Modelling habitat-suitability using museum collections: an example with three sympatric Apodemus species from the Alps

Aim, Location Although the alpine mouse Apodemus alpicola has been given species status since 1989, no distribution map has ever been constructed for this endemic alpine rodent in Switzerland. Based on redetermined museum material and using the Ecological-Niche Factor Analysis (ENFA), habitat-suitability maps were computed for A. alpicola, and also for the co-occurring A. flavicollis and A. sylvaticus. Methods In the particular case of habitat suitability models, classical approaches (GLMs, GAMs, discriminant analysis, etc.) generally require presence and absence data. The presence records provided by museums can clearly give useful information about species distribution and ecology and have already been used for knowledge-based mapping. In this paper, we apply the ENFA which requires only presence data, to build a habitat-suitability map of three species of Apodemus on the basis of museum skull collections. Results Interspecific niche comparisons showed that A. alpicola is very specialized concerning habitat selection, meaning that its habitat differs unequivocally from the average conditions in Switzerland, while both A. flavicollis and A. sylvaticus could be considered as 'generalists' in the study area. Main conclusions Although an adequate sampling design is the best way to collect ecological data for predictive modelling, this is a time and money consuming process and there are cases where time is simply not available, as for instance with endangered species conservation. On the other hand, museums, herbariums and other similar institutions are treasuring huge presence data sets. By applying the ENFA to such data it is possible to rapidly construct a habitat suitability model. The ENFA method not only provides two key measurements regarding the niche of a species (i.e. marginality and specialization), but also has ecological meaning, and allows the scientist to compare directly the niches of different species.

Population pharmacokinetic-pharmacodynamic modelling of angiotensin receptor blockade in healthy volunteers.

OBJECTIVE: To compare the pharmacokinetic and pharmacodynamic characteristics of angiotensin II receptor antagonists as a therapeutic class. DESIGN: Population pharmacokinetic-pharmacodynamic modelling study. METHODS: The data of 14 phase I studies with 10 different drugs were analysed. A common population pharmacokinetic model (two compartments, mixed zero- and first-order absorption, two metabolite compartments) was applied to the 2685 drug and 900 metabolite concentration measurements. A standard nonlinear mixed effect modelling approach was used to estimate the drug-specific parameters and their variabilities. Similarly, a pharmacodynamic model was applied to the 7360 effect measurements, i.e. the decrease of peak blood pressure response to intravenous angiotensin challenge recorded by finger photoplethysmography. The concentration of drug and metabolite in an effect compartment was assumed to translate into receptor blockade [maximum effect (Emax) model with first-order link]. RESULTS: A general pharmacokinetic-pharmacodynamic (PK-PD) model for angiotensin antagonism in healthy individuals was successfully built up for the 10 drugs studied. Representatives of this class share different pharmacokinetic and pharmacodynamic profiles. Their effects on blood pressure are dose-dependent, but the time course of the effect varies between the drugs. CONCLUSIONS: The characterisation of PK-PD relationships for these drugs gives the opportunity to optimise therapeutic regimens and to suggest dosage adjustments in specific conditions. Such a model can be used to further refine the use of this class of drugs.

Modelling short-term ultraviolet exposure as an alternative to individual dosimetry

