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.

Regional-scale integration of multi-scale hydrological and geophysical data using a two-step Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale for the purpose of improving predictions of groundwater flow and solute transport. However, extending corresponding approaches to the regional scale still represents one of the major challenges in the domain of hydrogeophysics. To address this problem, we have developed a regional-scale data integration methodology based on a two-step Bayesian sequential simulation approach. Our objective is to generate high-resolution stochastic realizations of the regional-scale hydraulic conductivity field in the common case where there exist spatially exhaustive but poorly resolved measurements of a related geophysical parameter, as well as highly resolved but spatially sparse collocated measurements of this geophysical parameter and the hydraulic conductivity. To integrate this multi-scale, multi-parameter database, we first link the low- and high-resolution geophysical data via a stochastic downscaling procedure. This is followed by relating the downscaled geophysical data to the high-resolution hydraulic conductivity distribution. After outlining the general methodology of the approach, we demonstrate its application to a realistic synthetic example where we consider as data high-resolution measurements of the hydraulic and electrical conductivities at a small number of borehole locations, as well as spatially exhaustive, low-resolution estimates of the electrical conductivity obtained from surface-based electrical resistivity tomography. The different stochastic realizations of the hydraulic conductivity field obtained using our procedure are validated by comparing their solute transport behaviour with that of the underlying ?true? hydraulic conductivity field. We find that, even in the presence of strong subsurface heterogeneity, our proposed procedure allows for the generation of faithful representations of the regional-scale hydraulic conductivity structure and reliable predictions of solute transport over long, regional-scale distances.

A multilevel approach to understanding circadian rhythmicity : social and sleep-dependent effects in ants and mice

