Co‐variation of tests commonly used in stroke rehabilitation

Background and Purpose . The aim of the present study was to analyse the co‐variation of different tests commonly used in stroke rehabilitation, and specifically used in a recent randomized, controlled study of two different physiotherapy models in stroke rehabilitation. Method . Correlations of the performed tests and recordings from previous work were studied. The test results from three‐month, one‐year and four‐year follow‐up were analysed in an SPSS Version 11 statistical package with Pearson and Spearman correlations. Results . There was an expected high correlation between the motor function tests, both based on partial and total scores. The correlations between Nottingham Health Profile Part 1 and Motor Assessment Scale (MAS), Sødring Motor Eevaluation Scale (SMES), the Berg Balance Scale (BBS) and Barthel Activities of Daily Living (ADL) index were low for all items except physical condition. The correlations between registered living conditions, assistive devices, recurrent stroke, motor function (MAS, SMES), ADL (Barthel ADL index) and balance (BBS) were high. The same variables showed weak or poor correlation to the Nottingham Health Profile (NHP). Conclusions . The co‐variations of motor function tests and functional tests were high, but the co‐variations of motor, functional and self‐reported life‐quality tests were poor. The patients rated themselves on a higher functional level in the self‐reported tests than was observed objectively in the performance‐based tests. A possible reason for this is that the patients may have been unaware they modified their performance to adjust for physical decline, and consequently overestimate their physical condition. This result underlines the importance of both performance‐based and self‐reported tests as complementary tools in a rehabilitation process. Copyright © 2006 John Wiley & Sons, Ltd.     

Ethanol dependence of α1-antitrypsin C-terminal Lys truncation mediated by basic carboxypeptidases

BACKGROUND: Patients with hereditary emphysema are treated with α₁-antitrypsin (α₁-proteinase inhibitor [A1PI]) concentrates. High-resolution isoelectric focusing (IEF) analysis of A1PI shows that commercial A1PI products have different glycoisoform band patterns predominantly caused by varying degrees of C-terminal Lys truncation at position 394 from the A1PI molecule. Basic carboxypeptidases (CPs) are a group of enzymes that specifically cleave C-terminal basic amino acids (Arg or Lys) from peptides and proteins.
STUDY DESIGN AND METHODS: In this study, whether A1PI is a substrate for basic CPs was investigated. CPN and CPU, two CPs present in plasma, and CPM, a GPI-anchored membrane protein highly expressed in lung tissues, were included.
RESULTS: Basic CPs are able to mediate the C-terminal Lys truncation of A1PI although with a very low efficiency. However, presence of ethanol, for example, during Cohn fractionation, renders A1PI highly susceptible to cleavage by CP with the extent of Lys truncation depending on the ethanol concentration. This ethanol concentration dependence elegantly explains the varying amounts of des-Lys A1PI present in commercial preparations purified from different Cohn fractions.
CONCLUSIONS: The cause of C-terminal truncation of A1PI present in products used for augmentation therapy has been identified, and it has been shown that A1PI becomes a substrate for CPs, specifically CPN, because of the presence of ethanol during Cohn fractionation.     

Multicenter evaluation of a rapid electrochemiluminescent adrenocorticotropic hormone (ACTH) immunoassay

BACKGROUND: Measuring plasma adrenocorticotropic hormone (ACTH) is a key step in the differential diagnosis of hypothalamic-pituitary-adrenal disorders. METHODS: The recently developed electrochemiluminescence Elecsys ACTH immunoassay (Roche Diagnostics, Mannheim, Germany) was evaluated at six clinical laboratories on the Modular E170 and/or the Elecsys 2010 (Roche Diagnostics) immunoanalysers. RESULTS: The within-run and between-run imprecision was 相似文献   

The influence of image enhancement and reconstruction on quantitative coronary arteriography

