The effect of past changes in inter‐annual temperature variability on tree distribution limits

Aim The northern limits of temperate broadleaved species in Fennoscanndia are controlled by their requirements for summer warmth for successful regeneration and growth as well as by the detrimental effects of winter cold on plant tissue. However, occurrences of meteorological conditions with detrimental effects on individual species are rare events rather than a reflection of average conditions. We explore the effect of changes in inter‐annual temperature variability on the abundances of the tree species Tilia cordata, Quercus robur and Ulmus glabra near their distribution limits using a process‐based model of ecosystem dynamics. Location A site in central Sweden and a site in southern Finland were used as examples for the ecotone between boreal and temperate forests in Fennoscandia. The Finnish site was selected because of the availability of varve‐thickness data. Methods The dynamic vegetation model LPJ‐GUESS was run with four scenarios of inter‐annual temperature forcing for the last 10,000 years. In one scenario the variability in the thickness of summer and winter varves from the annually laminated lake in Finland was used as a proxy for past inter‐annual temperature variability. Two scenarios were devised to explore systematically the effect of stepwise changes in the variance and shape parameter of a probability distribution. All variability scenarios were run both with and without the long‐term trend in Holocene temperature change predicted by an atmospheric general circulation model. Results Directional changes in inter‐annual temperature variability have significant effects on simulated tree distribution limits through time. Variations in inter‐annual temperature variability alone are shown to alter vegetation composition by magnitudes similar to the magnitude of changes driven by variation in mean temperatures. Main conclusions The varve data indicate that inter‐annual climate variability has changed in the past. The model results show that past changes in species abundance can be explained by changes in the inter‐annual variability of climate parameters as well as by mean climate. Because inter‐annual climatic variability is predicted to change in the future, this component of climate change should be taken into account both when making projections of future plant distributions and when interpreting vegetation history.     

Score Tests for Exploring Complex Models: Application to HIV Dynamics Models

In biostatistics, more and more complex models are being developed. This is particularly the case in system biology. Fitting complex models can be very time‐consuming, since many models often have to be explored. Among the possibilities are the introduction of explanatory variables and the determination of random effects. The particularity of this use of the score test is that the null hypothesis is not itself very simple; typically, some random effects may be present under the null hypothesis. Moreover, the information matrix cannot be computed, but only an approximation based on the score. This article examines this situation with the specific example of HIV dynamics models. We examine the score test statistics for testing the effect of explanatory variables and the variance of random effect in this complex situation. We study type I errors and the statistical powers of this score test statistics and we apply the score test approach to a real data set of HIV‐infected patients.     

An Efficient Timer and Sizer of Biomacromolecular Motions

1. Download : Download high-res image (92KB)
2. Download : Download full-size image

     

Determination of the maximum specific uptake capacities for glucose and oxygen in glucose-limited fed-batch cultivations of Escherichia coli

A simple pulse-based method for the determination of the maximum uptake capacities for glucose and oxygen in glucose limited cultivations of E. coli is presented. The method does not depend on the time-consuming analysis of glucose or acetate, and therefore can be used to control the feed rate in glucose limited cultivations, such as fed-batch processes. The application of this method in fed-batch processes of E. coli showed that the uptake capacity for neither glucose nor oxygen is a constant parameter, as often is assumed in fed-batch models. The glucose uptake capacity decreased significantly when the specific growth rate decreased below 0.15 h(-1) and fell to about 0.6 mmol g(-1) h(-1) (mmol per g cell dry weight and hour) at the end of fed-batch fermentations, where specific growth rate was approximately 0.02 h(-1). The oxygen uptake capacity started to decrease somewhat earlier when specific growth rate declined below 0.25 h(-1) and was 5 mmol g(-1) h(-1) at the end of the fermentations. The behavior of both uptake systems is integrated in a dynamic model which allows a better fitting of experimental values for glucose in fed-batch processes in comparison to generally used unstructured kinetic models.     

Kinetic resolution of chiral amines with omega-transaminase using an enzyme-membrane reactor

A kinetic resolution process for the production of chiral amines was developed using an enzyme-membrane reactor (EMR) and a hollow-fiber membrane contactor with (S)-specific omega-transaminases (omega-TA) from Vibrio fluvialis JS17 and Bacillus thuringiensis JS64. The substrate solution containing racemic amine and pyruvate was recirculated through the EMR and inhibitory ketone product was selectively extracted by the membrane contactor until enantiomeric excess of (R)-amine exceeded 95%. Using the reactor set-up with flat membrane reactor (10-mL working volume), kinetic resolutions of alpha-methylbenzylamine (alpha-MBA) and 1-aminotetralin (200 mM, 50 mL) were carried out. During the operation, concentration of ketone product, i.e., acetophenone or alpha-tetralone, in a substrate reservoir was maintained below 0.1 mM, suggesting efficient removal of the inhibitory ketone by the membrane contactor. After 47 and 32.5 h of operation using 5 U/mL of enzyme, 98.0 and 95.5% ee of (R)-alpha-MBA and (R)-1-aminotetralin were obtained at 49.5 and 48.8% of conversion, respectively. A hollow-fiber membrane reactor (39-mL working volume) was used for a preparative-scale kinetic resolution of 1-aminotetralin (200 mM, 1 L). After 133 h of operation, enantiomeric excess reached 95.6% and 14.3 g of (R)-1-aminotetralin was recovered (97.4% of yield). Mathematical modeling of the EMR process including the membrane contactor was performed to evaluate the effect of residence time. The simulation results suggest that residence time should be short to maintain the concentration of the ketone product in EMR sufficiently low so as to decrease conversion per cycle and, in turn, reduce the inhibition of the omega-TA activity.     

