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Guidelines for management of Melody transcatheter pulmonary valve (TPV) infective endocarditis (IE) are lacking. We aimed to identify factors associated with surgical valve removal versus antimicrobial therapy in Melody TPV IE. Multicenter retrospective analysis of all patients receiving Melody TPV from 10/2010 to 3/2019 was performed to identify cases of IE. Surgical explants versus non-surgical cases were compared. Of the 663 Melody TPV implants, there were 66 cases of IE in 59 patients (59/663, 8.8%). 39/66 (59%) were treated with IV antimicrobials and 27/66(41%) underwent valve explantation. 26/59 patients (44%) were treated medically without explantation or recurrence with average follow-up time of 3.5 years (range:1-9). 32% of Streptococcus cases, 53% of MSSA, and all MRSA cases were explanted. 2 of the 4 deaths had MSSA. CART analysis demonstrated two important parameters associated with explantation: a peak echo gradient ≥ 47 mmHg at IE diagnosis(OR 10.6, p  24 mmHg compared to baseline (OR 6.7, p = 0.01). Rates of explantation varied by institution (27 to 64%). In our multicenter experience, 44% of patients with Melody IE were successfully medically treated without valve explantation or recurrence. The degree of valve stenosis at time of IE diagnosis was strongly associated with explantation. Rates of explantation varied significantly among the institutions.

This paper reports on the second "Throughput" phase of the Tracking MachineLearning (TrackML) challenge on the Codalab platform. As in the first"Accuracy" phase, the participants had to solve a difficult experimentalproblem linked to tracking accurately the trajectory of particles as e.g.created at the Large Hadron Collider (LHC): given O($10^5$) points, theparticipants had to connect them into O($10^4$) individual groups thatrepresent the particle trajectories which are approximated helical. While inthe first phase only the accuracy mattered, the goal of this second phase was acompromise between the accuracy and the speed of inference. Both were measuredon the Codalab platform where the participants had to upload their software.The best three participants had solutions with good accuracy and speed an orderof magnitude faster than the state of the art when the challenge was designed.Although the core algorithms were less diverse than in the first phase, adiversity of techniques have been used and are described in this paper. Theperformance of the algorithms are analysed in depth and lessons derived.

This paper reports the results of an experiment in high energy physics: usingthe power of the "crowd" to solve difficult experimental problems linked totracking accurately the trajectory of particles in the Large Hadron Collider(LHC). This experiment took the form of a machine learning challenge organizedin 2018: the Tracking Machine Learning Challenge (TrackML). Its results werediscussed at the competition session at the Neural Information ProcessingSystems conference (NeurIPS 2018). Given 100.000 points, the participants hadto connect them into about 10.000 arcs of circles, following the trajectory ofparticles issued from very high energy proton collisions. The competition wasdifficult with a dozen front-runners well ahead of a pack. The singlecompetition score is shown to be accurate and effective in selecting the bestalgorithms from the domain point of view. The competition has exposed adiversity of approaches, with various roles for Machine Learning, a number ofwhich are discussed in the document

This paper reports the results of an experiment in high energy physics: usingthe power of the "crowd" to solve difficult experimental problems linked totracking accurately the trajectory of particles in the Large Hadron Collider(LHC). This experiment took the form of a machine learning challenge organizedin 2018: the Tracking Machine Learning Challenge (TrackML). Its results werediscussed at the competition session at the Neural Information ProcessingSystems conference (NeurIPS 2018). Given 100.000 points, the participants hadto connect them into about 10.000 arcs of circles, following the trajectory ofparticles issued from very high energy proton collisions. The competition wasdifficult with a dozen front-runners well ahead of a pack. The singlecompetition score is shown to be accurate and effective in selecting the bestalgorithms from the domain point of view. The competition has exposed adiversity of approaches, with various roles for Machine Learning, a number ofwhich are discussed in the document