Résumé françaisLa majorité des organismes vivants sont soumis à l'alternance du jour et de la nuit, conséquence de la rotation de la terre autour de son axe. Ils ont développé un système interne de mesure du temps, appelé horloge circadienne, leur permettant de s'adapter et de synchroniser leur comportement et leur physiologie aux cycles de lumière. Cette dernière est considérée comme étant le signal majeur entraînant l'horloge interne et. par conséquent, les rythmes journaliers d'éveil et de sommeil. Outre sa régulation circadienne, le sommeil est contrôlé par un processus homéostatique qui détermine son besoin. La contribution de ces deux processus dans le fonctionnement cellulaire du cerveau n'a pas encore été investiguée. La mesure de l'amplitude ainsi que de la prévalence des ondes delta de l'EEG (activité delta) constitue un index très fiable du besoin de sommeil. Il a été démontré que cette activité est génétiquement déterminée et associée à un locus de trait quantitatif situé sur le chromosome 13 de la souris.Grâce à des expériences de privation de sommeil et d'analyses de transcriptome du cerveau dans trois souches de souris présentant diverses réponses à la privation de sommeil, nous avons trouvé que Homerla, localisé dans la région d'intérêt du chromosome 13, est le meilleur marqueur du besoin de sommeil. Homerla est impliqué dans la récupération de l'hyperactivité neuronale induite par le glutamate, grâce à son effet tampon sur le calcium intracellulaire. Une fonction fondamentale du sommeil pourrait donc être de protéger le cerveau et de lui permettre de récupérer après une hyperactivité neuronale imposée par une veille prolongée.De plus, nous avons montré que 2032 transcrits sont exprimés rythmiqueraent dans le cerveau de la souris, parmi lesquels seulement 391 le restent après que les animaux aient été privés de sommeil à différents moments au cours des 24 heures. Cette observation montre clairement que la plupart des changements rythmiques au niveau du transcriptome dépendent du sommeil et non de l'horloge circadienne et souligne ainsi l'importance du sommeil dans la physiologie des mammifères.La plupart des expériences concernant les rythmes circadiens ont été réalisées sur des individus isolés en négligeant l'effet du contexte social sur les comportements circadiens. Les espèces sociales, telles que les fourmis, se caractérisent par une division du travail où une répartition des tâches s'effectue entre ses membres. De plus, certaines d'entre elles doivent être pratiquées en continu comme les soins au couvain tandis que d'autres requièrent une activité rythmique comme le fourragement. Ainsi la fourmi est un excellent modèle pour l'étude de 1 influence du contexte social sur les rythmes circadiens.A ces fins, nous avons décidé d'étudier les rythmes circadiens chez une espèce de fourmi Camponotus fellah et de caractériser au niveau moléculaire son horloge circadienne. Nous avons ainsi développé un système vidéo permettant de suivre l'activité locomotrice de tous les individus d'une colonie. Nos résultats montrent que, bien que la plupart des fourmis soient arythmiques à l'intérieur de la colonie, elles développent d'amples rythmes d'activité en isolation. De plus, ces rythmes disparaissent presque aussitôt que la fourmi est réintroduite dans la colonie. Cette rythmicité observée en isolation semble être générée par l'horloge circadienne car elle persiste en condition constante (obscurité totale). Nous avons ensuite regardé si cette apparente arythmie observée dans la colonie résultait d'un effet masquant des interactions sociales sur les rythmes circadiens d'activité. Nos résultats suggèrent que l'horloge interne est fonctionnelle dans la colonie mais que l'expression de ses rythmes au niveau comportemental est inhibée par les interactions sociales. Les analyses moléculaires du statut de l'horloge dans différents contextes sociaux sont actuellement en cours. Le contexte social semble donc un déterminant majeur du comportement circadien chez la fourmi.AbstractAlmost all living organisms on earth are subjected to the alternance of day and night re-sulting from the rotation of the earth around its axis. They have evolved with an internal timing system, termed the circadian clock, enabling them to adapt and synchronize their behavior and physiology to the daily changes in light and related environmental parame¬ters. Light is thought to be the major cue entraining the circadian clock and consequently the rhythms of rest/activity. In addition to its circadian dependent timing, sleep is reg¬ulated by a homeostatic process that determines its need. The contribution of these two processes in the cellular functioning of the brain has not yet been considered. A highly reliable index of the homeostatic process of sleep is the measure of the amplitude and prevalence of the EEG delta waves (delta activity). It has been shown that sleep need, measured by delta activity, is genetically determined and associated with a Quantitative Trait Locus (QTL) located on the mouse chromosome 13. By using sleep deprivation and brain transcriptome profiling in three inbred mouse strains showing different responses to sleep loss, we found that Homerla, localized within this QTL region is the best transcrip¬tional marker of sleep need. Interestingly Homerla is primarily involved in the recovery from glutamate-induced neuronal hyperactivity by its buffering effect on intracellular cal¬cium. A fundamental function of sleep may therefore reside in the protection and recovery of the brain from a neuronal hyperactivity imposed by prolonged wakefulness.Moreover, time course gene expression experiments showed that 2032 brain tran¬scripts present a rhythmic variation, but only 391 of those remain rhythmic when mice are sleep deprived at four time points around the clock. This finding clearly suggests that most changes in gene transcription over the day are sleep-wake dependent rather than clock dependent and underlines the importance of sleep in mammalian physiology.In the second part of this PhD, I was interested in the social influence on circadian behavior. Most experiments done in the circadian field have been performed on isolated individuals and have therefore ignored the effect of the social context on circadian behav-ior. Eusocial insect species such as ants are characterized by a division of labor: colony tasks are distributed among individuals, some of them requiring continuous activity such as nursing or rhythmic ones such as foraging. Thus ants represent a suitable model to study the influence of the social context on the circadian clock and its output rhythms.The aim of this part was to address the effect of social context on circadian rhythms in the ant species Camponotus fellah and to characterize its circadian clock at the molecu¬lar level. We therefore developed a video tracking system to follow the locomotor activity of all individuals in a colony. Our results show that most ants are arrhythmic within the colony, but develop, when subjected to social isolation, strong rhythms of activity that intriguingly disappear when individuals are reintroduced into the colony. The rhythmicity observed in isolated ants seems to be driven by the circadian clock as it persists under constant conditions (complete darkness). We then tested whether the apparent arrhyth- micity in the colony stemmed from a masking effect of social interactions on circadian rhythms. Indeed, we found that circadian clocks of ants in the colony are functional but their expression at the behavioral level is inhibited by social interactions. The molecular assessment of the circadian clock functional state in the different social context is still under investigation. Our results suggest that social context is a major determinant of circadian behavior in ants.