In the coming years, cinefilm will gradually be replaced by some digital medium for the archiving of angiographic images. However, not only the question which digital archiving medium will be used in the future is important, but also wich images are to be stored. Options are to either archive the raw, unprocessed images, or the enhanced images as they are displayed on the viewing monitor in the catheterization laboratory. In the first case, an off-line workstation will need additional hardware to display the images with the same image quality as they were acquired; in the second case, the question remains whether quantitative analysis programs still provide reliable results. Goal of this study was to investigate the possible effects of image enhancement and reconstruction on the results from quantitative coronary arteriographic (QCA) measurements with the Philips ACA-package (Automated Coronary Analysis). Image enhancement was achieved by an unsharp masking approach; the reconstruction of the original image from the enhanced image was attempted by an iterative deconvolution approach. The evaluation study consisted of two parts; a technical evaluation on eleven phantom tubes with known dimensions, and a clinical evaluation study on 48 coronary lesions. The results of the technical evaluation demonstrate that the measurement errors increase for the smaller vessel sizes (<1.2 mm) when QCA is applied to reconstructed images. The systematic difference on the smallest phantom tube (0.687 mm) on unprocessed images was limited to 0.050 mm, while it increased to 0.089 mm for the reconstructed images. Moreover, the random differences for the smaller vessel sizes increased for all processed images: for 0.159 mm for the unprocessed image to 0.189 mm for the enhanced and 0.204 mm for the reconstructed image (p<0.01). For the larger vessels, in general, no significant differences could be observed between the results of the unprocessed and processed images. The results of the clinical evaluation study demonstrate that especially the obstruction diameter is overestimated when QCA is applied to reconstructed images (0.113 mm). Although the measurements on the enhanced images did not show a significant overestimation of the obstruction diameter, the intra-observer random difference was much higher (0.199 mm for the enhanced images versus 0.140 mm for the unprocessed images, p<0.01). In more general terms, applying QCA on enhanced images increases the random difference values, while reconstructing the original image from the enhanced images increases the systematic errors in the measured diameters. This study has clearly demonstrated that especially the smaller diameter values (<1.2 mm) are influenced by image enhancement. Therefore, to obtain quantitative results with the desired small values for systematic and random differences, requires that the raw, unprocessed image data be archived.     

Independent component analysis of fMRI group studies by self-organizing clustering

Independent component analysis (ICA) is a valuable technique for the multivariate data-driven analysis of functional magnetic resonance imaging (fMRI) data sets. Applications of ICA have been developed mainly for single subject studies, although different solutions for group studies have been proposed. These approaches combine data sets from multiple subjects into a single aggregate data set before ICA estimation and, thus, require some additional assumptions about the separability across subjects of group independent components. Here, we exploit the application of similarity measures and a related visual tool to study the natural self-organizing clustering of many independent components from multiple individual data sets in the subject space. Our proposed framework flexibly enables multiple criteria for the generation of group independent components and their random-effects evaluation. We present real visual activation fMRI data from two experiments, with different spatiotemporal structures, and demonstrate the validity of this framework for a blind extraction and selection of meaningful activity and functional connectivity group patterns. Our approach is either alternative or complementary to the group ICA of aggregated data sets in that it exploits commonalities across multiple subject-specific patterns, while addressing as much as possible of the intersubject variability of the measured responses. This property is particularly of interest for a blind group and subgroup pattern extraction and selection.     

Potent inhibition of genital herpesvirus infection in goats by cidofovir

BACKGROUND: Like human herpesvirus 2 (HHV-2) in humans, infection by caprine herpesvirus 1 in goats is associated with genital lesions, and this provides a unique model to study the efficacy and effects of anti-herpetic drugs. METHODS: The antiviral activity of cidofovir was assessed in goats infected experimentally, using various therapeutic protocols. RESULTS: Topic administration of cidofovir 1% cream prevented the onset of virus-induced genital lesions and drastically reduced virus shedding. CONCLUSION: Cidofovir appears to be a very efficient drug for the prevention of genital lesions caused by an alphaherpesvirus.     

Validating the independent components of neuroimaging time series via clustering and visualization

Recently, independent component analysis (ICA) has been widely used in the analysis of brain imaging data. An important problem with most ICA algorithms is, however, that they are stochastic; that is, their results may be somewhat different in different runs of the algorithm. Thus, the outputs of a single run of an ICA algorithm should be interpreted with some reserve, and further analysis of the algorithmic reliability of the components is needed. Moreover, as with any statistical method, the results are affected by the random sampling of the data, and some analysis of the statistical significance or reliability should be done as well. Here we present a method for assessing both the algorithmic and statistical reliability of estimated independent components. The method is based on running the ICA algorithm many times with slightly different conditions and visualizing the clustering structure of the obtained components in the signal space. In experiments with magnetoencephalographic (MEG) and functional magnetic resonance imaging (fMRI) data, the method was able to show that expected components are reliable; furthermore, it pointed out components whose interpretation was not obvious but whose reliability should incite the experimenter to investigate the underlying technical or physical phenomena. The method is implemented in a software package called Icasso.     

Soft tissue tumors: grading, staging, and tissue-specific diagnosis

The value of medical imaging in detection, staging, grading, and tissue-specific diagnosis has been substantially increased, especially after the introduction of magnetic resonance imaging, the combined use of cytogenetic and molecular techniques and the refinement of biopsy techniques. In this paper, we will focus on the combination of parameters including clinical information, prevalence, age, location, and findings on medical imaging, yielding the highest diagnostic sensitivity and specificity. An imaging prototype of a malignant soft tissue tumor will be proposed. In a second part, we will present an overview of most common soft tissue tumors, especially focusing on these tumors having more characteristic imaging features that allow to make a more detailed tissue-specific diagnosis. Finally, we will give the radiologist a short list of important things to take home.