Spectral properties of microwave graphs with local absorption

The influence of absorption on the spectra of microwave graphs has been studied experimentally. The microwave networks were made up of coaxial cables and T junctions. First, absorption was introduced by attaching a 50 Ohm load to an additional vertex for graphs with and without time-reversal symmetry. The resulting level-spacing distributions were compared with a generalization of the Wigner surmise in the presence of open channels proposed recently by Poli et al. [Phys. Rev. Lett. 108, 174101 (2012)]. Good agreement was found using an effective coupling parameter. Second, absorption was introduced along one individual bond via a variable microwave attenuator, and the influence of absorption on the length spectrum was studied. The peak heights in the length spectra corresponding to orbits avoiding the absorber were found to be independent of the attenuation, whereas, the heights of the peaks belonging to orbits passing the absorber once or twice showed the expected decrease with increasing attenuation.Comment: 7 pages, 7 figure

Inferring latent task structure for Multitask Learning by Multiple Kernel Learning

<p>Abstract</p> <p>Background</p> <p>The lack of sufficient training data is the limiting factor for many Machine Learning applications in Computational Biology. If data is available for several different but related problem domains, Multitask Learning algorithms can be used to learn a model based on all available information. In Bioinformatics, many problems can be cast into the Multitask Learning scenario by incorporating data from several organisms. However, combining information from several tasks requires careful consideration of the degree of similarity between tasks. Our proposed method simultaneously learns or refines the similarity between tasks along with the Multitask Learning classifier. This is done by formulating the Multitask Learning problem as Multiple Kernel Learning, using the recently published <it>q</it>-Norm MKL algorithm.</p> <p>Results</p> <p>We demonstrate the performance of our method on two problems from Computational Biology. First, we show that our method is able to improve performance on a splice site dataset with given hierarchical task structure by refining the task relationships. Second, we consider an MHC-I dataset, for which we assume no knowledge about the degree of task relatedness. Here, we are able to learn the task similarities<it> ab initio</it> along with the Multitask classifiers. In both cases, we outperform baseline methods that we compare against.</p> <p>Conclusions</p> <p>We present a novel approach to Multitask Learning that is capable of learning task similarity along with the classifiers. The framework is very general as it allows to incorporate prior knowledge about tasks relationships if available, but is also able to identify task similarities in absence of such prior information. Both variants show promising results in applications from Computational Biology.</p

On the Link between Gaussian Homotopy Continuation and Convex Envelopes

Abstract. The continuation method is a popular heuristic in computer vision for nonconvex optimization. The idea is to start from a simpli-fied problem and gradually deform it to the actual task while tracking the solution. It was first used in computer vision under the name of graduated nonconvexity. Since then, it has been utilized explicitly or im-plicitly in various applications. In fact, state-of-the-art optical flow and shape estimation rely on a form of continuation. Despite its empirical success, there is little theoretical understanding of this method. This work provides some novel insights into this technique. Specifically, there are many ways to choose the initial problem and many ways to progres-sively deform it to the original task. However, here we show that when this process is constructed by Gaussian smoothing, it is optimal in a specific sense. In fact, we prove that Gaussian smoothing emerges from the best affine approximation to Vese’s nonlinear PDE. The latter PDE evolves any function to its convex envelope, hence providing the optimal convexification

EMC ASPECTS OF TURBULENCE HEATING OBSERVER (THOR) SPACECRAFT

Turbulence Heating ObserveR (THOR) is a spacecraft mission dedicated to the study of plasma turbulence in near-Earth space. The mission is currently under study for implementation as a part of ESA Cosmic Vision program. THOR will involve a single spinning spacecraft equipped with state of the art instruments capable of sensitive measurements of electromagnetic fields and plasma particles. The sensitive electric and magnetic field measurements require that the spacecraft-generated emissions are restricted and strictly controlled; therefore a comprehensive EMC program has been put in place already during the study phase. The THOR study team and a dedicated EMC working group are formulating the mission EMC requirements state of its EMC requirements

Phenotype Recognition with Combined Features and Random Subspace Classifier Ensemble

