Receptor mechanisms and their role in drug interactions:Effects of anaesthetics on G-protein-activated intracellular signalling pathways

Different types of receptor-mediated mechanism play a key role in cellular transmembrane communication. The majority of plasma membrane receptors mediate the effects of neurotransmitters and hormones through activation of GTP-binding proteins (G-proteins). Coupling of the activated receptor to a G-protein initiates (occasionally inhibits) a cascade of enzyme-catalysed reactions leading to the production of one or more second messengers, eventually leading to the physiological response. The most commonly known cascades are the phosphoinositide and the cAMP route. This paper will describe the key concepts of G-protein-mediated signalling of both cascades and introduce the concept of 'cross-talk'. Further, the effects of anaesthetics on the intracellular components of these signalling pathways will be reviewed.</p

On the dynamic resource availability in grids

Currently deployed grids gather together thousands of computational and storage resources for the benefit of a large community of scientists. However, the large scale, the wide geographical spread, and at times the decision of the rightful resource owners to commit the capacity elsewhere, raises serious resource availability issues. Little is known about the characteristics of the grid resource availability, and of the impact of resource unavailability on the performance of grids. In this work, we make first steps in addressing this twofold lack of information. First, we analyze a long-term availability trace and assess the resource availability characteristics of Grid'5000, an experimental grid environment of over 2,500 processors. The average utilization for the studied trace is increased by almost 5%, when availability is considered. Based on the results of the analysis, we further propose a model for grid resource availability. Our analysis and modeling results show that grid computational resources become unavailable at a high rate, negatively affecting the ability of grids to execute long jobs. Second, through trace-based simulation, we show evidence that resource availability can have a severe impact on the performance of the grid systems. The results of this step show evidence that the performance of a grid system can rise when availability is taken into consideration, and that human administration of availability change information results in 10-15 times more job failures than for an automated monitoring solution, even for a lowly utilized system

Pirates and Samaritans: A Decade of Measurements on Peer Production and their Implications for Net Neutrality and Copyright

This study traces the evolution of commons-based peer production by a measurementbased analysis of case studies and disusses the impact of peer production on net neutrality and copyright law. The measurements include websites such asSuprnova. org, Youtube.com, and Facebook.com, and the Peer-to-Peer (P2P) systems Kazaa, Bittorrent, and Tribler. The measurements show the two sides of peer production, the pirate side with free availability of Hollywood movies on these P2P systems and the samaritan side exhibited by the quick joining of 400,000+ people in a community to organize protests against events in Burma. The telecommunications and content industry are disrupted by this way of peer production. As a consequence, revenues of both industries are likely to suffer in the coming years. On the other hand, innovative P2P systems could win the battle on merit over classical distribution technologies. As a result, a continuation is expected of both legal actions against P2P and possible blocking actions of P2P traffic, violating net neutrality. It is argued that this hinders innovation and causes a large discrepancy between legal and user perspectives. A reform of copyright laws are clearly needed, otherwise they will be unenforceable around 2010. Key words: P2P, collaboration, commons-based peer production, copyright

Inotropic effects of propofol, thiopental, midazolam, etomidate, and ketamine on isolated human atrial muscle

Background: Cardiovascular instability after intravenous induction of anesthesia may be explained partly by direct negative inotropic effects. The direct inotropic influence of etomidate, ketamine, midazolam, propofol, and thiopental on the contractility of isolated human atrial tissue was determined. Effective concentrations were compared with those reported clinically. Methods: Atrial tissue was obtained from 16 patients undergoing coronary bypass surgery. Each fragment was divided into three strips, and one anesthetic was tested per strip in increasing concentrations (10 -6 to 10 - 2 M). Strips were stimulated at 0.5 Hz, and maximum isometric force was measured. Induction agents were studied in two groups, group 1 (n = 7) containing thiopental, midazolam, and propofol, and group 2 (n = 9) consisting of etomidate, ketamine, and propofol. Results: The tested anesthetics caused a concentration-dependent depression of contractility resulting in complete cessation of contractions at the highest concentrations. The IC 50s (mean ± SEM; μM) for inhibition of the contractility were: thiopental 43 ± 7.6, propofol 235 ± 48 (group 1), and 246 ± 42 (group 2), midazolam 145 ± 54, etomidate 133 ± 13, and ketamine 303 ± 54. Conclusions: This is the first study demonstrating a concentration-dependent negative inotropic effect of intravenous anesthetics in isolated human atrial muscle. NO inhibition of myocardial contractility was found in the clinical concentration ranges of propofol, midazolam, and etomidate. In contrast, thiopental showed strong and ketamine showed slight negative inotropic properties. Thus, negative inotropic effects may explain in part the cardiovascular depression on induction of anesthesia with thiopental but not with propofol, midazolam, and etomidate. Improvement of hemodynamics after induction of anesthesia with ketamine cannot be explained by intrinsic cardiac stimulation

