Bayesian Networks and the Value of the Evidence for the Forensic Two-Trace Transfer Problem

Forensic scientists face increasingly complex inference problems for evaluating likelihood ratios (LRs) for an appropriate pair of propositions. Up to now, scientists and statisticians have derived LR formulae using an algebraic approach. However, this approach reaches its limits when addressing cases with an increasing number of variables and dependence relationships between these variables. In this study, we suggest using a graphical approach, based on the construction of Bayesian networks (BNs). We first construct a BN that captures the problem, and then deduce the expression for calculating the LR from this model to compare it with existing LR formulae. We illustrate this idea by applying it to the evaluation of an activity level LR in the context of the two-trace transfer problem. Our approach allows us to relax assumptions made in previous LR developments, produce a new LR formula for the two-trace transfer problem and generalize this scenario to n traces.

Accelerated digestion for high-throughput proteomics analysis of whole bacterial proteomes.

In bottom-up proteomics, rapid and efficient protein digestion is crucial for data reliability. However, sample preparation remains one of the rate-limiting steps in proteomics workflows. In this study, we compared the conventional trypsin digestion procedure with two accelerated digestion protocols based on shorter reaction times and microwave-assisted digestion for the preparation of membrane-enriched protein fractions of the human pathogenic bacterium Staphylococcus aureus. Produced peptides were analyzed by Shotgun IPG-IEF, a methodology relying on separation of peptides by IPG-IEF before the conventional LC-MS/MS steps of shotgun proteomics. Data obtained on two LC-MS/MS platforms showed that accelerated digestion protocols, especially the one relying on microwave irradiation, enhanced the cleavage specificity of trypsin and thus improved the digestion efficiency especially for hydrophobic and membrane proteins. The combination of high-throughput proteomics with accelerated and efficient sample preparation should enhance the practicability of proteomics by reducing the time from sample collection to obtaining the results.

Geochemical compositions of Neogene phosphatic brachiopods: Implications for ancient environmental and marine conditions

Isotopic and trace element compositions of Miocene and Pliocene phosphatic brachiopods (Lingulidae and Discinidae) from southern North Sea, the Central Paratethys and the Atlantic coast of Europe were investigated in order to trace past environmental conditions and marine connections between the northern boreal and the southern subtropical-tropical marine basins. The North Sea genus Glottidia yielded low epsilon(Nd) and high delta O-18(PO4) values through the Mio-Pliocene indicating cold habitat temperature where the local seawater was dominated by the Atlantic Ocean. In contrast, the Middle Miocene Lingulidae and Discinidae of the Paratethys inhabited warm subtropical seawater with the possible influence of the Indian Ocean via the Mediterranean, as supported by their average epsilon(Nd) value of -8.3. The combined geochemical data support a thermal and marine separation of the Paratethys from the North Sea with no direct connection or major exchange of water from the Miocene onwards. The temperature in the Paratethys was very similar to that inferred from brachiopods from the Middle Miocene of western France, but the seawater epsilon(Nd) value here is identical to that of contemporaneous Atlantic Ocean. A Late Miocene lingulid brachiopod from southern Portugal has a high delta O-18(PO4), similar to the specimens investigated from the North Sea, reflecting either a deep water habitat or formation after the onset of major global cooling that resulted in an increased delta O-18 value of seawater. The epsilon(Nd) value of -8.4 for this site is compatible with an influence of Mediterranean outflow. (C) 2012 Elsevier B.V. All rights reserved.

The phylogeography of an alpine leaf beetle: divergence within Oreina elongata spans several ice ages.

