Diagnosis of focal liver lesions from ultrasound using deep learning

PURPOSE: The purpose of this study was to create an algorithm that simultaneously detects and characterizes (benign vs. malignant) focal liver lesion (FLL) using deep learning. MATERIALS AND METHODS: We trained our algorithm on a dataset proposed during a data challenge organized at the 2018 Journées Francophones de Radiologie. The dataset was composed of 367 two-dimensional ultrasound images from 367 individual livers, captured at various institutions. The algorithm was guided using an attention mechanism with annotations made by a radiologist. The algorithm was then tested on a new data set from 177 patients. RESULTS: The models reached mean ROC-AUC scores of 0.935 for FLL detection and 0.916 for FLL characterization over three shuffled three-fold cross-validations performed with the training data. On the new dataset of 177 patients, our models reached a weighted mean ROC-AUC scores of 0.891 for seven different tasks. CONCLUSION: This study that uses a supervised-attention mechanism focused on FLL detection and characterization from liver ultrasound images. This method could prove to be highly relevant for medical imaging once validated on a larger independent cohort

Solution Counting for CSP and SAT with Large Tree-Width

Рассмотрена проблема подсчета количества решений задачи совместимости ограничений (Constraint Satisfaction Problem). Для ее решения был адаптирован метод обратного прослеживания с ацикличным представлением графа ограничений (Backtracking with Tree-Decomposition). Предложен точный алгоритм, сложность которого экспоненциально зависит от ширины дерева, и приближенный алгоритм, экспоненциально зависящий от размера максимальной клики.The problem of counting the number of solutions of a CSP is considered. For solving the problem the Backtracking with a Tree-Decomposition method was adapted. The exact algorithm is suggested which has the worst-time complexity exponential in a tree width, as well as iterative algorithm that has computational complexity exponential in a maximum clique size.Розглянуто проблему підрахунку кількості розв’язків задачі сумісності обмежень (Constraint Satisfaction Problem). Для її розв’язку було адаптовано метод зворотного простеження з ациклічним поданням графа обмежень (Backtracking with Tree-Decomposition). Запропоновано точний алгоритм, складність якого експоненційно залежить від ширини дерева, і наближений алгоритм, експоненційно залежний від розміру максимальної кліки

Cr cluster characterization in Cu-Cr-Zr alloy after ECAP processing and aging using SANS and HAADF-STEM

International audienceThe precipitation of nano-sized Cr clusters was investigated in a commercial Cu-1Cr-0.1Zr (wt.%) alloy processed by Equal-Channel Angular Pressing (ECAP) and subsequent aging at 550 °C for 4 hours using small angle neutron scattering (SANS) measurements and high-angle annular dark-field-scanning transmission electron microscopy (HAADF-STEM). The size and volume fraction of nano-sized Cr clusters were estimated using both techniques. These parameters assessed from SANS (d~3.2 nm, Fv~1.1 %) agreed reasonably with those from HAADF-STEM (d ~2.5 nm, Fv~2.3%). Besides nano-sized Cr clusters, HAADF-STEM technique evidenced the presence of rare cuboid and spheroid sub-micronic Cr particles about 380-620 nm mean size. Both techniques did not evidence the presence of intermetallic CuxZry phases within the aging conditions

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

© 2019, The Author(s). Crohn Disease (CD) is a complex genetic disorder for which more than 140 genes have been identified using genome wide association studies (GWAS). However, the genetic architecture of the trait remains largely unknown. The recent development of machine learning (ML) approaches incited us to apply them to classify healthy and diseased people according to their genomic information. The Immunochip dataset containing 18,227 CD patients and 34,050 healthy controls enrolled and genotyped by the international Inflammatory Bowel Disease genetic consortium (IIBDGC) has been re-analyzed using a set of ML methods: penalized logistic regression (LR), gradient boosted trees (GBT) and artificial neural networks (NN). The main score used to compare the methods was the Area Under the ROC Curve (AUC) statistics. The impact of quality control (QC), imputing and coding methods on LR results showed that QC methods and imputation of missing genotypes may artificially increase the scores. At the opposite, neither the patient/control ratio nor marker preselection or coding strategies significantly affected the results. LR methods, including Lasso, Ridge and ElasticNet provided similar results with a maximum AUC of 0.80. GBT methods like XGBoost, LightGBM and CatBoost, together with dense NN with one or more hidden layers, provided similar AUC values, suggesting limited epistatic effects in the genetic architecture of the trait. ML methods detected near all the genetic variants previously identified by GWAS among the best predictors plus additional predictors with lower effects. The robustness and complementarity of the different methods are also studied. Compared to LR, non-linear models such as GBT or NN may provide robust complementary approaches to identify and classify genetic markers

