Parallel stepwise stochastic simulation: Harnessing GPUs to Explore Possible Futures States of a Chromosome Folding Model Thanks to the Possible Futures Algorithm (PFA)

International audienceFor the sake of software compatibility, simulations are often parallelized withoutmuch code rewriting. Performances can be further improved by optimizing codes so that to use themaximum power offered by parallel architectures. While this approach can provide some speed-up,performance of parallelized codes can be strongly limited a priori because traditional algorithmshave been designed for sequential technologies. Thus, additional increase of performance shouldultimately rely on some redesign of algorithms.Here, we redesign an algorithm that has traditionally been used to simulate the folding proper-ties of polymers. We address the issue of performance in the context of biological applications,more particularly in the active field of chromosome modelling. Due to the strong confinementof chromosomes in the cells, simulation of their motion is slowed down by the laborious searchfor the next valid states to progress. Our redesign, that we call the Possible Futures Algorithm(PFA), relies on the parallel computation of possible evolutions of the same state, which effectivelyincreases the probability to obtain a valid state at each step. We apply PFA on a GPU-basedarchitecture, allowing us to optimally reduce the latency induced by the computation overhead ofpossible futures. We show that compared to the initial sequential model the acceptance rate of newstates significantly increases without impacting the execution time. In particular, the stronger theconfinement of the chromosome, the more efficient PFA becomes, making our approach appealingfor biological applications.While most of our results were obtained using Fermi architecture GPUs from NVIDIA, we highlightimproved performance on the cutting-edge Kepler architecture K20 GPUs

Grid Analysis of Radiological Data

IGI-Global Medical Information Science Discoveries Research Award 2009International audienceGrid technologies and infrastructures can contribute to harnessing the full power of computer-aided image analysis into clinical research and practice. Given the volume of data, the sensitivity of medical information, and the joint complexity of medical datasets and computations expected in clinical practice, the challenge is to fill the gap between the grid middleware and the requirements of clinical applications. This chapter reports on the goals, achievements and lessons learned from the AGIR (Grid Analysis of Radiological Data) project. AGIR addresses this challenge through a combined approach. On one hand, leveraging the grid middleware through core grid medical services (data management, responsiveness, compression, and workflows) targets the requirements of medical data processing applications. On the other hand, grid-enabling a panel of applications ranging from algorithmic research to clinical use cases both exploits and drives the development of the services

Group-wise Construction of Reduced Models for Understanding and Characterization of Pulmonary Blood Flows from Medical Images

International audience3D computational fluid dynamics (CFD) in patient-specific geometries provides complementary insights to clinical imaging, to better understand how heart disease, and the side effects of treating heart disease, affect and are affected by hemodynamics. This information can be useful in treatment planning for designing artificial devices that are subject to stress and pressure from blood flow. Yet, these simulations remain relatively costly within a clinical context. The aim of this work is to reduce the complexity of patient-specific simulations by combining image analysis, computational fluid dynamics and model order reduction techniques. The proposed method makes use of a reference geometry estimated as an average of the population, within an efficient statistical framework based on the currents representation of shapes. Snapshots of blood flow simulations performed in the reference geometry are used to build a POD (Proper Orthogonal Decomposition) basis, which can then be mapped on new patients to perform reduced order blood flow simulations with patient specific boundary conditions. This approach is applied to a data-set of 17 tetralogy of Fallot patients to simulate blood flow through the pulmonary artery under normal (healthy or synthetic valves with almost no backflow) and pathological (leaky or absent valve with backflow) conditions to better understand the impact of regurgitated blood on pressure and velocity at the outflow tracts. The model reduction approach is further tested by performing patient simulations under exercise and varying degrees of pathophysiological conditions based on reduction of reference solutions (rest and medium backflow conditions respectively)

Sweet but Challenging: Tackling the Complexity of GAGs with Engineered Tailor‐Made Biomaterials

