QUIC on the Highway: Evaluating Performance on High-rate Links

QUIC is a new protocol standardized in 2021 designed to improve on the widely used TCP / TLS stack. The main goal is to speed up web traffic via HTTP, but it is also used in other areas like tunneling. Based on UDP it offers features like reliable in-order delivery, flow and congestion control, streambased multiplexing, and always-on encryption using TLS 1.3. Other than with TCP, QUIC implements all these features in user space, only requiring kernel interaction for UDP. While running in user space provides more flexibility, it profits less from efficiency and optimization within the kernel. Multiple implementations exist, differing in programming language, architecture, and design choices. This paper presents an extension to the QUIC Interop Runner, a framework for testing interoperability of QUIC implementations. Our contribution enables reproducible QUIC benchmarks on dedicated hardware. We provide baseline results on 10G links, including multiple implementations, evaluate how OS features like buffer sizes and NIC offloading impact QUIC performance, and show which data rates can be achieved with QUIC compared to TCP. Our results show that QUIC performance varies widely between client and server implementations from 90 Mbit/s to 4900 Mbit/s. We show that the OS generally sets the default buffer size too small, which should be increased by at least an order of magnitude based on our findings. Furthermore, QUIC benefits less from NIC offloading and AES NI hardware acceleration while both features improve the goodput of TCP to around 8000 Mbit/s. Our framework can be applied to evaluate the effects of future improvements to the protocol or the OS.Comment: Presented at the 2023 IFIP Networking Conference (IFIP Networking

In vitro characterisation of the anti-intravasative properties of the marine product heteronemin

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Where is VALDO? VAscular Lesions Detection and segmentatiOn challenge at MICCAI 2021

Imaging markers of cerebral small vessel disease provide valuable information on brain health, but their manual assessment is time-consuming and hampered by substantial intra- and interrater variability. Automated rating may benefit biomedical research, as well as clinical assessment, but diagnostic reliability of existing algorithms is unknown. Here, we present the results of the VAscular Lesions DetectiOn and Segmentation (Where is VALDO?) challenge that was run as a satellite event at the international conference on Medical Image Computing and Computer Aided Intervention (MICCAI) 2021. This challenge aimed to promote the development of methods for automated detection and segmentation of small and sparse imaging markers of cerebral small vessel disease, namely enlarged perivascular spaces (EPVS) (Task 1), cerebral microbleeds (Task 2) and lacunes of presumed vascular origin (Task 3) while leveraging weak and noisy labels. Overall, 12 teams participated in the challenge proposing solutions for one or more tasks (4 for Task 1-EPVS, 9 for Task 2-Microbleeds and 6 for Task 3-Lacunes). Multi-cohort data was used in both training and evaluation. Results showed a large variability in performance both across teams and across tasks, with promising results notably for Task 1-EPVS and Task 2-Microbleeds and not practically useful results yet for Task 3-Lacunes. It also highlighted the performance inconsistency across cases that may deter use at an individual level, while still proving useful at a population level

Genomic and transcriptomic changes complement each other in the pathogenesis of sporadic Burkitt lymphoma

Burkitt lymphoma (BL) is the most common B-cell lymphoma in children. Within the International Cancer Genome Consortium (ICGC), we performed whole genome and transcriptome sequencing of 39 sporadic BL. Here, we unravel interaction of structural, mutational, and transcriptional changes, which contribute to MYC oncogene dysregulation together with the pathognomonic IG-MYC translocation. Moreover, by mapping IGH translocation breakpoints, we provide evidence that the precursor of at least a subset of BL is a B-cell poised to express IGHA. We describe the landscape of mutations, structural variants, and mutational processes, and identified a series of driver genes in the pathogenesis of BL, which can be targeted by various mechanisms, including IG-non MYC translocations, germline and somatic mutations, fusion transcripts, and alternative splicing

The genomic and transcriptional landscape of primary central nervous system lymphoma