The Early Toarcian anoxia, a synchronous event in the Western Tethys? An approach by quantitative biochronology (Unitary Associations), applied on calcareous nannofossils

During the Early Toarcian, major paleoenvironnemental and paleoceanographical changes occurred, leading to an oceanic anoxic event (OAE) and to a perturbation of the carbon isotope cycle. Although the standard biochronology of the Lower Jurassic is essentially based upon ammonites, in recent years biostratigraphy based on calcareous nannofossils and dinoflagellate cysts is increasingly used to date Jurassic rocks. However, the precise dating and correlation of the Early Toarcian OAE, and of the associated delta C-13 anomaly in different settings of the western Tethys, are still partly problematic, and it is still unclear whether these events are synchronous or not. In order to allow more accurate correlations of the organic rich levels recorded in the Lower Toarcian OAE, this account proposes a new biozonation based on a quantitative biochronology approach, the Unitary Associations (UA), applied to calcareous nannofossils. This study represents the first attempt to apply the UA method to Jurassic nannofossils. The study incorporates eighteen sections distributed across western Tethys and ranging from the Pliensbachian to Aalenian, comprising 1220 samples and 72 calcareous nannofossil taxa. The BioGraph [Savary, J., Guex, J., 1999. Discrete biochronological scales and unitary associations: description of the Biograph Computer program. Memoires de Geologie de Lausanne 34, 282 pp] and UA-Graph (Copyright Hammer O., Guex and Savary, 2002) softwares provide a discrete biochronological framework based upon multi-taxa concurrent range zones in the different sections. The optimized dataset generates nine UAs using the co-occurrences of 56 taxa. These UAs are grouped into six Unitary Association Zones (UA-Z), which constitute a robust biostratigraphic synthesis of all the observed or deduced biostratigraphic relationships between the analysed taxa. The UA zonation proposed here is compared to ``classic'' calcareous nannofossil biozonations, which are commonly used for the southern and the northern sides of Tethys. The biostratigraphic resolution of the UA-Zones varies from one nannofossil subzone or part of it to several subzones, and can be related to the pattern of calcareous nannoplankton originations and extinctions during the studied time interval. The Late Pliensbachian - Early Toarcian interval (corresponding to the UA-Z II) represents a major step in the Jurassic nannoplankton radiation. The recognized UA-Zones are also compared to the carbon isotopic negative excursion and TOC maximum in five sections of central Italy, Germany and England, with the aim of providing a more reliable correlation tool for the Early Toarcian OAE, and of the associated isotopic anomaly, between the southern and northern part of western Tethys. The results of this work show that the TOC maximum and delta C-13 negative excursion correspond to the upper part of the UA-Z II (i.e., UA 3) in the sections analysed. This suggests that the Early Toarcian OAE was a synchronous event within the western Tethys. (c) 2006 Elsevier B.V. All rights reserved.

Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale

The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by processbased modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM). The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under www.flow-r.org) and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws.We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10m DEM resolution as a good compromise between processing time and quality of results. However, valuable results have still been obtained on the basis of lower quality DEMs with 25m resolution.

An evaluation of new parsimony-based versus parametric inference methods in biogeography: a case study using the globally distributed plant family Sapindaceae

Aim  Recently developed parametric methods in historical biogeography allow researchers to integrate temporal and palaeogeographical information into the reconstruction of biogeographical scenarios, thus overcoming a known bias of parsimony-based approaches. Here, we compare a parametric method, dispersal-extinction-cladogenesis (DEC), against a parsimony-based method, dispersal-vicariance analysis (DIVA), which does not incorporate branch lengths but accounts for phylogenetic uncertainty through a Bayesian empirical approach (Bayes-DIVA). We analyse the benefits and limitations of each method using the cosmopolitan plant family Sapindaceae as a case study.Location  World-wide.Methods  Phylogenetic relationships were estimated by Bayesian inference on a large dataset representing generic diversity within Sapindaceae. Lineage divergence times were estimated by penalized likelihood over a sample of trees from the posterior distribution of the phylogeny to account for dating uncertainty in biogeographical reconstructions. We compared biogeographical scenarios between Bayes-DIVA and two different DEC models: one with no geological constraints and another that employed a stratified palaeogeographical model in which dispersal rates were scaled according to area connectivity across four time slices, reflecting the changing continental configuration over the last 110 million years.Results  Despite differences in the underlying biogeographical model, Bayes-DIVA and DEC inferred similar biogeographical scenarios. The main differences were: (1) in the timing of dispersal events - which in Bayes-DIVA sometimes conflicts with palaeogeographical information, and (2) in the lower frequency of terminal dispersal events inferred by DEC. Uncertainty in divergence time estimations influenced both the inference of ancestral ranges and the decisiveness with which an area can be assigned to a node.Main conclusions  By considering lineage divergence times, the DEC method gives more accurate reconstructions that are in agreement with palaeogeographical evidence. In contrast, Bayes-DIVA showed the highest decisiveness in unequivocally reconstructing ancestral ranges, probably reflecting its ability to integrate phylogenetic uncertainty. Care should be taken in defining the palaeogeographical model in DEC because of the possibility of overestimating the frequency of extinction events, or of inferring ancestral ranges that are outside the extant species ranges, owing to dispersal constraints enforced by the model. The wide-spanning spatial and temporal model proposed here could prove useful for testing large-scale biogeographical patterns in plants.

