8,026 research outputs found

    Contributions to an improved phenytoin monitoring and dosing in hospitalized patients

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    Phenytoin (PHT) is one of the mostly used and well established anticonvulsants for the treatment of epilepsy and a standard in the antiepileptic prophylaxis in adults with severe traumatic brain injuries before and after neurosurgical intervention. Its therapeutic use is challenging as PHT has a narrow therapeutic range and shows non-linear kinetics. It is extensively metabolized by a variety of CYP enzymes. PHT shows 85-95% binding to plasma proteins mostly albumin. This renders PHT also an important drug interaction candidate. Therefore, therapeutic drug monitoring is often required. A rational timing for good interpretation of the lab data translated in optimal individual dosing are necessary. Therapeutic guidance especially in teaching hospitals are needed and have to be implemented. Bayesian Forecasting (BF) versus conventional dosing (CD): a retrospective, long-term, single centre analysis In the hospital, medication management for effective antiepileptic therapy with PHT often needs rapid IV loading and subsequent dose adjustment according to TDM. To investigate PHT performance in reaching therapeutic target serum concentration, a BF regimen was compared to CD, according to the official summary of product characteristics. In a Swiss acute care teaching hospital (Kantonsspital Aarau), a retrospective, single centre, and long-term analysis was assessed by using all PHT serum tests from the central lab from 1997 to 2007. The BF regimen consisted of a guided, body weight-adapted rapid IV PHT loading over five days with pre-defined TDM time points. The CD was applied without written guidance. Assuming non-normally distributed data, non-parametric statistical methods were used. A total of 6’120 PHT serum levels (2’819 BF and 3’301 CD) from 2’589 patients (869 BF and 1’720 CD) were evaluated and compared. 63.6% of the PHT serum levels from the BF group were within the therapeutic range versus only 34.0% in the CD group (p<0.0001). The mean BF serum level was 52.0 ± 22.1 µmol/L (within target range), whereas the mean serum level of the CD was 39.8 ± 28.2 µmol/L (sub-target range). In the BF group, men had small but significantly lower PHT serum levels compared to women (p<0.0001). The CD group showed no significant gender difference (p=0.187). A comparative sub-analysis of age-related groups (children, adolescents, adults, seniors, and elderly) showed significant lower target levels (p<0.0001) for each group in the CD group, compared to BF. Comparing the two groups, BF showed significantly better performance in reaching therapeutic PHT serum levels. Free PHT assessment However, total serum drug levels of difficult-to-dose drugs like PHT are sometimes insufficient. The knowledge of the free fraction is necessary for correct dosing. In a subgroup analysis of the above BF vs. CD study we evaluated the suitability of the Sheiner-Tozer algorithm to calculate the free PHT fraction in hypoalbuminemic patients. Free PHT serum concentrations were calculated from total PHT concentration in hypoalbuminemic patients and compared with the measured free PHT. The patients were separated into two groups (a low albumin group; 35 ≤ albumin ≥ 25 g/L and a very low albumin group; albumin < 25 g/L). These two groups were compared and statistically analysed for the calculated and the measured free PHT concentration. The calculated (1.2 mg/L, SD=0.7) and the measured (1.1 mg/L, SD=0.5) free PHT concentration correlated. The mean difference in the low and the very low albumin group was 0.10 mg/L (SD=1.4, n=11) and 0.13 mg/L (SD=0.24, n=12), respectively. Although the variability of the data could be a bias, no statistically significant difference between the groups was found: t-test (p=0.78), the Passing-Bablok regression, the Spearman’s rank correlation coefficient of r=0.907 and p=0.00, and the Bland-Altman plot including the regression analysis between the calculated and the measured value (M=0.11, SD=0.28). We concluded that in absence of a free PHT serum concentration measurement also in hypoalbuminemic patients, the Sheiner-Tozer algorithm represents a useful tool to assist TDM to calculate or control free PHT by using total PHT and the albumin concentration. GC-MS Analysis of biological PHT samples To correlate PHT blood serum levels, with “brain PHT levels” (the site of action of PHT), extracellular fluid from microdialysates in neurosurgical patients could be analyzed for PHT by an appropriate quantifying analytical method. In this investigation we describe the development and validation of a sensitive gas chromatography–mass spectrometry (GC–MS) method to identify and quantitate PHT in brain microdialysate, saliva and blood from human samples. For sample clean-up a SPE was performed with a nonpolar C8-SCX column. The eluate was evaporated with nitrogen (50°C) and derivatized with trimethylsulfonium hydroxide before GC-MS analysis. 5-(p-methylphenyl)-5-phenylhydantoin was used as internal standard. The MS was run in scan mode and the identification was made with three ion fragment masses. All peaks were identified with MassLib. Spiked PHT samples showed recovery after SPE of ≥ 94%. The calibration curve (PHT 50 to 1’200 ng/ml, n=6 at six concentration levels) showed good linearity and correlation (r2 > 0.998). The limit of detection was 15 ng/mL, the limit of quantification was 50 ng/mL. Dried extracted samples were stable within a 15% deviation range for ≥ 4 weeks at room temperature. The method met International Organization for Standardization standards and was able to detect and quantify PHT in different biological matrices and patient samples. The GC-MS method with SPE is specific, sensitive, robust and well reproducible and therefore, an appropriate candidate for pharmacokinetic assessment of PHT concentrations in different biological samples of treated patients

