pathmatrix: a geographical information system tool to compute effective distances among samples

pathmatrix is a tool used to compute matrices of effective geographical distances among samples using a least‐cost path algorithm. This program is dedicated to the study of the role of the environment on the spatial genetic structure of populations. Punctual locations (e.g. individuals) or zones encompassing sample data points (e.g. demes) are used in conjunction with a species‐specific friction map representing the cost of movement through the landscape. Matrices of effective distances can then be exported to population genetic software to test, for example, for isolation by distance. pathmatrix is an extension to the geographical information system (GIS) software arcview 3.x.     

Mitotic drug targets

Mitosis is the key event of the cell cycle during which the sister chromatids are segregated onto two daughter cells. It is well established that abrogation of the normal mitotic progression is a highly efficient concept for anti‐cancer treatment. In fact, various drugs that target microtubules and thus interfere with the function of the mitotic spindle are in clinical use for the treatment of various human malignancies for many years. However, since microtubule inhibitors not only target proliferating cells severe side effects limit their use. Therefore, the identification of novel mitotic drug targets other than microtubules have gained recently much attention. This review will summarize the latest developments on the identification and clinical evaluation of novel mitotic drug targets and will introduce novel concepts for chemotherapy that are based on recent progress in our understanding how mitotic progression is regulated and how anti‐mitotic drugs induce tumor cell death. J. Cell. Biochem. 111: 258–265, 2010. © 2010 Wiley‐Liss, Inc.     

EVOLUTION AND EXTINCTION IN A CHANGING ENVIRONMENT: A QUANTITATIVE-GENETIC ANALYSIS

Because of the ubiquity of genetic variation for quantitative traits, virtually all populations have some capacity to respond evolutionarily to selective challenges. However, natural selection imposes demographic costs on a population, and if these costs are sufficiently large, the likelihood of extinction will be high. We consider how the mean time to extinction depends on selective pressures (rate and stochasticity of environmental change, and strength of selection), population parameters (carrying capacity, and reproductive capacity), and genetics (rate of polygenic mutation). We assume that in a randomly mating, finite population subject to density-dependent population growth, individual fitness is determined by a single quantitative-genetic character under Gaussian stabilizing selection with the optimum phenotype exhibiting directional change, or random fluctuations, or both. The quantitative trait is determined by a finite number of freely recombining, mutationally equivalent, additive loci. The dynamics of evolution and extinction are investigated, assuming that the population is initially under mutation-selection-drift balance. Under this model, in a directionally changing environment, the mean phenotype lags behind the optimum, but on the average evolves parallel to it. The magnitude of the lag determines the vulnerability to extinction. In finite populations, stochastic variation in the genetic variance can be quite pronounced, and bottlenecks in the genetic variance temporarily can impair the population's adaptive capacity enough to cause extinction when it would otherwise be unlikely in an effectively infinite population. We find that maximum sustainable rates of evolution or, equivalently, critical rates of environmental change, may be considerably less than 10% of a phenotypic standard deviation per generation.     

Mass Coral Reef Bleaching: A Recent Outcome of Increased El Niño Activity?

Coral reefs are generally considered to be the most biologically productive of all marine ecosystems, but in recent times these vulnerable aquatic resources have been subject to unusual degradation. The general decline in reefs has been greatly accelerated by mass bleaching in which corals whiten en masse and often fail to recover. Empirical evidence indicates a coral reef bleaching cycle in which major bleaching episodes are synchronized with El Niño events that occur every 3–4 years on average. By heating vast areas of the Pacific Ocean, and affecting the Indian and Atlantic Oceans as well, El Niño causes widespread damage to reefs largely because corals are very sensitive to temperature changes. However, mass bleaching events were rarely observed before the 1970s and their abrupt appearance two decades ago remains an enigma. Here we propose a new explanation for the sudden occurrence of mass bleaching and show that it may be a response to the relative increase in El Niño experienced over the last two decades.     

