Web-based volunteer distributed computing for handling time-critical urgent workloads

Urgent computing workloads are time critical, unpredictable, and highly dynamic. Whilst efforts are on-going to run these on traditional HPC machines, another option is to leverage the computing power donated by volunteers. Volunteer computing, where members of the public donate some of their CPU time to large scale projects has been popular for many years because it is a powerful way of delivering compute for specific problems, with the public often eager to contribute to a good cause with societal benefits. However, traditional volunteer computing has required user installation of specialist software which is a barrier to entry, and the development of the software itself by the projects, even on-top of existing frameworks, is non-trivial. As such, the number of users donating CPU time to these volunteer computing projects has decreased in recent years, and this comes at a time when the frequency of disasters, often driven by climate change, are rising fast. We believe that an alternative approach, where visitors to websites donate some of their CPU time whilst they are browsing, has the potential to address these issues. However, web-based distributed computing is an immature field and there are numerous questions that must be answered to fully understand the viability of leveraging the large scale parallelism that website visitors represent. In this paper we describe our web-based distributed computing framework, Panther, and perform in-depth performance experiments for two benchmarks using real world hardware and real world browsing habits for the first time. By exploring the performance characteristics of our approach we demonstrate that this is viable for urgent workloads, but there are numerous caveats, not least the most appropriate visitor patterns to a website, that must be considered.Comment: Accepted version of paper presented at 2022 First Combined International Workshop on Interactive Urgent Supercomputing (CIW-IUS

A novel behavioral fish model of nociception for testing analgesics

Pain is a major symptom in many medical conditions, and often interferes significantly with a person's quality of life. Although a priority topic in medical research for many years, there are still few analgesic drugs approved for clinical use. One reason is the lack of appropriate animal models that faithfully represent relevant hallmarks associated with human pain. Here we propose zebrafish (Danio rerio) as a novel short-term behavioral model of nociception, and analyse its sensitivity and robustness. Firstly, we injected two different doses of acetic acid as the noxious stimulus. We studied individual locomotor responses of fish to a threshold level of nociception using two recording systems: a video tracking system and an electric biosensor (the MOBS system). We showed that an injection dose of 10% acetic acid resulted in a change in behavior that could be used to study nociception. Secondly, we validated our behavioral model by investigating the effect of the analgesic morphine. In time-course studies, first we looked at the dose-response relationship of morphine and then tested whether the effect of morphine could be modulated by naloxone, an opioid antagonist. Our results suggest that a change in behavioral responses of zebrafish to acetic acid is a reasonable model to test analgesics. The response scales with stimulus intensity, is attenuated by morphine, and the analgesic effect of morphine is blocked with naloxone. The change in behavior of zebrafish associated with the noxious stimulus can be monitored with an electric biosensor that measures changes in water impedance. © 2011 by the authors; licensee MDPI, Basel, Switzerland

External validation of novel clinical likelihood models to predict obstructive coronary artery disease and prognosis

Objectives The risk factor-weighted and coronary artery calcium score-weighted clinical likelihood (RF-CL and CACS-CL, respectively) models improve discrimination of patients with suspected obstructive coronary artery disease (CAD). However, external validation is warranted. Compared to the 2019 European Society of Cardiology pretest probability (ESC-PTP) model, the aims were (1) to validate the RF-CL and CACS-CL models for identification of obstructive CAD and revascularisation, and (2) to investigate prognosis by CL thresholds. Methods Stable de novo chest pain patients (n=1585) undergoing coronary CT angiography (CTA) were investigated. Obstructive CAD was defined as &gt;70% diameter stenosis in a major epicardial vessel on CTA. Decision of revascularisation within 120 days was based on onsite judgement. The endpoint was non-fatal myocardial infarction or cardiovascular death. The ESC-PTP was calculated based on age, sex and symptom typicality, the RF-CL additionally included number of risk factors, and the CACS-CL incorporated CACS to the RF-CL. Results Obstructive CAD was present in 386/1585 (24.4%) patients, and 91/1585 (5.7%) patients underwent revascularisation. Both the RF-CL and CACS-CL classified more patients to very-low CL (&lt;5%) of obstructive CAD compared with the ESC-PTP model (41.4% and 52.2% vs 19.2%, p&lt;0.001). In very-low CL patients, obstructive CAD and revascularisation prevalences (≤6% and &lt;1%) remained similar combined with low event risk during 5.0 years follow-up. Conclusion In an external validation cohort, the novel RF-CL and CACS-CL models improve categorisation to a very-low CL group with preserved prevalences of obstructive CAD, revascularisation and favourable prognosis.</p

