Wildflower areas within revitalized agricultural matrices boost small mammal populations but not breeding Barn Owls

Agro-ecosystems have recently experienced dramatic losses of biodiversity due to more intensive production methods. In order to increase species diversity, agri-environment schemes provide subsidies to farmers who devote a fraction of their land to ecological compensation areas (ECA). Several studies have shown that invertebrate biodiversity is actually higher in ECA than in nearby intensively cultivated farmland. It remains poorly understood, however, to what extent ECA also favour vertebrates, such as small mammals and their predators, which would contribute to restore functioning food chains within revitalized agricultural matrices. We studied small mammal populations among eight habitat types - including wildflower areas, a specific ECA in Switzerland - and habitat selection (radiotracking) by the barn owl Tyto alba, one of their principal predators. Our prediction was that habitats with higher abundances of small mammals would be more visited by foraging Barn owls during the period of chicks' provisioning. Small mammal abundance tended to be higher in wildflower areas than in any other habitat type. Barn owls, however, preferred to forage in cereal fields and grassland. They avoided all types of crops other than cereals, as well as wildflower areas, which suggests that they do not select their hunting habitat primarily with respect to prey density. Instead of prey abundance, prey accessibility may play a more crucial role: wildflower areas have a dense vegetation cover, which may impede access to prey for foraging owls. The exploitation of wildflower areas by the owls might be enhanced by creating open foraging corridors within or around wildflower areas. Wildflower areas managed in that way might contribute to restore functioning food chains within agro-ecosystems.

Spatial weights : constructing weight-compatible exchange matrices from proximity matrices

Exchange matrices represent spatial weights as symmetric probability distributions on pairs of regions, whose margins yield regional weights, generally well-specified and known in most contexts. This contribution proposes a mechanism for constructing exchange matrices, derived from quite general symmetric proximity matrices, in such a way that the margin of the exchange matrix coincides with the regional weights. Exchange matrices generate in turn diffusive squared Euclidean dissimilarities, measuring spatial remoteness between pairs of regions. Unweighted and weighted spatial frameworks are reviewed and compared, regarding in particular their impact on permutation and normal tests of spatial autocorrelation. Applications include tests of spatial autocorrelation with diagonal weights, factorial visualization of the network of regions, multivariate generalizations of Moran's I, as well as "landscape clustering", aimed at creating regional aggregates both spatially contiguous and endowed with similar features.

Minimal analytical characterisation of engineered nanomaterials need for hazard assessment in biological matrices

The safe and responsible development of engineered nanomaterials (ENM), nanotechnology-based materials and products, together with the definition of regulatory measures and implementation of "nano"-legislation in Europe require a widely supported scientific basis and sufficient high quality data upon which to base decisions. At the very core of such a scientific basis is a general agreement on key issues related to risk assessment of ENMs which encompass the key parameters to characterise ENMs, appropriate methods of analysis and best approach to express the effect of ENMs in widely accepted dose response toxicity tests. The following major conclusions were drawn: Due to high batch variability of ENMs characteristics of commercially available and to a lesser degree laboratory made ENMs it is not possible to make general statements regarding the toxicity resulting from exposure to ENMs. 1) Concomitant with using the OECD priority list of ENMs, other criteria for selection of ENMs like relevance for mechanistic (scientific) studies or risk assessment-based studies, widespread availability (and thus high expected volumes of use) or consumer concern (route of consumer exposure depending on application) could be helpful. The OECD priority list is focussing on validity of OECD tests. Therefore source material will be first in scope for testing. However for risk assessment it is much more relevant to have toxicity data from material as present in products/matrices to which men and environment are be exposed. 2) For most, if not all characteristics of ENMs, standardized methods analytical methods, though not necessarily validated, are available. Generally these methods are only able to determine one single characteristic and some of them can be rather expensive. Practically, it is currently not feasible to fully characterise ENMs. Many techniques that are available to measure the same nanomaterial characteristic produce contrasting results (e.g. reported sizes of ENMs). It was recommended that at least two complementary techniques should be employed to determine a metric of ENMs. The first great challenge is to prioritise metrics which are relevant in the assessment of biological dose response relations and to develop analytical methods for characterising ENMs in biological matrices. It was generally agreed that one metric is not sufficient to describe fully ENMs. 3) Characterisation of ENMs in biological matrices starts with sample preparation. It was concluded that there currently is no standard approach/protocol for sample preparation to control agglomeration/aggregation and (re)dispersion. It was recommended harmonization should be initiated and that exchange of protocols should take place. The precise methods used to disperse ENMs should be specifically, yet succinctly described within the experimental section of a publication. 4) ENMs need to be characterised in the matrix as it is presented to the test system (in vitro/ in vivo). 5) Alternative approaches (e.g. biological or in silico systems) for the characterisation of ENMS are simply not possible with the current knowledge. Contributors: Iseult Lynch, Hans Marvin, Kenneth Dawson, Markus Berges, Diane Braguer, Hugh J. Byrne, Alan Casey, Gordon Chambers, Martin Clift, Giuliano Elia1, Teresa F. Fernandes, Lise Fjellsbø, Peter Hatto, Lucienne Juillerat, Christoph Klein, Wolfgang Kreyling, Carmen Nickel1, and Vicki Stone.

