Parameter estimation for the distribution of single cell lag times

In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level.We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.     

Comparing Stochastically Restricted Linear Estimators in a Regression Model

Conditions for superiority of the minimum dispersion estimator over another with respect to the covariance matrix are derived when the vector parameter of a regression model is subject to competing stochastic restrictions. The restrictions may also consist both of a deterministic part and a stochastic part.     

Nitrosothiol Formation and Protection against Fenton Chemistry by Nitric Oxide-induced Dinitrosyliron Complex Formation from Anoxia-initiated Cellular Chelatable Iron Increase

Dinitrosyliron complexes (DNIC) have been found in a variety of pathological settings associated with ^•NO. However, the iron source of cellular DNIC is unknown. Previous studies on this question using prolonged ^•NO exposure could be misleading due to the movement of intracellular iron among different sources. We here report that brief ^•NO exposure results in only barely detectable DNIC, but levels increase dramatically after 1–2 h of anoxia. This increase is similar quantitatively and temporally with increases in the chelatable iron, and brief ^•NO treatment prevents detection of this anoxia-induced increased chelatable iron by deferoxamine. DNIC formation is so rapid that it is limited by the availability of ^•NO and chelatable iron. We utilize this ability to selectively manipulate cellular chelatable iron levels and provide evidence for two cellular functions of endogenous DNIC formation, protection against anoxia-induced reactive oxygen chemistry from the Fenton reaction and formation by transnitrosation of protein nitrosothiols (RSNO). The levels of RSNO under these high chelatable iron levels are comparable with DNIC levels and suggest that under these conditions, both DNIC and RSNO are the most abundant cellular adducts of ^•NO.     

Population dynamics of two small pelagic fish in the central-south area off Chile: delayed density-dependence and biological interaction

It is widely believed that environmental variability is the main cause for fluctuations in commercially exploited small pelagic fish populations around the world. Nevertheless, density-dependent factors also can drive population dynamics. In this paper, we analyzed thirteen years of a relative abundance index of two clupeoids fish populations coexisting in the central-south area off Chile, namely the common sardine, Strangomera bentincki, and anchovy, Engraulis ringens. We applied the classical diagnostic tools of time series analysis to the observed time-series. Also, the realized per capita population growth rate was studied with the aim of detecting the feedback structure that is characterizing the population dynamics of the two species. The analysis suggests that population fluctuations of the two species have an important density-dependent component, displaying first-order (direct density-dependent) and second-order (delayed density-dependent) simultaneously. The density-dependent component explained 70.5 and 55.6 % of the realized per capita population growth rate of common sardine and anchovy, respectively. The deterministic skeleton model showed an asymptotic convergence to equilibrium density. In presence of a stochastic environment, fluctuations were reproduced for the species showing a component of fluctuation with a period of 4 year. The intrinsic dynamics of each species is typical of interacting species resulting from trophic interactions. It is postulated that the second-order dynamics of S. bentincki and E. ringens in central-south Chile, may be the result from interactions with a specialist predator (the fishing fleet), interacting with exogenous environmental factors.     

A stochastic model for the membrane potential of a stimulated neuron

We present a simple model describing the transition between the prefiring, firing and postfiring phases of a single neuron in a large neural net. Using typical values for the physiological parameters that enter the model, we find average interspike times that are close to those reported in experimental measurements.     

Convergence to stationary distributions in two-species stochastic competition models

Two sets of sufficient conditions are given for convergence to stationary distributions, for some general models of two species competing in a randomly varying environment. The models are nonlinear stochastic difference equations which define Markov chains. One set of sufficient conditions involves strong continuity and -irreducibility of the transition probability for the chain. The second set has a much weaker irreducibility condition, but is only applicable to monotonic models. The results are applied to a stochastic two-species Ricker model, and to Chesson's lottery model with vacant space, to illustrate how the assumptions can be checked in specific models.     

Stochastic simulation of clonal growth in the tall goldenrod,Solidago altissima

Summary As clonal plants grow they move through space. The movement patterns that result can be complex and difficult to interpret without the aid of models. We developed a stochastic simulation model of clonal growth in the tall goldenrod, Solidago altissima. Our model was calibrated with field data on the clonal expansion of both seedlings and established clones, and model assumptions were verified by statistical analyses.When simulations were based on empirical distributions with long rhizome lengths, there was greater dispersal, less leaf overlap, and less spatial aggregation than when simulations were based on distributions with comparatively short rhizome lengths. For the field data that we utilized, variation in rhizome lengths had a greater effect than variation for either branching angles or rhizome initiation points (see text). We also found that observed patterns of clonal growth in S. altissima did not cause the formation of fairy rings. However, simulations with an artificial distribution of branching angles demonstrate that fairy rings can result solely from a plant's clonal morphology.Stochastic simulation models that incorporated variation in rhizome lengths, branching angles, and rhizome initiation points produced greater dispersal and less leaf overlap than deterministic models. Thus, variation for clonal growth parameters may increase the efficiency of substrate exploration by increasing the area covered and by decreasing the potential for intraclonal competition. We also demonstrated that ramet displacements were slightly, but consistently lower in stochastic simulation models than in random-walk models. This difference was due to the incorporation of details on rhizome bud initiation into stochastic simulation models, but not random-walk models. We discuss the advantages and disadvantages of deterministic, stochastic simulation, and random-walk models of clonal growth.     

1H and15N resonance assignments and secondary structure of the human thioredoxin C62A,C69A,C73A mutant

Summary The complete assignment of¹H and¹⁵N backbone resonances and near-complete¹H side-chain resonance assignments have been obtained for the reduced form of a mutant of human thioredoxin (105 residues) in which the three non-active site cysteines have been substituted by alanines: C62A, C69A, C73A. The assignments were made primarily on the basis of three-dimensional.¹⁵N-separated nuclear Overhauser and Hartmann-Hahn spectroscopy, in conjunction with two-dimensional homonuclear and heteronuclear correlation experiments. Based on comparisons of short-range and interstrand nuclear Overhauser effects, patterns of amide exchange, and chemical-shift differences, the structure appears essentially unchanged from that of the previously determined solution structure of the native protein [Forman-Kay. J.D. et al. (1991)Biochemistry, 30, 2685–2698). An assay for thioredoxin shows that the C62A, C69A, C73A mutant retains activity. The assignment of the spectrum for this mutant of human thioredoxin constitutes the basis for future studies aimed at comparing the details of the active-site conformation in the reduced and oxidized forms of the protein.     

A triple-resonance pulse scheme for selectively correlating amide1HN and15N nuclei with the1Hα proton of the preceding residue

Summary A 3D¹H–¹⁵N–¹³C triple resonance experiment is presented that contains exclusively cross peaks between the¹H^N and¹⁵N nuclei of one residue with the H of the preceding residue. The pulse sequence, designed to minimize the time coherence, is transverse on nuclei with short T₂ values. The experiment consists of coherence transfers via one-bond couplings from the H^N via N, CO, C to the H and back to the H^N for detection; it is called HN(COCA)HA. The experiment was tested on uniformly¹⁵N- and¹³C-enriched T4 lysozyme.