PAR4 (Protease-Activated Receptor 4) Antagonism with BMS-986120 Inhibits Human Ex Vivo Thrombus Formation

Objective-BMS-986120 is a novel first-in-class oral PAR4 (protease-Activated receptor 4) antagonist with potent and selective antiplatelet effects. We sought to determine for the first time, the effect of BMS-986120 on human ex vivo thrombus formation. Approach and Results-Forty healthy volunteers completed a phase 1 parallel-group PROBE trial (Prospective Randomized Open-Label Blinded End Point). Ex vivo platelet activation, platelet aggregation, and thrombus formation were measured at 0, 2, and 24 hours after (1) oral BMS-986120 (60 mg) or (2) oral aspirin (600 mg) followed at 18 hours with oral aspirin (600 mg) and oral clopidogrel (600 mg). BMS-986120 demonstrated highly selective and reversible inhibition of PAR4 agonist peptide (100 μM)-stimulated P-selectin expression, platelet-monocyte aggregates, and platelet aggregation (P<0.001 for all). Compared with pretreatment, total thrombus area (μm2/mm) at high shear was reduced by 29.2% (95% confidence interval, 18.3%-38.7%; P<0.001) at 2 hours and by 21.4% (9.3%-32.0%; P=0.002) at 24 hours. Reductions in thrombus formation were driven by a decrease in platelet-rich thrombus deposition: 34.8% (19.3%-47.3%; P<0.001) at 2 hours and 23.3% (5.1%-38.0%; P=0.016) at 24 hours. In contrast to aspirin alone, or in combination with clopidogrel, BMS-986120 had no effect on thrombus formation at low shear (P=nonsignificant). BMS-986120 administration was not associated with an increase in coagulation times or serious adverse events. Conclusions-BMS-986120 is a highly selective and reversible oral PAR4 antagonist that substantially reduces platelet-rich thrombus formation under conditions of high shear stress. Our results suggest PAR4 antagonism has major potential as a therapeutic antiplatelet strategy. Clinical Trial Registration-URL: http://www.clinicaltrials.gov. Unique identifier: NCT02439190

Implications of lowering threshold of plasma troponin concentration in diagnosis of myocardial infarction: cohort study

Objective To assess the relation between troponin concentration, assay precision, and clinical outcomes in patients with suspected acute coronary syndrome

Evaluation of an Artificial Intelligence Coronary Artery Calcium Scoring Model from Computed Tomography

OBJECTIVES: Coronary artery calcium (CAC) scores derived from computed tomography (CT) scans are used for cardiovascular risk stratification. Artificial intelligence (AI) can assist in CAC quantification and potentially reduce the time required for human analysis. This study aimed to develop and evaluate a fully automated model that identifies and quantifies CAC. METHODS: Fully convolutional neural networks for automated CAC scoring were developed and trained on 2439 cardiac CT scans and validated using 771 scans. The model was tested on an independent set of 1849 cardiac CT scans. Agatston CAC scores were further categorised into five risk categories (0, 1–10, 11–100, 101–400, and > 400). Automated scores were compared to the manual reference standard (level 3 expert readers). RESULTS: Of 1849 scans used for model testing (mean age 55.7 ± 10.5 years, 49% males), the automated model detected the presence of CAC in 867 (47%) scans compared with 815 (44%) by human readers (p = 0.09). CAC scores from the model correlated very strongly with the manual score (Spearman’s r = 0.90, 95% confidence interval [CI] 0.89–0.91, p < 0.001 and intraclass correlation coefficient = 0.98, 95% CI 0.98–0.99, p < 0.001). The model classified 1646 (89%) into the same risk category as human observers. The Bland–Altman analysis demonstrated little difference (1.69, 95% limits of agreement: −41.22, 44.60) and there was almost excellent agreement (Cohen’s κ = 0.90, 95% CI 0.88–0.91, p < 0.001). Model analysis time was 13.1 ± 3.2 s/scan. CONCLUSIONS: This artificial intelligence–based fully automated CAC scoring model shows high accuracy and low analysis times. Its potential to optimise clinical workflow efficiency and patient outcomes requires evaluation. KEY POINTS: • Coronary artery calcium (CAC) scores are traditionally assessed using cardiac computed tomography and require manual input by human operators to identify calcified lesions. • A novel artificial intelligence (AI)–based model for fully automated CAC scoring was developed and tested on an independent dataset of computed tomography scans, showing very high levels of correlation and agreement with manual measurements as a reference standard. • AI has the potential to assist in the identification and quantification of CAC, thereby reducing the time required for human analysis. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00330-022-09028-3

