Aortography Keypoint Tracking for Transcatheter Aortic Valve Implantation Based on Multi-Task Learning

Currently, transcatheter aortic valve implantation (TAVI) represents the most efficient treatment option for patients with aortic stenosis, yet its clinical outcomes largely depend on the accuracy of valve positioning that is frequently complicated when routine imaging modalities are applied. Therefore, existing limitations of perioperative imaging underscore the need for the development of novel visual assistance systems enabling accurate procedures. In this paper, we propose an original multi-task learning-based algorithm for tracking the location of anatomical landmarks and labeling critical keypoints on both aortic valve and delivery system during TAVI. In order to optimize the speed and precision of labeling, we designed nine neural networks and then tested them to predict 11 keypoints of interest. These models were based on a variety of neural network architectures, namely MobileNet V2, ResNet V2, Inception V3, Inception ResNet V2 and EfficientNet B5. During training and validation, ResNet V2 and MobileNet V2 architectures showed the best prediction accuracy/time ratio, predicting keypoint labels and coordinates with 97/96% accuracy and 4.7/5.6% mean absolute error, respectively. Our study provides evidence that neural networks with these architectures are capable to perform real-time predictions of aortic valve and delivery system location, thereby contributing to the proper valve positioning during TAVI

The position of the fixed combination of indacaterol, glycopyrronium, and mometasone furoate in the management of bronchial asthma. The Report of Expert Panel of Russian Respiratory Society

Achieving the control of bronchial asthma (BA) in real clinical practice remains an unresolved problem, despite the expansion of therapeutic options in this area. Guidelines about when and for whom should a particular treatment be used continue to develop. Increasing of inhaled corticosteroid dose (ICS) in combination with a long-acting β2-agonist (LABA) does not always lead to the desired result, although a combined LABA-ICS inhaler could improve the course of asthma and increase adherence. The addition of tiotropium bromide to LABA-ICS requires the use of two inhalers. The targeted biological therapy is associated with the complexity of phenotyping and is possible only in specialized medical centers. Mometasone furoate, indacaterol acetate, and glycopyrronium bromide in fixed doses were combined in Breezhaler® inhaler for asthma maintenance therapy once per day. This way of treatment helps to realize full potential of maintenance inhalation therapy of bronchial asthma and to simplify the achievement of control over the disease in routine clinical practice.Достижение контроля над бронхиальной астмой (БА) в реальной клинической практике остается нерешенной проблемой, несмотря на существенное расширение терапевтических возможностей в этом направлении. Рекомендации о том, когда и для кого должны использоваться те или иные методы лечения, продолжают расширяться. При увеличении дозы ингаляционного глюкокортикостероида (иГКС) в комбинации с длительно действующим β2-агонистом (ДДБА) далеко не всегда достигается желаемый результат, хотя при использовании единого ингалятора иГКС / ДДБА может улучшиться течение БА и повыситься приверженность терапии. При добавлении тиотропия бромида к иГКС / ДДБА требуется использование 2 ингаляторов, а назначение таргетной биологической терапии связано со сложностью фенотипирования и возможно только в специализированных медицинских центрах. Мометазона фуроат, индакатерола ацетат и гликопиррония бромид объединены в фиксированную комбинацию, доставляемую с помощью ингалятора Бризхалер® 1 раз в день для поддерживающей терапии БА. Этот способ лечения помогает реализовать потенциал базисной ингаляционной терапии БА и упростить достижение контроля над заболеванием в повседневной клинической практик

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Reconstruction and simulation of neocortical microcircuitry

We present a first-draft digital reconstruction of the microcircuitry of somatosensory cortex of juvenile rat. The reconstruction uses cellular and synaptic organizing principles to algorithmically reconstruct detailed anatomy and physiology from sparse experimental data. An objective anatomical method defines a neocortical volume of 0.29 ± 0.01 mm3 containing ∼31,000 neurons, and patch-clamp studies identify 55 layer-specific morphological and 207 morpho-electrical neuron subtypes. When digitally reconstructed neurons are positioned in the volume and synapse formation is restricted to biological bouton densities and numbers of synapses per connection, their overlapping arbors form ∼8 million connections with ∼37 million synapses. Simulations reproduce an array of in vitro and in vivo experiments without parameter tuning. Additionally, we find a spectrum of network states with a sharp transition from synchronous to asynchronous activity, modulated by physiological mechanisms. The spectrum of network states, dynamically reconfigured around this transition, supports diverse information processing strategies