Design space exploration for providing QoS within the HARMONY framework

ABSTRACT The HARMONY architectur

How are Real Grids Used? The Analysis of Four Grid Traces and Its Implications

The grid computing vision promises to provide the needed platform for a new and more demanding range of applications. For this promise to become true, a number of hurdles, including the design and deployment of adequate resource management and information services, need to be overcome. In this context, understanding the characteristics of real grid workloads is a crucial step for improving the quality of existing grid services, and in guiding the design of new solutions. Towards this goal, in this work we present the characteristics of traces of four real grid environments, namely LCG, Grid3, and TeraGrid, which are among the largest production grids currently deployed, and the DAS, which is a research grid. We focus our analysis on virtual organizations, on users, and on individual jobs characteristics. We further attempt to quantify the evolution and the performance of the grid systems from which our traces originate. Finally, given the scarcity of the information available for analysis purposes, we discuss the requirements of a new format for grid traces, and we propose the establishment of a virtual center for workload-based grid benchmarking data: the grid workloads archive

Limitations of Quantitative Blush Evaluator (QuBE) as myocardial perfusion assessment method on digital coronary angiograms

Background and Aim: Quantitative Blush Evaluator (QuBE) is a software application that allows quantifying myocardial perfusion in coronary angiograms after a percutaneous coronary intervention. QuBE has some limitations such as the application of a crude filter to remove large scale structures and the absence of correction for cardiac motion. This study investigates the extent of these limitations and we hypothesize that enhanced image analysis methods can provide improvements. Methods: We calculated QuBE scores of 117 patients from the HEBE Trial and determined its association with the Myocardial Blush Grade (MBG) score. Accuracy of large-structure removal is qualitatively assessed for various sizes of a median filter. The influence of cardiac motion was evaluated by comparing the blush curve and QuBE score of the native QuBE with manually motion-corrected QuBE for 40 patients. The effect of different kernel sizes and motion correction to a potential improvement of the association between QuBE score and MBG was studied. Results: In our population, there was no significant association between QuBE score and MBG (p = 0.14). Median filters of various kernel sizes were unable to remove large structure related noise. Variations in filters and cardiac movement correction did not result in an improvement in the association with MBG scores (observer 1: p = 0.66; observer 2: p = 0.72). Conclusions: There was no significant association of QuBE with MBG scores in our population, which suggests that QuBE is not suitable for a quantitative assessment of myocardial perfusion. Alternative kernel sizes for the large structure removal filter and cardiac motion correction did not improve QuBE performance. Relevance for patients: Further improvements of QuBE to overcome its inherent limitations are necessary in order to establish QuBE as a reliable myocardial perfusion assessment method

Comparison of Machine Learning Models Including Preoperative, Intraoperative, and Postoperative Data and Mortality After Cardiac Surgery

Importance: A variety of perioperative risk factors are associated with postoperative mortality risk. However, the relative contribution of routinely collected intraoperative clinical parameters to short-term and long-term mortality remains understudied. Objective: To examine the performance of multiple machine learning models with data from different perioperative periods to predict 30-day, 1-year, and 5-year mortality and investigate factors that contribute to these predictions. Design, Setting, and Participants: In this prognostic study using prospectively collected data, risk prediction models were developed for short-term and long-term mortality after cardiac surgery. Included participants were adult patients undergoing a first-time valve operation, coronary artery bypass grafting, or a combination of both between 1997 and 2017 in a single center, the University Medical Centre Groningen in the Netherlands. Mortality data were obtained in November 2017. Data analysis took place between February 2020 and August 2021. Exposure: Cardiac surgery. Main Outcomes and Measures: Postoperative mortality rates at 30 days, 1 year, and 5 years were the primary outcomes. The area under the receiver operating characteristic curve (AUROC) was used to assess discrimination. The contribution of all preoperative, intraoperative hemodynamic and temperature, and postoperative factors to mortality was investigated using Shapley additive explanations (SHAP) values. Results: Data from 9415 patients who underwent cardiac surgery (median [IQR] age, 68 [60-74] years; 2554 [27.1%] women) were included. Overall mortality rates at 30 days, 1 year, and 5 years were 268 patients (2.8%), 420 patients (4.5%), and 612 patients (6.5%), respectively. Models including preoperative, intraoperative, and postoperative data achieved AUROC values of 0.82 (95% CI, 0.78-0.86), 0.81 (95% CI, 0.77-0.85), and 0.80 (95% CI, 0.75-0.84) for 30-day, 1-year, and 5-year mortality, respectively. Models including only postoperative data performed similarly (30 days: 0.78 [95% CI, 0.73-0.82]; 1 year: 0.79 [95% CI, 0.74-0.83]; 5 years: 0.77 [95% CI, 0.73-0.82]). However, models based on all perioperative data provided less clinically usable predictions, with lower detection rates; for example, postoperative models identified a high-risk group with a 2.8-fold increase in risk for 5-year mortality (4.1 [95% CI, 3.3-5.1]) vs an increase of 11.3 (95% CI, 6.8-18.7) for the high-risk group identified by the full perioperative model. Postoperative markers associated with metabolic dysfunction and decreased kidney function were the main factors contributing to mortality risk. Conclusions and Relevance: This study found that the addition of continuous intraoperative hemodynamic and temperature data to postoperative data was not associated with improved machine learning-based identification of patients at increased risk of short-term and long-term mortality after cardiac operations