Dynamic Adaptation of Rules for Temporal Event Correlation in Distributed Systems

Event correlation is essential to realizing self-managing distributed systems. For example, distributed systems often require that events be correlated from multiple systems using temporal patterns to detect denial of service attacks and to warn of problems with business critical applications that run on multiple servers. This paper addresses how to specify timer values for temporal patterns so as to manage the trade-off between false alarms and undetected alarms. A central concern is addressing the variability of event propagation delays due to factors such as contention for network and server resources. To this end, we develop an architecture and an adaptive control algorithm that dynamically compensate for variations in propagation delays. Our approach makes Management Stations more autonomic by avoiding the need for manual adjustments of timer values in temporal rules. Further, studies we conducted of a testbed system suggest that our approach produces results that are at least as good as an optimal fixed setting of timer values

Recent advances in biomedical simulations: a manifesto for model engineering [version 1; referees: 3 approved]

Biomedical simulations are widely used to understand disease, engineer cells, and model cellular processes. In this article, we explore how to improve the quality of biomedical simulations by developing simulation models using tools and practices employed in software engineering. We refer to this direction as model engineering. Not all techniques used by software engineers are directly applicable to model engineering, and so some adaptations are required. That said, we believe that simulation models can benefit from software engineering practices for requirements, design, and construction as well as from software engineering tools for version control, error checking, and testing. Here we survey current efforts to improve simulation quality and discuss promising research directions for model engineering

Insulin resistance drives hepatic de novo lipogenesis in nonalcoholic fatty liver disease

BACKGROUNDAn increase in intrahepatic triglyceride (IHTG) is the hallmark feature of nonalcoholic fatty liver disease (NAFLD) and is decreased by weight loss. Hepatic de novo lipogenesis (DNL) contributes to steatosis in individuals with NAFLD. The physiological factors that stimulate hepatic DNL and the effect of weight loss on hepatic DNL are not clear.METHODSHepatic DNL, 24-hour integrated plasma insulin and glucose concentrations, and both liver and whole-body insulin sensitivity were determined in individuals who were lean (n = 14), obese with normal IHTG content (n = 26), or obese with NAFLD (n = 27). Hepatic DNL was assessed using the deuterated water method corrected for the potential confounding contribution of adipose tissue DNL. Liver and whole-body insulin sensitivity was assessed using the hyperinsulinemic-euglycemic clamp procedure in conjunction with glucose tracer infusion. Six subjects in the obese-NAFLD group were also evaluated before and after a diet-induced weight loss of 10%.RESULTSThe contribution of hepatic DNL to IHTG-palmitate was 11%, 19%, and 38% in the lean, obese, and obese-NAFLD groups, respectively. Hepatic DNL was inversely correlated with hepatic and whole-body insulin sensitivity, but directly correlated with 24-hour plasma glucose and insulin concentrations. Weight loss decreased IHTG content, in conjunction with a decrease in hepatic DNL and 24-hour plasma glucose and insulin concentrations.CONCLUSIONSThese data suggest hepatic DNL is an important regulator of IHTG content and that increases in circulating glucose and insulin stimulate hepatic DNL in individuals with NAFLD. Weight loss decreased IHTG content, at least in part, by decreasing hepatic DNL.TRIAL REGISTRATIONClinicalTrials.gov NCT02706262.FUNDINGThis study was supported by NIH grants DK56341 (Nutrition Obesity Research Center), DK20579 (Diabetes Research Center), DK52574 (Digestive Disease Research Center), and RR024992 (Clinical and Translational Science Award), and by grants from the Academy of Nutrition and Dietetics Foundation, the College of Natural Resources of UCB, and the Pershing Square Foundation

Homeostatic proliferation generates long-lived natural killer cells that respond against viral infection

Like memory T cells, natural killer cells that undergo homeostatic expansion in mice self-renew and retain the ability to respond to subsequent viral infection

BioSimulators: a central registry of simulation engines and services for recommending specific tools

Computational models have great potential to accelerate bioscience, bioengineering, and medicine. However, it remains challenging to reproduce and reuse simulations, in part, because the numerous formats and methods for simulating various subsystems and scales remain siloed by different software tools. For example, each tool must be executed through a distinct interface. To help investigators find and use simulation tools, we developed BioSimulators (https://biosimulators.org), a central registry of the capabilities of simulation tools and consistent Python, command-line and containerized interfaces to each version of each tool. The foundation of BioSimulators is standards, such as CellML, SBML, SED-ML and the COMBINE archive format, and validation tools for simulation projects and simulation tools that ensure these standards are used consistently. To help modelers find tools for particular projects, we have also used the registry to develop recommendation services. We anticipate that BioSimulators will help modelers exchange, reproduce, and combine simulations

Transcriptional Profiling in Pathogenic and Non-Pathogenic SIV Infections Reveals Significant Distinctions in Kinetics and Tissue Compartmentalization

Simian immunodeficiency virus (SIV) infection leads to AIDS in experimentally infected macaques, whereas natural reservoir hosts exhibit limited disease and pathology. It is, however, unclear how natural hosts can sustain high viral loads, comparable to those observed in the pathogenic model, without developing severe disease. We performed transcriptional profiling on lymph node, blood, and colon samples from African green monkeys (natural host model) and Asian pigtailed macaques (pathogenic model) to directly compare gene expression patterns during acute pathogenic versus non-pathogenic SIV infection. The majority of gene expression changes that were unique to either model were detected in the lymph nodes at the time of peak viral load. Results suggest a shift toward cellular stress pathways and Th1 profiles during pathogenic infection, with strong and sustained type I and II interferon responses. In contrast, a strong type I interferon response was initially induced during non-pathogenic infection but resolved after peak viral load. The natural host also exhibited controlled Th1 profiles and better preservation of overall cell homeostasis. This study identified gene expression patterns that are specific to disease susceptibility, tissue compartmentalization, and infection duration. These patterns provide a unique view of how host responses differ depending upon lentiviral infection outcome

Productivity, Wages, and Marriage: The Case of Major League Baseball

The effect of marriage on productivity and, consequently, wages has been long debated in economics. A primary explanation for the impact of marriage on wages has been through its impact on productivity, however, there has been no direct evidence for this. In this paper, we aim to fill this gap by directly measuring the impact of marriage on productivity using a sample of professional baseball players from 1871 - 2007. Our results show that only lower ability men see an increase in productivity, though this result is sensitive to the empirical specification and weakly significant. In addition, despite the lack of any effect on productivity, high ability married players earn roughly 16 - 20 percent more than their single counterparts. We discuss possible reasons why employers may favor married men