Selective maintenance of Drosophila tandemly arranged duplicated genes during evolution

Genes occurring in conserved, tandemly-arrayed clusters in Drosophila melanogaster are co-expressed to a much higher extent than other duplicated genes

dReDBox: Materializing a full-stack rack-scale system prototype of a next-generation disaggregated datacenter

Current datacenters are based on server machines, whose mainboard and hardware components form the baseline, monolithic building block that the rest of the system software, middleware and application stack are built upon. This leads to the following limitations: (a) resource proportionality of a multi-tray system is bounded by the basic building block (mainboard), (b) resource allocation to processes or virtual machines (VMs) is bounded by the available resources within the boundary of the mainboard, leading to spare resource fragmentation and inefficiencies, and (c) upgrades must be applied to each and every server even when only a specific component needs to be upgraded. The dRedBox project (Disaggregated Recursive Datacentre-in-a-Box) addresses the above limitations, and proposes the next generation, low-power, across form-factor datacenters, departing from the paradigm of the mainboard-as-a-unit and enabling the creation of function-block-as-a-unit. Hardware-level disaggregation and software-defined wiring of resources is supported by a full-fledged Type-1 hypervisor that can execute commodity virtual machines, which communicate over a low-latency and high-throughput software-defined optical network. To evaluate its novel approach, dRedBox will demonstrate application execution in the domains of network functions virtualization, infrastructure analytics, and real-time video surveillance.This work has been supported in part by EU H2020 ICTproject dRedBox, contract #687632.Peer ReviewedPostprint (author's final draft

Design Space Exploration of Accelerators and End-to-End DNN Evaluation with TFLITE-SOC

Recently there has been a rapidly growing demand for faster machine learning (ML) processing in data centers and migration of ML inference applications to edge devices. These developments have prompted both industry and academia to explore custom accelerators to optimize ML executions for performance and power. However, identifying which accelerator is best equipped for performing a particular ML task is challenging, especially given the growing range of ML tasks, the number of target environments, and the limited number of integrated modeling tools. To tackle this issue, it is of paramount importance to provide the computer architecture research community with a common framework capable of performing a comprehensive, uniform, and fair comparison across different accelerator designs targeting a particular ML task. To this aim, we propose a new framework named TFLITESOC (System On Chip) that integrates a lightweight system modeling library (SystemC) for fast design space exploration of custom ML accelerators into the build/execution environment of Tensorflow Lite (TFLite), a highly popular ML framework for ML inference. Using this approach, we are able to model and evaluate new accelerators developed in SystemC by leveraging the language’s hierarchical design capabilities, resulting in faster design prototyping. Furthermore, any accelerator designed using TFLITE-SOC can be benchmarked for inference with any DNN model compatible with TFLite, which enables end-to-end DNN processing and detailed (i.e., per DNN layer) performance analysis. In addition to providing rapid prototyping, integrated benchmarking, and a range of platform configurations, TFLITESOC offers comprehensive performance analysis of accelerator occupancy and execution time breakdown as well as a rich set of modules that can be used by new accelerators to implement scaling up studies and optimized memory transfer protocols. We present our framework and demonstrate its utility by considering the design space of a TPU-like systolic array and describing possible directions for optimization. Using a compression technique, we implement an optimization targeting reducing the memory traffic between DRAM and on-device buffers. Compared to the baseline accelerator, our optimized design shows up to 1.26x speedup on accelerated operations and up to 1.19x speedup on end-to-end DNN execution

dReDBox: A Disaggregated Architectural Perspective for Data Centers

Data centers are currently constructed with fixed blocks (blades); the hard boundaries of this approach lead to suboptimal utilization of resources and increased energy requirements. The dReDBox (disaggregated Recursive Datacenter in a Box) project addresses the problem of fixed resource proportionality in next-generation, low-power data centers by proposing a paradigm shift toward finer resource allocation granularity, where the unit is the function block rather than the mainboard tray. This introduces various challenges at the system design level, requiring elastic hardware architectures, efficient software support and management, and programmable interconnect. Memory and hardware accelerators can be dynamically assigned to processing units to boost application performance, while high-speed, low-latency electrical and optical interconnect is a prerequisite for realizing the concept of data center disaggregation. This chapter presents the dReDBox hardware architecture and discusses design aspects of the software infrastructure for resource allocation and management. Furthermore, initial simulation and evaluation results for accessing remote, disaggregated memory are presented, employing benchmarks from the Splash-3 and the CloudSuite benchmark suites.This work was supported in part by EU H2020 ICT project dRedBox, contract #687632.Peer ReviewedPostprint (author's final draft