Background: Excessive exposure to solar Ultra-Violet (UV) light is the main cause of most skin cancers in humans. Factors such as the increase of solar irradiation at ground level (anthropic pollution), the rise in standard of living (vacation in sunny areas), and (mostly) the development of outdoor activities have contributed to increase exposure. Thus, unsurprisingly, incidence of skin cancers has increased over the last decades more than that of any other cancer. Melanoma is the most lethal cutaneous cancer, while cutaneous carcinomas are the most common cancer type worldwide. UV exposure depends on environmental as well as individual factors related to activity. The influence of individual factors on exposure among building workers was investigated in a previous study. Posture and orientation were found to account for at least 38% of the total variance of relative individual exposure. A high variance of short-term exposure was observed between different body locations, indicating the occurrence of intense, subacute exposures. It was also found that effective short-term exposure ranged between 0 and 200% of ambient irradiation, suggesting that ambient irradiation is a poor predictor of effective exposure. Various dosimetric techniques enable to assess individual effective exposure, but dosimetric measurements remain tedious and tend to be situation-specific. As a matter of facts, individual factors (exposure time, body posture and orientation in the sun) often limit the extrapolation of exposure results to similar activities conducted in other conditions. Objective: The research presented in this paper aims at developing and validating a predictive tool of effective individual exposure to solar UV. Methods: Existing computer graphic techniques (3D rendering) were adapted to reflect solar exposure conditions and calculate short-term anatomical doses. A numerical model, represented as a 3D triangular mesh, is used to represent the exposed body. The amount of solar energy received by each "triangle is calculated, taking into account irradiation intensity, incidence angle and possible shadowing from other body parts. The model take into account the three components of the solar irradiation (direct, diffuse and albedo) as well as the orientation and posture of the body. Field measurements were carried out using a forensic mannequin at the Payerne MeteoSwiss station. Short-term dosimetric measurements were performed in 7 anatomical locations for 5 body postures. Field results were compared to the model prediction obtained from the numerical model. Results: The best match between prediction and measurements was obtained for upper body parts such as shoulders (Ratio Modelled/Measured; Mean = 1.21, SD = 0.34) and neck (Mean = 0.81, SD = 0.32). Small curved body parts such as forehead (Mean = 6.48, SD = 9.61) exhibited a lower matching. The prediction is less accurate for complex postures such as kneeling (Mean = 4.13, SD = 8.38) compared to standing up (Mean = 0.85, SD = 0.48). The values obtained from the dosimeters and the ones computed from the model are globally consistent. Conclusion: Although further development and validation are required, these results suggest that effective exposure could be predicted for a given activity (work or leisure) in various ambient irradiation conditions. Using a generic modelling approach is of high interest in terms of implementation costs as well as predictive and retrospective capabilities.

Dynamic modelling of an underwater vehicle

Nessie is an Autonomous Underwater Vehicle (AUV) created by a team of students in the Heriot Watt University to compete in the Student Autonomous Underwater Competition, Europe (SAUC-E) in August 2006. The main objective of the project is to find the dynamic equation of the robot, dynamic model. With it, the behaviour of the robot will be easier to understand and movement tests will be available by computer without the need of the robot, what is a way to save time, batteries, money and the robot from water inside itself. The object of the second part in this project is setting a control system for Nessie by using the model

An Interval Intelligent-based Approach for Fault Detection and Modelling

Not considered in the analytical model of the plant, uncertainties always dramatically decrease the performance of the fault detection task in the practice. To cope better with this prevalent problem, in this paper we develop a methodology using Modal Interval Analysis which takes into account those uncertainties in the plant model. A fault detection method is developed based on this model which is quite robust to uncertainty and results in no false alarm. As soon as a fault is detected, an ANFIS model is trained in online to capture the major behavior of the occurred fault which can be used for fault accommodation. The simulation results understandably demonstrate the capability of the proposed method for accomplishing both tasks appropriately

Sequencing and characterizing the genome of Estrella lausannensis as an undergraduate project: training students and biological insights.

With the widespread availability of high-throughput sequencing technologies, sequencing projects have become pervasive in the molecular life sciences. The huge bulk of data generated daily must be analyzed further by biologists with skills in bioinformatics and by "embedded bioinformaticians," i.e., bioinformaticians integrated in wet lab research groups. Thus, students interested in molecular life sciences must be trained in the main steps of genomics: sequencing, assembly, annotation and analysis. To reach that goal, a practical course has been set up for master students at the University of Lausanne: the "Sequence a genome" class. At the beginning of the academic year, a few bacterial species whose genome is unknown are provided to the students, who sequence and assemble the genome(s) and perform manual annotation. Here, we report the progress of the first class from September 2010 to June 2011 and the results obtained by seven master students who specifically assembled and annotated the genome of Estrella lausannensis, an obligate intracellular bacterium related to Chlamydia. The draft genome of Estrella is composed of 29 scaffolds encompassing 2,819,825 bp that encode for 2233 putative proteins. Estrella also possesses a 9136 bp plasmid that encodes for 14 genes, among which we found an integrase and a toxin/antitoxin module. Like all other members of the Chlamydiales order, Estrella possesses a highly conserved type III secretion system, considered as a key virulence factor. The annotation of the Estrella genome also allowed the characterization of the metabolic abilities of this strictly intracellular bacterium. Altogether, the students provided the scientific community with the Estrella genome sequence and a preliminary understanding of the biology of this recently-discovered bacterial genus, while learning to use cutting-edge technologies for sequencing and to perform bioinformatics analyses.

