Classification of radiologically isolated syndrome and clinically isolated syndrome with machine-learning techniques.

BACKGROUND AND PURPOSE: The unanticipated detection by magnetic resonance imaging (MRI) in the brain of asymptomatic subjects of white matter lesions suggestive of multiple sclerosis (MS) has been named radiologically isolated syndrome (RIS). As the difference between early MS [i.e. clinically isolated syndrome (CIS)] and RIS is the occurrence of a clinical event, it is logical to improve detection of the subclinical form without interfering with MRI as there are radiological diagnostic criteria for that. Our objective was to use machine-learning classification methods to identify morphometric measures that help to discriminate patients with RIS from those with CIS. METHODS: We used a multimodal 3-T MRI approach by combining MRI biomarkers (cortical thickness, cortical and subcortical grey matter volume, and white matter integrity) of a cohort of 17 patients with RIS and 17 patients with CIS for single-subject level classification. RESULTS: The best proposed models to predict the diagnosis of CIS and RIS were based on the Naive Bayes, Bagging and Multilayer Perceptron classifiers using only three features: the left rostral middle frontal gyrus volume and the fractional anisotropy values in the right amygdala and right lingual gyrus. The Naive Bayes obtained the highest accuracy [overall classification, 0.765; area under the receiver operating characteristic (AUROC), 0.782]. CONCLUSIONS: A machine-learning approach applied to multimodal MRI data may differentiate between the earliest clinical expressions of MS (CIS and RIS) with an accuracy of 78%.

SNOMED2HL7: A tool to normalize and bind SNOMED CT concepts to the HL7 Reference Information Model.

BACKGROUND: Current clinical research and practice requires interoperability among systems in a complex and highly dynamic domain. There has been a significant effort in recent years to develop integrative common data models and domain terminologies. Such efforts have not completely solved the challenges associated with clinical data that are distributed among different and heterogeneous institutions with different systems to encode the information. Currently, when providing homogeneous interfaces to exploit clinical data, certain transformations still involve manual and time-consuming processes that could be automated. OBJECTIVES: There is a lack of tools to support data experts adopting clinical standards. This absence is especially significant when links between data model and vocabulary are required. The objective of this work is to present SNOMED2HL7, a novel tool to automatically link biomedical concepts from widely used terminologies, and the corresponding clinical context, to the HL7 Reference Information Model (RIM). METHODS: Based on the recommendations of the International Health Terminology Standards Development Organisation (IHTSDO), the SNOMED Normal Form has been implemented within SNOMED2HL7 to decompose and provide a method to reduce the number of options to store the same information. The binding of clinical terminologies to HL7 RIM components is the core of SNOMED2HL7, where terminology concepts have been annotated with the corresponding options within the interoperability standard. A web-based tool has been developed to automatically provide information from the normalization mechanisms and the terminology binding. RESULTS: SNOMED2HL7 binding coverage includes the majority of the concepts used to annotate legacy systems. It follows HL7 recommendations to solve binding overlaps and provides the binding of the normalized version of the concepts. The first version of the tool, available at http://kandel.dia.fi.upm.es:8078, has been validated in EU funded projects to integrate real world data for clinical research with an 88.47% of accuracy. CONCLUSIONS: This paper presents the first initiative to automatically retrieve concept-centered information required to transform legacy data into widely adopted interoperability standards. Although additional functionality will extend capabilities to automate data transformations, SNOMED2HL7 already provides the functionality required for the clinical interoperability community.

Electrochemical characteristics of bioresorbable binary MgCa alloys in Ringer's solution: Revealing the impact of local pH distributions during in-vitro dissolution.

Biodegradable magnesium-calcium (MgCa) alloy is a very attractive biomaterial. Two MgCa alloys below the solid solubility of Ca were considered, as to solely investigate the effect of Ca content on the behavior of magnesium and the pH changes associated to metal dissolution. X-ray diffraction analysis and optical microscopy showed that both Mg-0.63Ca and Mg-0.89Ca alloys were solely composed of α(Mg) phase. Degradation characteristics and electrochemical characterization of MgCa alloys were investigated during exposure to Ringer's solution at 37 °C by electrochemical impedance spectroscopy and scanning electrochemical microscopy. The impedance behavior showed both capacitive and inductive features that are related to the alloy charge transfer reaction and the relaxation of the absorbed corrosion compounds, and can be described in terms of an equivalent circuit. Scanning electron microscopy (SEM) was employed to view the surface morphology of the MgCa samples after 1 week immersion in Ringer's solution showing extensive precipitation of corrosion products, whereas the substrate shows evidence of a non-uniform corrosion process. Energy dispersive analysis showed that the precipitates contained oxygen, calcium, magnesium and chlorine, and the Mg:Ca ratios were smaller than in the alloys. Scanning electrochemical microscopy (SECM) was used to visualize local pH changes associated to these physicochemical processes with high spatial resolution. The occurrence of pH variations in excess of 3 units between anodic and cathodic half-cell reactions was monitored in situ.

Nanoinformatics: developing new computing applications for nanomedicine.