Publisher correction: Re-analysis of public genetic data reveals a rare X-chromosomal variant associated with type 2 diabetes (vol 9, 321, 2018)

Correction to: Nature Communications https://doi.org/10.1038/s41467-017-02380-9 , published online 22 January 2018 In the originally published version of this Article, the af fi liation details for Santi González, Jian ’ an Luan and Claudia Langenberg were inadvertently omitted. Santi González should have been af fi liated with 'Barcelona Supercomputing Center (BSC), Joint BSC-CRG-IRB Research Program in Computational Biology, 08034 Barcelona, Spain ’ , and Jian ’ an Luan and Claudia Langenberg should have been af fi liated with ‘ MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK ’ . Furthermore, the abstract contained an error in the SNP ID for the rare variant in chromosome Xq23, which was incorrectly given as rs146662057 and should have been rs146662075. These errors have now been corrected in both the PDF and HTML versions of the Article

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Homicides and suicides by firearm in Marseille: An 8-year review

International audienceThe regions of Provence-Alpes-Côte d'Azur and Corsica in southeast France are regularly affected by firearm deaths, and a large amount of data has been collected by our forensic institute. We carried out a single-center retrospective descriptive study of the records of our institute between January 1, 2011, and 31 December, 2018, relating to firearm deaths (homicides and suicides). There were 302 cases (218 homicides and 84 suicides). The anatomic locations most frequently involved were the thorax, abdomen and head, in that order, in homicides and the head in suicides. More than 80% of the homicides in our series had more than one wound complex and nearly one in four homicides had more than 7. The weapon most frequently used in suicides was a hunting smooth bore gun, followed by the 9mm Luger and then by the .22 Long Rifle. In homicides, the caliber most frequently used was the 7.62 × 39 (29.6%), followed by the 9mm Luger (29%) and lastly by hunting calibers (27%). More than 10% of cases involved two weapons of two different calibers. Our study, which used a dual forensic and ballistic approach, was carried out in one of the most heavily populated regions of metropolitan France. We observed very few similarities with the literature regarding type of caliber and wound complexes. This may be explained, among other factors, by differences in political, societal or cultural contexts

Transmission of force to the hyoid bone during manual strangulation: Simulation using finite element numerical models

Introduction Strangulation is a medicolegal form of mechanical asphyxia, and can be difficult to identify if cutaneous damage to the neck is limited. We began by creating a numerical model of a hyoid bone with adjustable anthropometric parameters and then subjected our model to compression simulating a precision grip on the neck from the front. Materials and methods We selected six bones from the 77 hyoid bones contained in the database we created during a previous study led by our laboratory, in which we demonstrated the sexual dimorphism of this bone and identified the minimal force required for fracture. The anthropometric characteristics of these six bones (angle, length and width) corresponded to those of the 10th, 50th and 90th percentiles from cluster 1 (male individuals) and cluster 2 (female individuals), respectively. After enhancing, developing and meshing the selected 3D models, we analysed and reproduced simulation conditions that were as close as possible to the in vivo conditions of neck strangulation from the front (area of pressure on the bone, tissue environment, and biological variability of this bone). Results We modelled the six numerical hyoid bone models using the finite element method. For all models, the simulation of mechanical pressure applied to simulate anterior strangulation resulted in fractures. The forces required to produce these fractures matched the results obtained in the experimental testing of dissected hyoid bones. Conclusion Six finite element numerical models were created, covering the anthropometric morphological variability of the hyoid bone. These six models enabled numerical simulation of the in vivo behaviour of a hyoid bone subjected to one-handed strangulation