15 research outputs found

    RPCValet: NI-Driven Tail-Aware Balancing of µs-Scale RPCs

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    Modern online services come with stringent quality requirements in terms of response time tail latency. Because of their decomposition into fine-grained communicating software layers, a single user request fans out into a plethora of short, μs-scale RPCs, aggravating the need for faster inter-server communication. In reaction to that need, we are witnessing a technological transition characterized by the emergence of hardware-terminated user-level protocols (e.g., InfiniBand/RDMA) and new architectures with fully integrated Network Interfaces (NIs). Such architectures offer a unique opportunity for a new NI-driven approach to balancing RPCs among the cores of manycore server CPUs, yielding major tail latency improvements for μs-scale RPCs. We introduce RPCValet, an NI-driven RPC load-balancing design for architectures with hardware-terminated protocols and integrated NIs, that delivers near-optimal tail latency. RPCValet's RPC dispatch decisions emulate the theoretically optimal single-queue system, without incurring synchronization overheads currently associated with single-queue implementations. Our design improves throughput under tight tail latency goals by up to 1.4x, and reduces tail latency before saturation by up to 4x for RPCs with μs-scale service times, as compared to current systems with hardware support for RPC load distribution. RPCValet performs within 15% of the theoretically optimal single-queue system

    The Case for RackOut: Scalable Data Serving Using Rack-Scale Systems

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    To provide low latency and high throughput guarantees, most large key-value stores keep the data in the memory of many servers. Despite the natural parallelism across lookups, the load imbalance, introduced by heavy skew in the popularity distribution of keys, limits performance. To avoid violating tail latency service-level objectives, systems tend to keep server utilization low and organize the data in micro-shards, which provides units of migration and replication for the purpose of load balancing. These techniques reduce the skew, but incur additional monitoring, data replication and consistency maintenance overheads. In this work, we introduce RackOut, a memory pooling technique that leverages the one-sided remote read primitive of emerging rack-scale systems to mitigate load imbalance while respecting service-level objectives. In RackOut, the data is aggregated at rack-scale granularity, with all of the participating servers in the rack jointly servicing all of the rack’s micro-shards. We develop a queuing model to evaluate the impact of RackOut at the datacenter scale. In addition, we implement a RackOut proof-of-concept key-value store, evaluate it on two experimental platforms based on RDMA and Scale-Out NUMA, and use these results to validate the model. Our results show that RackOut can increase throughput up to 6× for RDMA and 8.6× for Scale-Out NUMA compared to a scale-out deployment, while respecting tight tail latency service-level objectives

    Antibody correlates of protection against Delta infection after vaccination: A nested case-control within the UK-based SIREN study

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    Objectives: To investigate serological correlates of protection against SARS-CoV-2 B.1.617.2 (Delta) infection after two vaccinations.// Methods: We performed a case-control study, where cases were Delta infections after the second vaccine dose and controls were vaccinated, never infected participants, matched by age, gender and region. Sera were tested for anti-SARS-CoV-2 Spike antibody levels (anti-S) and neutralising antibody titres (nAbT), using live virus microneutralisation against Ancestral, Delta and Omicron (BA.1, B.1.1.529). We modelled the decay of anti-S and nAbT for both groups, inferring levels at matched calendar times since the second vaccination. We assessed differences in inferred antibody titres between groups and used conditional logistic regression to explore the relationship between titres and odds of infection.// Results: In total, 130 sequence-confirmed Delta cases and 318 controls were included. Anti-S and Ancestral nAbT decayed similarly between groups, but faster in cases for Delta nAbT (p = 0.02) and Omicron nAbT (p = 0.002). At seven days before infection, controls had higher anti-S levels (p 40 were associated with reduced odds of Delta infection (89%, [69–96%]; p 100 (p = 0.009) and >400 (p = 0.007).// Conclusions: We have identified correlates of protection against SARS-CoV-2 Delta, with potential implications for vaccine deployment, development, and public health response

    Antibody correlates of protection from SARS-CoV-2 reinfection prior to vaccination : a nested case-control within the SIREN study

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    Funding: This study was supported by the U.K. Health Security Agency, the U.K. Department of Health and Social Care (with contributions from the governments in Northern Ireland, Wales, and Scotland), the National Institute for Health Research, and grant from the UK Medical Research Council (grant number MR/W02067X/1). This work was supported by the Francis Crick Institute which receives its core funding from Cancer Research UK (CC2087, CC1283), the UK Medical Research Council (CC2087, CC1283), and the Wellcome Trust (CC2087, CC1283).Objectives To investigate serological differences between SARS-CoV-2 reinfection cases and contemporary controls, to identify antibody correlates of protection against reinfection. Methods We performed a case-control study, comparing reinfection cases with singly infected individuals pre-vaccination, matched by gender, age, region and timing of first infection. Serum samples were tested for anti-SARS-CoV-2 spike (anti-S), anti-SARS-CoV-2 nucleocapsid (anti-N), live virus microneutralisation (LV-N) and pseudovirus microneutralisation (PV-N). Results were analysed using fixed effect linear regression and fitted into conditional logistic regression models. Results We identified 23 cases and 92 controls. First infections occurred before November 2020; reinfections occurred before February 2021, pre-vaccination. Anti-S levels, LV-N and PV-N titres were significantly lower among cases; no difference was found for anti-N levels. Increasing anti-S levels were associated with reduced risk of reinfection (OR 0·63, CI 0·47-0·85), but no association for anti-N levels (OR 0·88, CI 0·73-1·05). Titres >40 were correlated with protection against reinfection for LV-N Wuhan (OR 0·02, CI 0·001–0·31) and LV-N Alpha (OR 0·07, CI 0·009–0·62). For PV-N, titres >100 were associated with protection against Wuhan (OR 0·14, CI 0·03–0·64) and Alpha (0·06, CI 0·008–0·40). Conclusions Before vaccination, protection against SARS-CoV-2 reinfection was directly correlated with anti-S levels, PV-N and LV-N titres, but not with anti-N levels. Detectable LV-N titres were sufficient for protection, whilst PV-N titres >100 were required for a protective effect. Trial registration number ISRCTN11041050Publisher PDFPeer reviewe

    Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

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    Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

    Protection against SARS-CoV-2 after Covid-19 Vaccination and Previous Infection.

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    BACKGROUND: The duration and effectiveness of immunity from infection with and vaccination against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are relevant to pandemic policy interventions, including the timing of vaccine boosters. METHODS: We investigated the duration and effectiveness of immunity in a prospective cohort of asymptomatic health care workers in the United Kingdom who underwent routine polymerase-chain-reaction (PCR) testing. Vaccine effectiveness (≤10 months after the first dose of vaccine) and infection-acquired immunity were assessed by comparing the time to PCR-confirmed infection in vaccinated persons with that in unvaccinated persons, stratified according to previous infection status. We used a Cox regression model with adjustment for previous SARS-CoV-2 infection status, vaccine type and dosing interval, demographic characteristics, and workplace exposure to SARS-CoV-2. RESULTS: Of 35,768 participants, 27% (9488) had a previous SARS-CoV-2 infection. Vaccine coverage was high: 95% of the participants had received two doses (78% had received BNT162b2 vaccine [Pfizer-BioNTech] with a long interval between doses, 9% BNT162b2 vaccine with a short interval between doses, and 8% ChAdOx1 nCoV-19 vaccine [AstraZeneca]). Between December 7, 2020, and September 21, 2021, a total of 2747 primary infections and 210 reinfections were observed. Among previously uninfected participants who received long-interval BNT162b2 vaccine, adjusted vaccine effectiveness decreased from 85% (95% confidence interval [CI], 72 to 92) 14 to 73 days after the second dose to 51% (95% CI, 22 to 69) at a median of 201 days (interquartile range, 197 to 205) after the second dose; this effectiveness did not differ significantly between the long-interval and short-interval BNT162b2 vaccine recipients. At 14 to 73 days after the second dose, adjusted vaccine effectiveness among ChAdOx1 nCoV-19 vaccine recipients was 58% (95% CI, 23 to 77) - considerably lower than that among BNT162b2 vaccine recipients. Infection-acquired immunity waned after 1 year in unvaccinated participants but remained consistently higher than 90% in those who were subsequently vaccinated, even in persons infected more than 18 months previously. CONCLUSIONS: Two doses of BNT162b2 vaccine were associated with high short-term protection against SARS-CoV-2 infection; this protection waned considerably after 6 months. Infection-acquired immunity boosted with vaccination remained high more than 1 year after infection. (Funded by the U.K. Health Security Agency and others; ISRCTN Registry number, ISRCTN11041050.)

    Antibody correlates of protection from SARS-CoV-2 reinfection prior to vaccination: A nested case-control within the SIREN study.

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    Funder: Medical Research CouncilFunder: National Institute for Health Research (NIHR)Funder: Wellcome TrustFunder: UK Health Security AgencyFunder: Cancer Research UKOBJECTIVES: To investigate serological differences between SARS-CoV-2 reinfection cases and contemporary controls, to identify antibody correlates of protection against reinfection. METHODS: We performed a case-control study, comparing reinfection cases with singly infected individuals pre-vaccination, matched by gender, age, region and timing of first infection. Serum samples were tested for anti-SARS-CoV-2 spike (anti-S), anti-SARS-CoV-2 nucleocapsid (anti-N), live virus microneutralisation (LV-N) and pseudovirus microneutralisation (PV-N). Results were analysed using fixed effect linear regression and fitted into conditional logistic regression models. RESULTS: We identified 23 cases and 92 controls. First infections occurred before November 2020; reinfections occurred before February 2021, pre-vaccination. Anti-S levels, LV-N and PV-N titres were significantly lower among cases; no difference was found for anti-N levels. Increasing anti-S levels were associated with reduced risk of reinfection (OR 0·63, CI 0·47-0·85), but no association for anti-N levels (OR 0·88, CI 0·73-1·05). Titres >40 were correlated with protection against reinfection for LV-N Wuhan (OR 0·02, CI 0·001-0·31) and LV-N Alpha (OR 0·07, CI 0·009-0·62). For PV-N, titres >100 were associated with protection against Wuhan (OR 0·14, CI 0·03-0·64) and Alpha (0·06, CI 0·008-0·40). CONCLUSIONS: Before vaccination, protection against SARS-CoV-2 reinfection was directly correlated with anti-S levels, PV-N and LV-N titres, but not with anti-N levels. Detectable LV-N titres were sufficient for protection, whilst PV-N titres >100 were required for a protective effect. TRIAL REGISTRATION NUMBER: ISRCTN11041050
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