    The size and polydispersity of silica nanoparticles under simulated hot spring conditions

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    The nucleation and growth of silica nanoparticles in supersaturated geothermal waters was simulated using a flow-through geothermal simulator system. The effect of silica concentration ([SiO2]), ionic strength (IS), temperature (T) and organic additives on the size and polydispersity of the forming silica nanoparticles was quantified. A decrease in temperature (58 to 33°C) and the addition of glucose restricted particle growth to sizes &#60;20 nm, while varying [SiO2] or ISdid not affect the size (30-35 nm) and polydispersity (±9 nm) observed at 58°C. Conversely, the addition of xanthan gum induced the development of thin films that enhanced silica aggregation

    A literature survey of low-rank tensor approximation techniques

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    During the last years, low-rank tensor approximation has been established as a new tool in scientific computing to address large-scale linear and multilinear algebra problems, which would be intractable by classical techniques. This survey attempts to give a literature overview of current developments in this area, with an emphasis on function-related tensors

    The metagenomics of biosilicification: causes and effects

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    In order to determine the links between geochemical parameters controlling the formation of silica sinter in hot springs and their associated microbial diversity, a detailed characterisation of the waters and of in situ-grown silica sinters was combined with molecular phylogenetic analyses of the bacterial communities in Icelandic geothermal environments. At all but one site, the microorganisms clearly affected, and in part controlled, the formation of the macroscopic textures and structures of silica sinter edifices. In addition, the class and genera level phylogenetic diversity and distribution appeared to be closely linked to variations in temperature, salinity and pH regimes

    Diffusion-based method for producing density equalizing maps

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    Map makers have long searched for a way to construct cartograms -- maps in which the sizes of geographic regions such as countries or provinces appear in proportion to their population or some other analogous property. Such maps are invaluable for the representation of census results, election returns, disease incidence, and many other kinds of human data. Unfortunately, in order to scale regions and still have them fit together, one is normally forced to distort the regions' shapes, potentially resulting in maps that are difficult to read. Many methods for making cartograms have been proposed, some of them extremely complex, but all suffer either from this lack of readability or from other pathologies, like overlapping regions or strong dependence on the choice of coordinate axes. Here we present a new technique based on ideas borrowed from elementary physics that suffers none of these drawbacks. Our method is conceptually simple and produces useful, elegant, and easily readable maps. We illustrate the method with applications to the results of the 2000 US presidential election, lung cancer cases in the State of New York, and the geographical distribution of stories appearing in the news.Comment: 12 pages, 3 figure

    The Quadratic Transportation Problem as a Model of Interregional Migration Patterns

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    Spatial interaction models have played an important role in two tasks in the Human Settlements and Services Area. In the Public Facilities Location Task they have been used to represent the locational behavior of establishments and households. In the Urban Change Task they have been used to describe internal migration patterns. In this paper, Waldo Tobler introduces a new spatial interaction model and outlines some of its properties. Variants of the basic model are noted and a computer listing is provided for readers wishing to explore the usefulness of the model as a descriptor of movement patterns

    Looking at Some Data from Isard’s “Methods of Regional Analysis”

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    Isard has argued for greater presentation of empirical data in regional studies by displaying tables and geographical maps. In this note his suggestion is followed by displaying two sets of computer maps using tables given in his classic 1960s boo
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