The success of ground-based, high contrast imaging for the detection of exoplanets in part depends on the ability to differentiate between quasi-static speckles caused by aberrations not corrected by adaptive optics (AO) systems, known as non-common path aberrations (NCPAs), and the planet intensity signal. Frazin (ApJ, 2013) introduced a post-processing algorithm demonstrating that simultaneous millisecond exposures in the science camera and wavefront sensor (WFS) can be used with a statistical inference procedure to determine both the series expanded NCPA coefficients and the planetary signal. We demonstrate, via simulation, that using this algorithm in a closed-loop AO system, real-time estimation and correction of the quasi-static NCPA is possible without separate deformable mirror (DM) probes. Thus the use of this technique allows for the removal of the quasi-static speckles that can be mistaken for planetary signals without the need for new optical hardware, improving the efficiency of ground-based exoplanet detection. In our simulations, we explore the behavior of the Frazin Algorithm (FA) and the dependence of its convergence to an accurate estimate on factors such as Strehl ratio, NCPA strength, and number of algorithm search basis functions. We then apply this knowledge to simulate running the algorithm in real-time in a nearly ideal setting. We then discuss adaptations that can be made to the algorithm to improve its real-time performance, and show their efficacy in simulation. A final simulation tests the technique's resilience against imperfect knowledge of the AO residual phase, motivating an analysis of the feasibility of using this technique in a real closed-loop Extreme AO system such as SCExAO or MagAO-X, in terms of computational complexity and the accuracy of the estimated quasi-static NCPA correction.

High-throughput RNA sequencing (RNA-seq) has recently become the method of choice to define and analyze transcriptomes. For the model moss Physcomitrella patens, although this method has been used to help analyze specific perturbations, no overall reference dataset has yet been established. In the framework of the Gene Atlas project, the Joint Genome Institute selected P. patens as a flagship genome, opening the way to generate the first comprehensive transcriptome dataset for this moss. The first round of sequencing described here is composed of 99 independent libraries spanning 34 different developmental stages and conditions. Upon dataset quality control and processing through read mapping, 28 509 of the 34 361 v3.3 gene models (83%) were detected to be expressed across the samples. Differentially expressed genes (DEGs) were calculated across the dataset to permit perturbation comparisons between conditions. The analysis of the three most distinct and abundant P. patens growth stages - protonema, gametophore and sporophyte - allowed us to define both general transcriptional patterns and stage-specific transcripts. As an example of variation of physico-chemical growth conditions, we detail here the impact of ammonium supplementation under standard growth conditions on the protonemal transcriptome. Finally, the cooperative nature of this project allowed us to analyze inter-laboratory variation, as 13 different laboratories around the world provided samples. We compare differences in the replication of experiments in a single laboratory and between different laboratories.

High-throughput RNA sequencing (RNA-seq) has recently become the method of choice to define and analyze transcriptomes. For the model moss Physcomitrella patens, although this method has been used to help analyze specific perturbations, no overall reference dataset has yet been established. In the framework of the Gene Atlas project, the Joint Genome Institute selected P. patens as a flagship genome, opening the way to generate the first comprehensive transcriptome dataset for this moss. The first round of sequencing described here is composed of 99 independent libraries spanning 34 different developmental stages and conditions. Upon dataset quality control and processing through read mapping, 28 509 of the 34 361 v3.3 gene models (83%) were detected to be expressed across the samples. Differentially expressed genes (DEGs) were calculated across the dataset to permit perturbation comparisons between conditions. The analysis of the three most distinct and abundant P. patens growth stages - protonema, gametophore and sporophyte - allowed us to define both general transcriptional patterns and stage-specific transcripts. As an example of variation of physico-chemical growth conditions, we detail here the impact of ammonium supplementation under standard growth conditions on the protonemal transcriptome. Finally, the cooperative nature of this project allowed us to analyze inter-laboratory variation, as 13 different laboratories around the world provided samples. We compare differences in the replication of experiments in a single laboratory and between different laboratories.

The success of ground-based, high contrast imaging for the detection of exoplanets in part depends on the ability to differentiate between quasi-static speckles caused by aberrations not corrected by adaptive optics (AO) systems, known as non-common path aberrations (NCPAs), and the planet intensity signal. Frazin (ApJ, 2013) introduced a post-processing algorithm demonstrating that simultaneous millisecond exposures in the science camera and wavefront sensor (WFS) can be used with a statistical inference procedure to determine both the series expanded NCPA coefficients and the planetary signal. We demonstrate, via simulation, that using this algorithm in a closed-loop AO system, real-time estimation and correction of the quasi-static NCPA is possible without separate deformable mirror (DM) probes. Thus the use of this technique allows for the removal of the quasi-static speckles that can be mistaken for planetary signals without the need for new optical hardware, improving the efficiency of ground-based exoplanet detection. In our simulations, we explore the behavior of the Frazin Algorithm (FA) and the dependence of its convergence to an accurate estimate on factors such as Strehl ratio, NCPA strength, and number of algorithm search basis functions. We then apply this knowledge to simulate running the algorithm in real-time in a nearly ideal setting. We then discuss adaptations that can be made to the algorithm to improve its real-time performance, and show their efficacy in simulation. A final simulation tests the technique's resilience against imperfect knowledge of the AO residual phase, motivating an analysis of the feasibility of using this technique in a real closed-loop Extreme AO system such as SCExAO or MagAO-X, in terms of computational complexity and the accuracy of the estimated quasi-static NCPA correction.