Mobile Health–Supported HIV Self-Testing Strategy Among Urban Refugee and Displaced Youth in Kampala, Uganda: Protocol for a Cluster Randomized Trial (Tushirikiane, Supporting Each Other)

© Carmen Logie, Moses Okumu, Robert Hakiza, Daniel Kibuuka Musoke, Isha Berry, Simon Mwima, Peter Kyambadde, Uwase Mimy Kiera, Miranda Loutet, Stella Neema, Katie Newby, Clara McNamee, Stefan D Baral, Richard Lester, Joshua Musinguzi, Lawrence Mbuagbaw. Originally published in JMIR Research Protocols. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/)Background: HIV is the leading cause of mortality among youth in sub-Saharan Africa. Uganda hosts over 1.43 million refugees, and more than 83,000 live in Kampala, largely in informal settlements. There is limited information about HIV testing uptake and preferences among urban refugee and displaced youth. HIV self-testing is a promising method for increasing testing uptake. Further, mobile health (mHealth) interventions have been effective in increasing HIV testing uptake and could be particularly useful among youth. Objective: This study aims to evaluate the feasibility and effectiveness of two HIV self-testing implementation strategies (HIV self-testing intervention alone and HIV self-testing combined with an mHealth intervention) in comparison with the HIV testing standard of care in terms of HIV testing outcomes among refugee/displaced youth aged 16 to 24 years in Kampala, Uganda. Methods: A three-arm cluster randomized controlled trial will be implemented across five informal settlements grouped into three sites, based on proximity, and randomization will be performed with a 1:1:1 method. Approximately 450 adolescents (150 per cluster) will be enrolled and followed for 12 months. Data will be collected at the following three time points: baseline enrollment, 8 months after enrollment, and 12 months after enrollment. Primary outcomes (HIV testing frequency, HIV status knowledge, linkage to confirmatory testing, and linkage to HIV care) and secondary outcomes (depression, condom use efficacy, consistent condom use, sexual relationship power, HIV stigma, and adolescent sexual and reproductive health stigma) will be evaluated. Results: The study has been conducted in accordance with CONSORT (Consolidated Standards of Reporting Trials) guidelines. The study has received ethical approval from the University of Toronto (June 14, 2019), Mildmay Uganda (November 11, 2019), and the Uganda National Council for Science and Technology (August 3, 2020). The Tushirikiane trial launched in February 2020, recruiting a total of 452 participants. Data collection was paused for 8 months due to COVID-19. Data collection for wave 2 resumed in November 2020, and as of December 10, 2020, a total of 295 participants have been followed-up. The third, and final, wave of data collection will be conducted between February and March 2021. Conclusions: This study will contribute to the knowledge of differentiated HIV testing implementation strategies for urban refugee and displaced youth living in informal settlements. We will share the findings in peer-reviewed manuscripts and conference presentations.Peer reviewe

Methotrexate and relative risk of dementia amongst patients with rheumatoid arthritis:A multi-national multi-database case-control study

Background: Inflammatory processes have been shown to play a role in dementia. To understand this role, we selected two anti-inflammatory drugs (methotrexate and sulfasalazine) to study their association with dementia risk. Methods: A retrospective matched case-control study of patients over 50 with rheumatoid arthritis (486 dementia cases and 641 controls) who were identified from ele

