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.

Integration of local-scale hydrological and regional-scale geophysical based on a nonlinear Bayesian sequential simulation approach

Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the regional scale represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed a downscaling procedure based on a non-linear Bayesian sequential simulation approach. The basic objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity, which is available throughout the model space. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariate kernel density function. This method is then applied to the stochastic integration of low-resolution, re- gional-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities. Finally, the overall viability of this downscaling approach is tested and verified by performing and comparing flow and transport simulation through the original and the downscaled hydraulic conductivity fields. Our results indicate that the proposed procedure does indeed allow for obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

Role of the V-ATPase in regulation of the vacuolar fission-fusion equilibrium.

Like numerous other eukaryotic organelles, the vacuole of the yeast Saccharomyces cerevisiae undergoes coordinated cycles of membrane fission and fusion in the course of the cell cycle and in adaptation to environmental conditions. Organelle fission and fusion processes must be balanced to ensure organelle integrity. Coordination of vacuole fission and fusion depends on the interactions of vacuolar SNARE proteins and the dynamin-like GTPase Vps1p. Here, we identify a novel factor that impinges on the fusion-fission equilibrium: the vacuolar H(+)-ATPase (V-ATPase) performs two distinct roles in vacuole fission and fusion. Fusion requires the physical presence of the membrane sector of the vacuolar H(+)-ATPase sector, but not its pump activity. Vacuole fission, in contrast, depends on proton translocation by the V-ATPase. Eliminating proton pumping by the V-ATPase either pharmacologically or by conditional or constitutive V-ATPase mutations blocked salt-induced vacuole fragmentation in vivo. In living cells, fission defects are epistatic to fusion defects. Therefore, mutants lacking the V-ATPase display large single vacuoles instead of multiple smaller vacuoles, the phenotype that is generally seen in mutants having defects only in vacuolar fusion. Its dual involvement in vacuole fission and fusion suggests the V-ATPase as a potential regulator of vacuolar morphology and membrane dynamics.

Implementing statistical learning methods through Bayesian networks. Part 1: a guide to Bayesian parameter estimation using forensic science data

As a thorough aggregation of probability and graph theory, Bayesian networks currently enjoy widespread interest as a means for studying factors that affect the coherent evaluation of scientific evidence in forensic science. Paper I of this series of papers intends to contribute to the discussion of Bayesian networks as a framework that is helpful for both illustrating and implementing statistical procedures that are commonly employed for the study of uncertainties (e.g. the estimation of unknown quantities). While the respective statistical procedures are widely described in literature, the primary aim of this paper is to offer an essentially non-technical introduction on how interested readers may use these analytical approaches - with the help of Bayesian networks - for processing their own forensic science data. Attention is mainly drawn to the structure and underlying rationale of a series of basic and context-independent network fragments that users may incorporate as building blocs while constructing larger inference models. As an example of how this may be done, the proposed concepts will be used in a second paper (Part II) for specifying graphical probability networks whose purpose is to assist forensic scientists in the evaluation of scientific evidence encountered in the context of forensic document examination (i.e. results of the analysis of black toners present on printed or copied documents).

Wide resection of the lateral malleolus and adjacent tibial, talar and calcanear bones with ankle fusion and allograft reconstruction for an osteosarcoma.

Introduction: Primary bone sarcomas around the ankle are rare. Due to the proximity of neurovascular structures and limited soft tissue reserves, limb salvage is often not possible. Case report: A 19 yo male presented with pain and a progressive swelling of his ankle. X-rays revealed cortical erosions and an extensive periosteal reaction (sunburst) of the distal fibula. MRI showed a large mass of the fibula invading adjacent soft tissue. The lesion appeared close to the ankle joint, but with the articular cartilage as a barrier and without joint effusion. Core-needle biopsy revealed a high-grade chondroblastic osteosarcoma. No metastases were detected. After presentation at our multidisciplinary sarcoma board, the patient was subjected to neo-adjuvant chemotherapy (AOST 03-331). Without any sign of intra-articular contamination of the ankle joint, surgical treatment consisted of wide resection of the lateral malleolus including a large skin patch, the distal third of the fibula, the lateral surfaces of the tibia and talus as well as the insertion of the lateral ligament on the calcaneus. The distal parts of the anterior, peroneal, and posterior muscular compartments were resected en bloc with the tumor. The defect was reconstructed with tibio-talar and talo-calcanear fusion, bony allograft and a plate. Soft-tissue coverage was achieved with a free fascio-cutaneous flap from the controlateral thigh. Histological analysis revealed clear margins and 50% of tumor necrosis. The oncologic treatment was completed with adjuvant chemotherapy. Conclusion: Wide resection and reconstruction of the lateral malleolus is technically demanding but possible in selected cases. Despite some important functional loss, limb salvage is superior to an amputation.