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.

Detection of Optimal Models in Parameter Space with Support Vector Machines

The paper proposes an approach aimed at detecting optimal model parameter combinations to achieve the most representative description of uncertainty in the model performance. A classification problem is posed to find the regions of good fitting models according to the values of a cost function. Support Vector Machine (SVM) classification in the parameter space is applied to decide if a forward model simulation is to be computed for a particular generated model. SVM is particularly designed to tackle classification problems in high-dimensional space in a non-parametric and non-linear way. SVM decision boundaries determine the regions that are subject to the largest uncertainty in the cost function classification, and, therefore, provide guidelines for further iterative exploration of the model space. The proposed approach is illustrated by a synthetic example of fluid flow through porous media, which features highly variable response due to the parameter values' combination.

Improved HIV-1 RNA quantitation by COBAS AmpliPrep/COBAS TaqMan HIV-1 Test, v2.0 using a novel dual-target approach.

BACKGROUND: HIV-1 RNA viral load is a key parameter for reliable treatment monitoring of HIV-1 infection. Accurate HIV-1 RNA quantitation can be impaired by primer and probe sequence polymorphisms as a result of tremendous genetic diversity and ongoing evolution of HIV-1. A novel dual HIV-1 target amplification approach was realized in the quantitative COBAS AmpliPrep/COBAS TaqMan HIV-1 Test, v2.0 (HIV-1 TaqMan test v2.0) to cope with the high genetic diversity of the virus. OBJECTIVES AND STUDY DESIGN: The performance of the new assay was evaluated for sensitivity, dynamic range, precision, subtype inclusivity, diagnostic and analytical specificity, interfering substances, and correlation with the COBAS AmpliPrep/COBAS TaqMan HIV-1 (HIV-1 TaqMan test v1.0) predecessor test in patients specimens. RESULTS: The new assay demonstrated a sensitivity of 20 copies/mL, a linear measuring range of 20-10,000,000 copies/mL, with a lower limit of quantitation of 20 copies/mL. HIV-1 Group M subtypes and HIV-1 Group O were quantified within +/-0.3 log(10) of the assigned titers. Specificity was 100% in 660 tested specimens, no cross reactivity was found for 15 pathogens nor any interference for endogenous substances or 29 drugs. Good comparability with the predecessor assay was demonstrated in 82 positive patient samples. In selected clinical samples 35/66 specimens were found underquantitated in the predecessor assay; all were quantitated correctly in the new assay. CONCLUSIONS: The dual-target approach for the HIV-1 TaqMan test v2.0 enables superior HIV-1 Group M subtype coverage including HIV-1 Group O detection. Correct quantitation of specimens underquantitated in the HIV-1 TaqMan test v1.0 test was demonstrated.

iLOGP: A Simple, Robust, and Efficient Description of n-Octanol/Water Partition Coefficient for Drug Design Using the GB/SA Approach.

The n-octanol/water partition coefficient (log Po/w) is a key physicochemical parameter for drug discovery, design, and development. Here, we present a physics-based approach that shows a strong linear correlation between the computed solvation free energy in implicit solvents and the experimental log Po/w on a cleansed data set of more than 17,500 molecules. After internal validation by five-fold cross-validation and data randomization, the predictive power of the most interesting multiple linear model, based on two GB/SA parameters solely, was tested on two different external sets of molecules. On the Martel druglike test set, the predictive power of the best model (N = 706, r = 0.64, MAE = 1.18, and RMSE = 1.40) is similar to six well-established empirical methods. On the 17-drug test set, our model outperformed all compared empirical methodologies (N = 17, r = 0.94, MAE = 0.38, and RMSE = 0.52). The physical basis of our original GB/SA approach together with its predictive capacity, computational efficiency (1 to 2 s per molecule), and tridimensional molecular graphics capability lay the foundations for a promising predictor, the implicit log P method (iLOGP), to complement the portfolio of drug design tools developed and provided by the SIB Swiss Institute of Bioinformatics.

