Hyperpolarized lithium-6 as a sensor of nanomolar contrast agents.

Lithium is widely used in psychotherapy. The (6)Li isotope has a long intrinsic longitudinal relaxation time T(1) on the order of minutes, making it an ideal candidate for hyperpolarization experiments. In the present study we demonstrated that lithium-6 can be readily hyperpolarized within 30 min, while retaining a long polarization decay time on the order of a minute. We used the intrinsically long relaxation time for the detection of 500 nM contrast agent in vitro. Hyperpolarized lithium-6 was administered to the rat and its signal retained a decay time on the order of 70 sec in vivo. Localization experiments imply that the lithium signal originated from within the brain and that it was detectable up to 5 min after administration. We conclude that the detection of submicromolar contrast agents using hyperpolarized NMR nuclei such as (6)Li may provide a novel avenue for molecular imaging.

Parametric imaging for characterizing focal liver lesions in contrast-enhanced ultrasound.

The differentiation between benign and malignant focal liver lesions plays an important role in diagnosis of liver disease and therapeutic planning of local or general disease. This differentiation, based on characterization, relies on the observation of the dynamic vascular patterns (DVP) of lesions with respect to adjacent parenchyma, and may be assessed during contrast-enhanced ultrasound imaging after a bolus injection. For instance, hemangiomas (i.e., benign lesions) exhibit hyper-enhanced signatures over time, whereas metastases (i.e., malignant lesions) frequently present hyperenhanced foci during the arterial phase and always become hypo-enhanced afterwards. The objective of this work was to develop a new parametric imaging technique, aimed at mapping the DVP signatures into a single image called a DVP parametric image, conceived as a diagnostic aid tool for characterizing lesion types. The methodology consisted in processing a time sequence of images (DICOM video data) using four consecutive steps: (1) pre-processing combining image motion correction and linearization to derive an echo-power signal, in each pixel, proportional to local contrast agent concentration over time; (2) signal modeling, by means of a curve-fitting optimization, to compute a difference signal in each pixel, as the subtraction of adjacent parenchyma kinetic from the echopower signal; (3) classification of difference signals; and (4) parametric image rendering to represent classified pixels as a support for diagnosis. DVP parametric imaging was the object of a clinical assessment on a total of 146 lesions, imaged using different medical ultrasound systems. The resulting sensitivity and specificity were 97% and 91%, respectively, which compare favorably with scores of 81 to 95% and 80 to 95% reported in medical literature for sensitivity and specificity, respectively.

Spatial evaluation of larvae of Culicidae (Diptera) from different breeding sites: application of a geospatial method and implications for vector control

Spatial evaluation of Culicidae (Diptera) larvae from different breeding sites: application of a geospatial method and implications for vector control. This study investigates the spatial distribution of urban Culicidae and informs entomological monitoring of species that use artificial containers as larval habitats. Collections of mosquito larvae were conducted in the São Paulo State municipality of Santa Bárbara d' Oeste between 2004 and 2006 during house-to-house visits. A total of 1,891 samples and nine different species were sampled. Species distribution was assessed using the kriging statistical method by extrapolating municipal administrative divisions. The sampling method followed the norms of the municipal health services of the Ministry of Health and can thus be adopted by public health authorities in disease control and delimitation of risk areas. Moreover, this type of survey and analysis can be employed for entomological surveillance of urban vectors that use artificial containers as larval habitat.

Modeling complex wells with the multi-scale finite-volume method

In this paper, an extension of the multi-scale finite-volume (MSFV) method is devised, which allows to Simulate flow and transport in reservoirs with complex well configurations. The new framework fits nicely into the data Structure of the original MSFV method,and has the important property that large patches covering the whole well are not required. For each well. an additional degree of freedom is introduced. While the treatment of pressure-constraint wells is trivial (the well-bore reference pressure is explicitly specified), additional equations have to be solved to obtain the unknown well-bore pressure of rate-constraint wells. Numerical Simulations of test cases with multiple complex wells demonstrate the ability of the new algorithm to capture the interference between the various wells and the reservoir accurately. (c) 2008 Elsevier Inc. All rights reserved.

Inequalities for a new data-based method for selecting nonparametric density estimates

We continue the development of a method for the selection of a bandwidth or a number of design parameters in density estimation. We provideexplicit non-asymptotic density-free inequalities that relate the $L_1$ error of the selected estimate with that of the best possible estimate,and study in particular the connection between the richness of the classof density estimates and the performance bound. For example, our methodallows one to pick the bandwidth and kernel order in the kernel estimatesimultaneously and still assure that for {\it all densities}, the $L_1$error of the corresponding kernel estimate is not larger than aboutthree times the error of the estimate with the optimal smoothing factor and kernel plus a constant times $\sqrt{\log n/n}$, where $n$ is the sample size, and the constant only depends on the complexity of the family of kernels used in the estimate. Further applications include multivariate kernel estimates, transformed kernel estimates, and variablekernel estimates.

New method for rearing Spodoptera frugiperda in laboratory shows that larval cannibalism is not obligatory

New method for rearing Spodoptera frugiperda in laboratory shows that larval cannibalism is not obligatory. Here we show, for the first time, that larvae of the fall armyworm (FAW), Spodoptera frugiperda (Lepidoptera, Noctuidae), can be successfully reared in a cohort-based manner with virtually no cannibalism. FAW larvae were reared since the second instar to pupation in rectangular plastic containers containing 40 individuals with a surprisingly ca. 90% larval survivorship. Adult females from the cohort-based method showed fecundity similar to that already reported on literature for larvae reared individually, and fertility higher than 99%, with the advantage of combining economy of time, space and material resources. These findings suggest that the factors affecting cannibalism of FAW larvae in laboratory rearings need to be reevaluated, whilst the new technique also show potential to increase the efficiency of both small and mass FAW rearings.

Use of 2D Sensitivity Encoding for Slow-Infusion Contrast-Enhanced Isotropic 3-T Whole-Heart Coronary MR Angiography.

OBJECTIVE. The purpose of this study was to improve the blood-pool signal-to-noise ratio (SNR) and blood-myocardium contrast-to-noise ratio (CNR) of slow-infusion 3-T whole-heart coronary MR angiography (MRA).SUBJECTS AND METHODS. In 2D sensitivity encoding (SENSE), the number of acquired k-space lines is reduced, allowing less radiofrequency excitation per cardiac cycle and a longer TR. The former can be exploited for signal enhancement with a higher radiofrequency excitation angle, and the latter leads to noise reduction due to lower data-sampling bandwidth. Both effects contribute to SNR gain in coronary MRA when spatial and temporal resolution and acquisition time remain identical. Numeric simulation was performed to select the optimal 2D SENSE pulse sequence parameters and predict the SNR gain. Eleven patients underwent conventional unenhanced and the proposed 2D SENSE contrast-enhanced coronary MRA acquisition. Blood-pool SNR, blood-myocardium CNR, visible vessel length, vessel sharpness, and number of side branches were evaluated.RESULTS. Consistent with the numeric simulation, using 2D SENSE in contrast-enhanced coronary MRA resulted in significant improvement in aortic blood-pool SNR (unenhanced vs contrast-enhanced, 37.5 +/- 14.7 vs 121.3 +/- 44.0; p < 0.05) and CNR (14.4 +/- 6.9 vs 101.5 +/- 40.8; p < 0.05) in the patient sample. A longer length of left anterior descending coronary artery was visualized, but vessel sharpness, coronary artery coverage, and image quality score were not improved with the proposed approach.CONCLUSION. In combination with contrast administration, 2D SENSE was found effective in improving SNR and CNR in 3-T whole-heart coronary MRA. Further investigation of cardiac motion compensation is necessary to exploit the SNR and CNR advantages and to achieve submillimeter spatial resolution.

Weighted Euclidean biplots

We construct a weighted Euclidean distance that approximates any distance or dissimilarity measure between individuals that is based on a rectangular cases-by-variables data matrix. In contrast to regular multidimensional scaling methods for dissimilarity data, the method leads to biplots of individuals and variables while preserving all the good properties of dimension-reduction methods that are based on the singular-value decomposition. The main benefits are the decomposition of variance into components along principal axes, which provide the numerical diagnostics known as contributions, and the estimation of nonnegative weights for each variable. The idea is inspired by the distance functions used in correspondence analysis and in principal component analysis of standardized data, where the normalizations inherent in the distances can be considered as differential weighting of the variables. In weighted Euclidean biplots we allow these weights to be unknown parameters, which are estimated from the data to maximize the fit to the chosen distances or dissimilarities. These weights are estimated using a majorization algorithm. Once this extra weight-estimation step is accomplished, the procedure follows the classical path in decomposing the matrix and displaying its rows and columns in biplots.

Testing the response of macroinvertebrate functional structure and biodiversity to flooding and confinement

The aim of the present study was to investigate the relative importance of flooding- and confinement-related environmentalfeatures in explaining macroinvertebrate trait structure and diversity in a pool of wetlands located in a Mediterranean riverfloodplain. To test hypothesized trait-environment relationships, we employed a recently implemented statistical procedure, thefourth-corner method. We found that flooding-related variables, mainly pH and turbidity, were related to traits that confer an abilityof the organism to resist flooding (e.g., small body-shape, protection of eggs) or recuperate faster after flooding (e.g., short life-span, asexual reproduction). In contrast, confinement-related variables, mainly temperature and organic matter, enhanced traits that allow organisms to interact and compete with other organisms (e.g., large size, sexual reproduction) and to efficiently use habitat and resources (e.g., diverse locomotion and feeding strategies). These results are in agreement with predictions made under the River Habitat Templet for lotic ecosystems, and demonstrate the ability of the fourth-corner method to test hypothesis that posit traitenvironment relationships. Trait diversity was slightly higher in flooded than in confined sites, whereas trait richness was not significantly different. This suggests that although trait structure may change in response to the main environmental factors, as evidenced by the fourth-corner method, the number of life-history strategies needed to persist in the face of such constraints remains more or less constant; only their relative dominance differs

Impact of personality on termination of short-term group psychotherapy in depressed elderly outpatients

Objective Termination in group psychotherapy is an essential phase of the psychotherapeutic process, yet its clinical determinants remain largely unknown, especially in elderly patients. The aim of this study was to assess how patients' personality traits influence their way of leaving a short-term psychotherapy group as well as a larger therapeutic community program. <p>Method Personality traits were assessed with the NEO Five-Factor Inventory in 24 elderly depressed outpatients. Patients' terminations from the group as well as from the community were ranked into four classes according to their appropriateness (completeness of experience and ability to deal with feelings of separation). Results Neuroticism was not related to the quality of termination. In contrast, agreeableness and openness to experience were strongly associated with successful termination. Conscientiousness and extraversion may have a differential impact depending on the type of group (group psychotherapy versus therapeutic community). Conclusion Personality traits may be important clinical determinants of the quality of termination process in both group psychotherapy and therapeutic community settings for elderly depressed patients.

Improved statistical analysis of low abundance phenomena in bimodal bacterial populations.

Accurate detection of subpopulation size determinations in bimodal populations remains problematic yet it represents a powerful way by which cellular heterogeneity under different environmental conditions can be compared. So far, most studies have relied on qualitative descriptions of population distribution patterns, on population-independent descriptors, or on arbitrary placement of thresholds distinguishing biological ON from OFF states. We found that all these methods fall short of accurately describing small population sizes in bimodal populations. Here we propose a simple, statistics-based method for the analysis of small subpopulation sizes for use in the free software environment R and test this method on real as well as simulated data. Four so-called population splitting methods were designed with different algorithms that can estimate subpopulation sizes from bimodal populations. All four methods proved more precise than previously used methods when analyzing subpopulation sizes of transfer competent cells arising in populations of the bacterium Pseudomonas knackmussii B13. The methods' resolving powers were further explored by bootstrapping and simulations. Two of the methods were not severely limited by the proportions of subpopulations they could estimate correctly, but the two others only allowed accurate subpopulation quantification when this amounted to less than 25% of the total population. In contrast, only one method was still sufficiently accurate with subpopulations smaller than 1% of the total population. This study proposes a number of rational approximations to quantifying small subpopulations and offers an easy-to-use protocol for their implementation in the open source statistical software environment R.

Buffer Capacity Allocation: A method to QoS support on MPLS networks

This paper describes an optimized model to support QoS by mean of Congestion minimization on LSPs (Label Switching Path). In order to perform this model, we start from a CFA (Capacity and Flow Allocation) model. As this model does not consider the buffer size to calculate the capacity cost, our model- named BCA (Buffer Capacity Allocation)- take into account this issue and it improve the CFA performance. To test our proposal, we perform several simulations; results show that BCA model minimizes LSP congestion and uniformly distributes flows on the network

The profiling of false identity documents: a promising method to fight identity fraud

Under the influence of intelligence-led policing models, crime analysis methods have known of important developments in recent years. Applications have been proposed in several fields of forensic science to exploit and manage various types of material evidence in a systematic and more efficient way. However, nothing has been suggested so far in the field of false identity documents.This study seeks to fill this gap by proposing a simple and general method for profiling false identity documents which aims to establish links based on their visual forensic characteristics. A sample of more than 200 false identity documents including French stolen blank passports, counterfeited driving licenses from Iraq and falsified Bulgarian driving licenses was gathered from nine Swiss police departments and integrated into an ad hoc developed database called ProfID. Links detected automatically and systematically through this database were exploited and analyzed to produce strategic and tactical intelligence useful to the fight against identity document fraud.The profiling and intelligence process established for these three types of false identity documents has confirmed its efficiency, more than 30% of documents being linked. Identity document fraud appears as a structured and interregional criminality, against which material and forensic links detected between false identity documents might serve as a tool for investigation.