The genetic landscape of the European flora and fauna was shaped by the ebb and flow of populations with the shifting ice during Quaternary climate cycles. While this has been well demonstrated for lowland species, less is known about high altitude taxa. Here we analyze the phylogeography of the leaf beetle Oreina elongata from 20 populations across the Alps and Apennines. Three mitochondrial and one nuclear region were sequenced in 64 individuals. Within an mtDNA phylogeny, three of seven subspecies are monophyletic. The species is chemically defended and aposematic, with green and blue forms showing geographic variation and unexpected within-population polymorphism. These warning colors show pronounced east-west geographical structure in distribution, but the phylogeography suggests repeated origin and loss. Basal clades come from the central Alps. Ancestors of other clades probably survived across northern Italy and the northern Adriatic, before separation of eastern, southern and western populations and rapid spread through the western Alps. After reviewing calibrated gene-specific substitution rates in the literature, we use partitioned Bayesian coalescent analysis to date our phylogeography. The major clades diverged long before the last glacial maximum, suggesting that O. elongata persisted many glacial cycles within or at the edges of the Alps and Apennines. When analyzing additional barcoding pairwise distances, we find strong evidence to consider O. elongata as a species complex rather than a single species.

Resident health-related quality of life in Swiss nursing homes.

BACKGROUND: Health-related quality of life (HRQOL) levels and their determinants in those living in nursing homes are unclear. The aim of this study was to investigate different HRQOL domains as a function of the degree of cognitive impairment and to explore associations between them and possible determinants of HRQOL. METHOD: Five HRQOL domains using the Minimum Data Set - Health Status Index (MDS-HSI) were investigated in a large sample of nursing home residents depending on cognitive performance levels derived from the Cognitive Performance Scale. Large effect size associations between clinical variables and the different HRQOL domains were looked for. RESULTS: HRQOL domains are impaired to variable degrees but with similar profiles depending on the cognitive performance level. Basic activities of daily living are a major factor associated with some but not all HRQOL domains and vary little with the degree of cognitive impairment. LIMITATIONS: This study is limited by the general difficulties related to measuring HRQOL in patients with cognitive impairment and the reduced number of variables considered among those potentially influencing HRQOL. CONCLUSION: HRQOL dimensions are not all linearly associated with increasing cognitive impairment in NH patients. Longitudinal studies are required to determine how the different HRQOL domains evolve over time in NH residents.

Assessing the use of very high resolution data to predict species distribution in a mountain environment