Model-based Segmentation and Image Fusion of 3D Computed Tomography and 3D Ultrasound of the Eye for Radiotherapy Planning

For radiotherapy treatment planning of retinoblastoma inchildhood, Computed Tomography (CT) represents thestandard method for tumor volume delineation, despitesome inherent limitations. CT scan is very useful inproviding information on physical density for dosecalculation and morphological volumetric information butpresents a low sensitivity in assessing the tumorviability. On the other hand, 3D ultrasound (US) allows ahigh accurate definition of the tumor volume thanks toits high spatial resolution but it is not currentlyintegrated in the treatment planning but used only fordiagnosis and follow-up. Our ultimate goal is anautomatic segmentation of gross tumor volume (GTV) in the3D US, the segmentation of the organs at risk (OAR) inthe CT and the registration of both. In this paper, wepresent some preliminary results in this direction. Wepresent 3D active contour-based segmentation of the eyeball and the lens in CT images; the presented approachincorporates the prior knowledge of the anatomy by usinga 3D geometrical eye model. The automated segmentationresults are validated by comparing with manualsegmentations. Then, for the fusion of 3D CT and USimages, we present two approaches: (i) landmark-basedtransformation, and (ii) object-based transformation thatmakes use of eye ball contour information on CT and USimages.

ABCtoolbox: a versatile toolkit for approximate Bayesian computations.

BACKGROUND: The estimation of demographic parameters from genetic data often requires the computation of likelihoods. However, the likelihood function is computationally intractable for many realistic evolutionary models, and the use of Bayesian inference has therefore been limited to very simple models. The situation changed recently with the advent of Approximate Bayesian Computation (ABC) algorithms allowing one to obtain parameter posterior distributions based on simulations not requiring likelihood computations. RESULTS: Here we present ABCtoolbox, a series of open source programs to perform Approximate Bayesian Computations (ABC). It implements various ABC algorithms including rejection sampling, MCMC without likelihood, a Particle-based sampler and ABC-GLM. ABCtoolbox is bundled with, but not limited to, a program that allows parameter inference in a population genetics context and the simultaneous use of different types of markers with different ploidy levels. In addition, ABCtoolbox can also interact with most simulation and summary statistics computation programs. The usability of the ABCtoolbox is demonstrated by inferring the evolutionary history of two evolutionary lineages of Microtus arvalis. Using nuclear microsatellites and mitochondrial sequence data in the same estimation procedure enabled us to infer sex-specific population sizes and migration rates and to find that males show smaller population sizes but much higher levels of migration than females. CONCLUSION: ABCtoolbox allows a user to perform all the necessary steps of a full ABC analysis, from parameter sampling from prior distributions, data simulations, computation of summary statistics, estimation of posterior distributions, model choice, validation of the estimation procedure, and visualization of the results.

Transition from hemifusion to pore opening is rate limiting for vacuole membrane fusion.

Fusion pore opening and expansion are considered the most energy-demanding steps in viral fusion. Whether this also applies to soluble N-ethyl-maleimide sensitive fusion protein attachment protein receptor (SNARE)- and Rab-dependent fusion events has been unknown. We have addressed the problem by characterizing the effects of lysophosphatidylcholine (LPC) and other late-stage inhibitors on lipid mixing and pore opening during vacuole fusion. LPC inhibits fusion by inducing positive curvature in the bilayer and changing its biophysical properties. The LPC block reversibly prevented formation of the hemifusion intermediate that allows lipid, but not content, mixing. Transition from hemifusion to pore opening was sensitive to guanosine-5'-(gamma-thio)triphosphate. It required the vacuolar adenosine triphosphatase V0 sector and coincided with its transformation. Pore opening was rate limiting for the reaction. As with viral fusion, opening the fusion pore may be the most energy-demanding step for intracellular, SNARE-dependent fusion reactions, suggesting that fundamental aspects of lipid mixing and pore opening are related for both systems.