<p>Abstract</p> <p>Background</p> <p>Automated, image based high-content screening is a fundamental tool for discovery in biological science. Modern robotic fluorescence microscopes are able to capture thousands of images from massively parallel experiments such as RNA interference (RNAi) or small-molecule screens. As such, efficient computational methods are required for automatic cellular phenotype identification capable of dealing with large image data sets. In this paper we investigated an efficient method for the extraction of quantitative features from images by combining second order statistics, or Haralick features, with curvelet transform. A random subspace based classifier ensemble with multiple layer perceptron (MLP) as the base classifier was then exploited for classification. Haralick features estimate image properties related to second-order statistics based on the grey level co-occurrence matrix (GLCM), which has been extensively used for various image processing applications. The curvelet transform has a more sparse representation of the image than wavelet, thus offering a description with higher time frequency resolution and high degree of directionality and anisotropy, which is particularly appropriate for many images rich with edges and curves. A combined feature description from Haralick feature and curvelet transform can further increase the accuracy of classification by taking their complementary information. We then investigate the applicability of the random subspace (RS) ensemble method for phenotype classification based on microscopy images. A base classifier is trained with a RS sampled subset of the original feature set and the ensemble assigns a class label by majority voting.</p> <p>Results</p> <p>Experimental results on the phenotype recognition from three benchmarking image sets including HeLa, CHO and RNAi show the effectiveness of the proposed approach. The combined feature is better than any individual one in the classification accuracy. The ensemble model produces better classification performance compared to the component neural networks trained. For the three images sets HeLa, CHO and RNAi, the Random Subspace Ensembles offers the classification rates 91.20%, 98.86% and 91.03% respectively, which compares sharply with the published result 84%, 93% and 82% from a multi-purpose image classifier WND-CHARM which applied wavelet transforms and other feature extraction methods. We investigated the problem of estimation of ensemble parameters and found that satisfactory performance improvement could be brought by a relative medium dimensionality of feature subsets and small ensemble size.</p> <p>Conclusions</p> <p>The characteristics of curvelet transform of being multiscale and multidirectional suit the description of microscopy images very well. It is empirically demonstrated that the curvelet-based feature is clearly preferred to wavelet-based feature for bioimage descriptions. The random subspace ensemble of MLPs is much better than a number of commonly applied multi-class classifiers in the investigated application of phenotype recognition.</p

Filopodyan: An open-source pipeline for the analysis of filopodia

Filopodia have important sensory and mechanical roles in motile cells. The recruitment of actin regulators, such as ENA/ VASP proteins, to sites of protrusion underlies diverse molecular mechanisms of filopodia formation and extension. We developed Filopodyan (filopodia dynamics analysis) in Fiji and R to measure fluorescence in filopodia and at their tips and bases concurrently with their morphological and dynamic properties. Filopodyan supports high-throughput phenotype characterization as well as detailed interactive editing of filopodia reconstructions through an intuitive graphical user interface. Our highly customizable pipeline is widely applicable, capable of detecting filopodia in four different cell types in vitro and in vivo. We use Filopodyan to quantify the recruitment of ENA and VASP preceding filopodia formation in neuronal growth cones, and uncover a molecular heterogeneity whereby different filopodia display markedly different responses to changes in the accumulation of ENA and VASP fluorescence in their tips over time.J.L. Gallop and V. Urbančič are supported by the Wellcome Trust (WT095829AIA). J. Mason and B. Richier are supported by the European Research Council (281971). C.E. Holt is supported by the Wellcome Trust (program grant 085314) and the European Research Council (advanced grant 322817). The Gurdon Institute is funded by the Wellcome Trust (203144) and Cancer Research UK (C6946/A24843)

Magnetic resonance imaging, computed tomography, and 68Ga-DOTATOC positron emission tomography for imaging skull base meningiomas with infracranial extension treated with stereotactic radiotherapy - a case series

