Climate change, anthropogenic disturbance and the northward range expansion of Lactuca serriola (Asteraceae)

The distribution range of Lactuca serriola, a species native to the summer-dry mediterranean climate, has expanded northwards during the last 250 years. This paper assesses the influence of climate on the range expansion of this species and highlights the importance of anthropogenic disturbance to its spread. Location Central and Northern Europe. Methods Data on the geographic distribution of L. serriola were assembled through a literature search as well as through floristic and herbarium surveys. Maps of the spread of L. serriola in Central and Northern Europe were prepared based on herbarium data. The spread was assessed more precisely in Germany, Austria and Great Britain by pooling herbarium and literature data. We modelled the bioclimatic niche of the species using occurrence and climatic data covering the last century to generate projections of suitable habitats under the climatic conditions of five time periods. We tested whether the observed distribution of L. serriola could be explained for each time period, assuming that the climatic niche of the species was conserved across time. Results The species has spread northwards since the beginning of the 19th century. We show that climate warming in Europe increased the number of sites suitable for the species at northern latitudes. Until the late 1970s, the distribution of the species corresponded to the climatically suitable sites available. For the last two decades, however, we could not show any significant relationship between the increase in suitable sites and the distributional range change of L. serriola. However, we highlight potential areas the species could spread to in the future (Great Britain, southern Scandinavia and the Swedish coast). It is predominantly non-climatic influences of global change that have contributed to its rapid spread. Main conclusions The observation that colonizing species are not filling their climatically suitable range might imply that, potentially, other ruderal species could expand far beyond their current range. Our work highlights the importance of historical floristic and herbarium data for understanding the expansion of a species. Such historical distributional data can provide valuable information for those planning the management of contemporary environmental problems, such as species responses to environmental change.

Retrovirus-mediated gene transfer in polyclonal T cells results in lower apoptosis and enhanced ex vivo cell expansion of CMV-reactive CD8 T cells as compared with EBV-reactive CD8 T cells.

To modulate alloreactivity after hematopoietic stem cell transplantation, "suicide" gene-modified donor T cells (GMCs) have been administered with an allogeneic T-cell-depleted marrow graft. We previously demonstrated that such GMCs, generated after CD3 activation, retrovirus-mediated transduction, and G418 selection, had an impaired Epstein-Barr virus (EBV) reactivity, likely to result in an altered control of EBV-induced lymphoproliferative disease. To further characterize the antiviral potential of GMCs, we compared the frequencies of cytomegalovirus (CMV)-specific CD8+ T (CMV-T) cells and EBV-specific CD8+ T (EBV-T) cells within GMCs from CMV- and EBV-double seropositive donors. Unlike anti-EBV responses, the anti-CMV responses were not altered by GMC preparation. During the first days of culture, CMV-T cells exhibited a lower level of CD3-induced apoptosis than did EBV-T cells. In addition, the CMV-T cells escaping initial apoptosis subsequently underwent a higher expansion rate than EBV-T cells. The differential early sensitivity to apoptosis could be in relation to the "recent activation" phenotype of EBV-T cells as evidenced by a higher level of CD69 expression. Furthermore, EBV-T cells were found to have a CD45RA-CD27+CCR7- effector memory phenotype, whereas CMV-T cells had a CD45RA+CD27-CCR7- terminal effector phenotype. Such differences could be contributive, because bulk CD8+CD27- cells had a higher expansion than did bulk CD8+CD27+ cells. Overall, ex vivo T-cell culture differentially affects apoptosis, long-term proliferation, and overall survival of CMV-T and EBV-T cells. Such functional differences need to be taken into account when designing cell and/or gene therapy protocols involving ex vivo T-cell manipulation.

Cryptic diversity among Western Palearctic tree frogs: postglacial range expansion, range limits, and secondary contacts of three European tree frog lineages (Hyla arborea group).