Assessment of Optimal Selected Prognostic Factors

The identification and assessment of prognostic factors is one of the major tasks in clinical research. The assessment of one single prognostic factor can be done by recently established methods for using optimal cutpoints. Here, we suggest a method to consider an optimal selected prognostic factor from a set of prognostic factors of interest. This can be viewed as a variable selection method and is the underlying decision problem at each node of various tree building algorithms. We propose to use maximally selected statistics where the selection is defined over the set of prognostic factors and over all cutpoints in each prognostic factor. We demonstrate that it is feasible to compute the approximate null distribution. We illustrate the new variable selection test with data of the German Breast Cancer Study Group and of a small study on patients with diffuse large B‐cell lymphoma. Using the null distribution for a p‐value adjusted regression trees algorithm, we adjust for the number of variables analysed at each node as well. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Conditional and Unconditional Simulation of Healthy Patients' Visual Fields

This paper describes a simulation problem, motivated by the study of glaucoma, a very serious and widespread ocular illness. To ascertain whether a patient suffers from glaucoma, a perimetric test is done, but the evolution of the disease is very slow, and large longitudinal sets of tests taken on the same patient are needed to study its evolution, to analyze the efficiency of existing methods to detect the progression of glaucoma and to develop new ones. Simulation can be a very useful procedure to get appropriate data sets to work with. Our aim in this work is to simulate several VFs in a healthy patient to reflect his evolution in time. We use a spatio‐temporal model to simulate from, taking into account the correlation existing between the observed (or simulated) values in space and time. Two different simulation procedures (unconditional and conditional) are studied, and applied to obtain the simulations we are interested in. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Reaction mechanism of surfactant‐sensitized chemiluminescence of bis(2,4,6‐trichlorophyenyl) oxalate and hydrogen peroxide induced by gold nanoparticles

The chemiluminescence (CL) of bis(2,4,6‐trichlorophyenyl) oxalate with hydrogen peroxide in the present of cationic surfactant and gold nanoparticles was studied. The CL emission was obviously enhanced in the presence of surfactant at a suitable concentration, with a synergetic catalysis effect exhibited. Different sizes of gold nanoparticles (15 and 50 nm) showed different effects on CL intensity. Mechanisms of the CL reaction and sensitization effect are discussed. Copyright © 2008 John Wiley & Sons, Ltd.     

Floristic turnover in Iceland from 15 to 6 Ma – extracting biogeographical signals from fossil floral assemblages

Aim This study aims to document the floristic changes that occurred in Iceland between 15 and 6 Ma and to establish the dispersal mechanisms for the plant taxa encountered. Using changing patterns of dispersal, two factors controlling floristic changes are tested. Possible factors are (1) climate change, and (2) the changing biogeography of Iceland over the time interval studied; that is, the presence or absence of a Miocene North Atlantic Land Bridge. Location The North Atlantic. Methods Species lists of fossil plants from Iceland in the time period 15 to 6 Ma were compiled using published data and new data. Closest living analogues were used to establish dispersal properties for the fossil taxa. Dispersal mechanisms of fossil plants were then used to reconstruct how Iceland was colonized during various periods. Results Miocene floras of Iceland (15–6 Ma) show relatively high floristic turnover from the oldest floras towards the youngest; and few taxa from the oldest floras persist in the younger floras. The frequencies of the various dispersal mechanisms seen in the 15‐Ma floras are quite different from those recorded in the 6‐Ma floras, and there is a gradual change in the prevailing mode of dispersal from short‐distance anemochory and dyschory to long‐distance anemochory. Two mechanisms can be used to explain changing floral composition: (1) climate change, and (2) the interaction between the dispersal mechanisms of plants and the increasing isolation of proto‐Iceland during the Miocene. Main conclusions Dispersal mechanisms can be used to extract palaeogeographic signals from fossil floras. The composition of floras and dispersal mechanisms indicate that Iceland was connected both to Greenland and to Europe in the early Middle Miocene, allowing transcontinental migration. The change in prevalence of dispersal modes from 15 to 6 Ma appears to reflect the break‐up of a land bridge and the increasing isolation of Iceland after 12 Ma. Concurrent gradual cooling and isolation caused changes in species composition. Specifically, the widening of the North Atlantic Ocean prevented taxa with limited dispersal capability from colonizing Iceland, while climate cooling led to the extinction of thermophilous taxa.