Major depression with ischemic heart disease: Effects of paroxetine and nortriptyline on measures of nonlinearity and chaos of heart rate

Depression is associated with increased cardiovascular mortality in patients with preexisting cardiac illness. A decrease in cardiac vagal function as suggested by a decrease in heart rate variability (HRV) or heart period variability has been linked to sudden death in patients with cardiac disease as well as in normal controls. Recent studies have shown decreased vagal function in cardiac patients with depression as well as in depressed patients without cardiac illness. In this study, we compared 20 h awake and sleep heart period nonlinear measures using quantification of nonlinearity and chaos in two groups of patients with major depression and ischemic heart disease (mean age 59-60 years) before and after 6 weeks of treatment with paroxetine or nortriptyline. Patients received paroxetine, 20-30 mg/day or nortriptyline targeted to 190-570 nmol/l for 6 weeks. For HRV analysis, 24 patients were included in the paroxetine treatment study and 20 patients in the nortriptyline study who had at least 20,000 s of awake data. The ages of these groups were 60.4 +/- 10.5 years for paroxetine and 60.8 +/- 13.4 years for nortriptyline. There was a significant decrease in the largest Lyapunov exponent (LLE) after treatment with nortriptyline but not paroxetine. There were also significant decreases in nonlinearity scores on S-netPR and S-netGS after nortriptyline, which may be due to a decrease in cardiac vagal modulation of HRV. S-netGS and awake LLE were the most significant variables that contributed to the discrimination of postparoxetine and postnortriptyline groups even with the inclusion of time and frequency domain measures. These findings suggest that nortriptyline decreases the measures of chaos probably through its stronger vagolytic effects on cardiac autonomic function compared with paroxetine, which is in agreement with previous clinical and preclinical reports. Nortriptyline was also associated with a significant decrease in nonlinearity scores, which may be due to anticholinergic and/or sympatholytic effects. As depression is associated with a strong risk factor for cardiovascular mortality, one should be careful about using any drug that adversely affects cardiac vagal function. Copyright (C) 2002 S. Karger AG, Basel

Cytotoxicity in the Age of Nano: The Role of Fourth Period Transition Metal Oxide Nanoparticle Physicochemical Properties

A clear understanding of physicochemical factors governing nanoparticle toxicity is still in its infancy. We used a systematic approach to delineate physicochemical properties of nanoparticles that govern cytotoxicity. The cytotoxicity of fourth period metal oxide nanoparticles (NPs): TiO2, Cr2O3, Mn2O3, Fe2O3, NiO, CuO, and ZnO increases with the atomic number of the transition metal oxide. This trend was not cell-type specific, as observed in non-transformed human lung cells (BEAS-2B) and human bronchoalveolar carcinoma-derived cells (A549). Addition of NPs to the cell culture medium did not significantly alter pH. Physiochemical properties were assessed to discover the determinants of cytotoxicity: (1) point-of-zero charge (PZC) (i.e., isoelectric point) described the surface charge of NPs in cytosolic and lysosomal compartments; (2) relative number of available binding sites on the NP surface quantified by X-ray photoelectron spectroscopy was used to estimate the probability of biomolecular interactions on the particle surface; (3) band-gap energy measurements to predict electron abstraction from NPs which might lead to oxidative stress and subsequent cell death; and (4) ion dissolution. Our results indicate that cytotoxicity is a function of particle surface charge, the relative number of available surface binding sites, and metal ion dissolution from NPs. These findings provide a physicochemical basis for both risk assessment and the design of safer nanomaterials

Population trapping in a pair of periodically driven Rydberg atoms

We study the population trapping extensively in a periodically driven Rydberg pair. The periodic modulation of the atom-light detuning effectively suppresses the Rabi couplings and, together with Rydberg-Rydberg interactions, leads to the state-dependent population trapping. We identify a simple yet general scheme to determine population trapping regions using driving-induced resonances, the Floquet spectrum, and the inverse participation ratio. Contrary to the single-atom case, we show that the population trapping in the two-atom setup may not necessarily be associated with level crossings in the Floquet spectrum. Further, we discuss under what criteria population trapping can be related to dynamical stabilization, taking specific and experimentally relevant initial states, which include both product and the maximally entangled Bell states. The behavior of the entangled states is further characterized by the bipartite entanglement entropy

Growth landscape formed by perception and import of glucose in yeast

An important challenge in systems biology is to quantitatively describe microbial growth using a few measurable parameters that capture the essence of this complex phenomenon. Two key events at the cell membrane—extracellular glucose sensing and uptake—initiate the budding yeast’s growth on glucose. However, conventional growth models focus almost exclusively on glucose uptake. Here we present results from growth-rate experiments that cannot be explained by focusing on glucose uptake alone. By imposing a glucose uptake rate independent of the sensed extracellular glucose level, we show that despite increasing both the sensed glucose concentration and uptake rate, the cell’s growth rate can decrease or even approach zero. We resolve this puzzle by showing that the interaction between glucose perception and import, not their individual actions, determines the central features of growth, and characterize this interaction using a quantitative model. Disrupting this interaction by knocking out two key glucose sensors significantly changes the cell’s growth rate, yet uptake rates are unchanged. This is due to a decrease in burden that glucose perception places on the cells. Our work shows that glucose perception and import are separate and pivotal modules of yeast growth, the interaction of which can be precisely tuned and measured.National Institutes of Health (U.S.). Pioneer AwardNatural Sciences and Engineering Research Council of Canada (NSERC). Graduate Fellowshi

