Modeling the effects of a Staphylococcal Enterotoxin B (SEB) on the apoptosis pathway

BACKGROUND: The lack of detailed understanding of the mechanism of action of many biowarfare agents poses an immediate challenge to biodefense efforts. Many potential bioweapons have been shown to affect the cellular pathways controlling apoptosis [1-4]. For example, pathogen-produced exotoxins such as Staphylococcal Enterotoxin B (SEB) and Anthrax Lethal Factor (LF) have been shown to disrupt the Fas-mediated apoptotic pathway [2,4]. To evaluate how these agents affect these pathways it is first necessary to understand the dynamics of a normally functioning apoptosis network. This can then serve as a baseline against which a pathogen perturbed system can be compared. Such comparisons can expose both the proteins most susceptible to alteration by the agent as well as the most critical reaction rates to better instill control on a biological network. RESULTS: We explore this through the modeling and simulation of the Fas-mediated apoptotic pathway under normal and SEB influenced conditions. We stimulated human Jurkat cells with an anti-Fas antibody in the presence and absence of SEB and determined the relative levels of seven proteins involved in the core pathway at five time points following exposure. These levels were used to impute relative rate constants and build a quantitative model consisting of a series of ordinary differential equations (ODEs) that simulate the network under both normal and pathogen-influenced conditions. Experimental results show that cells exposed to SEB exhibit an increase in the rate of executioner caspase expression (and subsequently apoptosis) of 1 hour 43 minutes (± 14 minutes), as compared to cells undergoing normal cell death. CONCLUSION: Our model accurately reflects these results and reveals intervention points that can be altered to restore SEB-influenced system dynamics back to levels within the range of normal conditions

The effect of hepatic stimulatory substance, isolated from regenerating hepatic cytosol, and 50,000 and 300,000 subfractions in enhancing survival in experimental acute hepatic failure in rats treated with D‐galactosamine

Galactosamine induces a dose‐dependent hepatic injury in rats and many other animals. The toxicity of D‐galactosamine appears to be a consequence of the loss of hepatic UTP. It has previously been reported that regenerating liver cytosol is able to prevent, at least in part, the lethal effect of this substance by stimulating hepatic regeneration. Recently, we have separated a fraction using alcohol precipitation (80%) from regenerating liver cytosol and from weanling rat liver cytosol prepared in acetate buffer (100 mM, pH 6.5). We named this fraction hepatic stimulatory substance because of its ability to stimulate DNA synthesis in vivo when injected intraperitoneally in 40% hepatectomized rats and in vitro in the presence of hepatocytes isolated and maintained in monolayer cultures. The stimulatory activity of the hepatic stimulatory substance is fully evident in subfractions of molecular weight up to 300,000 and 50,000 daltons of the crude material obtained using Amicon Ultra membrane filters. The present report describes the ability of hepatic stimulatory substance and its subfractions to stimulate hepatocyte proliferation and the application of these hepatic extracts in successfully reversing the lethality of D‐galactosamine‐induced hepatic necrosis in rats. D‐Galactosamine (2.6 gm per kg of body weight) was administered intraperitoneally to 438 male Lewis strain rats. The animals were divided into six groups according to the type of treatment: Group 1 (n = 131) saline; Group 2 (n = 40) cytosol (75 mg total protein); Group 3 (n = 75) hepatic stimulatory substance (20 mg total protein); Group 4 (n = 42) 300,000 subfraction (4 mg total protein); Group 5 (n = 68) 300,000 subfraction (2 mg total protein), and Group 6 (n = 82) 50,000 subfraction (0.6 mg total protein). All rats received 4 ml of the test solution intraperitoneally at 48 hr after D‐galactosamine administration. The percentage of rats surviving in each group was determined daily for 20 days. Although hepatic stimulatory substance and 50,000 subfraction tended to improve survival in intoxicated rats, only those rats treated with the 300,000 subfraction attained statistical significance with respect to the saline control. Copyright © 1986 American Association for the Study of Liver Disease

Improving Situational Awareness in the Arctic Ocean

To successfully operate in a harsh environment like the Arctic Ocean, one must be able to understand and predict how that environment will evolve over different spatial and temporal scales. This is particularly challenging given the on-going and significant environmental changes that are occurring in the region. Access to the most recent environmental information provides timely knowledge that enables ship-based operations to proceed efficiently, effectively and safely in this difficult arena. Knowledge of the evolving environmental conditions during a field campaign is critical for effective planning, optimal execution of sampling strategies, and to provide a broader context to data collected at specific times and places. We describe the collaborations and processes that enabled an operational system to be developed to provide a remote field-team, located on USCGC Healy in the Beaufort Sea, with near real-time situational awareness information regarding the weather, sea ice conditions, and oceanographic processes. The developed system included the punctual throughput of near real-time products such as satellite imagery, meteorological forecasts, ice charts, model outputs, and up to date locations of key sea ice and ocean-based assets. Science and operational users, as well as onshore personnel, used this system for real-time practical considerations such as ship navigation, and to time scientific operations to ensure the appropriate sea ice and weather conditions prevailed. By presenting the outputs of the system within the context of case studies our results clearly demonstrate the benefits that improved situational awareness brings to ship-based operations in the Arctic Ocean, both today and in the future

