How does the body-scale model affect back-calculated growth: the example of arctic charr Salvelinus alpinus (L.) of Lake Geneva (Switzerland)

When back-calculating fish length from scale measurements, the choice of the body-scale relationship is a fundamental step. Using data from the arctic charrSalvelinus alpinus (L.) of Lake Geneva (Switzerland) we show the need for a curvilinear model, on both statistical and biological grounds. From several 2-parameters models, the log-linear relationship appears to provide the best fit. A 3-parameters, Bertalanffy model did not improve the fit. We show moreover that using the proportional model would lead to important misinterpretations of the data.

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.

Preparation with fasting and acipimox increases myocardial glucose uptake in mice during cardiac 18F-FDG microPET

Purpose: Cardiac 18F-FDG PET is considered as the gold standard to assess myocardial metabolism and infarct size. The myocardial demand for glucose can be influenced by fasting and/or following pharmacological preparation. In the rat, it has been previously shown that fasting combined with preconditioning with acipimox, a nicotinic acid derivate and lipidlowering agent, increased dramatically 18F-FDG uptake in the myocardium. Strategies aimed at reducing infarct scar are evaluated in a variety of mouse models. PET would particularly useful for assessing cardiac viability in the mouse. However, prior knowledge of the best preparation protocol is a prerequisite for accurate measurement of glucose uptake in mice. Therefore, we studied the effect of different protocols on 18F-FDG uptake in the mouse heart.Methods: Mice (n = 15) were separated into three treatment groups according to preconditioning and underwent a 18FDG PET scan. Group 1: No preconditioning (n = 3); Group 2: Overnight fasting (n = 8); and Group 3: Overnight fasting and acipimox (25mg/kg SC) (n = 4). MicroPET images were processed with PMOD to determine 18F-FDG mean standard uptake value (SUV) at 30 min for the whole left ventricle (LV) and for each region of the 17-segments AHA model. For comparisons, we used Mann-Whitney test and multilevel mixed-effects linear regression (Stata 11.0).Results: In total, 27 microPET were performed successfully in 15 animals. Overnight fasting led to a dramatic increase in LV-SUV compared to mice without preconditioning (8.6±0.7g/mL vs. 3.7±1.1g/mL, P<0.001). In addition, LV-SUV was slightly but not significantly higher in animals treated with acipimox compared to animals with overnight fasting alone (10.2±0.5 g/mL, P = 0.06). Fastening increased segmental SUV by 5.1±0.5g/mL as compared to free-feeding mice (from 3.7±0.8g/mL to 8.8±0.4g/mL, P<0.001); segmental-SUV also significantly increased after administration of acipimox (from 8.8±0.4g/mL to 10.1±0.4g/mL, P<0.001).Conclusion: Overnight fasting led to myocardial glucose deprivation and increases 18F-FDG myocardial uptake. Additional administration of acipimox enhances myocardial 18F-FDG uptake, at least at the segmental level. Thus, preconditioning with acipimox may provide better image quality that may help for assessing segmental myocardial metabolism.

A modular magnetic anastomotic device for minimally invasive digestive anastomosis: proof of concept and preliminary data in the pig model.

BACKGROUND: The aim of our study was to assess the feasibility of minimally invasive digestive anastomosis using a modular flexible magnetic anastomotic device made up of a set of two flexible chains of magnetic elements. The assembly possesses a non-deployed linear configuration which allows it to be introduced through a dedicated small-sized applicator into the bowel where it takes the deployed form. A centering suture allows the mating between the two parts to be controlled in order to include the viscerotomy between the two magnetic rings and the connected viscera. METHODS AND PROCEDURES: Eight pigs were involved in a 2-week survival experimental study. In five colorectal anastomoses, the proximal device was inserted by a percutaneous endoscopic technique, and the colon was divided below the magnet. The distal magnet was delivered transanally to connect with the proximal magnet. In three jejunojejunostomies, the first magnetic chain was injected in its linear configuration through a small enterotomy. Once delivered, the device self-assembled into a ring shape. A second magnet was injected more distally through the same port. The centering sutures were tied together extracorporeally and, using a knot pusher, magnets were connected. Ex vivo strain testing to determine the compression force delivered by the magnetic device, burst pressure of the anastomosis, and histology were performed. RESULTS: Mean operative time including endoscopy was 69.2 ± 21.9 min, and average time to full patency was 5 days for colorectal anastomosis. Operative times for jejunojejunostomies were 125, 80, and 35 min, respectively. The postoperative period was uneventful. Burst pressure of all anastomoses was ≥ 110 mmHg. Mean strain force to detach the devices was 6.1 ± 0.98 and 12.88 ± 1.34 N in colorectal and jejunojejunal connections, respectively. Pathology showed a mild-to-moderate inflammation score. CONCLUSIONS: The modular magnetic system showed enormous potential to create minimally invasive digestive anastomoses, and may represent an alternative to stapled anastomoses, being easy to deliver, effective, and low cost.