26th Annual Computational Neuroscience Meeting (CNS*2017): Part 3 - Meeting Abstracts - Antwerp, Belgium. 15–20 July 2017

This work was produced as part of the activities of FAPESP Research,\ud Disseminations and Innovation Center for Neuromathematics (grant\ud 2013/07699-0, S. Paulo Research Foundation). NLK is supported by a\ud FAPESP postdoctoral fellowship (grant 2016/03855-5). ACR is partially\ud supported by a CNPq fellowship (grant 306251/2014-0)

SYMMETRY PECULIARITIES OF THE INTRACRYSTALLINE FIELDS LAYERED SEMICONDUCTOR CRYSTALS (PbI2_2)(1−x)_{(1-x)} (BiI3_3)(x)_{(x)}

Author Institution: Institute of Physics National Academy of Sciences of Ukraine; 46, Prospect Nauki, 03680 Kiev, UkraineIn this work the results of the investigation of the $^{127}$I NQR spectra at 77K for mixed layered semiconductor crystals (PbI$_2$)$_{(1-x)}$ (BiI$_3$)$_{(x)}$ in a wide range of value (0 \textless x \textless 0.50) are presented. It is shown that in the range 0.05 \textless x \textless 0.20 of admixture PbI$_2$ the observed behavior of parameters of the $^{127}$I NQR spectra testify about entrance of admixture atoms PbI$_2$ into the crystal layers. It is shown, that at 0.05 \textlessÊ x \textless 0.20 clusters from groups of atoms PbI$_2$ insular type can be formed, which lay within the limits of the layers of crystal (PbI$_2$)$_{(1-x)}$ (BiI$_3$)$_{(x)}$. Upon further increasing of the containing of admixture PbI$_2$ in crystal BiI$_3$ the "new" $^{127}$I NQR line is appearing. The observed at x _\textasciitilde 0.20 the new line in spectrum $^{127}$I NQR can testify that the mixed crystal (PbI$_2$)$_{(1-x)}$ (BiI$_3$)$_{(x)}$ undergoes structural phase transition. It is concluded that at x\textgreater 0.20 a new crystal presents a solid mixture glassy crystal of substitution type in which of PbI$_2$ atoms are fully or partially are ordering and lay between crystal

Selective permeability of carbyne membranes

The paper considers carbyne nanostructures as filtering members for separation of gas mixtures based on selective adsorption of its components, in particular, hydrogen, helium and methane. The size of a highlyselective cell is determined in this paper. It is found that the number of layers in carbyne membrane has no effect on the selective separation of gas mixtures

CoreNEURON : An Optimized Compute Engine for the NEURON Simulator

The NEURON simulator has been developed over the past three decades and is widely used by neuroscientists to model the electrical activity of neuronal networks. Large network simulation projects using NEURON have supercomputer allocations that individually measure in the millions of core hours. Supercomputer centers are transitioning to next generation architectures and the work accomplished per core hour for these simulations could be improved by an order of magnitude if NEURON was able to better utilize those new hardware capabilities. In order to adapt NEURON to evolving computer architectures, the compute engine of the NEURON simulator has been extracted and has been optimized as a library called CoreNEURON. This paper presents the design, implementation, and optimizations of CoreNEURON. We describe how CoreNEURON can be used as a library with NEURON and then compare performance of different network models on multiple architectures including IBM BlueGene/Q, Intel Skylake, Intel MIC and NVIDIA GPU. We show how CoreNEURON can simulate existing NEURON network models with 4-7x less memory usage and 2-7x less execution time while maintaining binary result compatibility with NEURON

Leveraging a Cluster-Booster Architecture for Brain-Scale Simulations

The European Dynamical Exascale Entry Platform (DEEP) is an example of a new type of heterogeneous supercomputing architecture that include both a standard multicore-based “Cluster” used to run less scalable parts of an application, and an Intel MIC-based “Booster” used to run highly scalable compute kernels. In this paper we describe how the compute engine of the widely used NEURON scientific application has been ported on both the DEEP and the Intel MIC platform. We discuss the design and implementation of the core simulator with an emphasis on the development workflow and implementation details that enable the efficient use of the new “Cluster-Booster” type of architectures. We describe optimizations of the data structures and algorithms tailored to the Intel Xeon Phi coprocessor which contributed to improve the overall performance of NEURON by a factor 5. Validation of our implementation has first been done on STAMPEDE supercomputer in order to emulate the DEEP architecture performance. Building on these results, we then explored opportunities offered by the DEEP platform to efficiently support complex scientific workflow