Evaluation and improvement of the regulatory inference for large co-expression networks with limited sample size

Abstract Background Co-expression has been widely used to identify novel regulatory relationships using high throughput measurements, such as microarray and RNA-seq data. Evaluation studies on co-expression network analysis methods mostly focus on networks of small or medium size of up to a few hundred nodes. For large networks, simulated expression data usually consist of hundreds or thousands of profiles with different perturbations or knock-outs, which is uncommon in real experiments due to their cost and the amount of work required. Thus, the performances of co-expression network analysis methods on large co-expression networks consisting of a few thousand nodes, with only a small number of profiles with a single perturbation, which more accurately reflect normal experimental conditions, are generally uncharacterized and unknown. Methods We proposed a novel network inference methods based on Relevance Low order Partial Correlation (RLowPC). RLowPC method uses a two-step approach to select on the high-confidence edges first by reducing the search space by only picking the top ranked genes from an intial partial correlation analysis and, then computes the partial correlations in the confined search space by only removing the linear dependencies from the shared neighbours, largely ignoring the genes showing lower association. Results We selected six co-expression-based methods with good performance in evaluation studies from the literature: Partial correlation, PCIT, ARACNE, MRNET, MRNETB and CLR. The evaluation of these methods was carried out on simulated time-series data with various network sizes ranging from 100 to 3000 nodes. Simulation results show low precision and recall for all of the above methods for large networks with a small number of expression profiles. We improved the inference significantly by refinement of the top weighted edges in the pre-inferred partial correlation networks using RLowPC. We found improved performance by partitioning large networks into smaller co-expressed modules when assessing the method performance within these modules. Conclusions The evaluation results show that current methods suffer from low precision and recall for large co-expression networks where only a small number of profiles are available. The proposed RLowPC method effectively reduces the indirect edges predicted as regulatory relationships and increases the precision of top ranked predictions. Partitioning large networks into smaller highly co-expressed modules also helps to improve the performance of network inference methods. The RLowPC R package for network construction, refinement and evaluation is available at GitHub: https://github.com/wyguo/RLowPC

Investigating aggression in children with a history of maltreatment

© 2012 Dr. John DileoExperiences of abuse and neglect are a significant community problem and lead to a range of long term personal and social consequences that place a considerable strain on victims and society. Aggression is a significant problem following child maltreatment, however research into the individual mechanisms underpinning the development of these behaviours is limited. The current study used neurodevelopmental theory to examine why some children develop aggression following early adversity whilst others do not. Measures linked with orbitofrontal-limbic-autonomic pathways were selected for the investigation, namely: stress function (i.e. cardiovascular function), emotion regulation and cognitive function (i.e. IQ, Executive Function, Social Cognition, Smell Deficits). A group of children with a protective care history (n=20) and a community control group (n=30) between the ages of 6 and 12 were compared on these measures. Whilst no between groups differences were found on stress variables (i.e. resting heart rate, HR reactivity, HR variability), the protective care group performed worse on all emotion regulation and cognitive measures. Mediation analysis indicated that whilst some psychological impairments had no impact on aggression following early adversity (i.e. IQ, smell identification), several did (i.e. Executive Function, Social Cognition, Emotion Regulation). Furthermore, the analysis of aggression subtypes found that whilst executive dysfunction and emotion dysregulation mediated reactive aggression, proactive aggression was also mediated by social reasoning biases. These findings offer impetus for further research in larger samples, studies using longitudinal designs and more direct investigation of the implicated neurobiological pathways via neuroimaging. These results also suggest that interventions targeting aggression in maltreated children will be enhanced through a deeper understanding of individual differences, where executive dysfunction and social cognition may be important treatment foci

The Developing Utility of Zebrafish in Modeling Neurobehavioral Disorders

The zebrafish (Danio rerio) is becoming increasingly popular in the field of neurobehavioral research, including experimental, genetic, and pharmacological models of human brain disorders. While zebrafish research is rapidly expanding, its application as a translational neurobehavioral model is still in its relative infancy. Therefore, further investigation of new models is needed for targeting more domains and new, more complex brain disorders. The main aim of this paper is to discuss recent developments in the field of zebrafish neurobehavioral research, and to outline important emerging topics for further studies