Nowadays, Species Distribution Models (SDMs) are a widely used tool. Using different statistical approaches these models reconstruct the realized niche of a species using presence data and a set of variables, often topoclimatic. There utilization range is quite large from understanding single species requirements, to the creation of nature reserve based on species hotspots, or modeling of climate change impact, etc... Most of the time these models are using variables at a resolution of 50km x 50km or 1 km x 1 km. However in some cases these models are used with resolutions below the kilometer scale and thus called high resolution models (100 m x 100 m or 25 m x 25 m). Quite recently a new kind of data has emerged enabling precision up to lm x lm and thus allowing very high resolution modeling. However these new variables are very costly and need an important amount of time to be processed. This is especially the case when these variables are used in complex calculation like models projections over large areas. Moreover the importance of very high resolution data in SDMs has not been assessed yet and is not well understood. Some basic knowledge on what drive species presence-absences is still missing. Indeed, it is not clear whether in mountain areas like the Alps coarse topoclimatic gradients are driving species distributions or if fine scale temperature or topography are more important or if their importance can be neglected when balance to competition or stochasticity. In this thesis I investigated the importance of very high resolution data (2-5m) in species distribution models using either very high resolution topographic, climatic or edaphic variables over a 2000m elevation gradient in the Western Swiss Alps. I also investigated more local responses of these variables for a subset of species living in this area at two precise elvation belts. During this thesis I showed that high resolution data necessitates very good datasets (species and variables for the models) to produce satisfactory results. Indeed, in mountain areas, temperature is the most important factor driving species distribution and needs to be modeled at very fine resolution instead of being interpolated over large surface to produce satisfactory results. Despite the instinctive idea that topographic should be very important at high resolution, results are mitigated. However looking at the importance of variables over a large gradient buffers the importance of the variables. Indeed topographic factors have been shown to be highly important at the subalpine level but their importance decrease at lower elevations. Wether at the mountane level edaphic and land use factors are more important high resolution topographic data is more imporatant at the subalpine level. Finally the biggest improvement in the models happens when edaphic variables are added. Indeed, adding soil variables is of high importance and variables like pH are overpassing the usual topographic variables in SDMs in term of importance in the models. To conclude high resolution is very important in modeling but necessitate very good datasets. Only increasing the resolution of the usual topoclimatic predictors is not sufficient and the use of edaphic predictors has been highlighted as fundamental to produce significantly better models. This is of primary importance, especially if these models are used to reconstruct communities or as basis for biodiversity assessments. -- Ces dernières années, l'utilisation des modèles de distribution d'espèces (SDMs) a continuellement augmenté. Ces modèles utilisent différents outils statistiques afin de reconstruire la niche réalisée d'une espèce à l'aide de variables, notamment climatiques ou topographiques, et de données de présence récoltées sur le terrain. Leur utilisation couvre de nombreux domaines allant de l'étude de l'écologie d'une espèce à la reconstruction de communautés ou à l'impact du réchauffement climatique. La plupart du temps, ces modèles utilisent des occur-rences issues des bases de données mondiales à une résolution plutôt large (1 km ou même 50 km). Certaines bases de données permettent cependant de travailler à haute résolution, par conséquent de descendre en dessous de l'échelle du kilomètre et de travailler avec des résolutions de 100 m x 100 m ou de 25 m x 25 m. Récemment, une nouvelle génération de données à très haute résolution est apparue et permet de travailler à l'échelle du mètre. Les variables qui peuvent être générées sur la base de ces nouvelles données sont cependant très coûteuses et nécessitent un temps conséquent quant à leur traitement. En effet, tout calcul statistique complexe, comme des projections de distribution d'espèces sur de larges surfaces, demande des calculateurs puissants et beaucoup de temps. De plus, les facteurs régissant la distribution des espèces à fine échelle sont encore mal connus et l'importance de variables à haute résolution comme la microtopographie ou la température dans les modèles n'est pas certaine. D'autres facteurs comme la compétition ou la stochasticité naturelle pourraient avoir une influence toute aussi forte. C'est dans ce contexte que se situe mon travail de thèse. J'ai cherché à comprendre l'importance de la haute résolution dans les modèles de distribution d'espèces, que ce soit pour la température, la microtopographie ou les variables édaphiques le long d'un important gradient d'altitude dans les Préalpes vaudoises. J'ai également cherché à comprendre l'impact local de certaines variables potentiellement négligées en raison d'effets confondants le long du gradient altitudinal. Durant cette thèse, j'ai pu monter que les variables à haute résolution, qu'elles soient liées à la température ou à la microtopographie, ne permettent qu'une amélioration substantielle des modèles. Afin de distinguer une amélioration conséquente, il est nécessaire de travailler avec des jeux de données plus importants, tant au niveau des espèces que des variables utilisées. Par exemple, les couches climatiques habituellement interpolées doivent être remplacées par des couches de température modélisées à haute résolution sur la base de données de terrain. Le fait de travailler le long d'un gradient de température de 2000m rend naturellement la température très importante au niveau des modèles. L'importance de la microtopographie est négligeable par rapport à la topographie à une résolution de 25m. Cependant, lorsque l'on regarde à une échelle plus locale, la haute résolution est une variable extrêmement importante dans le milieu subalpin. À l'étage montagnard par contre, les variables liées aux sols et à l'utilisation du sol sont très importantes. Finalement, les modèles de distribution d'espèces ont été particulièrement améliorés par l'addition de variables édaphiques, principalement le pH, dont l'importance supplante ou égale les variables topographique lors de leur ajout aux modèles de distribution d'espèces habituels.