting step in the metastatic process, we explored beta1 integrin alterations on several RCC cell lines (A498, Caki1, KTC26) before and after contacting vascular endothelium in a tumour-endothelium (HUVEC) co-culture assay. Notably, alpha2, alpha3 and alpha5 integrins became down-regulated immediately after the tumour cells attached to HUVEC, followed by re-expression shortly thereafter. Integrin down-regulation on RCC cells was caused by direct contact with endothelial cells, since the isolated endothelial membrane fragments but not the cell culture supernatant contributed to the observed effects. Integrin loss was accompanied by a reduced focal adhesion kinase (FAK) expression, FAK activity and diminished binding of tumour cells to matrix proteins. Furthermore, intracellular signalling proteins RCC cells were altered in the presence of HUVEC membrane fragments, in particular 14-3-3 epsilon, ERK2, PKCdelta, PKCepsilon and RACK1, which are involved in regulating tumour cell motility. We, therefore, speculate that contact of RCC cells with the vascular endothelium converts integrin-dependent adhesion to integrin-independent cell movement. The process of dynamic integrin regulation may be an important part in tumour cell migration strategy, switching the cells from being adhesive to becoming motile and invasive

Photonic polarization gears for ultra-sensitive angular measurements

Quantum metrology bears a great promise in enhancing measurement precision, but is unlikely to become practical in the near future. Its concepts can nevertheless inspire classical or hybrid methods of immediate value. Here, we demonstrate NOON-like photonic states of m quanta of angular momentum up to m=100, in a setup that acts as a "photonic gear", converting, for each photon, a mechanical rotation of an angle {\theta} into an amplified rotation of the optical polarization by m{\theta}, corresponding to a "super-resolving" Malus' law. We show that this effect leads to single-photon angular measurements with the same precision of polarization-only quantum strategies with m photons, but robust to photon losses. Moreover, we combine the gear effect with the quantum enhancement due to entanglement, thus exploiting the advantages of both approaches. The high "gear ratio" m boosts the current state-of-the-art of optical non-contact angular measurements by almost two orders of magnitude.Comment: 10 pages, 4 figures, + supplementary information (10 pages, 3 figures

End to End Deep Neural Network Frequency Demodulation of Speech Signals

Frequency modulation (FM) is a form of radio broadcasting which is widely used nowadays and has been for almost a century. We suggest a software-defined-radio (SDR) receiver for FM demodulation that adopts an end-to-end learning based approach and utilizes the prior information of transmitted speech message in the demodulation process. The receiver detects and enhances speech from the in-phase and quadrature components of its base band version. The new system yields high performance detection for both acoustical disturbances, and communication channel noise and is foreseen to out-perform the established methods for low signal to noise ratio (SNR) conditions in both mean square error and in perceptual evaluation of speech quality score

The cuttlefish Sepia officinalis (Sepiidae, Cephalopoda) constructs cuttlebone from a liquid-crystal precursor

Cuttlebone, the sophisticated buoyancy device of cuttlefish, is made of extensive superposed chambers that have a complex internal arrangement of calcified pillars and organic membranes. It has not been clear how this structure is assembled. We find that the membranes result from a myriad of minor membranes initially filling the whole chamber, made of nanofibres evenly oriented within each membrane and slightly rotated with respect to those of adjacent membranes, producing a helical arrangement. We propose that the organism secretes a chitin-protein complex, which self-organizes layer-by-layer as a cholesteric liquid crystal, whereas the pillars are made by viscous fingering. The liquid crystallization mechanism permits us to homologize the elements of the cuttlebone with those of other coleoids and with the nacreous septa and the shells of nautiloids. These results challenge our view of this ultra-light natural material possessing desirable mechanical, structural and biological properties, suggesting that two self-organizing physical principles suffice to understand its formation.Spanish Ministerio de Ciencia e Innovacion [CGL2010-20748-CO2-01, CGL2013-48247-P, FIS2013-48444-C2-2-P]; Andalusian Consejeria de Innovacion Ciencia y Tecnologia [RNM6433]; (Sepiatech, PROMAR program) of the Portuguese Ministerio da Agricultura e do Mar, Portugal [31.03.05.FEP.002]; Junta de Andalucia [RNM363]; FP7 COST Action of the European Community. [TD0903]info:eu-repo/semantics/publishedVersio

Stochastic Development Regression on Non-Linear Manifolds

We introduce a regression model for data on non-linear manifolds. The model describes the relation between a set of manifold valued observations, such as shapes of anatomical objects, and Euclidean explanatory variables. The approach is based on stochastic development of Euclidean diffusion processes to the manifold. Defining the data distribution as the transition distribution of the mapped stochastic process, parameters of the model, the non-linear analogue of design matrix and intercept, are found via maximum likelihood. The model is intrinsically related to the geometry encoded in the connection of the manifold. We propose an estimation procedure which applies the Laplace approximation of the likelihood function. A simulation study of the performance of the model is performed and the model is applied to a real dataset of Corpus Callosum shapes

Event-by-event non-rigid data-driven PET respiratory motion correction methods: comparison of principal component analysis and centroid of distribution