Regional specificity of MRI contrast parameter changes in normal ageing revealed by voxel-based quantification (VBQ).

Normal ageing is associated with characteristic changes in brain microstructure. Although in vivo neuroimaging captures spatial and temporal patterns of age-related changes of anatomy at the macroscopic scale, our knowledge of the underlying (patho)physiological processes at cellular and molecular levels is still limited. The aim of this study is to explore brain tissue properties in normal ageing using quantitative magnetic resonance imaging (MRI) alongside conventional morphological assessment. Using a whole-brain approach in a cohort of 26 adults, aged 18-85years, we performed voxel-based morphometric (VBM) analysis and voxel-based quantification (VBQ) of diffusion tensor, magnetization transfer (MT), R1, and R2* relaxation parameters. We found age-related reductions in cortical and subcortical grey matter volume paralleled by changes in fractional anisotropy (FA), mean diffusivity (MD), MT and R2*. The latter were regionally specific depending on their differential sensitivity to microscopic tissue properties. VBQ of white matter revealed distinct anatomical patterns of age-related change in microstructure. Widespread and profound reduction in MT contrasted with local FA decreases paralleled by MD increases. R1 reductions and R2* increases were observed to a smaller extent in overlapping occipito-parietal white matter regions. We interpret our findings, based on current biophysical models, as a fingerprint of age-dependent brain atrophy and underlying microstructural changes in myelin, iron deposits and water. The VBQ approach we present allows for systematic unbiased exploration of the interaction between imaging parameters and extends current methods for detection of neurodegenerative processes in the brain. The demonstrated parameter-specific distribution patterns offer insights into age-related brain structure changes in vivo and provide essential baseline data for studying disease against a background of healthy ageing.

Employment risk, unemployment insurance and search strategies: a disaggregated equilibrium approach with application to the Swiss labour market in the 1990-ies

The Organization of the Thesis The remainder of the thesis comprises five chapters and a conclusion. The next chapter formalizes the envisioned theory into a tractable model. Section 2.2 presents a formal description of the model economy: the individual heterogeneity, the individual objective, the UI setting, the population dynamics and the equilibrium. The welfare and efficiency criteria for qualifying various equilibrium outcomes are proposed in section 2.3. The fourth section shows how the model-generated information can be computed. Chapter 3 transposes the model from chapter 2 in conditions that enable its use in the analysis of individual labor market strategies and their implications for the labor market equilibrium. In section 3.2 the Swiss labor market data sets, stylized facts, and the UI system are presented. The third section outlines and motivates the parameterization method. In section 3.4 the model's replication ability is evaluated and some aspects of the parameter choice are discussed. Numerical solution issues can be found in the appendix. Chapter 4 examines the determinants of search-strategic behavior in the model economy and its implications for the labor market aggregates. In section 4.2, the unemployment duration distribution is examined and related to search strategies. Section 4.3 shows how the search- strategic behavior is influenced by the UI eligibility and section 4.4 how it is determined by individual heterogeneity. The composition effects generated by search strategies in labor market aggregates are examined in section 4.5. The last section evaluates the model's replication of empirical unemployment escape frequencies reported in Sheldon [67]. Chapter 5 applies the model economy to examine the effects on the labor market equilibrium of shocks to the labor market risk structure, to the deep underlying labor market structure and to the UI setting. Section 5.2 examines the effects of the labor market risk structure on the labor market equilibrium and the labor market strategic behavior. The effects of alterations in the labor market deep economic structural parameters, i.e. individual preferences and production technology, are shown in Section 5.3. Finally, the UI setting impacts on the labor market are studied in Section 5.4. This section also evaluates the role of the UI authority monitoring and the differences in the Way changes in the replacement rate and the UI benefit duration affect the labor market. In chapter 6 the model economy is applied in counterfactual experiments to assess several aspects of the Swiss labor market movements in the nineties. Section 6.2 examines the two equilibria characterizing the Swiss labor market in the nineties, the " growth" equilibrium with a "moderate" UI regime and the "recession" equilibrium with a more "generous" UI. Section 6.3 evaluates the isolated effects of the structural shocks, while the isolated effects of the UI reforms are analyzed in section 6.4. Particular dimensions of the UI reforms, the duration, replacement rate and the tax rate effects, are studied in section 6.5, while labor market equilibria without benefits are evaluated in section 6.6. In section 6.7 the structural and institutional interactions that may act as unemployment amplifiers are discussed in view of the obtained results. A welfare analysis based on individual welfare in different structural and UI settings is presented in the eighth section. Finally, the results are related to more favorable unemployment trends after 1997. The conclusion evaluates the features embodied in the model economy with respect to the resulting model dynamics to derive lessons from the model design." The thesis ends by proposing guidelines for future improvements of the model and directions for further research.