Glycosaminoglycans (GAGs) play a crucial role in tissue homeostasis by regulating the activity and diffusion of bioactive molecules. Incorporating GAGs into biomaterials has emerged as a widely adopted strategy in medical applications, owing to their biocompatibility and ability to control the release of bioactive molecules. Nevertheless, immobilized GAGs on biomaterials can elicit distinct cellular responses compared to their soluble forms, underscoring the need to understand the This article is protected by copyright. All rights reserved. 2 interactions between GAG and bioactive molecules within engineered functional biomaterials. By controlling critical parameters such as GAG type, density, and sulfation, it becomes possible to precisely delineate GAG functions within a biomaterial context and to better mimic specific tissue properties, enabling tailored design of GAG-based biomaterials for specific medical applications. However, this requires access to pure and well-characterized GAG compounds, which remains challenging. This review focuses on different strategies for producing well-defined GAGs and explores high-throughput approaches employed to investigate GAG-growth factor interactions and to quantify cellular responses on GAG-based biomaterials. These automated methods hold considerable promise for improving our understanding of the diverse functions of GAGs. In perspectives, we encourage the scientific community to adopt a rational approach in designing GAG-based biomaterials, taking into account the in vivo properties of the targeted tissue for medical applications

BMP2 binds non-specifically to PEG-passivated biomaterials and induces substantial signaling

Biomaterials are widely employed across diverse biomedical applications and represent an attractive strategy to explore physiologically how extracellular matrix components influence the cellular response. In this study, we aimed to use previously developed biomimetic streptavidin platforms to investigate the role of glycosaminoglycans (GAGs) in bone morphogenetic protein 2 (BMP2) signaling. However, we observed that the interpretation of our findings was skewed due to the GAG-unrelated, non-specific adsorption of BMP2 on components of our biomaterials. Non-specific adsorption of proteins is a recurrent and challenging issue for biomaterial studies. Despite the initial incorporation of anti-fouling poly(ethylene glycol) (PEG) chains within our biomaterials, the residual non-specific BMP2 adsorption still triggered BMP2 signaling within the same range as our conditions of interest. To tackle this issue, we explored various options to prevent BMP2 non-specific adsorption. Specifically, we tested alternative constructions of our biomaterials on gold or glass substrate using distinct PEG-based linkers. We identified the aggregation of BMP2 at neutral pH as a potential cause of non-specific adsorption and thus determined specific buffer conditions to prevent it. We also investigated the induced BMP2 signaling over different culture periods. Nevertheless, none of these options resulted in a viable suitable solution to reduce the non-specific BMP2 signaling. Next, we studied the effect of various blocking strategies. We identified a blocking condition involving a combination of bovine serum albumin and trehalose that successfully reduced the unspecific attachment of BMP2 and the non-specific signaling. Furthermore, the effect of this blocking step was improved when using gold platforms instead of glass, particularly with Chinese hamster ovary (CHO) cells that seemed less responsive to non-specifically bound BMP2 than C2C12 cells

Multiple-slot antennas on high resistivity silicon substrate for impedance control in a co-design with amplifier scheme

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Dedicated measurement setup for MMW silicon integrated antennas : BiCMOS and CMOS high resistivity SOI processes characterization

International audienceThanks to the competitive performances of CMOS and BiCMOS transistors, we are able to integrate the complete RF front-end on a same silicon substrate, including the antenna. In this paper, we describe a state-of-the-art measurement setup dedicated to the full characterization of silicon integrated antennas. This anechoic chamber is able to address radiation pattern and gain extraction as well as return loss measurements as far as the appropriate calibration technique is applied. First, a standard 22.5 dBi-gain horn antenna is measured to validate the extraction method. Then, a 40 GHz dipole antenna on a low resistivity substrate and a 60 GHz folded-slot antenna on a high resistivity SOI substrate are characterized. Gain values of -11.9 dBi and -0.4 dBi are extracted, respectively. For these antennas we are also able to plot their radiation pattern in their E and H planes

Folded slot integrated antenna array for millimeter wave CMOS applications on standard HR SOI Silicon substrate

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Folded slot integrated antenna array for millimeter wave CMOS applications on standard HR SOI Silicon substrate

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94 GHz silicon co-integrated LNA and Antenna in a mm-wave dedicated BiCMOS technology

International audienceA co-integrated Low Noise Amplifier (LNA) with a dipole antenna is designed considering a millimeter-wave dedicated BiCMOS technology. The targeted application is a 94 GHz passive imaging for security applications. The LNA is based on a high-speed SiGe:C 130 nm HBT. The interest of the co-integration on a common silicon substrate is demonstrated through the decrease of insertion losses between the antenna and the amplifier. The capability of the BiCMOS9MW technology is illustrated to achieve this co-integration reaching a total gain of 3.0 dB (Gantenna + GLNA) for a power consumption of 11 mW, in a single-stage LNA configuration. A two-stage configuration achieves a total gain of 8.5 dB with a power consumption of 21 mW