Reactive oxygen species (ROS) have been often viewed as toxic byproducts of mitochondrial function. However, the new pathway that will be described uses low levels of ROS (e.g. superoxide, hydrogen peroxide – H2O2 , etc.) in physiological communications to rapidly (millisecond to seconds) and reversibly and locally modulate function. This is called “X-ROS signaling.”
X-ROS signaling is a novel redox signaling pathway that links mechanical “stress” to changes in [Ca2+]i. X-ROS signaling is activated rapidly and locally within a muscle cell under physiological conditions, but under certain conditions can also contribute to Ca2+-dependent arrhythmia in heart and to the dystrophic phenotype in heart and skeletal muscle 1, 2. Upon physiologic cellular stretch (as is seen with every heartbeat during diastolic filling), microtubules serve as mechano-transducers to activate the trans-membrane enzyme NADPH oxidase 2 (NOX2). NOX2 is found in the plasma membranes of the transverse tubules and external sarcolemmal membranes and, when activated, produces reactive oxygen species (ROS) (hence: X-ROS). We have shown that in heart, the NOX2 derived ROS acts locally to activate ryanodine receptor Ca2+ release channels (RyR2) in the junctional sarcoplasmic reticulum (jSR), increasing the Ca2+ spark rate and “tuning” excitation-contraction coupling. In skeletal muscle, where Ca2+ sparks are not normally observed, the X-ROS signaling process is muted. However in muscular dystrophies, such as Duchenne Muscular Dystrophy and dysferlinopathy, X-ROS signaling is significantly enhanced and contributes to the myopathies. Importantly, in skeletal muscle Ca2+ permeable stretch-activated channels are activated by X-ROS and contribute to the cellular pathology. In brief, X-ROS provides an exciting new mechanism for the mechanical control of redox and Ca2+ signaling in cardiac and skeletal muscle. X-ROS signaling thus underlies both normal Ca2+ signaling in heart and contributes to specific pathologies in both cardiac and skeletal muscle3-5.
1. Prosser BL, Ward CW, Lederer WJ. X-ROS signaling: rapid mechano-chemo transduction in heart. Science. 2011;333:1440-1445
2. Khairallah RJ, Shi G, Sbrana F, Prosser BL, Borroto C, Mazaitis MJ, Hoffman EP, Mahurkar A, Sachs F, Sun Y, Chen YW, Raiteri R, Lederer WJ, Dorsey SG, Ward CW. Microtubules underlie dysfunction in duchenne muscular dystrophy. Sci Signal. 2012;5:ra56
3. Ward CW, Prosser BL, Lederer WJ. Mechanical stretch induced activation of ROS/RNS signaling in striated muscle. Antioxid Redox Signal. 2013
4. Prosser BL, Ward CW, Lederer WJ. X-ROS signalling is enhanced and graded by cyclic cardiomyocyte stretch. Cardiovasc Res. 2013;98:307-314
5. Prosser BL, Khairallah RJ, Ziman AP, Ward CW, Lederer WJ. X-ROS signaling in the heart and skeletal muscle: Stretch-dependent local ROS regulates [Ca2+]i. J Mol Cell Cardiol. 2013;58:172-181]]>
Recent work by the European Research Council (ERC)-funded EUROEVOL research project has established with a high degree of certainty that radiocarbon-inferred human demography during the Neolithic exhibits a boom-and-bust pattern that is probably driven by endogenous population dynamics rather than climate forcing. This finding suggests one of humanity’s major advances in technology—agriculture—failed to buffer against widespread social collapse.
Early warning signals are statistical indices that have proven effective in forecasting critical transitions in global climate systems such as lake eutrophication and grasslands. But such analyses require long time-series data that are not typically available for human societies. The EUROEVOL archaeological radiocarbon database spans over 4,000 years of human history and provides the opportunity to test whether changes in prehistoric human population levels contain the signal of forthcoming collapse.
This talk will introduce our computational methodology for inferring prehistoric population patterns from archaeological radiocarbon date distributions, and explore the implications of our findings by asking, (1) whether the resulting demographic patterns contain the signal of human demographic cycling, and (2) if it is possible to retrodict collapse of European farming using early warning signals. I conclude by discussing how modeling could be used to explore several hypotheses regarding the possible causes of collapse.
In contemplating paths to a sustainable future, it is worth considering the consequences of failure during the transition from foraging to farming in Europe, and successful retrodiction of collapse would be an important contribution to contemporary debates about sustainability.