Foam pore size is a critical interface parameter of suction-based wound healing devices.

BACKGROUND: Suction-based wound healing devices with open-pore foam interfaces are widely used to treat complex tissue defects. The impact of changes in physicochemical parameters of the wound interfaces has not been investigated. METHODS: Full-thickness wounds in diabetic mice were treated with occlusive dressing or a suction device with a polyurethane foam interface varying in mean pore size diameter. Wound surface deformation on day 2 was measured on fixed tissues. Histologic cross-sections were analyzed for granulation tissue thickness (hematoxylin and eosin), myofibroblast density (α-smooth muscle actin), blood vessel density (platelet endothelial cell adhesion molecule-1), and cell proliferation (Ki67) on day 7. RESULTS: Polyurethane foam-induced wound surface deformation increased with polyurethane foam pore diameter: 15 percent (small pore size), 60 percent (medium pore size), and 150 percent (large pore size). The extent of wound strain correlated with granulation tissue thickness that increased 1.7-fold in small pore size foam-treated wounds, 2.5-fold in medium pore size foam-treated wounds, and 4.9-fold in large pore size foam-treated wounds (p < 0.05) compared with wounds treated with an occlusive dressing. All polyurethane foams increased the number of myofibroblasts over occlusive dressing, with maximal presence in large pore size foam-treated wounds compared with all other groups (p < 0.05). CONCLUSIONS: The pore size of the interface material of suction devices has a significant impact on the wound healing response. Larger pores increased wound surface strain, tissue growth, and transformation of contractile cells. Modification of the pore size is a powerful approach for meeting biological needs of specific wounds.

Toxic substances in blood: an analysis of current recommendations under a Bayesian (decision) approach

This article extends existing discussion in literature on probabilistic inference and decision making with respect to continuous hypotheses that are prevalent in forensic toxicology. As a main aim, this research investigates the properties of a widely followed approach for quantifying the level of toxic substances in blood samples, and to compare this procedure with a Bayesian probabilistic approach. As an example, attention is confined to the presence of toxic substances, such as THC, in blood from car drivers. In this context, the interpretation of results from laboratory analyses needs to take into account legal requirements for establishing the 'presence' of target substances in blood. In a first part, the performance of the proposed Bayesian model for the estimation of an unknown parameter (here, the amount of a toxic substance) is illustrated and compared with the currently used method. The model is then used in a second part to approach-in a rational way-the decision component of the problem, that is judicial questions of the kind 'Is the quantity of THC measured in the blood over the legal threshold of 1.5 μg/l?'. This is pointed out through a practical example.

Impacts of climate change on Swiss biodiversity: An indicator taxa approach

We present a new indicator taxa approach to the prediction of climate change effects on biodiversity at the national level in Switzerland. As indicators, we select a set of the most widely distributed species that account for 95% of geographical variation in sampled species richness of birds, butterflies, and vascular plants. Species data come from a national program designed to monitor spatial and temporal trends in species richness. We examine some opportunities and limitations in using these data. We develop ecological niche models for the species as functions of both climate and land cover variables. We project these models to the future using climate predictions that correspond to two IPCC 3rd assessment scenarios for the development of 'greenhouse' gas emissions. We find that models that are calibrated with Swiss national monitoring data perform well in 10-fold cross-validation, but can fail to capture the hot-dry end of environmental gradients that constrain some species distributions. Models for indicator species in all three higher taxa predict that climate change will result in turnover in species composition even where there is little net change in predicted species richness. Indicator species from high elevations lose most areas of suitable climate even under the relatively mild B2 scenario. We project some areas to increase in the number of species for which climate conditions are suitable early in the current century, but these areas become less suitable for a majority of species by the end of the century. Selection of indicator species based on rank prevalence results in a set of models that predict observed species richness better than a similar set of species selected based on high rank of model AUC values. An indicator species approach based on selected species that are relatively common may facilitate the use of national monitoring data for predicting climate change effects on the distribution of biodiversity.