Primary lymphomas of the central nervous system (PCNSL) are mainly diffuse large B-cell lymphomas (DLBCLs) confined to the central nervous system (CNS). Molecular drivers of PCNSL have not been fully elucidated. Here, we profile and compare the whole-genome and transcriptome landscape of 51 CNS lymphomas (CNSL) to 39 follicular lymphoma and 36 DLBCL cases outside the CNS. We find recurrent mutations in JAK-STAT, NFkB, and B-cell receptor signaling pathways, including hallmark mutations in MYD88 L265P (67%) and CD79B (63%), and CDKN2A deletions (83%). PCNSLs exhibit significantly more focal deletions of HLA-D (6p21) locus as a potential mechanism of immune evasion. Mutational signatures correlating with DNA replication and mitosis are significantly enriched in PCNSL. TERT gene expression is significantly higher in PCNSL compared to activated B-cell (ABC)-DLBCL. Transcriptome analysis clearly distinguishes PCNSL and systemic DLBCL into distinct molecular subtypes. Epstein-Barr virus (EBV)+ CNSL cases lack recurrent mutational hotspots apart from IG and HLA-DRB loci. We show that PCNSL can be clearly distinguished from DLBCL, having distinct expression profiles, IG expression and translocation patterns, as well as specific combinations of genetic alterations

ARTEFACTS: How do we want to deal with the future of our one and only planet?

The European Commission’s Science and Knowledge Service, the Joint Research Centre (JRC), decided to try working hand-in-hand with leading European science centres and museums. Behind this decision was the idea that the JRC could better support EU Institutions in engaging with the European public. The fact that European Union policies are firmly based on scientific evidence is a strong message which the JRC is uniquely able to illustrate. Such a collaboration would not only provide a platform to explain the benefits of EU policies to our daily lives but also provide an opportunity for European citizens to engage by taking a more active part in the EU policy making process for the future. A PILOT PROGRAMME To test the idea, the JRC launched an experimental programme to work with science museums: a perfect partner for three compelling reasons. Firstly, they attract a large and growing number of visitors. Leading science museums in Europe have typically 500 000 visitors per year. Furthermore, they are based in large European cities and attract local visitors as well as tourists from across Europe and beyond. The second reason for working with museums is that they have mastered the art of how to communicate key elements of sophisticated arguments across to the public and making complex topics of public interest readily accessible. That is a high-value added skill and a crucial part of the valorisation of public-funded research, never to be underestimated. Finally museums are, at present, undergoing something of a renaissance. Museums today are vibrant environments offering new techniques and technologies to both inform and entertain, and attract visitors of all demographics.JRC.H.2-Knowledge Management Methodologies, Communities and Disseminatio

Multicountry Distribution and Characterization of Extended-spectrum β-Lactamase-associated Gram-negative Bacteria From Bloodstream Infections in Sub-Saharan Africa.

BACKGROUND: Antimicrobial resistance (AMR) is a major global health concern, yet, there are noticeable gaps in AMR surveillance data in regions such as sub-Saharan Africa. We aimed to measure the prevalence of extended-spectrum β-lactamase (ESBL) producing Gram-negative bacteria in bloodstream infections from 12 sentinel sites in sub-Saharan Africa. METHODS: Data were generated during the Typhoid Fever Surveillance in Africa Program (TSAP), in which standardized blood cultures were performed on febrile patients attending 12 health facilities in 9 sub-Saharan African countries between 2010 and 2014. Pathogenic bloodstream isolates were identified at the sites and then subsequently confirmed at a central reference laboratory. Antimicrobial susceptibility testing, detection of ESBL production, and conventional multiplex polymerase chain reaction (PCR) testing for genes encoding for β-lactamase were performed on all pathogens. RESULTS: Five hundred and five pathogenic Gram-negative bloodstream isolates were isolated during the study period and available for further characterization. This included 423 Enterobacteriaceae. Phenotypically, 61 (12.1%) isolates exhibited ESBL activity, and genotypically, 47 (9.3%) yielded a PCR amplicon for at least one of the screened ESBL genes. Among specific Gram-negative isolates, 40 (45.5%) of 88 Klebsiella spp., 7 (5.7%) of 122 Escherichia coli, 6 (16.2%) of 37 Acinetobacter spp., and 2 (1.3%) of 159 of nontyphoidal Salmonella (NTS) showed phenotypic ESBL activity. CONCLUSIONS: Our findings confirm the presence of ESBL production among pathogens causing bloodstream infections in sub-Saharan Africa. With few alternatives for managing ESBL-producing pathogens in the African setting, measures to control the development and proliferation of AMR organisms are urgently needed

Incidence of invasive salmonella disease in sub-Saharan Africa: a multicentre population-based surveillance study.