Respiratory motion is a major cause of degradation of PET image quality. Respiratory gating and motion correction can be performed to reduce the effects of respiratory motion; these methods require motion information, typically obtained from external tracking systems. Various groups have studied data-driven (DD) motion estimation methods. Recently, a data-driven respiratory motion estimation method was established by calculating the centroid of distribution (COD) of listmode events, which was then used with event-by-event respiratory motion correction (EBE-MC), and showed results comparable to those with an external motion tracking device. The EBE-MC method only corrected for rigid motion, so that non-rigid components still contributed to motion-induced blurring. A nonrigid respiratory motion correction (NRMC) was later developed to overcome this problem, but was only evaluated using signal from an external monitor. Thus, it is desirable to further develop data-driven to achieve the best respiratory motion correction results. 
 We evaluated 2 data-driven respiratory motion detection methods, COD and Principal Component Analysis (PCA), by comparing the extracted motion trace to that acquired by the Anzai system in dynamic studies with two tracers. PCA was chosen as a preliminary study indicated that it produced stable results than other DD methods. We then developed and performed DD-EBE-NRMC using either COD- or PCA-derived respiratory motion information. Data-driven correction results were compared with Anzai-based results. For all tested studies, both COD and PCA showed good-to-excellent match with Anzai signals, with PCA showing a higher correlation with Anzai signals. The DD-EBE-NRMC results showed that both COD and PCA provide comparable image quality improvement as the Anzai-based correction. Although COD showed a lower correlation with Anzai than PCA, COD-based NRMC results are comparable to those of PCA, both of which showed great reduction in motion-induced blurring

Predatory Bacteria: A Potential Ally against Multidrug-Resistant Gram-Negative Pathogens

Multidrug-resistant (MDR) Gram-negative bacteria have emerged as a serious threat to human and animal health. Bdellovibrio spp. and Micavibrio spp. are Gram-negative bacteria that prey on other Gram-negative bacteria. In this study, the ability of Bdellovibrio bacteriovorus and Micavibrio aeruginosavorus to prey on MDR Gram-negative clinical strains was examined. Although the potential use of predatory bacteria to attack MDR pathogens has been suggested, the data supporting these claims is lacking. By conducting predation experiments we have established that predatory bacteria have the capacity to attack clinical strains of a variety of ß-lactamase-producing, MDR Gram-negative bacteria. Our observations indicate that predatory bacteria maintained their ability to prey on MDR bacteria regardless of their antimicrobial resistance, hence, might be used as therapeutic agents where other antimicrobial drugs fail. © 2013 Kadouri et al

Hierarchical semantic representations of online news comments for emotion tagging using multiple information sources

With the development of online news services, users now can actively respond to online news by expressing subjective emotions, which can help us understand the predilections and opinions of an individual user, and help news publishers to provide more relevant services. Neural network methods have achieved promising results, but still have challenges in the field of emotion tagging. Firstly, these methods regard the whole document as a stream or bag of words and can't encode the intrinsic relations between sentences. So these methods cannot properly express the semantic meaning of the document in which sentences may have logical relations. Secondly, these methods only use semantics of the document itself, while ignoring the accompanying information sources, which can significantly influence the interpretation of the sentiment contained in documents. Therefore, this paper presents a hierarchical semantic representation model of news comments using multiple information sources, called Hierarchical Semantic Neural Network (HSNN). In particular, we begin with a novel neural network model to learn document representation in a bottom-up way, capturing not only the semantics within sentence but also semantics or logical relations between sentences. On top of this, we tackle the task of predicting emotions for online news comments by exploiting multiple information sources including the content of comments, the content of news articles, and the user-generated emotion votes. A series of experiments and tests on real-world datasets have demonstrated the effectiveness of our proposed approach

A Study of Brain Networks Associated with Swallowing Using Graph-Theoretical Approaches

Functional connectivity between brain regions during swallowing tasks is still not well understood. Understanding these complex interactions is of great interest from both a scientific and a clinical perspective. In this study, functional magnetic resonance imaging (fMRI) was utilized to study brain functional networks during voluntary saliva swallowing in twenty-two adult healthy subjects (all females, 23.1±1.52 years of age). To construct these functional connections, we computed mean partial correlation matrices over ninety brain regions for each participant. Two regions were determined to be functionally connected if their correlation was above a certain threshold. These correlation matrices were then analyzed using graph-theoretical approaches. In particular, we considered several network measures for the whole brain and for swallowing-related brain regions. The results have shown that significant pairwise functional connections were, mostly, either local and intra-hemispheric or symmetrically inter-hemispheric. Furthermore, we showed that all human brain functional network, although varying in some degree, had typical small-world properties as compared to regular networks and random networks. These properties allow information transfer within the network at a relatively high efficiency. Swallowing-related brain regions also had higher values for some of the network measures in comparison to when these measures were calculated for the whole brain. The current results warrant further investigation of graph-theoretical approaches as a potential tool for understanding the neural basis of dysphagia. © 2013 Luan et al

Structural Synthesis for GXW Specifications

We define the GXW fragment of linear temporal logic (LTL) as the basis for synthesizing embedded control software for safety-critical applications. Since GXW includes the use of a weak-until operator we are able to specify a number of diverse programmable logic control (PLC) problems, which we have compiled from industrial training sets. For GXW controller specifications, we develop a novel approach for synthesizing a set of synchronously communicating actor-based controllers. This synthesis algorithm proceeds by means of recursing over the structure of GXW specifications, and generates a set of dedicated and synchronously communicating sub-controllers according to the formula structure. In a subsequent step, 2QBF constraint solving identifies and tries to resolve potential conflicts between individual GXW specifications. This structural approach to GXW synthesis supports traceability between requirements and the generated control code as mandated by certification regimes for safety-critical software. Synthesis for GXW specifications is in PSPACE compared to 2EXPTIME-completeness of full-fledged LTL synthesis. Indeed our experimental results suggest that GXW synthesis scales well to industrial-sized control synthesis problems with 20 input and output ports and beyond.Comment: The long (including appendix) version being reviewed by CAV'16 program committee. Compared to the submitted version, one author (out of her wish) is moved to the Acknowledgement. (v2) Corrected typos. (v3) Add an additional remark over environment assumption and easy corner case