TACI, an enigmatic BAFF/APRIL receptor, with new unappreciated biochemical and biological properties.

BAFF is a B cell survival factor that binds to three receptors BAFF-R, TACI and BCMA. BAFF-R is the receptor triggering naïve B cell survival and maturation while BCMA supports the survival of plasma cells in the bone marrow. Excessive BAFF production leads to autoimmunity, presumably as the consequence of inappropriate survival of self-reactive B cells. The function of TACI has been more elusive with TACI(-/-) mice revealing two sides of this receptor, a positive one driving T cell-independent immune responses and a negative one down-regulating B cell activation and expansion. Recent work has revealed that the regulation of TACI expression is intimately linked to the activation of innate receptors on B cells and that TACI signalling in response to multimeric BAFF and APRIL provides positive signals to plasmablasts. How TACI negatively regulates B cells remains elusive but may involve an indirect control of BAFF levels. The discovery of TACI mutations associated with common variable immunodeficiency (CVID) in humans not only reinforces its important role for humoral responses but also suggests a more complex role than first anticipated from knockout animals. TACI is emerging as an unusual TNF receptor-like molecule with a sophisticated mode of action.

Identification and modelling of human breast cancer subtypes

Résumé Le cancer du sein est le cancer le plus commun chez les femmes et est responsable de presque 30% de tous les nouveaux cas de cancer en Europe. On estime le nombre de décès liés au cancer du sein en Europe est à plus de 130.000 par an. Ces chiffres expliquent l'impact social considérable de cette maladie. Les objectifs de cette thèse étaient: (1) d'identifier les prédispositions et les mécanismes biologiques responsables de l'établissement des sous-types spécifiques de cancer du sein; (2) les valider dans un modèle ín vivo "humain-dans-souris"; et (3) de développer des traitements spécifiques à chaque sous-type de cancer du sein identifiés. Le premier objectif a été atteint par l'intermédiaire de l'analyse des données d'expression de gènes des tumeurs, produite dans notre laboratoire. Les données obtenues par puces à ADN ont été produites à partir de 49 biopsies des tumeurs du sein provenant des patientes participant dans l'essai clinique EORTC 10994/BIG00-01. Les données étaient très riches en information et m'ont permis de valider des données précédentes des autres études d'expression des gènes dans des tumeurs du sein. De plus, cette analyse m'a permis d'identifier un nouveau sous-type biologique de cancer du sein. Dans la première partie de la thèse, je décris I identification des tumeurs apocrines du sein par l'analyse des puces à ADN et les implications potentielles de cette découverte pour les applications cliniques. Le deuxième objectif a été atteint par l'établissement d'un modèle de cancer du sein humain, basé sur des cellules épithéliales mammaires humaines primaires (HMECs) dérivées de réductions mammaires. J'ai choisi d'adapter un système de culture des cellules en suspension basé sur des mammosphères précédemment décrit et pat décidé d'exprimer des gènes en utilisant des lentivirus. Dans la deuxième partie de ma thèse je décris l'établissement d'un système de culture cellulaire qui permet la transformation quantitative des HMECs. Par la suite, j'ai établi un modèle de xénogreffe dans les souris immunodéficientes NOD/SCID, qui permet de modéliser la maladie humaine chez la souris. Dans la troisième partie de ma thèse je décris et je discute les résultats que j'ai obtenus en établissant un modèle estrogène-dépendant de cancer du sein par transformation quantitative des HMECs avec des gènes définis, identifiés par analyse de données d'expression des gènes dans le cancer du sein. Les cellules transformées dans notre modèle étaient estrogène-dépendantes pour la croissance, diploïdes et génétiquement normales même après la culture cellulaire in vitro prolongée. Les cellules formaient des tumeurs dans notre modèle de xénogreffe et constituaient des métastases péritonéales disséminées et du foie. Afin d'atteindre le troisième objectif de ma thèse, j'ai défini et examiné des stratégies de traitement qui permettent réduire les tumeurs et les métastases. J'ai produit un modèle de cancer du sein génétiquement défini et positif pour le récepteur de l'estrogène qui permet de modéliser le cancer du sein estrogène-dépendant humain chez la souris. Ce modèle permet l'étude des mécanismes impliqués dans la formation des tumeurs et des métastases. Abstract Breast cancer is the most common cancer in women and accounts for nearly 30% of all new cancer cases in Europe. The number of deaths from breast cancer in Europe is estimated to be over 130,000 each year, implying the social impact of the disease. The goals of this thesis were first, to identify biological features and mechanisms --responsible for the establishment of specific breast cancer subtypes, second to validate them in a human-in-mouse in vivo model and third to develop specific treatments for identified breast cancer subtypes. The first objective was achieved via the analysis of tumour gene expression data produced in our lab. The microarray data were generated from 49 breast tumour biopsies that were collected from patients enrolled in the clinical trial EORTC 10994/BIG00-01. The data set was very rich in information and allowed me to validate data of previous breast cancer gene expression studies and to identify biological features of a novel breast cancer subtype. In the first part of the thesis I focus on the identification of molecular apacrine breast tumours by microarray analysis and the potential imptìcation of this finding for the clinics. The second objective was attained by the production of a human breast cancer model system based on primary human mammary epithelial cells {HMECs) derived from reduction mammoplasties. I have chosen to adopt a previously described suspension culture system based on mammospheres and expressed selected target genes using lentiviral expression constructs. In the second part of my thesis I mainly focus on the establishment of a cell culture system allowing for quantitative transformation of HMECs. I then established a xenograft model in immunodeficient NOD/SCID mice, allowing to model human disease in a mouse. In the third part of my thesis I describe and discuss the results that I obtained while establishing an oestrogen-dependent model of breast cancer by quantitative transformation of HMECs with defined genes identified after breast cancer gene expression data analysis. The transformed cells in our model are oestrogen-dependent for growth; remain diploid and genetically normal even after prolonged cell culture in vitro. The cells farm tumours and form disseminated peritoneal and liver metastases in our xenograft model. Along the lines of the third objective of my thesis I defined and tested treatment schemes allowing reducing tumours and metastases. I have generated a genetically defined model of oestrogen receptor alpha positive human breast cancer that allows to model human oestrogen-dependent breast cancer in a mouse and enables the study of mechanisms involved in tumorigenesis and metastasis.