Minimal analytical characterization of engineered nanomaterials needed for hazard assessment in biological matrices.

Abstract This paper presents the outcomes from a workshop of the European Network on the Health and Environmental Impact of Nanomaterials (NanoImpactNet). During the workshop, 45 experts in the field of safety assessment of engineered nanomaterials addressed the need to systematically study sets of engineered nanomaterials with specific metrics to generate a data set which would allow the establishment of dose-response relations. The group concluded that international cooperation and worldwide standardization of terminology, reference materials and protocols are needed to make progress in establishing lists of essential metrics. High quality data necessitates the development of harmonized study approaches and adequate reporting of data. Priority metrics can only be based on well-characterized dose-response relations derived from the systematic study of the bio-kinetics and bio-interactions of nanomaterials at both organism and (sub)-cellular levels. In addition, increased effort is needed to develop and validate analytical methods to determine these metrics in a complex matrix.

Effects of selection and drift on G matrix evolution in a heterogeneous environment: a multivariate Qst-Fst Test with the freshwater snail Galba truncatula.

Unraveling the effect of selection vs. drift on the evolution of quantitative traits is commonly achieved by one of two methods. Either one contrasts population differentiation estimates for genetic markers and quantitative traits (the Q(st)-F(st) contrast) or multivariate methods are used to study the covariance between sets of traits. In particular, many studies have focused on the genetic variance-covariance matrix (the G matrix). However, both drift and selection can cause changes in G. To understand their joint effects, we recently combined the two methods into a single test (accompanying article by Martin et al.), which we apply here to a network of 16 natural populations of the freshwater snail Galba truncatula. Using this new neutrality test, extended to hierarchical population structures, we studied the multivariate equivalent of the Q(st)-F(st) contrast for several life-history traits of G. truncatula. We found strong evidence of selection acting on multivariate phenotypes. Selection was homogeneous among populations within each habitat and heterogeneous between habitats. We found that the G matrices were relatively stable within each habitat, with proportionality between the among-populations (D) and the within-populations (G) covariance matrices. The effect of habitat heterogeneity is to break this proportionality because of selection for habitat-dependent optima. Individual-based simulations mimicking our empirical system confirmed that these patterns are expected under the selective regime inferred. We show that homogenizing selection can mimic some effect of drift on the G matrix (G and D almost proportional), but that incorporating information from molecular markers (multivariate Q(st)-F(st)) allows disentangling the two effects.

Evaluation of cumulative PCB exposure estimated by a job exposure matrix versus PCB serum concentrations.

Although polychlorinated biphenyls (PCBs) have been banned in many countries for more than three decades, exposures to PCBs continue to be of concern due to their long half-lives and carcinogenic effects. In National Institute for Occupational Safety and Health studies, we are using semiquantitative plant-specific job exposure matrices (JEMs) to estimate historical PCB exposures for workers (n = 24,865) exposed to PCBs from 1938 to 1978 at three capacitor manufacturing plants. A subcohort of these workers (n = 410) employed in two of these plants had serum PCB concentrations measured at up to four times between 1976 and 1989. Our objectives were to evaluate the strength of association between an individual worker's measured serum PCB levels and the same worker's cumulative exposure estimated through 1977 with the (1) JEM and (2) duration of employment, and to calculate the explained variance the JEM provides for serum PCB levels using (3) simple linear regression. Consistent strong and statistically significant associations were observed between the cumulative exposures estimated with the JEM and serum PCB concentrations for all years. The strength of association between duration of employment and serum PCBs was good for highly chlorinated (Aroclor 1254/HPCB) but not less chlorinated (Aroclor 1242/LPCB) PCBs. In the simple regression models, cumulative occupational exposure estimated using the JEMs explained 14-24% of the variance of the Aroclor 1242/LPCB and 22-39% for Aroclor 1254/HPCB serum concentrations. We regard the cumulative exposure estimated with the JEM as a better estimate of PCB body burdens than serum concentrations quantified as Aroclor 1242/LPCB and Aroclor 1254/HPCB.