Human development is an outcome of the interplay between many social, economic, institutional, and environmental factors and forces at multiple levels. Because each place has its unique social and environmental characteristics, place-based studies that examine specific characteristics of places and their variations are important for supporting development policy making in the developing world. Three kinds of scientific analyses can be useful: (i) assessing multiple dimensions of human well-being to understand the current state of development, (ii) analyzing multi-source and multi-level causes of well-being to untangle the complex interactions that shape development, and (iii) exploring future development paths under certain policy interventions. I present a case study in the Poyang Lake Region of China to demonstrate how multiple research methods (i.e., geospatial analysis, social surveys and interviews, and agent-based modeling) can be combined to implement these analyses. Particular attention was paid to local variations and their policy implications.]]>
When Markov chain models of intracellular Ca-regulated Ca channels are coupled via a mathematical representation of a Ca microdomain, simulated release sites exhibit Ca puffs and sparks, i.e., stochastic Ca excitability where the IP3Rs or RyRs open and close in a concerted fashion. Such mathematical models provide insight into the relationship between single-channel kinetics and the statistics of puff/spark duration, and clarify the role of stochastic attrition, Ca inactivation, luminal depletion, and allosteric interactions in the dynamics of puff/spark termination.
The stochastic dynamics of Ca signaling is an important aspect of excitation-contraction coupling in cardiac myocytes, where sarcoplasmic reticulum Ca-induced Ca release is locally controlled by trigger Ca influx via L-type channels of the plasma membrane. A recently developed whole cell modeling approach is able to avoid the computationally demanding task of resolving spatial aspects of global Ca signaling by using probability densities and associated moment equations to representing heterogeneous local Ca signals in a population of Ca release units. This new class of whole cell models of Ca handling facilitates simulation and analysis of the bidirectional coupling of localized calcium elevations and whole cell calcium responses in cardiac myocytes.]]>
Dr. Yuan received her B.S. from Lanzhou University, China and earned her Ph.D. In 2005 from the University of Pennsylvania, where she studied the role of serotonergic regulation in circadian rhythms and sleep with Dr. Amita Sehgal. From 2006 to 2012, Dr. Yuan received her postdoctoral training at University of California, San Francisco in Dr. Lily Jan and YuhNung Jan’s laboratory, where she developed a system to study experience-dependent structural and functional plasticity in Drosophila larval visual circuit. Dr. Yuan joined NINDS as an investigator in 2013. Her laboratory employs Drosophila as a model system to study the cellular and molecular mechanism underlying the regulation of dendrite morphogenesis and developmental plasticity.]]>
Dr. Greig received his B.S. from Chelsea College, University of London, in 1978. He received his Ph.D. in pharmacology from the University of London in 1982. Dr. Greig did his postdoctoral training in the NIA, designing and developing drug candidates for cancer and drug abuse, and investigating technology to augment delivery of neuropeptides and antisense into the brain. He left the NIA in 1989 to help initiate Athena Neurosciences, a biotechnology company in San Francisco, California. Dr. Greig returned to the NIA as a Senior Investigator in 1992 and is currently chief of the Drug Design and Development Section. His laboratory’s research focuses on the conception, design and development of novel therapeutics for treatment of Alzheimer’s disease, other neurodegenerative diseases and type-2 diabetes.]]>
While the perception of basic social stimuli, such as biological motion, has been suggested to be the hallmark of social cognition, there has been little to link such perception to the formation of social and friendship networks. I will discuss new research examining the relationship between neural processing of social cues, interpersonal abilities, and the size and nature of social networks.]]>
The Global Database of Events, Language and Tone (GDELT) is a new dataset of detailed, politically-relevant events from around the world, updated daily and freely available — over 250 million events, from 1979 to yesterday. It offers new opportunities to find spatial and temporal patterns and trends in international events, develop new theories and models, and even build and test forecasts of future events. As the largest dataset of its kind, it also introduces new challenges, and invites the application of tools from other fields and across disciplines.
This presentation will provide an introduction to GDELT and some of the work that has already been done with it. It will touch on the history of event data and on GDELT’s machine-coding approach (and how it compares to human coding); it will describe some of the research that has already utilized GDELT, and the strengths and weaknesses of the data that the research community is discovering. Finally, it will discuss the future of GDELT research, and invite questions and interdisciplinary discussion.]]>
Calcium dynamics in the cardiac myocyte links the electrical excitation of the heart to contraction in a process known as excitation-contraction coupling. Dysfunction of critical calcium signaling proteins in heart is associated with lethal inherited cardiac arrhythmias. However, how the altered proteins lead to arrhythmias remains both unknown and controversial. We have used computational models to investigate fundamental mechanisms that underlie calcium-dependent arrhythmias, the same class of arrhythmias that follow myocardial infarction, heart failure and diverse genetic arrhythmic diseases. Even very common arrhythmias (one episode of sudden cardiac death in a month) are rare when normalized to the events occurring within a single cell over the period of a typical long experiment (e.g. one hour). Stochastic modeling, however, with the powerful computer clusters available and with our recent advances in computational algorithms, enable us to examine stochastic model systems over prolonged periods without missing the rare events. We start with the most elementary event of cardiac calcium release, the calcium spark, and construct stochastic models that explain mechanisms of calcium release termination, calcium homeostasis and the sarcoplasmic reticulum calcium leak, and the generation of arrhythmias from defects in calcium signaling. These insights begin to provide insight in to the normal and abnormal physiology of cardiac excitation-contraction coupling.