<p>Abstract</p> <p>Introduction</p> <p>Magnetic resonance imaging (MRI) and computed tomography (CT) with ⁶⁸Ga-DOTATOC positron emission tomography (⁶⁸Ga-DOTATOC-PET) were compared retrospectively for their ability to delineate infracranial extension of skull base (SB) meningiomas treated with fractionated stereotactic radiotherapy.</p> <p>Methods</p> <p>Fifty patients with 56 meningiomas of the SB underwent MRI, CT, and ⁶⁸Ga-DOTATOC PET/CT prior to fractionated stereotactic radiotherapy. The study group consisted of 16 patients who had infracranial meningioma extension, visible on MRI ± CT (MRI/CT) <it>or </it>PET, and were evaluated further. The respective findings were reviewed independently, analyzed with respect to correlations, and compared with each other.</p> <p>Results</p> <p>Within the study group, SB transgression was associated with bony changes visible by CT in 14 patients (81%). Tumorous changes of the foramen ovale and rotundum were evident in 13 and 8 cases, respectively, which were accompanied by skeletal muscular invasion in 8 lesions. We analysed six designated anatomical sites of the SB in each of the 16 patients. Of the 96 sites, 42 had infiltration that was delineable by MRI/CT and PET in 35 cases and by PET only in 7 cases. The mean infracranial volume that was delineable in PET was 10.1 ± 10.6 cm³, which was somewhat larger than the volume detectable in MRI/CT (8.4 ± 7.9 cm³).</p> <p>Conclusions</p> <p>⁶⁸Ga-DOTATOC-PET allows detection and assessment of the extent of infracranial meningioma invasion. This method seems to be useful for planning fractionated stereotactic radiation when used in addition to conventional imaging modalities that are often inconclusive in the SB region.</p

The formation of actin waves during regeneration after axonal lesion is enhanced by BDNF

During development, axons of neurons in the mammalian central nervous system lose their ability to regenerate. To study the regeneration process, axons of mouse hippocampal neurons were partially damaged by an UVA laser dissector system. The possibility to deliver very low average power to the sample reduced the collateral thermal damage and allowed studying axonal regeneration of mouse neurons during early days in vitro. Force spectroscopy measurements were performed during and after axon ablation with a bead attached to the axonal membrane and held in an optical trap. With this approach, we quantified the adhesion of the axon to the substrate and the viscoelastic properties of the membrane during regeneration. The reorganization and regeneration of the axon was documented by long-term live imaging. Here we demonstrate that BDNF regulates neuronal adhesion and favors the formation of actin waves during regeneration after axonal lesion

Comment on the letter of the Society of Vertebrate Paleontology (SVP) dated April 21, 2020 regarding “Fossils from conflict zones and reproducibility of fossil‑based scientific data”: Myanmar amber

Non peer reviewe

Ephrin-A5 Suppresses Neurotrophin Evoked Neuronal Motility, ERK Activation and Gene Expression

During brain development, growth cones respond to attractive and repulsive axon guidance cues. How growth cones integrate guidance instructions is poorly understood. Here, we demonstrate a link between BDNF (brain derived neurotrophic factor), promoting axonal branching and ephrin-A5, mediating axonal repulsion via Eph receptor tyrosine kinase activation. BDNF enhanced growth cone filopodial dynamics and neurite branching of primary neurons. We show that ephrin-A5 antagonized this BDNF-evoked neuronal motility. BDNF increased ERK phosphorylation (P-ERK) and nuclear ERK entry. Ephrin-A5 suppressed BDNF-induced ERK activity and might sequester P-ERK in the cytoplasm. Neurotrophins are well established stimulators of a neuronal immediate early gene (IEG) response. This is confirmed in this study by e.g. c-fos, Egr1 and Arc upregulation upon BDNF application. This BDNF-evoked IEG response required the transcription factor SRF (serum response factor). Notably, ephrin-A5 suppressed a BDNF-evoked neuronal IEG response, suggesting a role of Eph receptors in modulating gene expression. In opposite to IEGs, long-term ephrin-A5 application induced cytoskeletal gene expression of tropomyosin and actinin. To uncover specific Eph receptors mediating ephrin-As impact on neurotrophin signaling, EphA7 deficient mice were analyzed. In EphA7 deficient neurons alterations in growth cone morphology were observed. However, ephrin-A5 still counteracted neurotrophin signaling suggesting that EphA7 is not required for ephrin and BDNF crosstalk. In sum, our data suggest an interaction of ephrin-As and neurotrophin signaling pathways converging at ERK signaling and nuclear gene activity. As ephrins are involved in development and function of many organs, such modulation of receptor tyrosine kinase signaling and gene expression by Ephs might not be limited to the nervous system