Intrinsic dynamic behavior of fascin in filopodia

Author Posting. © American Society for Cell Biology, 2007. This article is posted here by permission of American Society for Cell Biology for personal use, not for redistribution. The definitive version was published in Molecular Biology of the Cell 18 (2007): 3928-3940, doi:10.1091/mbc.E07-04-0346.Recent studies showed that the actin cross-linking protein, fascin, undergoes rapid cycling between filopodial filaments. Here, we used an experimental and computational approach to dissect features of fascin exchange and incorporation in filopodia. Using expression of phosphomimetic fascin mutants, we determined that fascin in the phosphorylated state is primarily freely diffusing, whereas actin bundling in filopodia is accomplished by fascin dephosphorylated at serine 39. Fluorescence recovery after photobleaching analysis revealed that fascin rapidly dissociates from filopodial filaments with a kinetic off-rate of 0.12 s–1 and that it undergoes diffusion at moderate rates with a coefficient of 6 µm2s–1. This kinetic off-rate was recapitulated in vitro, indicating that dynamic behavior is intrinsic to the fascin cross-linker. A computational reaction–diffusion model showed that reversible cross-linking is required for the delivery of fascin to growing filopodial tips at sufficient rates. Analysis of fascin bundling indicated that filopodia are semiordered bundles with one bound fascin per 25–60 actin monomers.This work was supported by a National Institutes of Health F31National Research Service Award NS055565-01 (to Y.S.A.), Northwestern University Pulmonary and Critical Care Division T32 (to T.E.S.), and National Institutes of Health grant GM-70898 (to G.G.B.)

Coordination of Membrane and Actin Cytoskeleton Dynamics during Filopodia Protrusion

Leading edge protrusion of migrating cells involves tightly coordinated changes in the plasma membrane and actin cytoskeleton. It remains unclear whether polymerizing actin filaments push and deform the membrane, or membrane deformation occurs independently and is subsequently stabilized by actin filaments. To address this question, we employed an ability of the membrane-binding I-BAR domain of IRSp53 to uncouple the membrane and actin dynamics and to induce filopodia in expressing cells. Using time-lapse imaging and electron microscopy of IRSp53-I-BAR-expressing B16F1 melanoma cells, we demonstrate that cells are not able to protrude or maintain durable long extensions without actin filaments in their interior, but I-BAR-dependent membrane deformation can create a small and transient space at filopodial tips that is subsequently filled with actin filaments. Moreover, the expressed I-BAR domain forms a submembranous coat that may structurally support these transient actin-free protrusions until they are further stabilized by the actin cytoskeleton. Actin filaments in the I-BAR-induced filopodia, in contrast to normal filopodia, do not have a uniform length, are less abundant, poorly bundled, and display erratic dynamics. Such unconventional structural organization and dynamics of actin in I-BAR-induced filopodia suggests that a typical bundle of parallel actin filaments is not necessary for generation and mechanical support of the highly asymmetric filopodial geometry. Together, our data suggest that actin filaments may not directly drive the protrusion, but only stabilize the space generated by the membrane deformation; yet, such stabilization is necessary for efficient protrusion

Automatic Compilation from High-Level Biologically-Oriented Programming Language to Genetic Regulatory Networks

Background The field of synthetic biology promises to revolutionize our ability to engineer biological systems, providing important benefits for a variety of applications. Recent advances in DNA synthesis and automated DNA assembly technologies suggest that it is now possible to construct synthetic systems of significant complexity. However, while a variety of novel genetic devices and small engineered gene networks have been successfully demonstrated, the regulatory complexity of synthetic systems that have been reported recently has somewhat plateaued due to a variety of factors, including the complexity of biology itself and the lag in our ability to design and optimize sophisticated biological circuitry. Methodology/Principal Findings To address the gap between DNA synthesis and circuit design capabilities, we present a platform that enables synthetic biologists to express desired behavior using a convenient high-level biologically-oriented programming language, Proto. The high level specification is compiled, using a regulatory motif based mechanism, to a gene network, optimized, and then converted to a computational simulation for numerical verification. Through several example programs we illustrate the automated process of biological system design with our platform, and show that our compiler optimizations can yield significant reductions in the number of genes () and latency of the optimized engineered gene networks. Conclusions/Significance Our platform provides a convenient and accessible tool for the automated design of sophisticated synthetic biological systems, bridging an important gap between DNA synthesis and circuit design capabilities. Our platform is user-friendly and features biologically relevant compiler optimizations, providing an important foundation for the development of sophisticated biological systems.National Institutes of Health (U.S.) (Grant # 7R01GM74712-5)United States. Defense Advanced Research Projects Agency (contract HR0011-10-C-0168)National Science Foundation (U.S.) (NSF CAREER award 0968682)BBN Technologie