EEG-based functional brain networks: does the network size matter?

Functional connectivity in human brain can be represented as a network using electroencephalography (EEG) signals. These networks--whose nodes can vary from tens to hundreds--are characterized by neurobiologically meaningful graph theory metrics. This study investigates the degree to which various graph metrics depend upon the network size. To this end, EEGs from 32 normal subjects were recorded and functional networks of three different sizes were extracted. A state-space based method was used to calculate cross-correlation matrices between different brain regions. These correlation matrices were used to construct binary adjacency connectomes, which were assessed with regards to a number of graph metrics such as clustering coefficient, modularity, efficiency, economic efficiency, and assortativity. We showed that the estimates of these metrics significantly differ depending on the network size. Larger networks had higher efficiency, higher assortativity and lower modularity compared to those with smaller size and the same density. These findings indicate that the network size should be considered in any comparison of networks across studies.

New concepts for the design of dermal substitutes

Objectives: Skin can be partially regenerated after full thickness defects by collagen matrices, In this study, we identified the main limitations of induced regeneration aiming to improve the design of dermal matrices. Methods: Single mice received a 1 cm2, full thickness skin wound on the dorsum, which were grafted with collagen-GAG matrices or left ungrafted. The healing modulation induced by the collagen-GAG matrices was compared to spontaneous healing and to custom designed, bioactive, poly-N-Acetyl- Glucosamine (NAG) matrices. Wound staging was based on macroscopic, histological and immunhistochemical analysis on days 3, 7, 10 and 21 post wounding. Results: Cell density was higher in spontaneously granulating wounds compared to grafted wounds. While grafted wounds exhibited increased levels of cell proliferation on days 7 and 10, vascularity was dramatically reduced. NAG scaffolds accelerated both angiogenesis and wound re-epithelialization. Conclusions: Since slow integration and revascularization severely limit the engraftment of clinically used dermal scaffolds, the design of dermal matrices using bioactive materials represent the next step in skin regeneration.

Human urothelial cells grown on collagen adsorbed to surface-modified polymers.

OBJECTIVES: Tissue engineering methods can be applied to regenerate diseased, or congenitally missing, urinary tract tissues. Urinary tract tissue cell cultures must be established in vitro and adequate matrices, acting as cell carriers, must be developed. Although degradable and nondegradable polymer matrices offer adequate mechanical stability, they are not optimal for cell adherence and growth. To overcome this problem, extracellular matrix proteins, permitting cell adhesion and regulation of cell proliferation and differentiation, can be adsorbed to the surface-modified polymer. METHODS: In this study, nondegradable polymer films, poly(ethylene terephthalate), were used as an experimental model. Films were modified by graft polymerization of acrylic acid to subsequently allow collagen type I and III immobilization. The following adhesion, proliferation of human urothelial cells, and induction of their stratification were analyzed. RESULTS: Collagen adsorption on 0.2 microg/cm2 poly(acrylic acid)-grafted polymer films rendered the matrix apt for human urothelial cell adhesion and proliferation. Furthermore, stratification of urothelial cells was demonstrated on these surface-modified matrices. CONCLUSIONS: These results have shown that surface-modified polymer matrices can be used to act as cell carriers for cultured human urothelial cells. Such a cell-matrix construct could be applied in reparative surgery of the urinary tract.

The eukaryotic promoter database (EPD).