We characterize divergence times, intraspecific diversity and distributions for recently recognized lineages within the Hyla arborea species group, based on mitochondrial and nuclear sequences from 160 localities spanning its whole distribution. Lineages of H. arborea, H. orientalis, H. molleri have at least Pliocene age, supporting species level divergence. The genetically uniform Iberian H. molleri, although largely isolated by the Pyrenees, is parapatric to H. arborea, with evidence for successful hybridization in a small Aquitanian corridor (southwestern France), where the distribution also overlaps with H. meridionalis. The genetically uniform H. arborea, spread from Crete to Brittany, exhibits molecular signatures of a postglacial range expansion. It meets different mtDNA clades of H. orientalis in NE-Greece, along the Carpathians, and in Poland along the Vistula River (there including hybridization). The East-European H. orientalis is strongly structured genetically. Five geographic mitochondrial clades are recognized, with a molecular signature of postglacial range expansions for the clade that reached the most northern latitudes. Hybridization with H. savignyi is suggested in southwestern Turkey. Thus, cryptic diversity in these Pliocene Hyla lineages covers three extremes: a genetically poor, quasi-Iberian endemic (H. molleri), a more uniform species distributed from the Balkans to Western Europe (H. arborea), and a well-structured Asia Minor-Eastern European species (H. orientalis).

Fault diagnosis by refining the parameter uncertainty space of nonlinear dynamic systems

This paper deals with fault detection and isolation problems for nonlinear dynamic systems. Both problems are stated as constraint satisfaction problems (CSP) and solved using consistency techniques. The main contribution is the isolation method based on consistency techniques and uncertainty space refining of interval parameters. The major advantage of this method is that the isolation speed is fast even taking into account uncertainty in parameters, measurements, and model errors. Interval calculations bring independence from the assumption of monotony considered by several approaches for fault isolation which are based on observers. An application to a well known alcoholic fermentation process model is presented

A hierarchical approach to model parameter optimization for developmental systems.

In the context of Systems Biology, computer simulations of gene regulatory networks provide a powerful tool to validate hypotheses and to explore possible system behaviors. Nevertheless, modeling a system poses some challenges of its own: especially the step of model calibration is often difficult due to insufficient data. For example when considering developmental systems, mostly qualitative data describing the developmental trajectory is available while common calibration techniques rely on high-resolution quantitative data. Focusing on the calibration of differential equation models for developmental systems, this study investigates different approaches to utilize the available data to overcome these difficulties. More specifically, the fact that developmental processes are hierarchically organized is exploited to increase convergence rates of the calibration process as well as to save computation time. Using a gene regulatory network model for stem cell homeostasis in Arabidopsis thaliana the performance of the different investigated approaches is evaluated, documenting considerable gains provided by the proposed hierarchical approach.

Range expansion of the greater white-toothed shrew Crocidura russula in Switzerland results in local extinction of the bicoloured white-toothed shrew C-leucodon

The distribution limits of Crocidura russula (Hermann, 1780) and C. leucodon (Hermann, 1780) were investigated during an interval of 25 years in the bottom of the Rhone valley above Lake Geneva, Switzerland (total data set: 105 spatio-temporal occurrences, 1137 shrews). In 1975, the contact zone between the two species was situated in the region of Martigny. In 1999/2000, new sampling revealed three results: (1) The contact zone showed an upward shift of about 25 km. (2) In the expanded range of C. russula, the resident species has totally disappeared (confirmed by owl pellets analysis). (3) This demonstrates a dominance of C, russula over C. leucodon. Three hypotheses which may explain the range expansion of C. russula were evaluated: (1) habitat modification favouring linear dispersal due to the construction of a highway; (2) temporal event favoured by climate fluctuations, or (3) ongoing postglacial colonisation of Europe. Hypothesis 1 was rejected, because the progression of the shrews anticipated the construction. Hypothesis 3 received only weak support because range limits of C. russula in the region of Nice have been stable for thousands of years. Therefore hypothesis 2, admitting that ongoing climate change has facilitated range expansion, is the most probable.