Mobile robot experimental modeling and control strategies using sensor fusion

This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational, and research tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system. In this context the research developed includes the visual information as a meaningful source that allows detecting the obstacle position coordinates as well as planning the free obstacle trajectory that should be reached by the robot

Improvement of therapeutic drug monitoring of imatinib by Bayesian prediction of trough levels. Personalized drug dosage

Aims: Plasma concentrations of imatinib differ largely between patients despite same dosage, owing to large inter-individual variability in pharmacokinetic (PK) parameters. As the drug concentration at the end of the dosage interval (Cmin) correlates with treatment response and tolerability, monitoring of Cmin is suggested for therapeutic drug monitoring (TDM) of imatinib. Due to logistic difficulties, random sampling during the dosage interval is however often performed in clinical practice, thus rendering the respective results not informative regarding Cmin values.Objectives: (I) To extrapolate randomly measured imatinib concentrations to more informative Cmin using classical Bayesian forecasting. (II) To extend the classical Bayesian method to account for correlation between PK parameters. (III) To evaluate the predictive performance of both methods.Methods: 31 paired blood samples (random and trough levels) were obtained from 19 cancer patients under imatinib. Two Bayesian maximum a posteriori (MAP) methods were implemented: (A) a classical method ignoring correlation between PK parameters, and (B) an extended one accounting for correlation. Both methods were applied to estimate individual PK parameters, conditional on random observations and covariate-adjusted priors from a population PK model. The PK parameter estimates were used to calculate trough levels. Relative prediction errors (PE) were analyzed to evaluate accuracy (one-sample t-test) and to compare precision between the methods (F-test to compare variances).Results: Both Bayesian MAP methods allowed non-biased predictions of individual Cmin compared to observations: (A) - 7% mean PE (CI95% - 18 to 4 %, p = 0.15) and (B) - 4% mean PE (CI95% - 18 to 10 %, p = 0.69). Relative standard deviations of actual observations from predictions were 22% (A) and 30% (B), i.e. comparable to the intraindividual variability reported. Precision was not improved by taking into account correlation between PK parameters (p = 0.22).Conclusion: Clinical interpretation of randomly measured imatinib concentrations can be assisted by Bayesian extrapolation to maximum likelihood Cmin. Classical Bayesian estimation can be applied for TDM without the need to include correlation between PK parameters. Both methods could be adapted in the future to evaluate other individual pharmacokinetic measures correlated to clinical outcomes, such as area under the curve(AUC).

Bayesian-MCMC inversion of time-lapse geophysical data to characterize vadose zone hydraulic behaviour

Geophysical methods have the potential to provide valuable information on hydrological properties in the unsaturated zone. In particular, time-lapse geophysical data, when coupled with a hydrological model and inverted stochastically, may allow for the effective estimation of subsurface hydraulic parameters and their corresponding uncertainties. In this study, we use a Bayesian Markov-chain-Monte-Carlo (MCMC) inversion approach to investigate how much information regarding vadose zone hydraulic properties can be retrieved from time-lapse crosshole GPR data collected at the Arrenaes field site in Denmark during a forced infiltration experiment.

Stomatal analysis of citrus somatic hybrids obtained by protoplast fusion

The objective of this work was to evaluate leaf epidermis morphological characteristics of three citrus somatic hybrids, compared to their parents. Parental and somatic hybrid young leaves were collected and processed for scanning electron microscope observations. Citrus polyploid hybrids have fewer stomata per area and these are larger compared to their diploid parental parents. No differences in internal arrangement of the stomatal cells were detected between parental plants and somatic hybrids. Additional studies may determine if these differences will influence physiological behavior of the plants in the field.