An experimental and theoretical study of the inhibition of Escherichia coli lac operon gene expression by antigene oligonucleotides

Previously, we have developed a genetically structured mathematical model to describe the inhibition of Escherichia coli lac operon gene expression by antigene oligos. Our model predicted that antigene oligos targeted to the operator region of the lac operon would have a significant inhibitory effect on beta-galactosidase production. In this investigation, the E. coli lac operon gene expression in the presence of antigene oligos was studied experimentally. A 21-mer oligo, which was designed to form a triplex with the operator, was found to be able to specifically inhibit beta-galactosidase production in a dose-dependent manner. In contrast to the 21-mer triplex-forming oligonucleotide (TFO), several control oligos showed no inhibitory effect. The ineffectiveness of the various control oligos, along with the fact that the 21-mer oligo has no homology sequence with lacZYA, and no mRNA is transcribed from the operator, suggests that the 21-mer oligo inhibits target gene expression by an antigene mechanism. To simulate the kinetics of lac operon gene expression in the presence of antigene oligos, a genetically structured kinetic model, which includes transport of oligo into the cell, growth of bacteria cells, and lac operon gene expression, was developed. Predictions of the kinetic model fit the experimental data quite well after adjustment of the value of the oligonucleotide transport rate constant (9.0 x 10(-)(3) min(-)(1)) and oligo binding affinity constant (1.05 x 10(6) M(-)(1)). Our values for these two adjusted parameters are in the range of reported literature values.     

Mirrored Genome Size Distributions in Monocot and Dicot Plants

The variation in genome size and basic chromosome number was analyzed in the wide range of angiosperm plants. A divergence of monocots vs. dicots (eudicots) genome size distributions was revealed. A similar divergence was found for annual vs. perennial dicots. The divergence of monocots vs. dicots genome size distributions holds at different taxonomic levels and is more pronounced for species with larger genomes. Using nested analysis of variance, it was shown that putative constraints on genome size variation are not only stronger in dicots as compared to monocots but in the former they start to operate already at the family level, whereas in the latter they do so only at the order level. At the same time, variation in basic chromosome number is constrained at the order level in both groups. Higher basic chromosome numbers were found in perennial plants as compared to the annual ones, which can be explained by their need for a higher genetic recombination as compensation for the longer life-cycles. A negative correlation was found between genome size and basic chromosome number, which can be explained as a trade-off between different recombination mechanisms.     

Minimizing model fitting objectives that contain spurious local minima by bootstrap restarting

Objective functions that arise when fitting nonlinear models often contain local minima that are of little significance except for their propensity to trap minimization algorithms. The standard methods for attempting to deal with this problem treat the objective function as fixed and employ stochastic minimization approaches in the hope of randomly jumping out of local minima. This article suggests a simple trick for performing such minimizations that can be employed in conjunction with most conventional nonstochastic fitting methods. The trick is to stochastically perturb the objective function by bootstrapping the data to be fit. Each bootstrap objective shares the large-scale structure of the original objective but has different small-scale structure. Minimizations of bootstrap objective functions are alternated with minimizations of the original objective function starting from the parameter values with which minimization of the previous bootstrap objective terminated. An example is presented, fitting a nonlinear population dynamic model to population dynamic data and including a comparison of the suggested method with simulated annealing. Convergence diagnostics are discussed.     

Nonparametric estimation in a cure model with random cure times

Acute respiratory distress syndrome (ARDS) is a life-threatening acute condition that sometimes follows pneumonia or surgery. Patients who recover and leave the hospital are considered to have been cured at the time they leave the hospital. These data differ from typical data in which cure is a possibility: death times are not observed for patients who are cured and cure times are observed and vary among patients. Here we apply a competing risks model to these data and show it to be equivalent to a mixture model, the more common approach for cure data. Further, we derive an estimator for the variance of the cumulative incidence function from the competing risks model, and thus for the cure rate, based on elementary calculations. We compare our variance estimator to Gray's (1988, Annals of Statistics 16, 1140-1154) estimator, which is based on counting process theory. We find our estimator to be slightly more accurate in small samples. We apply these results to data from an ARDS clinical trial.