Neuropsychiatric and sleep study in autosomal dominant dopa-responsive dystonia.

Introduction: Although the diurnal fluctuation of motor dysfunction, reversible with small doses of dopamine, is a cornerstone for the phenotype of the autosomal dominant Segawa syndrome, the non-motor symptoms of this neurotransmitter deficiency have still received limited attention. Objective: This study aims to evaluate non-motor symptoms of this dopa-responsive dystonia through an intrafamilial comparative cross-sectional study. Methods: Seventeen individuals with a c.IVS5 + 3insT (c.626 + 3insT) variation in the GTP cyclohydrolase-1 gene (GCH1, HGNC: 4193) and 34 intrafamilial controls were studied using the Beck Depression Inventory-II, the Wiener Matrizen Test 2, the Epworth Sleepiness Scale, the Pittsburgh Sleep Quality Index, the MINI/MINI PLUS Questionnaires, the World Health Organization Quality of Life - BREF Instrument and a drug use assessment questionnaire. Results: No significant difference was found between the groups in the prevalence of sleep disorders and in cognitive function. Nevertheless, generalized anxiety disorder (p = 0.050) and attention-deficit/hyperactivity disorder in childhood (p = 0.011) were observed only in individuals without the molecular variation. The group with the GCH1 variation presented a worse perception about how safe they feel in their daily lives (p = 0.034), less satisfaction with themselves (p = 0.049) and with their relationships (p = 0.029), and a higher prevalence of past major depressive episodes before use of L-Dopa (p = 0.046). Conclusion: Low dopamine could have been protective against generalized anxiety disorder and attention-deficit/hyperactivity disorder in childhood in Segawa group individuals. The prevalence of depression was higher in individuals with the molecular variant prior to the L-Dopa treatment. Considering it, the penetrance estimates for the variant carriers increased from 58.8% to up to 88% in this large studied family. Additionally, neuropsychiatric tests of all individuals with a molecular diagnosis in an affected family are a valuable instrument for its clinical management.

Raman spectroscopy with a 1064-nm wavelength laser as a potential molecular tool for prostate cancer diagnosis: a pilot study.

Raman spectroscopy is widely used to investigate the structure and property of the molecules from their vibrational transitions and may allow for the diagnosis of cancer in a fast, objective, and nondestructive manner. This experimental study aims to propose the use of the 1064-nm wavelength laser in a Raman spectroscopy and to evaluate its discrimination capability in prostate cancer diagnosis. Seventy-four spectra from patients who underwent radical prostatectomy were evaluated. The acquired signals were filtered, normalized, and corrected for possible oscillations in the laser intensity and fluorescence effects. Wilcoxon tests revealed significant differences between the benign and malign samples associated with the deformation vibration characteristic of nucleic acids, proteins, and lipids. A classifier based on support vector machines was able to predict the Gleason scores of the samples with 95% of accuracy, opening a perspective for the use of the 1064-nm excitatory wavelength in prostatic cancer diagnosis.

MammoSys: A content-based image retrieval system using breast density patterns.

In this paper, we present a content-based image retrieval system designed to retrieve mammographies from large medical image database. The system is developed based on breast density, according to the four categories defined by the American College of Radiology, and is integrated to the database of the Image Retrieval in Medical Applications (IRMA) project, that provides images with classification ground truth. Two-dimensional principal component analysis is used in breast density texture characterization, in order to effectively represent texture and allow for dimensionality reduction. A support vector machine is used to perform the retrieval process. Average precision rates are in the range from 83% to 97% considering a data set of 5024 images. The results indicate the potential of the system as the first stage of a computer-aided diagnosis framework.

Corpus callosum morphology and ventricular size in chromosome 22q11.2 deletion syndrome.

In this paper, novel methods were used to map the corpus callosum morphology of children with chromosome 22q11.2 deletion syndrome in order to further investigate changes to that structure and to examine their possible effects on cognitive function. The callosal profiles were extracted from the centermost MRI midsagittal slice by supervised thresholding and the structure's boundary and midline were computed automatically. Difference analysis was based on non-rigid registration, in which a template image is warped to conform to the shape of each corpus callosum in the sample. Boundaries and midlines were registered to a template and the results used to determine the average callosal shapes for children with the deletion and for controls. Pointwise registration also enabled the detailed evaluation of callosal curvature, width, area and length. Significant differences between the two groups were found in shape, size and bending angle. Results showed group differences that were concentrated in the anterior part of the structure, more specifically in the rostrum, which was larger and longer in the group with the syndrome. Correlation analyses showed that ventricular enlargement does not fully account for callosal morphology differences in children with the deletion. However, areal measurements did reveal important relationships between changes in callosal morphology and cognitive function. These novel findings reveal intricate relationships between genetic and disease-specific factors in the callosal anatomy and the potential impact of those changes on cognitive functions.

Structural shape characterization via exploratory factor analysis.

UNLABELLED: This article presents an exploratory factor analytic approach to morphometry in which a high-dimensional set of shape-related variables is examined with the purpose of finding clusters with strong correlation. This clustering can potentially identify regions that have anatomic significance and thus lend insight to knowledge discovery and morphometric investigations. METHODS: The information about regional shape is extracted by registering a reference image to a set of test images. Based on the displacement fields obtained form image registration, the amount of pointwise volume enlargement or reduction is computed and statistically analyzed with the purpose of extracting a reduced set of common factors. EXPERIMENTS: The effectiveness and robustness of the method is demonstrated in a study of gender-related differences of the human corpus callosum anatomy, based on a sample of 84 right-handed normal controls. RESULTS: The method is able to automatically partition the structure into regions of interest, in which the most relevant shape differences can be observed. The confidence of results is evaluated by analyzing the statistical fit of the model and compared to previous experimental works.