The Eukaryotic Promoter Database (EPD) is an annotated non-redundant collection of eukaryotic POL II promoters for which the transcription start site has been determined experimentally. Access to promoter sequences is provided by pointers to positions in nucleotide sequence entries. The annotation part of an entry includes a description of the initiation site mapping data, exhaustive cross-references to the EMBL nucleotide sequence database, SWISS-PROT, TRANSFAC and other databases, as well as bibliographic references. EPD is structured in a way that facilitates dynamic extraction of biologically meaningful promoter subsets for comparative sequence analysis. WWW-based interfaces have been developed that enable the user to view EPD entries in different formats, to select and extract promoter sequences according to a variety of criteria, and to navigate to related databases exploiting different cross-references. The EPD web site also features yearly updated base frequency matrices for major eukaryotic promoter elements. EPD can be accessed at http://www.epd.isb-sib.ch

Analyse des cannabinoïdes par spectrométrie de masse en mode tandem = Analysis of cannabinoids by tandem mass spectrometry

Depuis quelques années, la spectrométrie de masse en tandem (MS/MS) ne cesse de gagner du terrain comme méthode d'analyse en toxicologie forensique, notamment pour le dosage des cannabinoïdes. Couplée à la chromatographie liquide (LC) ou gazeuse (GC), elle permet l'identification fiable et le dosage rapide du THC, de son précurseur acide, et de ses principaux métabolites, y compris les glucuronides. Au cours de ces dix dernières années, un nombre significatif de publications sont parues sur ce sujet. L'objectif de cet article est de passer en revue les analyses par spectrométrie de masse en tandem des cannabinoïdes dans diverses matrices biologiques. In recent years, tandem mass spectrometry (MS/MS) is gaining ground as a reference method of analysis in clinical and forensic toxicology, especially for the determination of cannabinoids. Coupled to liquid chromatography (LC) or gas chromatography (GC), it allows the definitive identification and rapid determination of THC, its acid precursor, and its major metabolites, including the glucuronides. During the past decade, several methods of analysis of cannabinoids in different matrices have appeared on this subject. The aim of this paper is to review the analysis of cannabinoids by tandem mass spectrometry methods in various biological matrices

Identifying genetic signatures of selection in a non-model species, alpine gentian (Gentiana nivalis L.), using a landscape genetic approach

It is generally accepted that most plant populations are locally adapted. Yet, understanding how environmental forces give rise to adaptive genetic variation is a challenge in conservation genetics and crucial to the preservation of species under rapidly changing climatic conditions. Environmental variation, phylogeographic history, and population demographic processes all contribute to spatially structured genetic variation, however few current models attempt to separate these confounding effects. To illustrate the benefits of using a spatially-explicit model for identifying potentially adaptive loci, we compared outlier locus detection methods with a recently-developed landscape genetic approach. We analyzed 157 loci from samples of the alpine herb Gentiana nivalis collected across the European Alps. Principle coordinates of neighbor matrices (PCNM), eigenvectors that quantify multi-scale spatial variation present in a data set, were incorporated into a landscape genetic approach relating AFLP frequencies with 23 environmental variables. Four major findings emerged. 1) Fifteen loci were significantly correlated with at least one predictor variable (R (adj) (2) > 0.5). 2) Models including PCNM variables identified eight more potentially adaptive loci than models run without spatial variables. 3) When compared to outlier detection methods, the landscape genetic approach detected four of the same loci plus 11 additional loci. 4) Temperature, precipitation, and solar radiation were the three major environmental factors driving potentially adaptive genetic variation in G. nivalis. Techniques presented in this paper offer an efficient method for identifying potentially adaptive genetic variation and associated environmental forces of selection, providing an important step forward for the conservation of non-model species under global change.

Prenatally engineered autologous amniotic fluid stem cell-based heart valves in the fetal circulation.

Prenatal heart valve interventions aiming at the early and systematic correction of congenital cardiac malformations represent a promising treatment option in maternal-fetal care. However, definite fetal valve replacements require growing implants adaptive to fetal and postnatal development. The presented study investigates the fetal implantation of prenatally engineered living autologous cell-based heart valves. Autologous amniotic fluid cells (AFCs) were isolated from pregnant sheep between 122 and 128 days of gestation via transuterine sonographic sampling. Stented trileaflet heart valves were fabricated from biodegradable PGA-P4HB composite matrices (n = 9) and seeded with AFCs in vitro. Within the same intervention, tissue engineered heart valves (TEHVs) and unseeded controls were implanted orthotopically into the pulmonary position using an in-utero closed-heart hybrid approach. The transapical valve deployments were successful in all animals with acute survival of 77.8% of fetuses. TEHV in-vivo functionality was assessed using echocardiography as well as angiography. Fetuses were harvested up to 1 week after implantation representing a birth-relevant gestational age. TEHVs showed in vivo functionality with intact valvular integrity and absence of thrombus formation. The presented approach may serve as an experimental basis for future human prenatal cardiac interventions using fully biodegradable autologous cell-based living materials.