Cloud computing has become an attractive and easy-To-use solution for users who want to externalize the run of their applications. However, data centers hosting cloud systems consume enormous amounts of energy. Reducing this consumption becomes an urgent challenge with the rapid growth of cloud utilization. In this paper, we explore a way for energy-Aware HPC cloud users to reduce their footprint on cloud infrastructures by reducing the size of the virtual resources they are asking for. We study the influence of green users on the system energy consumption and compare it with the consumption of more aggressive users in terms of resource utilization. We found that larger resources are more energy demanding even if they are faster in executing the applications. But, reducing too much the resources' size is also not beneficial for the energy consumption. A tradeoff lies in between these two options.

Cloud computing has become an attractive and easy-To-use solution for users who want to externalize the run of their applications. However, data centers hosting cloud systems consume enormous amounts of energy. Reducing this consumption becomes an urgent challenge with the rapid growth of cloud utilization. In this paper, we explore a way for energy-Aware HPC cloud users to reduce their footprint on cloud infrastructures by reducing the size of the virtual resources they are asking for. We study the influence of green users on the system energy consumption and compare it with the consumption of more aggressive users in terms of resource utilization. We found that larger resources are more energy demanding even if they are faster in executing the applications. But, reducing too much the resources' size is also not beneficial for the energy consumption. A tradeoff lies in between these two options.

NMDA receptors, which regulate synaptic strength and are implicated in learning and memory, consist of several subtypes with distinct subunit compositions and functional properties. To enable spatiotemporally defined, rapid and reproducible manipulation of function of specific subtypes, we engineered a set of photoswitchable GluN subunits ('LiGluNs'). Photo-agonism of GluN2A or GluN2B elicits an excitatory drive to hippocampal neurons that can be shaped in time to mimic synaptic activation. Photo-agonism of GluN2A at single dendritic spines evokes spine-specific calcium elevation and expansion, the morphological correlate of LTP. Photo-antagonism of GluN2A alone, or in combination with photo-antagonism of GluN1a, reversibly blocks excitatory synaptic currents, prevents the induction of long-term potentiation and prevents spine expansion. In addition, photo-antagonism in vivo disrupts synaptic pruning of developing retino-tectal projections in larval zebrafish. By providing precise and rapidly reversible optical control of NMDA receptor subtypes, LiGluNs should help unravel the contribution of specific NMDA receptors to synaptic transmission, integration and plasticity.

NMDA receptors, which regulate synaptic strength and are implicated in learning and memory, consist of several subtypes with distinct subunit compositions and functional properties. To enable spatiotemporally defined, rapid and reproducible manipulation of function of specific subtypes, we engineered a set of photoswitchable GluN subunits ('LiGluNs'). Photo-agonism of GluN2A or GluN2B elicits an excitatory drive to hippocampal neurons that can be shaped in time to mimic synaptic activation. Photo-agonism of GluN2A at single dendritic spines evokes spine-specific calcium elevation and expansion, the morphological correlate of LTP. Photo-antagonism of GluN2A alone, or in combination with photo-antagonism of GluN1a, reversibly blocks excitatory synaptic currents, prevents the induction of long-term potentiation and prevents spine expansion. In addition, photo-antagonism in vivo disrupts synaptic pruning of developing retino-tectal projections in larval zebrafish. By providing precise and rapidly reversible optical control of NMDA receptor subtypes, LiGluNs should help unravel the contribution of specific NMDA receptors to synaptic transmission, integration and plasticity.