BACKGROUND: Available incidence data for invasive salmonella disease in sub-Saharan Africa are scarce. Standardised, multicountry data are required to better understand the nature and burden of disease in Africa. We aimed to measure the adjusted incidence estimates of typhoid fever and invasive non-typhoidal salmonella (iNTS) disease in sub-Saharan Africa, and the antimicrobial susceptibility profiles of the causative agents. METHODS: We established a systematic, standardised surveillance of blood culture-based febrile illness in 13 African sentinel sites with previous reports of typhoid fever: Burkina Faso (two sites), Ethiopia, Ghana, Guinea-Bissau, Kenya, Madagascar (two sites), Senegal, South Africa, Sudan, and Tanzania (two sites). We used census data and health-care records to define study catchment areas and populations. Eligible participants were either inpatients or outpatients who resided within the catchment area and presented with tympanic (≥38·0°C) or axillary temperature (≥37·5°C). Inpatients with a reported history of fever for 72 h or longer were excluded. We also implemented a health-care utilisation survey in a sample of households randomly selected from each study area to investigate health-seeking behaviour in cases of self-reported fever lasting less than 3 days. Typhoid fever and iNTS disease incidences were corrected for health-care-seeking behaviour and recruitment. FINDINGS: Between March 1, 2010, and Jan 31, 2014, 135 Salmonella enterica serotype Typhi (S Typhi) and 94 iNTS isolates were cultured from the blood of 13 431 febrile patients. Salmonella spp accounted for 33% or more of all bacterial pathogens at nine sites. The adjusted incidence rate (AIR) of S Typhi per 100 000 person-years of observation ranged from 0 (95% CI 0-0) in Sudan to 383 (274-535) at one site in Burkina Faso; the AIR of iNTS ranged from 0 in Sudan, Ethiopia, Madagascar (Isotry site), and South Africa to 237 (178-316) at the second site in Burkina Faso. The AIR of iNTS and typhoid fever in individuals younger than 15 years old was typically higher than in those aged 15 years or older. Multidrug-resistant S Typhi was isolated in Ghana, Kenya, and Tanzania (both sites combined), and multidrug-resistant iNTS was isolated in Burkina Faso (both sites combined), Ghana, Kenya, and Guinea-Bissau. INTERPRETATION: Typhoid fever and iNTS disease are major causes of invasive bacterial febrile illness in the sampled locations, most commonly affecting children in both low and high population density settings. The development of iNTS vaccines and the introduction of S Typhi conjugate vaccines should be considered for high-incidence settings, such as those identified in this study. FUNDING: Bill & Melinda Gates Foundation

Study of the rare B-s(0) and B-0 decays into the pi(+) pi(-) mu(+) mu(-) final state

