X-Device Query Processing by Bitwise Distribution

The diversity of hardware components within a single system calls for strategies for efficient cross-device data processing. For exam- ple, existing approaches to CPU/GPU co-processing distribute individual relational operators to the “most appropriate” device. While pleasantly simple, this strategy has a number of problems: it may leave the “inappropriate” devices idle while overloading the “appropriate” device and putting a high pressure on the PCI bus. To address these issues we distribute data among the devices by par- tially decomposing relations at the granularity of individual bits. Each of the resulting bit-partitions is stored and processed on one of the available devices. Using this strategy, we implemented a processor for spatial range queries that makes efficient use of all available devices. The performance gains achieved indicate that bitwise distribution makes a good cross-device processing strategy

Scalable Generation of Synthetic GPS Traces with Real-life Data Characteristics

Database benchmarking is most valuable if real-life data and workloads are available. However, real-life data (and workloads) are often not publicly available due to IPR constraints or privacy concerns. And even if available, they are often limited regarding scalability and variability of data characteristics. On the oth

Serum IL-33, a new marker predicting response to rituximab in rheumatoid arthritis

Background. Recent works have suggested a possible link between IL-33 and B-cell biology. We aimed to study in different cohorts and with an accurate ELISA assay the possible association between serum IL-33 detection and response to rituximab (RTX) in rheumatoid arthritis (RA) patients. Method. Serum IL-33, rheumatoid factor (RF), anti-citrullinated cyclic peptide antibodies (anti-CCP), high serum IgG level were assessed in 111 RA patients receiving a first course of 2 grams RTX (cohort 1) in an observational study and in 74 RA patients treated with the same schedule in routine care (cohort 2). Uni and multivariate analyzes identified factors associated with a European League Against Rheumatism response at 24 weeks. Results. At week 24, 84/111 (76%) and 54/74 (73%) patients reached EULAR response in the cohorts 1 and 2, respectively. Serum IL-33 was detectable in only 33,5% of the patients. In the combined cohorts, presence of RF or anti-CCP (OR 3.27, 95%CI [1.13-9.46]; p=0.03), high serum IgG (OR 2.32, 95%CI [1.01-5.33]; p=0.048) and detectable serum IL-33 (OR 2.40, 95%CI [1.01-5.72]; p=0.047) were all associated with RTX response in multivariate analysis. Combination of these 3 factors increased the likelihood to response to RTX. When serum IL-33 detection was added to seropositivity and serum IgG level, 100% of the patients with the 3 risk factors (corresponding to 9% of the population) responded to RTX (OR versus patients with none of the 3 risk factors = 29.61; 95% CI [1.30-674.79] p=0.034) Conclusion. Detectable serum IL-33 may predict clinical response to RTX, independently of and synergistically with autoantibodies and serum IgG level

Response to Biologic Drugs in Patients with Rheumatoid Arthritis and Antidrug Antibodies

Importance: There are conflicting data on the association of antidrug antibodies with response to biologic disease-modifying antirheumatic drugs (bDMARDs) in rheumatoid arthritis (RA). Objective: To analyze the association of antidrug antibodies with response to treatment for RA. Design, Setting, and Participants: This cohort study analyzed data from the ABI-RA (Anti-Biopharmaceutical Immunization: Prediction and Analysis of Clinical Relevance to Minimize the Risk of Immunization in Rheumatoid Arthritis Patients) multicentric, open, prospective study of patients with RA from 27 recruiting centers in 4 European countries (France, Italy, the Netherlands, and the UK). Eligible patients were 18 years or older, had RA diagnosis, and were initiating a new bDMARD. Recruitment spanned from March 3, 2014, to June 21, 2016. The study was completed in June 2018, and data were analyzed in June 2022. Exposures: Patients were treated with a new bDMARD: adalimumab, infliximab (grouped as anti-tumor necrosis factor [TNF] monoclonal antibodies [mAbs]), etanercept, tocilizumab, and rituximab according to the choice of the treating physician. Main Outcomes and Measures: The primary outcome was the association of antidrug antibody positivity with EULAR (European Alliance of Associations for Rheumatology; formerly, European League Against Rheumatism) response to treatment at month 12 assessed through univariate logistic regression. The secondary end points were the EULAR response at month 6 and at visits from month 6 to months 15 to 18 using generalized estimating equation models. Detection of antidrug antibody serum levels was performed at months 1, 3, 6, 12, and 15 to 18 using electrochemiluminescence (Meso Scale Discovery) and drug concentration for anti-TNF mAbs, and etanercept in the serum was measured using enzyme-linked immunosorbent assay. Results: Of the 254 patients recruited, 230 (mean [SD] age, 54.3 [13.7] years; 177 females [77.0%]) were analyzed. At month 12, antidrug antibody positivity was 38.2% in patients who were treated with anti-TNF mAbs, 6.1% with etanercept, 50.0% with rituximab, and 20.0% with tocilizumab. There was an inverse association between antidrug antibody positivity (odds ratio [OR], 0.19; 95% CI, 0.09-0.38; P <.001) directed against all biologic drugs and EULAR response at month 12. Analyzing all the visits starting at month 6 using generalized estimating equation models confirmed the inverse association between antidrug antibody positivity and EULAR response (OR, 0.35; 95% CI, 0.18-0.65; P <.001). A similar association was found for tocilizumab alone (OR, 0.18; 95% CI, 0.04-0.83; P =.03). In the multivariable analysis, antidrug antibodies, body mass index, and rheumatoid factor were independently inversely associated with response to treatment. There was a significantly higher drug concentration of anti-TNF mAbs in patients with antidrug antibody-negative vs antidrug antibody-positive status (mean difference, -9.6 [95% CI, -12.4 to -6.9] mg/L; P < 001). Drug concentrations of etanercept (mean difference, 0.70 [95% CI, 0.2-1.2] mg/L; P =.005) and adalimumab (mean difference, 1.8 [95% CI, 0.4-3.2] mg/L; P =.01) were lower in nonresponders vs responders. Methotrexate comedication at baseline was inversely associated with antidrug antibodies (OR, 0.50; 95% CI, 0.25-1.00; P =.05). Conclusions and Relevance: Results of this prospective cohort study suggest an association between antidrug antibodies and nonresponse to bDMARDs in patients with RA. Monitoring antidrug antibodies could be considered in the treatment of these patients, particularly nonresponders to biologic RA drugs