A new coronagraphic instrument for the Large Binocular Telescope (LBT) has successfully passed the conceptual design phase. SHARK-NIR channel will be installed in one arm of the Large Binocular Telescope and it is designed to use different coronagraphic techniques, both to match as much as possible the different requirements of the different science cases and to explore the capabilities of such techniques for the next-generation of ELTs. By exploiting the combination with SHARK-VIS channel mounted at the other LBT arm, the instrument will offer simultaneous coronagraphic observations at different wavelengths, characterized by high contrast, even for relatively faint targets. This will be achievable thanks to the very efficient Adaptive Optics (AO) systems already operating at LBT (First Light AO, FLAO). Furthermore, the latter will be soon upgraded with new detectors, promising even better performance in terms of limiting magnitude. In this paper we present the status of the SHARK-NIR channel design.

The Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) instrument, currently under development for the Subaru Telescope, optimally combines state-of-the-art technologies to study exoplanets and stellar environments at the diffraction limit, both in visible and infrared light (0.6 to 2.4 μm). The instrument already includes an ultra-fast visible pyramid wavefront sensor operating at 3.5 kHz, a 2k-actuator deformable mirror, a set of optimal coronagraphs that can work as close as 1 l/D, a low-order wavefront sensor, a high-speed speckle control loop, and two visible interferometric modules, VAMPIRES and FIRST. After the integration of the integral field spectrograph CHARIS and a Microwave Kinetic Inductance Detector (MKID) in 2016, SCExAO will be one of the most powerful and effective tools for characterizing exoplanets and disks. None of the ELTs include a high-contrast imager and spectrograph among the first generation of instruments. To address this, we propose to upgrade SCExAO and deliver it as a first light visitor instrument to the Thirty Meter Telescope (TMT), a decade before the second generation instruments come online. SCExAO’s flexibility assures that it will include the latest technologies when it arrives on TMT, achieving the ultimate goal of characterizing the first terrestrial planets in the habitable zones of M-type stars.

Cichlid fishes are famous for large, diverse and replicated adaptive radiations in the Great Lakes of East Africa. To understand the molecular mechanisms underlying cichlid phenotypic diversity, we sequenced the genomes and transcriptomes of five lineages of African cichlids: the Nile tilapia (Oreochromis niloticus), an ancestral lineage with low diversity; and four members of the East African lineage: Neolamprologus brichardi/pulcher (older radiation, Lake Tanganyika), Metriaclima zebra (recent radiation, Lake Malawi), Pundamilia nyererei (very recent radiation, Lake Victoria), and Astatotilapia burtoni (riverine species around Lake Tanganyika). We found an excess of gene duplications in the East African lineage compared to tilapia and other teleosts, an abundance of non-coding element divergence, accelerated coding sequence evolution, expression divergence associated with transposable element insertions, and regulation by novel microRNAs. In addition, we analysed sequence data from sixty individuals representing six closely related species from Lake Victoria, and show genome-wide diversifying selection on coding and regulatory variants, some of which were recruited from ancient polymorphisms. We conclude that a number of molecular mechanisms shaped East African cichlid genomes, and that amassing of standing variation during periods of relaxed purifying selection may have been important in facilitating subsequent evolutionary diversification.

Cichlid fishes are famous for large, diverse and replicated adaptive radiations in the Great Lakes of East Africa. To understand the molecular mechanisms underlying cichlid phenotypic diversity, we sequenced the genomes and transcriptomes of five lineages of African cichlids: the Nile tilapia (Oreochromis niloticus), an ancestral lineage with low diversity; and four members of the East African lineage: Neolamprologus brichardi/pulcher (older radiation, Lake Tanganyika), Metriaclima zebra (recent radiation, Lake Malawi), Pundamilia nyererei (very recent radiation, Lake Victoria), and Astatotilapia burtoni (riverine species around Lake Tanganyika). We found an excess of gene duplications in the East African lineage compared to tilapia and other teleosts, an abundance of non-coding element divergence, accelerated coding sequence evolution, expression divergence associated with transposable element insertions, and regulation by novel microRNAs. In addition, we analysed sequence data from sixty individuals representing six closely related species from Lake Victoria, and show genome-wide diversifying selection on coding and regulatory variants, some of which were recruited from ancient polymorphisms. We conclude that a number of molecular mechanisms shaped East African cichlid genomes, and that amassing of standing variation during periods of relaxed purifying selection may have been important in facilitating subsequent evolutionary diversification.

Atrophic age-related macular degeneration (AMD) is associated with the subretinal accumulation of mononuclear phagocytes (MPs). Their role in promoting or inhibiting retinal degeneration is unknown. We here show that atrophic AMD is associated with increas

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