Evaluating Multimedia Features and Fusion for Example-Based Event Detection

Multimedia event detection (MED) is a challenging problem because of the heterogeneous content and variable quality found in large collections of Internet videos. To study the value of multimedia features and fusion for representing and learning events from a set of example video clips, we created SESAME, a system for video SEarch with Speed and Accuracy for Multimedia Events. SESAME includes multiple bag-of-words event classifiers based on single data types: low-level visual, motion, and audio features; high-level semantic visual concepts; and automatic speech recognition. Event detection performance was evaluated for each event classifier. The performance of low-level visual and motion features was improved by the use of difference coding. The accuracy of the visual concepts was nearly as strong as that of the low-level visual features. Experiments with a number of fusion methods for combining the event detection scores from these classifiers revealed that simple fusion methods, such as arithmetic mean, perform as well as or better than other, more complex fusion methods. SESAME’s performance in the 2012 TRECVID MED evaluation was one of the best reported

Parallel assessment of male reproductive function in workers and wild rats exposed to pesticides in banana plantations in Guadeloupe

<p>Abstract</p> <p>Background</p> <p>There is increasing evidence that reproductive abnormalities are increasing in frequency in both human population and among wild fauna. This increase is probably related to exposure to toxic contaminants in the environment. The use of sentinel species to raise alarms relating to human reproductive health has been strongly recommended. However, no simultaneous studies at the same site have been carried out in recent decades to evaluate the utility of wild animals for monitoring human reproductive disorders. We carried out a joint study in Guadeloupe assessing the reproductive function of workers exposed to pesticides in banana plantations and of male wild rats living in these plantations.</p> <p>Methods</p> <p>A cross-sectional study was performed to assess semen quality and reproductive hormones in banana workers and in men working in non-agricultural sectors. These reproductive parameters were also assessed in wild rats captured in the plantations and were compared with those in rats from areas not directly polluted by humans.</p> <p>Results</p> <p>No significant difference in sperm characteristics and/or hormones was found between workers exposed and not exposed to pesticide. By contrast, rats captured in the banana plantations had lower testosterone levels and gonadosomatic indices than control rats.</p> <p>Conclusion</p> <p>Wild rats seem to be more sensitive than humans to the effects of pesticide exposure on reproductive health. We conclude that the concept of sentinel species must be carefully validated as the actual nature of exposure may varies between human and wild species as well as the vulnerable time period of exposure and various ecological factors.</p

On the Benefits of Transparent Compression for Cost-Effective Cloud Data Storage

International audienceInfrastructure-as-a-Service (IaaS) cloud computing has revolutionized the way we think of acquiring computational resources: it allows users to deploy virtual machines (VMs) at large scale and pay only for the resources that were actually used throughout the runtime of the VMs. This new model raises new challenges in the design and development of IaaS middleware: excessive storage costs associated with both user data and VM images might make the cloud less attractive, especially for users that need to manipulate huge data sets and a large number of VM images. Storage costs result not only from storage space utilization, but also from bandwidth consumption: in typical deployments, a large number of data transfers between the VMs and the persistent storage are performed, all under high performance requirements. This paper evaluates the trade-off resulting from transparently applying data compression to conserve storage space and bandwidth at the cost of slight computational overhead. We aim at reducing the storage space and bandwidth needs with minimal impact on data access performance. Our solution builds on BlobSeer, a distributed data management service specifically designed to sustain a high throughput for concurrent accesses to huge data sequences that are distributed at large scale. Extensive experiments demonstrate that our approach achieves large reductions (at least 40%) of bandwidth and storage space utilization, while still attaining high performance levels that even surpass the original (no compression) performance levels in several data-intensive scenarios

SPIN90 associates with mDia1 and the Arp2/3 complex to regulate cortical actin organization

Cell shape is controlled by the submembranous cortex, an actomyosin network mainly generated by two actin nucleators: the Arp2/3 complex and the formin mDia1. Changes in relative nucleator activity may alter cortical organization, mechanics and cell shape. Here we investigate how nucleation-promoting factors mediate interactions between nucleators. In vitro, the nucleation-promoting factor SPIN90 promotes formation of unbranched filaments by Arp2/3, a process thought to provide the initial filament for generation of dendritic networks. Paradoxically, in cells, SPIN90 appears to favour a formin-dominated cortex. Our in vitro experiments reveal that this feature stems mainly from two mechanisms: efficient recruitment of mDia1 to SPIN90-Arp2/3 nucleated filaments and formation of a ternary SPIN90-Arp2/3-mDia1 complex that greatly enhances filament nucleation. Both mechanisms yield rapidly elongating filaments with mDia1 at their barbed ends and SPIN90-Arp2/3 at their pointed ends. Thus, in networks, SPIN90 lowers branching densities and increases the proportion of long filaments elongated by mDia1