The Candida genome database incorporates multiple Candida species: multispecies search and analysis tools with curated gene and protein information for Candida albicans and Candida glabrata

The Candida Genome Database (CGD, http://www.candidagenome.org/) is an internet-based resource that provides centralized access to genomic sequence data and manually curated functional information about genes and proteins of the fungal pathogen Candida albicans and other Candida species. As the scope of Candida research, and the number of sequenced strains and related species, has grown in recent years, the need for expanded genomic resources has also grown. To answer this need, CGD has expanded beyond storing data solely for C. albicans, now integrating data from multiple species. Herein we describe the incorporation of this multispecies information, which includes curated gene information and the reference sequence for C. glabrata, as well as orthology relationships that interconnect Locus Summary pages, allowing easy navigation between genes of C. albicans and C. glabrata. These orthology relationships are also used to predict GO annotations of their products. We have also added protein information pages that display domains, structural information and physicochemical properties; bibliographic pages highlighting important topic areas in Candida biology; and a laboratory strain lineage page that describes the lineage of commonly used laboratory strains. All of these data are freely available at http://www.candidagenome.org/. We welcome feedback from the research community at [email protected]

Access to the next wave of biologic therapies (Abatacept and Tocilizumab) for the treatment of rheumatoid arthritis in England and Wales: Addressing treatment outside the current NICE guidance

Patients in England and Wales with rheumatoid arthritis (RA) receive treatment from the National Health Service (NHS) with therapies approved by the European Medicines Agency (EMA), under guidance from the National Institute for Health and Clinical Excellence (NICE). This document overviews the current NICE guidelines for the treatment of RA and identifies scenarios when such guidance may not represent the optimum management strategy for individual patients. Specifically, we consider the use of tocilizumab or abatacept as the most appropriate treatments for some patients. In such scenarios, it may be possible for the clinician to secure access to the required therapy through an application procedure known as an ‘individual funding request’, the process of which is described in detail here. At present, it is unclear the extent to which the proposed reform of the NHS will affect the role of NICE in providing guidance and setting standards of care. Until the full impact of the proposed changes are realized, individual funding requests will remain a valuable way of securing the optimal treatment for all patients suffering from RA

Right drug, right patient, right time: aspiration or future promise for biologics in rheumatoid arthritis?

Individualising biologic disease-modifying anti-rheumatic drugs (bDMARDs) to maximise outcomes and deliver safe and cost-effective care is a key goal in the management of rheumatoid arthritis (RA). Investigation to identify predictive tools of bDMARD response is a highly active and prolific area of research. In addition to clinical phenotyping, cellular and molecular characterisation of synovial tissue and blood in patients with RA, using different technologies, can facilitate predictive testing. This narrative review will summarise the literature for the available bDMARD classes and focus on where progress has been made. We will also look ahead and consider the increasing use of ‘omics’ technologies, the potential they hold as well as the challenges, and what is needed in the future to fully realise our ambition of personalised bDMARD treatment

Prediction of Phenotype-Associated Genes via a Cellular Network Approach: A Candida albicans Infection Case Study

Candida albicans is the most prevalent opportunistic fungal pathogen in humans causing superficial and serious systemic infections. The infection process can be divided into three stages: adhesion, invasion, and host cell damage. To enhance our understanding of these C. albicans infection stages, this study aimed to predict phenotype-associated genes involved during these three infection stages and their roles in C. albicans–host interactions. In light of the principles that proteins that lie closer to one another in a protein interaction network are more likely to have similar functions, and that genes regulated by the same transcription factors tend to have similar functions, a cellular network approach was proposed to predict the phenotype-associated genes in this study. A total of 4, 12, and 3 genes were predicted as adhesion-, invasion-, and damage-associated genes during C. albicans infection, respectively. These predicted genes highlight the facts that cell surface components are critical for cell adhesion, and that morphogenesis is crucial for cell invasion. In addition, they provide targets for further investigations into the mechanisms of the three C. albicans infection stages. These results give insights into the responses elicited in C. albicans during interaction with the host, possibly instrumental in identifying novel therapies to treat C. albicans infection