Vascular effects of serelaxin in patients with stable coronary artery disease:A randomized placebo-controlled trial

Aims: The effects of serelaxin, a recombinant form of human relaxin-2 peptide, on vascular function in the coronary microvascular and systemic macrovascular circulation remain largely unknown. This mechanistic, clinical study assessed the effects of serelaxin on myocardial perfusion, aortic stiffness, and safety in patients with stable coronary artery disease (CAD). Methods and results: In this multicentre, double-blind, parallel-group, placebo-controlled study, 58 patients were randomized 1:1 to 48 h intravenous infusion of serelaxin (30 µg/kg/day) or matching placebo. The primary endpoints were change from baseline to 47 h post-initiation of the infusion in global myocardial perfusion reserve (MPR) assessed using adenosine stress perfusion cardiac magnetic resonance imaging, and applanation tonometry-derived augmentation index (AIx). Secondary endpoints were: change from baseline in AIx and pulse wave velocity, assessed at 47 h, Day 30, and Day 180; aortic distensibility at 47 h; pharmacokinetics and safety. Exploratory endpoints were the effect on cardiorenal biomarkers [N-terminal pro-brain natriuretic peptide (NT-proBNP), high-sensitivity troponin T (hsTnT), endothelin-1, and cystatin C]. Of 58 patients, 51 were included in the primary analysis (serelaxin, n = 25; placebo, n = 26). After 2 and 6 h of serelaxin infusion, mean placebo-corrected blood pressure reductions of −9.6 mmHg (P = 0.01) and −13.5 mmHg (P = 0.0003) for systolic blood pressure and −5.2 mmHg (P = 0.02) and −8.4 mmHg (P = 0.001) for diastolic blood pressure occurred. There were no between-group differences from baseline to 47 h in global MPR (−0.24 vs. −0.13, P = 0.44) or AIx (3.49% vs. 0.04%, P = 0.21) with serelaxin compared with placebo. Endothelin-1 and cystatin C levels decreased from baseline in the serelaxin group, and there were no clinically relevant changes observed with serelaxin for NT-proBNP or hsTnT. Similar numbers of serious adverse events were observed in both groups (serelaxin, n = 5; placebo, n = 7) to 180-day follow-up. Conclusion: In patients with stable CAD, 48 h intravenous serelaxin reduced blood pressure but did not alter myocardial perfusion

Inhaled Nanoparticles Accumulate at Sites of Vascular Disease

The development of engineered nanomaterials is growing exponentially, despite concerns over their potential similarities to environmental nanoparticles that are associated with significant cardiorespiratory morbidity and mortality. The mechanisms through which inhalation of nanoparticles could trigger acute cardiovascular events are emerging, but a fundamental unanswered question remains: Do inhaled nanoparticles translocate from the lung in man and directly contribute to the pathogenesis of cardiovascular disease? In complementary clinical and experimental studies, we used gold nanoparticles to evaluate particle translocation, permitting detection by high-resolution inductively coupled mass spectrometry and Raman microscopy. Healthy volunteers were exposed to nanoparticles by acute inhalation, followed by repeated sampling of blood and urine. Gold was detected in the blood and urine within 15 min to 24 h after exposure, and was still present 3 months after exposure. Levels were greater following inhalation of 5 nm (primary diameter) particles compared to 30 nm particles. Studies in mice demonstrated the accumulation in the blood and liver following pulmonary exposure to a broader size range of gold nanoparticles (2-200 nm primary diameter), with translocation markedly greater for particles <10 nm diameter. Gold nanoparticles preferentially accumulated in inflammation-rich vascular lesions of fat-fed apolipoproteinE-deficient mice. Furthermore, following inhalation, gold particles could be detected in surgical specimens of carotid artery disease from patients at risk of stroke. Translocation of inhaled nanoparticles into the systemic circulation and accumulation at sites of vascular inflammation provides a direct mechanism that can explain the link between environmental nanoparticles and cardiovascular disease and has major implications for risk management in the use of engineered nanomaterials