Predicting current and future biological invasions: both native and invaded ranges matter.

The classical approach to predicting the geographical extent of species invasions consists of training models in the native range and projecting them in distinct, potentially invasible areas. However, recent studies have demonstrated that this approach could be hampered by a change of the realized climatic niche, allowing invasive species to spread into habitats in the invaded ranges that are climatically distinct from those occupied in the native range. We propose an alternative approach that involves fitting models with pooled data from all ranges. We show that this pooled approach improves prediction of the extent of invasion of spotted knapweed (Centaurea maculosa) in North America on models based solely on the European native range. Furthermore, it performs equally well on models based on the invaded range, while ensuring the inclusion of areas with similar climate to the European niche, where the species is likely to spread further. We then compare projections from these models for 2080 under a severe climate warming scenario. Projections from the pooled models show fewer areas of intermediate climatic suitability than projections from the native or invaded range models, suggesting a better consensus among modelling techniques and reduced uncertainty.

A validated assay for measuring doxorubicin in biological fluids and tissues in an isolated lung perfusion model: matrix effect and heparin interference strongly influence doxorubicin measurements.

Doxorubicin is an antineoplasic agent active against sarcoma pulmonary metastasis, but its clinical use is hampered by its myelotoxicity and its cumulative cardiotoxicity, when administered systemically. This limitation may be circumvented using the isolated lung perfusion (ILP) approach, wherein a therapeutic agent is infused locoregionally after vascular isolation of the lung. The influence of the mode of infusion (anterograde (AG): through the pulmonary artery (PA); retrograde (RG): through the pulmonary vein (PV)) on doxorubicin pharmacokinetics and lung distribution was unknown. Therefore, a simple, rapid and sensitive high-performance liquid chromatography method has been developed to quantify doxorubicin in four different biological matrices (infusion effluent, serum, tissues with low or high levels of doxorubicin). The related compound daunorubicin was used as internal standard (I.S.). Following a single-step protein precipitation of 500 microl samples with 250 microl acetone and 50 microl zinc sulfate 70% aqueous solution, the obtained supernatant was evaporated to dryness at 60 degrees C for exactly 45 min under a stream of nitrogen and the solid residue was solubilized in 200 microl of purified water. A 100 microl-volume was subjected to HPLC analysis onto a Nucleosil 100-5 microm C18 AB column equipped with a guard column (Nucleosil 100-5 microm C(6)H(5) (phenyl) end-capped) using a gradient elution of acetonitrile and 1-heptanesulfonic acid 0.2% pH 4: 15/85 at 0 min-->50/50 at 20 min-->100/0 at 22 min-->15/85 at 24 min-->15/85 at 26 min, delivered at 1 ml/min. The analytes were detected by fluorescence detection with excitation and emission wavelength set at 480 and 550 nm, respectively. The calibration curves were linear over the range of 2-1000 ng/ml for effluent and plasma matrices, and 0.1 microg/g-750 microg/g for tissues matrices. The method is precise with inter-day and intra-day relative standard deviation within 0.5 and 6.7% and accurate with inter-day and intra-day deviations between -5.4 and +7.7%. The in vitro stability in all matrices and in processed samples has been studied at -80 degrees C for 1 month, and at 4 degrees C for 48 h, respectively. During initial studies, heparin used as anticoagulant was found to profoundly influence the measurements of doxorubicin in effluents collected from animals under ILP. Moreover, the strong matrix effect observed with tissues samples indicate that it is mandatory to prepare doxorubicin calibration standard samples in biological matrices which would reflect at best the composition of samples to be analyzed. This method was successfully applied in animal studies for the analysis of effluent, serum and tissue samples collected from pigs and rats undergoing ILP.