Resting-State Functional Connectivity Emerges from Structurally and Dynamically Shaped Slow Linear Fluctuations.

Brain fluctuations at rest are not random but are structured in spatial patterns of correlated activity across different brain areas. The question of how resting-state functional connectivity (FC) emerges from the brain's anatomical connections has motivated several experimental and computational studies to understand structure-function relationships. However, the mechanistic origin of resting state is obscured by large-scale models' complexity, and a close structure-function relation is still an open problem. Thus, a realistic but simple enough description of relevant brain dynamics is needed. Here, we derived a dynamic mean field model that consistently summarizes the realistic dynamics of a detailed spiking and conductance-based synaptic large-scale network, in which connectivity is constrained by diffusion imaging data from human subjects. The dynamic mean field approximates the ensemble dynamics, whose temporal evolution is dominated by the longest time scale of the system. With this reduction, we demonstrated that FC emerges as structured linear fluctuations around a stable low firing activity state close to destabilization. Moreover, the model can be further and crucially simplified into a set of motion equations for statistical moments, providing a direct analytical link between anatomical structure, neural network dynamics, and FC. Our study suggests that FC arises from noise propagation and dynamical slowing down of fluctuations in an anatomically constrained dynamical system. Altogether, the reduction from spiking models to statistical moments presented here provides a new framework to explicitly understand the building up of FC through neuronal dynamics underpinned by anatomical connections and to drive hypotheses in task-evoked studies and for clinical applications.

A multilevel multiscale finite volume method

The Multiscale Finite Volume (MsFV) method has been developed to efficiently solve reservoir-scale problems while conserving fine-scale details. The method employs two grid levels: a fine grid and a coarse grid. The latter is used to calculate a coarse solution to the original problem, which is interpolated to the fine mesh. The coarse system is constructed from the fine-scale problem using restriction and prolongation operators that are obtained by introducing appropriate localization assumptions. Through a successive reconstruction step, the MsFV method is able to provide an approximate, but fully conservative fine-scale velocity field. For very large problems (e.g. one billion cell model), a two-level algorithm can remain computational expensive. Depending on the upscaling factor, the computational expense comes either from the costs associated with the solution of the coarse problem or from the construction of the local interpolators (basis functions). To ensure numerical efficiency in the former case, the MsFV concept can be reapplied to the coarse problem, leading to a new, coarser level of discretization. One challenge in the use of a multilevel MsFV technique is to find an efficient reconstruction step to obtain a conservative fine-scale velocity field. In this work, we introduce a three-level Multiscale Finite Volume method (MlMsFV) and give a detailed description of the reconstruction step. Complexity analyses of the original MsFV method and the new MlMsFV method are discussed, and their performances in terms of accuracy and efficiency are compared.

Violent adolescents and their educational environment: a multilevel analysis.

OBJECTIVE: This study examined the respective roles of personal and environmental factors in youth violence in a nationally representative sample of 7548 postmandatory school students and apprentices ages 16-20 years in Switzerland. METHODS: Youth violence was defined as having committed at least one of the following in the previous 12 months: attacking an adult, snatching something, carrying a weapon, or using a weapon in a fight. Different ecological levels were tested, resulting in a three-level model only in males (individual, classroom, and school) as the low prevalence of female violence did not allow for a multilevel analysis. Dependent variables were attributed to each level. For males, the classroom level (10%) and the school level (24%) accounted for more than one third in interindividual variance. RESULTS: Factors associated with violence perpetration in females were being a victim of physical violence and sensation seeking at the individual level. In males, practicing unsafe sex, sensation seeking, being a victim of physical violence, having a poor relationship with parents, being depressed, and living in a single-parent household at the individual level; violence and antisocial acts at the classroom level; and being in a vocational school at the school level showed a correlation with violence perpetration. CONCLUSION: Interventions at the classroom level as well as an explicit school policy on violence and other risk behaviors should be considered a priority when dealing with the problem of youth violence. Furthermore, prevention should take into account gender differences.

Update on the non-prewhitening model observer in computed tomography for the assessment of the adaptive statistical and model-based iterative reconstruction algorithms.