A search for the rare decays $B_s^0 \to \pi^+\pi^-\mu^+\mu^-$ and $B^0 \to \pi^+\pi^-\mu^+\mu^-$ is performed in a data set corresponding to an integrated luminosity of 3.0 fb$^{-1}$ collected by the LHCb detector in proton-proton collisions at centre-of-mass energies of 7 and 8 TeV. Decay candidates with pion pairs that have invariant mass in the range 0.5-1.3 GeV/$c^2$ and with muon pairs that do not originate from a resonance are considered. The first observation of the decay $B_s^0 \to \pi^+\pi^-\mu^+\mu^-$ and the first evidence of the decay $B^0 \to \pi^+\pi^-\mu^+\mu^-$ are obtained and the branching fractions are measured to be $\mathcal{B}(B_s^0 \to \pi^+\pi^-\mu^+\mu^-)=(8.6\pm 1.5\,({\rm stat}) \pm 0.7\,({\rm syst})\pm 0.7\,({\rm norm}))\times 10^{-8}$ and $\mathcal{B}(B^0 \to \pi^+\pi^-\mu^+\mu^-)=(2.11\pm 0.51\,({\rm stat}) \pm 0.15\,({\rm syst})\pm 0.16\,({\rm norm}) )\times 10^{-8}$, where the third uncertainty is due to the branching fraction of the decay $B^0\to J/\psi(\to \mu^+\mu^-)K^*(890)^0(\to K^+\pi^-)$, used as a normalisation.A search for the rare decays Bs0→π+π−μ+μ− and B0→π+π−μ+μ− is performed in a data set corresponding to an integrated luminosity of 3.0 fb−1 collected by the LHCb detector in proton–proton collisions at centre-of-mass energies of 7 and 8 TeV . Decay candidates with pion pairs that have invariant mass in the range 0.5–1.3 GeV/c2 and with muon pairs that do not originate from a resonance are considered. The first observation of the decay Bs0→π+π−μ+μ− and the first evidence of the decay B0→π+π−μ+μ− are obtained and the branching fractions, restricted to the dipion-mass range considered, are measured to be B(Bs0→π+π−μ+μ−)=(8.6±1.5 (stat)±0.7 (syst)±0.7(norm))×10−8 and B(B0→π+π−μ+μ−)=(2.11±0.51(stat)±0.15(syst)±0.16(norm))×10−8 , where the third uncertainty is due to the branching fraction of the decay B0→J/ψ(→μ+μ−)K⁎(892)0(→K+π−) , used as a normalisation.A search for the rare decays Bs0→π+π−μ+μ− and B0→π+π−μ+μ− is performed in a data set corresponding to an integrated luminosity of 3.0 fb−1 collected by the LHCb detector in proton–proton collisions at centre-of-mass energies of 7 and 8 TeV . Decay candidates with pion pairs that have invariant mass in the range 0.5–1.3 GeV/c2 and with muon pairs that do not originate from a resonance are considered. The first observation of the decay Bs0→π+π−μ+μ− and the first evidence of the decay B0→π+π−μ+μ− are obtained and the branching fractions, restricted to the dipion-mass range considered, are measured to be B(Bs0→π+π−μ+μ−)=(8.6±1.5 (stat)±0.7 (syst)±0.7(norm))×10−8 and B(B0→π+π−μ+μ−)=(2.11±0.51(stat)±0.15(syst)±0.16(norm))×10−8 , where the third uncertainty is due to the branching fraction of the decay B0→J/ψ(→μ+μ−)K⁎(892)0(→K+π−) , used as a normalisation.A search for the rare decays $B_s^0 \to \pi^+\pi^-\mu^+\mu^-$ and $B^0 \to \pi^+\pi^-\mu^+\mu^-$ is performed in a data set corresponding to an integrated luminosity of 3.0 fb$^{-1}$ collected by the LHCb detector in proton-proton collisions at centre-of-mass energies of 7 and 8 TeV. Decay candidates with pion pairs that have invariant mass in the range 0.5-1.3 GeV/$c^2$ and with muon pairs that do not originate from a resonance are considered. The first observation of the decay $B_s^0 \to \pi^+\pi^-\mu^+\mu^-$ and the first evidence of the decay $B^0 \to \pi^+\pi^-\mu^+\mu^-$ are obtained and the branching fractions, restricted to the dipion-mass range considered, are measured to be $\mathcal{B}(B_s^0 \to \pi^+\pi^-\mu^+\mu^-)=(8.6\pm 1.5\,({\rm stat}) \pm 0.7\,({\rm syst})\pm 0.7\,({\rm norm}))\times 10^{-8}$ and $\mathcal{B}(B^0 \to \pi^+\pi^-\mu^+\mu^-)=(2.11\pm 0.51\,({\rm stat}) \pm 0.15\,({\rm syst})\pm 0.16\,({\rm norm}) )\times 10^{-8}$, where the third uncertainty is due to the branching fraction of the decay $B^0\to J/\psi(\to \mu^+\mu^-)K^*(890)^0(\to K^+\pi^-)$, used as a normalisation