Initial convergence of the perturbation series expansion for vibrational nonlinear optical properties

Initial convergence of the perturbation series expansion for vibrational nonlinear optical (NLO) properties was analyzed. The zero-point vibrational average (ZPVA) was obtained through first-order in mechanical plus electrical anharmonicity. Results indicated that higher-order terms in electrical and mechanical anharmonicity can make substantial contributions to the pure vibrational polarizibility of typical NLO molecules

Long-term ex vivo expansion of human fetal liver primitive haematopoietic progenitor cells in stroma-free cultures

Successful expansion of haematopoietic cells in ex vivo cultures will have important applications in transplantation, gene therapy, immunotherapy and potentially also in the production of non-haematopoietic cell types. Haematopoietic stem cells (HSC), with their capacity to both self-renew and differentiate into all blood lineages, represent the ideal target for expansion protocols. However, human HSC are rare, poorly characterized phenotypically and genotypically, and difficult to test functionally. Defining optimal culture parameters for ex vivo expansion has been a major challenge. We devised a simple and reproducible stroma-free liquid culture system enabling long-term expansion of putative haematopoietic progenitors contained within frozen human fetal liver (FL) crude cell suspensions. Starting from a small number of total nucleated cells, a massive haematopoietic cell expansion, reaching > 1013-fold the input cell number after approximately 300 d of culture, was consistently achieved. Cells with a primitive phenotype were present throughout the culture and also underwent a continuous expansion. Moreover, the capacity for multilineage lymphomyeloid differentiation, as well as the recloning capacity of primitive myeloid progenitors, was maintained in culture. With its better proliferative potential as compared with adult sources, FL represents a promising alternative source of HSC and the culture system described here should be useful for clinical applications.

Probabilistic evidential assessment of gunshot residue particle evidence (Part II) : Bayesian parameter estimation for experimental count data.

Part I of this series of articles focused on the construction of graphical probabilistic inference procedures, at various levels of detail, for assessing the evidential value of gunshot residue (GSR) particle evidence. The proposed models - in the form of Bayesian networks - address the issues of background presence of GSR particles, analytical performance (i.e., the efficiency of evidence searching and analysis procedures) and contamination. The use and practical implementation of Bayesian networks for case pre-assessment is also discussed. This paper, Part II, concentrates on Bayesian parameter estimation. This topic complements Part I in that it offers means for producing estimates useable for the numerical specification of the proposed probabilistic graphical models. Bayesian estimation procedures are given a primary focus of attention because they allow the scientist to combine (his/her) prior knowledge about the problem of interest with newly acquired experimental data. The present paper also considers further topics such as the sensitivity of the likelihood ratio due to uncertainty in parameters and the study of likelihood ratio values obtained for members of particular populations (e.g., individuals with or without exposure to GSR).

An analysis of the metabolic patterns of two rural communities affected by soy expansion in the North of Argentina

The soy expansion model in Argentina generates structural changes in traditional lifestyles that can be associated with different biophysical and socioeconomic impacts. To explore this issue, we apply an innovative method for integrated assessment - the Multi Scale Integrated Analysis of Societal and Ecosystem Metabolism (MuSIASEM) framework - to characterize two communities in the Chaco Region, Province of Formosa, North of Argentina. These communities have recently experienced the expansion of soy production, altering their economic activity, energy consumption patterns, land use, and human time allocation. The integrated characterization presented in the paper illustrates the differences (biophysical, socioeconomic, and historical) between the two communities that can be associated with different responses. The analysis of the factors behind these differences has important policy implications for the sustainable development of local communities in the area.

S-system parameter estimation for noisy metabolic profiles using newton-flow analysis.

Biochemical systems are commonly modelled by systems of ordinary differential equations (ODEs). A particular class of such models called S-systems have recently gained popularity in biochemical system modelling. The parameters of an S-system are usually estimated from time-course profiles. However, finding these estimates is a difficult computational problem. Moreover, although several methods have been recently proposed to solve this problem for ideal profiles, relatively little progress has been reported for noisy profiles. We describe a special feature of a Newton-flow optimisation problem associated with S-system parameter estimation. This enables us to significantly reduce the search space, and also lends itself to parameter estimation for noisy data. We illustrate the applicability of our method by applying it to noisy time-course data synthetically produced from previously published 4- and 30-dimensional S-systems. In addition, we propose an extension of our method that allows the detection of network topologies for small S-systems. We introduce a new method for estimating S-system parameters from time-course profiles. We show that the performance of this method compares favorably with competing methods for ideal profiles, and that it also allows the determination of parameters for noisy profiles.