Will the Convention on Biological Diversity put an end to biological control?

Will the Convention on Biological Diversity put an end to biological control? Under the Convention on Biological Diversity countries have sovereign rights over their genetic resources. Agreements governing the access to these resources and the sharing of the benefits arising from their use need to be established between involved parties. This also applies to species collected for potential use in biological control. Recent applications of access and benefit sharing principles have already made it difficult or impossible to collect and export natural enemies for biological control research in several countries. If such an approach is widely applied it would impede this very successful and environmentally safe pest management method based on the use of biological diversity. The International Organization for Biological Control of Noxious Animals and Plants has, therefore, created the "Commission on Biological Control and Access and Benefit Sharing". This commission is carrying out national and international activities to make clear how a benefit sharing regime might seriously frustrate the future of biological control. In addition, the IOBC Commission members published information on current regulations and perceptions concerning exploration for natural enemies and drafted some 30 case studies selected to illustrate a variety of points relevant to access and benefit sharing. In this article, we summarize our concern about the effects of access and benefit sharing systems on the future of biological control.

Impact of biological and environmental variabilities on biological monitoring: an approach using toxicokinetic models

Biological monitoring of occupational exposure is characterized by important variability, due both to variability in the environment and to biological differences between workers. A quantitative description and understanding of this variability is important for a dependable application of biological monitoring. This work describes this variability,using a toxicokinetic model, for a large range of chemicals for which reference biological reference values exist. A toxicokinetic compartmental model describing both the parent compound and its metabolites was used. For each chemical, compartments were given physiological meaning. Models were elaborated based on physiological, physicochemical, and biochemical data when available, and on half-lives and central compartment concentrations when not available. Fourteen chemicals were studied (arsenic, cadmium, carbon monoxide, chromium, cobalt, ethylbenzene, ethyleneglycol monomethylether, fluorides, lead, mercury, methyl isobutyl ketone, penthachlorophenol, phenol, and toluene), representing 20 biological indicators. Occupational exposures were simulated using Monte Carlo techniques with realistic distributions of both individual physiological parameters and exposure conditions. Resulting biological indicator levels were then analyzed to identify the contribution of environmental and biological variability to total variability. Comparison of predicted biological indicator levels with biological exposure limits showed a high correlation with the model for 19 out of 20 indicators. Variability associated with changes in exposure levels (GSD of 1.5 and 2.0) is shown to be mainly influenced by the kinetics of the biological indicator. Thus, with regard to variability, we can conclude that, for the 14 chemicals modeled, biological monitoring would be preferable to air monitoring. For short half-lives (less than 7 hr), this is very similar to the environmental variability. However, for longer half-lives, estimated variability decreased. [Supplementary materials are available for this article. Go to the publisher's online edition of Journal of Occupational and Environmental Hygiene for the following free supplemental resource: tables detailing the CBTK models for all 14 chemicals and the symbol nomenclature that was used.] [Authors]

SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools.

BACKGROUND: Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. RESULTS: We present the Systems Biology Markup Language (SBML) Qualitative Models Package ("qual"), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the collective effort to define the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyse qualitative models. CONCLUSIONS: SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks.