Comparison of the Legiolert™/Quanti-Tray® MPN test for the enumeration of Legionella pneumophila from potable water samples with the German regulatory requirements methods ISO 11731-2 and ISO 11731.

Due to the promising results of a previous study of the performance of the novel MPN method (Legiolert™/Quanti-Tray®) compared to ISO 11731-2, this study was performed to compare Legiolert for Legionella pneumophila with the German regulatory requirements methods ISO 11731-2 (100 ml membrane filtration) and ISO 11731 (1 ml direct plating) for the enumeration of L. pneumophila and Legionella spp. from potable water. Data from a multi-laboratory study according to ISO 17994 showed that Legiolert yielded on average higher counts of L. pneumophila than the ISO 11731-2 method, but the comparison with ISO 11731 was inconclusive due to the number of samples needing to be tested. Likewise, comparisons of the MPN method for 100 ml to the highest result of either ISO 11731 or ISO 11731-2 according to Federal Environmental Agency recommendation (2012) yielded no conclusive difference, regardless of whether non-pneumophila species of Legionella were included in the evaluation. The MPN method has a high specificity for L. pneumophila of 97.9% which compares favourably to the specificity of 95.3% quoted for ISO 11731. The new method represents a significant improvement in the enumeration of L. pneumophila from drinking water and related samples.

Determination of Permeability Coefficients of Polymersomal Membranes for Hydrophilic Molecules.

Polymer vesicles, so-called polymersomes, can be applied as carrier-systems and universal reaction compartments, due to the possibility to encapsulate guest molecules. Compared to common lipid vesicles, polymersomes show an increased stability and decreased membrane permeability. Control of the mass transport across the membrane is necessary for any application, requiring the precise knowledge of the permeability. So far, data on permeability coefficients of polymersomal membranes are scarce because commonly applied release assays are confronted with the challenge of high detection limits and alternative methods developed so far are either restricted to the use of a certain permeating molecule or rely on the use of nuclear magnetic resonance measurements. In contrast, an influx assay that is broadly applicable to hydrophilic molecules and does not involve specialized equipment was developed in this work, which is based on the passive diffusion of compounds into initially empty vesicles. The method is valid for hydrophilic molecules that show no membrane retention and, thus, do not accumulate within the membrane. Using this method, the permeability of polymersomes made of poly(2-methyloxazoline)15-poly(dimethylsiloxane)68-poly(2-methyloxazoline)15 for seven model compounds was investigated under varying conditions. Permeability coefficients as low as 1.9 × 10-14 cm s-1 could be measured.

Challenges of Inversely Estimating Jacobian from Metabolomics Data.

Inferring dynamics of metabolic networks directly from metabolomics data provides a promising way to elucidate the underlying mechanisms of biological systems, as reported in our previous studies (Weckwerth, 2011; Sun and Weckwerth, 2012; Nägele et al., 2014) by a differential Jacobian approach. The Jacobian is solved from an overdetermined system of equations as JC + CJ(T) = -2D, called Lyapunov Equation in its generic form, where J is the Jacobian, C is the covariance matrix of metabolomics data, and D is the fluctuation matrix. Lyapunov Equation can be further simplified as the linear form Ax = b. Frequently, this linear equation system is ill-conditioned, i.e., a small variation in the right side b results in a big change in the solution x, thus making the solution unstable and error-prone. At the same time, inaccurate estimation of covariance matrix and uncertainties in the fluctuation matrix bring biases to the solution x. Here, we first reviewed common approaches to circumvent the ill-conditioned problems, including total least squares, Tikhonov regularization, and truncated singular value decomposition. Then, we benchmarked these methods on several in silico kinetic models with small to large perturbations on the covariance and fluctuation matrices. The results identified that the accuracy of the reverse Jacobian is mainly dependent on the condition number of A, the perturbation amplitude of C, and the stiffness of the kinetic models. Our research contributes a systematical comparison of methods to inversely solve Jacobian from metabolomics data.

Modeling of leishmaniasis infection dynamics: novel application to the design of effective therapies.

BACKGROUND: The WHO considers leishmaniasis as one of the six most important tropical diseases worldwide. It is caused by parasites of the genus Leishmania that are passed on to humans and animals by the phlebotomine sandfly. Despite all of the research, there is still a lack of understanding on the metabolism of the parasite and the progression of the disease. In this study, a mathematical model of disease progression was developed based on experimental data of clinical symptoms, immunological responses, and parasite load for Leishmania amazonensis in BALB/c mice. RESULTS: Four biologically significant variables were chosen to develop a differential equation model based on the GMA power-law formalism. Parameters were determined to minimize error in the model dynamics and time series experimental data. Subsequently, the model robustness was tested and the model predictions were verified by comparing them with experimental observations made in different experimental conditions. The model obtained helps to quantify relationships between the selected variables, leads to a better understanding of disease progression, and aids in the identification of crucial points for introducing therapeutic methods. CONCLUSIONS: Our model can be used to identify the biological factors that must be changed to minimize parasite load in the host body, and contributes to the design of effective therapies.

Increased prevalence of microangiopathic brain lesions among siblings of patients with lacunar stroke. A prospective multicenter study.

BACKGROUND: Family and twin studies suggest predisposing genetic factors in stroke. Lacunar infarcts represent a homogeneous phenotype, which is a prerequisite for genetic analyses. Applying an affected sib -pair analysis, we prospectively assessed the prevalence of microangiopathic brain lesions (MBL) and associated risk factors among siblings of patients with lacunar stroke. METHODS: Index patients fulfilled clinical criteria of a lacunar stroke in combination with a corresponding MBL on CT or MRI. Siblings were characterized as affected if MBL demonstrated on MRI. The prevalence of MBL was compared with population prevalence data extracted from other studies. RESULTS: From 784 patients screened, 81 index patients with lacunar stroke and 97 siblings were recruited, of which 42% were identified as affected. Compared with data from unselected historical controls and stratified by age groups, prevalence was between 2 and 5 times higher. CONCLUSIONS: Our results indicate that genetic stroke studies are feasible even in subtypes of ischemic stroke. The high prevalence of MBL among siblings of patients with lacunar infarct might suggest a familial aggregation. However, due to the small sample size these results need to be interpreted with caution and require confirmation by planned genetic analyses.