Multiuser detection in a dynamic environment — Part II: Joint user identification and parameter estimation

The problem of jointly estimating the number, the identities, and the data of active users in a time-varying multiuser environment was examined in a companion paper (IEEE Trans. Information Theory, vol. 53, no. 9, September 2007), at whose core was the use of the theory of finite random sets on countable spaces. Here we extend that theory to encompass the more general problem of estimating unknown continuous parameters of the active-user signals. This problem is solved here by applying the theory of random finite sets constructed on hybrid spaces. We doso deriving Bayesian recursions that describe the evolution withtime of a posteriori densities of the unknown parameters and data.Unlike in the above cited paper, wherein one could evaluate theexact multiuser set posterior density, here the continuous-parameter Bayesian recursions do not admit closed-form expressions. To circumvent this difficulty, we develop numerical approximationsfor the receivers that are based on Sequential Monte Carlo (SMC)methods (“particle filtering”). Simulation results, referring to acode-divisin multiple-access (CDMA) system, are presented toillustrate the theory.

TCR-MHC class II interaction is required for peripheral expansion of CD4 cells in a T cell-deficient host.

It is well established that T cell-deficient nude and SCID mice can be reconstituted by i.v. injection of small numbers of purified peripheral CD4+ T cells; however, the requirements for expansion of the transferred T cells in such systems are not clear. We show here that blood and lymphoid organs of MHC class II-deficient mice (which selectively lack mature CD4+ T cells) cannot be reconstituted by transfer of purified splenic CD4+ T cells, whereas TCRalpha-deficient mice (which lack both CD4+ and CD8+ mature T cells) are readily reconstituted. The failure of CD4+ T cell reconstitution in MHC class II-deficient mice was not due to the presence of CD8+ T cells, since similar results were obtained in TCRalpha-MHC class II double-deficient mice. Consistent with most previous studies CD4+ T cells in reconstituted TCRalpha-deficient mice had a diverse TCR Vbeta repertoire and were predominantly of an activated/memory (CD44high) phenotype. Collectively our data demonstrate that the expansion of peripheral CD4+ T cells in a T cell-deficient host is dependent upon interactions of the TCR with MHC class II.

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.

ILS-ESP An efficient, simple, and parameter-free algorithm for solving the permutation flow-shop problem

From a managerial point of view, the more effcient, simple, and parameter-free (ESP) an algorithm is, the more likely it will be used in practice for solving real-life problems. Following this principle, an ESP algorithm for solving the Permutation Flowshop Sequencing Problem (PFSP) is proposed in this article. Using an Iterated Local Search (ILS) framework, the so-called ILS-ESP algorithm is able to compete in performance with other well-known ILS-based approaches, which are considered among the most effcient algorithms for the PFSP. However, while other similar approaches still employ several parameters that can affect their performance if not properly chosen, our algorithm does not require any particular fine-tuning process since it uses basic "common sense" rules for the local search, perturbation, and acceptance criterion stages of the ILS metaheuristic. Our approach defines a new operator for the ILS perturbation process, a new acceptance criterion based on extremely simple and transparent rules, and a biased randomization process of the initial solution to randomly generate different alternative initial solutions of similar quality -which is attained by applying a biased randomization to a classical PFSP heuristic. This diversification of the initial solution aims at avoiding poorly designed starting points and, thus, allows the methodology to take advantage of current trends in parallel and distributed computing. A set of extensive tests, based on literature benchmarks, has been carried out in order to validate our algorithm and compare it against other approaches. These tests show that our parameter-free algorithm is able to compete with state-of-the-art metaheuristics for the PFSP. Also, the experiments show that, when using parallel computing, it is possible to improve the top ILS-based metaheuristic by just incorporating to it our biased randomization process with a high-quality pseudo-random number generator.