The state of the art to describe image quality in medical imaging is to assess the performance of an observer conducting a task of clinical interest. This can be done by using a model observer leading to a figure of merit such as the signal-to-noise ratio (SNR). Using the non-prewhitening (NPW) model observer, we objectively characterised the evolution of its figure of merit in various acquisition conditions. The NPW model observer usually requires the use of the modulation transfer function (MTF) as well as noise power spectra. However, although the computation of the MTF poses no problem when dealing with the traditional filtered back-projection (FBP) algorithm, this is not the case when using iterative reconstruction (IR) algorithms, such as adaptive statistical iterative reconstruction (ASIR) or model-based iterative reconstruction (MBIR). Given that the target transfer function (TTF) had already shown it could accurately express the system resolution even with non-linear algorithms, we decided to tune the NPW model observer, replacing the standard MTF by the TTF. It was estimated using a custom-made phantom containing cylindrical inserts surrounded by water. The contrast differences between the inserts and water were plotted for each acquisition condition. Then, mathematical transformations were performed leading to the TTF. As expected, the first results showed a dependency of the image contrast and noise levels on the TTF for both ASIR and MBIR. Moreover, FBP also proved to be dependent of the contrast and noise when using the lung kernel. Those results were then introduced in the NPW model observer. We observed an enhancement of SNR every time we switched from FBP to ASIR to MBIR. IR algorithms greatly improve image quality, especially in low-dose conditions. Based on our results, the use of MBIR could lead to further dose reduction in several clinical applications.

A random linear functional approach to efficiency bounds

This paper suggests a method for obtaining efficiency bounds in models containing either only infinite-dimensional parameters or both finite- and infinite-dimensional parameters (semiparametric models). The method is based on a theory of random linear functionals applied to the gradient of the log-likelihood functional and is illustrated by computing the lower bound for Cox's regression model

Measuring the relative effect of factors affecting species distribution model predictions

1. Species distribution models are increasingly used to address conservation questions, so their predictive capacity requires careful evaluation. Previous studies have shown how individual factors used in model construction can affect prediction. Although some factors probably have negligible effects compared to others, their relative effects are largely unknown. 2. We introduce a general "virtual ecologist" framework to study the relative importance of factors involved in the construction of species distribution models. 3. We illustrate the framework by examining the relative importance of five key factors-a missing covariate, spatial autocorrelation due to a dispersal process in presences/absences, sample size, sampling design and modeling technique-in a real study framework based on plants in a mountain landscape at regional scale, and show that, for the parameter values considered here, most of the variation in prediction accuracy is due to sample size and modeling technique. Contrary to repeatedly reported concerns, spatial autocorrelation has only comparatively small effects. 4. This study shows the importance of using a nested statistical framework to evaluate the relative effects of factors that may affect species distribution models.

An active strain electromechanical model for cardiac tissue

We propose a finite element approximation of a system of partial differential equations describing the coupling between the propagation of electrical potential and large deformations of the cardiac tissue. The underlying mathematical model is based on the active strain assumption, in which it is assumed that a multiplicative decomposition of the deformation tensor into a passive and active part holds, the latter carrying the information of the electrical potential propagation and anisotropy of the cardiac tissue into the equations of either incompressible or compressible nonlinear elasticity, governing the mechanical response of the biological material. In addition, by changing from an Eulerian to a Lagrangian configuration, the bidomain or monodomain equations modeling the evolution of the electrical propagation exhibit a nonlinear diffusion term. Piecewise quadratic finite elements are employed to approximate the displacements field, whereas for pressure, electrical potentials and ionic variables are approximated by piecewise linear elements. Various numerical tests performed with a parallel finite element code illustrate that the proposed model can capture some important features of the electromechanical coupling, and show that our numerical scheme is efficient and accurate.

A Population-Based Model to Consider the Effect of Seasonal Variation on Serum 25(OH)D and Vitamin D Status.

Background. We elaborated a model that predicts the centiles of the 25(OH)D distribution taking into account seasonal variation. Methods. Data from two Swiss population-based studies were used to generate (CoLaus) and validate (Bus Santé) the model. Serum 25(OH)D was measured by ultra high pressure LC-MS/MS and immunoassay. Linear regression models on square-root transformed 25(OH)D values were used to predict centiles of the 25(OH)D distribution. Distribution functions of the observations from the replication set predicted with the model were inspected to assess replication. Results. Overall, 4,912 and 2,537 Caucasians were included in original and replication sets, respectively. Mean (SD) 25(OH)D, age, BMI, and % of men were 47.5 (22.1) nmol/L, 49.8 (8.5) years, 25.6 (4.1) kg/m(2), and 49.3% in the original study. The best model included gender, BMI, and sin-cos functions of measurement day. Sex- and BMI-specific 25(OH)D centile curves as a function of measurement date were generated. The model estimates any centile of the 25(OH)D distribution for given values of sex, BMI, and date and the quantile corresponding to a 25(OH)D measurement. Conclusions. We generated and validated centile curves of 25(OH)D in the general adult Caucasian population. These curves can help rank vitamin D centile independently of when 25(OH)D is measured.