Stratospheric aerosols from the Sarychev volcano eruption in the 2009 Arctic summer

Aerosols from the Sarychev volcano eruption (Kuril Islands, northeast of Japan) were observed in the Arctic lower stratosphere a few days after the strongest SO2 injection which occurred on 15 and 16 June 2009. From the observations provided by the Infrared Atmospheric Sounding Interferometer (IASI) an estimated 0.9 Tg of sulphur dioxide was injected into the upper troposphere and lower stratosphere (UTLS). The resultant stratospheric sulphate aerosols were detected from satellites by the Optical Spectrograph and Infrared Imaging System (OSIRIS) limb sounder and by the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) and from the surface by the Network for the Detection of Atmospheric Composition Changes (NDACC) lidar deployed at OHP (Observatoire de Haute-Provence, France). By the first week of July the aerosol plume had spread out over the entire Arctic region. The Sarychev-induced stratospheric aerosol over the Kiruna region (north of Sweden) was measured by the Stratospheric and Tropospheric Aerosol Counter (STAC) during eight balloon flights planned in August and September 2009. During this balloon campaign the Micro Radiomètre Ballon (MicroRADIBAL) and the Spectroscopie d'Absorption Lunaire pour l'Observation des Minoritaires Ozone et NOx (SALOMON) remote-sensing instruments also observed these aerosols. Aerosol concentrations returned to near-background levels by spring 2010. The effective radius, the surface area density (SAD), the aerosol extinction, and the total sulphur mass from STAC in situ measurements are enhanced with mean values in the range 0.15-0.21 μm, 5.5-14.7 μm2 cm-3, 5.5-29.5 × 10-4 km-1, and 4.9-12.6 × 10-10 kg[S] kg-1[air], respectively, between 14 km and 18 km. The observed and modelled e-folding time of sulphate aerosols from the Sarychev eruption is around 70-80 days, a value much shorter than the 12-14 months calculated for aerosols from the 1991 eruption of Mt Pinatubo. The OSIRIS stratospheric aerosol optical depth (AOD) at 750 nm is enhanced by a factor of 6, with a value of 0.02 in late July compared to 0.0035 before the eruption. The HadGEM2 and MIMOSA model outputs indicate that aerosol layers in polar region up to 14-15 km are largely modulated by stratosphere-troposphere exchange processes. The spatial extent of the Sarychev plume is well represented in the HadGEM2 model with lower altitudes of the plume being controlled by upper tropospheric troughs which displace the plume downward and upper altitudes around 18-20 km, in agreement with lidar observations. Good consistency is found between the HadGEM2 sulphur mass density and the value inferred from the STAC observations, with a maximum located about 1 km above the tropopause ranging from 1 to 2 × 10 -9 kg[S] kg-1[air], which is one order of magnitude higher than the background level. © Author(s) 2013.The authors thank the CNES balloon launching team for successful operations and the Swedish Space Corporation at Esrange. The ETHER database (CNES-INSUCNRS) and the CNES “sous-direction Ballon” are partners of the project. The StraPolEt ´ e project has been funded by the French ´ “Agence Nationale de la Recherche” (ANR-BLAN08-1-31627), the “Centre National d’Etudes Spatiales” (CNES), and the “Institut ´ Polaire Paul-Emile Victor” (IPEV). The AEROWAVE (Aerosols, Water Vapor and Electricity) and the HALOHA (HALOgen in High Altitudes) projects have been funded by the recently created French CNES-INSU Balloon Committee (so-called CSTB). We are grateful to Slimane Bekki and David Cugniet for their constructive comments about the AER-UPMC 2-D model, to Marc-Antoine Drouin for his help about the MIMOSA model, and to the LPC2E technical team for this successful campaign. Jim Haywood and Andy Jones were supported by the Joint DECC/Defra Met Office Hadley Centre Climate Programme (GA01101). IASI was developed and built under the responsibility of the Centre National d’Etudes Spatiales (CNES, France). It is flown on board the Metop ´ satellites as part of the EUMETSAT Polar System. The IASI L1 data are received through the EUMETCast near-real-time data distribution service. L. Clarisse is a postdoctoral researcher with FRS-FNRS. We acknowledge the CALIOP team for acquiring and processing data as well as the ICARE team for providing and maintaining the computational facilities to store them. Odin is a Swedish-led satellite project funded jointly by Sweden (SNSB), Canada (CSA), France (CNES), and Finland (Tekes). This study was supported by the French VOLTAIRE Labex (Laboratoire d’Excellence ANR-10-LABX-100-01) managed by the University of Orleans