The interplay between discrete noise and nonlinear chemical kinetics in a signal amplification cascade

We used various analytical and numerical techniques to elucidate signal propagation in a small enzymatic cascade which is subjected to external and internal noise. The nonlinear character of catalytic reactions, which underlie protein signal transduction cascades, renders stochastic signaling dynamics in cytosol biochemical networks distinct from the usual description of stochastic dynamics in gene regulatory networks. For a simple 2-step enzymatic cascade which underlies many important protein signaling pathways, we demonstrated that the commonly used techniques such as the linear noise approximation and the Langevin equation become inadequate when the number of proteins becomes too low. Consequently, we developed a new analytical approximation, based on mixing the generating function and distribution function approaches, to the solution of the master equation that describes nonlinear chemical signaling kinetics for this important class of biochemical reactions. Our techniques work in a much wider range of protein number fluctuations than the methods used previously. We found that under certain conditions the burst-phase noise may be injected into the downstream signaling network dynamics, resulting possibly in unusually large macroscopic fluctuations. In addition to computing first and second moments, which is the goal of commonly used analytical techniques, our new approach provides the full time-dependent probability distributions of the colored non-Gaussian processes in a nonlinear signal transduction cascade.Comment: 16 pages, 9 figure

A stochastic spectral analysis of transcriptional regulatory cascades

The past decade has seen great advances in our understanding of the role of noise in gene regulation and the physical limits to signaling in biological networks. Here we introduce the spectral method for computation of the joint probability distribution over all species in a biological network. The spectral method exploits the natural eigenfunctions of the master equation of birth-death processes to solve for the joint distribution of modules within the network, which then inform each other and facilitate calculation of the entire joint distribution. We illustrate the method on a ubiquitous case in nature: linear regulatory cascades. The efficiency of the method makes possible numerical optimization of the input and regulatory parameters, revealing design properties of, e.g., the most informative cascades. We find, for threshold regulation, that a cascade of strong regulations converts a unimodal input to a bimodal output, that multimodal inputs are no more informative than bimodal inputs, and that a chain of up-regulations outperforms a chain of down-regulations. We anticipate that this numerical approach may be useful for modeling noise in a variety of small network topologies in biology

Deficiency of NOX1 or NOX4 Prevents Liver Inflammation and Fibrosis in Mice through Inhibition of Hepatic Stellate Cell Activation.

Reactive oxygen species (ROS) produced by nicotinamide adenine dinucleotide phosphate oxidase (NOX) play a key role in liver injury and fibrosis. Previous studies demonstrated that GKT137831, a dual NOX1/4 inhibitor, attenuated liver fibrosis in mice as well as pro-fibrotic genes in hepatic stellate cells (HSCs) as well as hepatocyte apoptosis. The effect of NOX1 and NOX4 deficiency in liver fibrosis is unclear, and has never been directly compared. HSCs are the primary myofibroblasts in the pathogenesis of liver fibrosis. Therefore, we aimed to determine the role of NOX1 and NOX4 in liver fibrosis, and investigated whether NOX1 and NOX4 signaling mediates liver fibrosis by regulating HSC activation. Mice were treated with carbon tetrachloride (CCl4) to induce liver fibrosis. Deficiency of either NOX1 or NOX4 attenuates liver injury, inflammation, and fibrosis after CCl4 compared to wild-type mice. NOX1 or NOX4 deficiency reduced lipid peroxidation and ROS production in mice with liver fibrosis. NOX1 and NOX4 deficiency are approximately equally effective in preventing liver injury in the mice. The NOX1/4 dual inhibitor GKT137831 suppressed ROS production as well as inflammatory and proliferative genes induced by lipopolysaccharide (LPS), platelet-derived growth factor (PDGF), or sonic hedgehog (Shh) in primary mouse HSCs. Furthermore, the mRNAs of proliferative and pro-fibrotic genes were downregulated in NOX1 and NOX4 knock-out activated HSCs (cultured on plastic for 5 days). Finally, NOX1 and NOX4 protein levels were increased in human livers with cirrhosis compared with normal controls. Thus, NOX1 and NOX4 signaling mediates the pathogenesis of liver fibrosis, including the direct activation of HSC

The Impact of Physician Intervention and Tobacco Control Policies on Average Daily Cigarette Consumption Among Adult Smokers

Physicians' advice to stop smoking has been found to increase smoking cessation rates in controlled clinical trials. However, these finding may not be applicable under real world conditions. This paper investigates the impact of physicians' advice and tobacco control policies on conditional cigarette demand among adults employing non-experimental data. Because the data is non-experimental, the variable reflect physician advice to stop smoking and cigarette consumption are likely to be endogenous. We implement a three stage least squares regression technique designed to take account the joint determination of physician advice and cigarette smoking. The results from these models imply that smokers that received advice from their physician to quit smoking will decrease their average daily consumption by between 5-6 cigarettes per day as compared to smoker who do not receive advice. This result implies that physicians' advice is effective in curtailing smoking in real world settings. Other policies that were found to decrease average smoking by smokers include: the real price of cigarettes and clean indoor air laws.

Explaining Growth in Dutch Agriculture: Prices, Public R&D, and Technological Change

This paper analyzes the sources of growth of Dutch agriculture (arable, meat, and dairy sectors). Because the time series data (1950-1997) are non-stationary and not cointegrated, it is argued that a model estimated in first differences should be used. Estimated price elasticities turn out to be very inelastic, both in the short-run and the long-run. The direct distortionary effect of price support has therefore been rather limited. However, price support has an important indirect effect by improving the sectors investment possibilities and therewith the capital stock. Public R&D expenditure mainly affected agriculture by contributing to yield improvement therewith favoring intensification of production.growth, technology, cointegration, non-stationarity, agricultural policy, Agribusiness, Q18, O13,

Intrinsic flat stability of the positive mass theorem for graphical hypersurfaces of Euclidean space

The rigidity of the Positive Mass Theorem states that the only complete asymptotically flat manifold of nonnegative scalar curvature and zero mass is Euclidean space. We study the stability of this statement for spaces that can be realized as graphical hypersurfaces in Euclidean space. We prove (under certain technical hypotheses) that if a sequence of complete asymptotically flat graphs of nonnegative scalar curvature has mass approaching zero, then the sequence must converge to Euclidean space in the pointed intrinsic flat sense. The appendix includes a new Gromov-Hausdorff and intrinsic flat compactness theorem for sequences of metric spaces with uniform Lipschitz bounds on their metrics.Comment: 31 pages, 2 figures, v2: to appear in Crelle's Journal, many minor changes, one new exampl

Tracking excited states in wave function optimization using density matrices and variational principles

We present a method for finding individual excited states' energy stationary points in complete active space self-consistent field theory that is compatible with standard optimization methods and highly effective at overcoming difficulties due to root flipping and near-degeneracies. Inspired by both the maximum overlap method and recent progress in excited state variational principles, our approach combines these ideas in order to track individual excited states throughout the orbital optimization process. In a series of tests involving root flipping, near-degeneracies, charge transfers, and double excitations, we show that this approach is more effective for state-specific optimization than either the naive selection of roots based on energy ordering or a more direct generalization of the maximum overlap method. Furthermore, we provide evidence that this state-specific approach improves the performance of complete active space perturbation theory. With a simple implementation, a low cost, and compatibility with large active space methods, the approach is designed to be useful in a wide range of excited state investigations.Comment: 13 pages, submitted to JCT