Nanoinformatics has recently emerged to address the need of computing applications at the nano level. In this regard, the authors have participated in various initiatives to identify its concepts, foundations and challenges. While nanomaterials open up the possibility for developing new devices in many industrial and scientific areas, they also offer breakthrough perspectives for the prevention, diagnosis and treatment of diseases. In this paper, we analyze the different aspects of nanoinformatics and suggest five research topics to help catalyze new research and development in the area, particularly focused on nanomedicine. We also encompass the use of informatics to further the biological and clinical applications of basic research in nanoscience and nanotechnology, and the related concept of an extended "nanotype" to coalesce information related to nanoparticles. We suggest how nanoinformatics could accelerate developments in nanomedicine, similarly to what happened with the Human Genome and other -omics projects, on issues like exchanging modeling and simulation methods and tools, linking toxicity information to clinical and personal databases or developing new approaches for scientific ontologies, among many others.

Surface characteristics of retrieved coated and nickel-titanium orthodontic archwires.

OBJECTIVE: The purpose of this study was to investigate the effects of oral fluids and archwire-bracket friction on the surface characteristics of NiTi alloy orthodontic archwires with/without aesthetic coating, in vivo for 2-3 months. MATERIALS AND METHODS: Different cross-sections of NiTi Archwires (DENTSPLY GAC International) and Titanol Cosmetic Archwires (FORESTADENT® USA Inc.) were examined by electron microscopy with dual-beam and spectroscopy analysis, before and after a collecting protocol from patients with multi-technique. RESULTS: Initially, the orthodontic archwires showed microscopic manufacturing and coating defects in the physiognomic layer. After intra-oral exposure, amorphous organic matter deposits were observed on the surface of the NiTi Archwires and the wire coating presented exfoliation on the oral areas of friction with brackets. X-ray microanalysis revealed changes in all atomic and mass percentages of chemical elements from the surface of all retrieved dental archwires, nickel and titanium ion depletion and the occurrence of additional elements due to interactions with saliva. CONCLUSIONS: Intra-oral exposure of NiTi Archwires and the archwire-bracket friction of coated wire altered the morphology and changed the elemental composition of the surface due to the process of corrosion, adhesion of organic matters and ionic exchange with oral fluids.

3D entropy and moments prediction of enzyme classes and experimental-theoretic study of peptide fingerprints in Leishmania parasites.

The number of protein 3D structures without function annotation in Protein Data Bank (PDB) has been steadily increased. This fact has led in turn to an increment of demand for theoretical models to give a quick characterization of these proteins. In this work, we present a new and fast Markov chain model (MCM) to predict the enzyme classification (EC) number. We used both linear discriminant analysis (LDA) and/or artificial neural networks (ANN) in order to compare linear vs. non-linear classifiers. The LDA model found is very simple (three variables) and at the same time is able to predict the first EC number with an overall accuracy of 79% for a data set of 4755 proteins (859 enzymes and 3896 non-enzymes) divided into both training and external validation series. In addition, the best non-linear ANN model is notably more complex but has an overall accuracy of 98.85%. It is important to emphasize that this method may help us to predict not only new enzyme proteins but also to select peptide candidates found on the peptide mass fingerprints (PMFs) of new proteins that may improve enzyme activity. In order to illustrate the use of the model in this regard, we first report the 2D electrophoresis (2DE) and MADLI-TOF mass spectra characterization of the PMF of a new possible malate dehydrogenase sequence from Leishmania infantum. Next, we used the models to predict the contribution to a specific enzyme action of 30 peptides found in the PMF of the new protein. We implemented the present model in a server at portal Bio-AIMS (http://miaja.tic.udc.es/Bio-AIMS/EnzClassPred.php). This free on-line tool is based on PHP/HTML/Python and MARCH-INSIDE routines. This combined strategy may be used to identify and predict peptides of prokaryote and eukaryote parasites and their hosts as well as other superior organisms, which may be of interest in drug development or target identification.

Generalized lattice graphs for 2D-visualization of biological information.

Several graph representations have been introduced for different data in theoretical biology. For instance, complex networks based on Graph theory are used to represent the structure and/or dynamics of different large biological systems such as protein-protein interaction networks. In addition, Randic, Liao, Nandy, Basak, and many others developed some special types of graph-based representations. This special type of graph includes geometrical constrains to node positioning in space and adopts final geometrical shapes that resemble lattice-like patterns. Lattice networks have been used to visually depict DNA and protein sequences but they are very flexible. However, despite the proved efficacy of new lattice-like graph/networks to represent diverse systems, most works focus on only one specific type of biological data. This work proposes a generalized type of lattice and illustrates how to use it in order to represent and compare biological data from different sources. We exemplify the following cases: protein sequence; mass spectra (MS) of protein peptide mass fingerprints (PMF); molecular dynamic trajectory (MDTs) from structural studies; mRNA microarray data; single nucleotide polymorphisms (SNPs); 1D or 2D-Electrophoresis study of protein polymorphisms and protein-research patent and/or copyright information. We used data available from public sources for some examples but for other, we used experimental results reported herein for the first time. This work may break new ground for the application of Graph theory in theoretical biology and other areas of biomedical sciences.

Antithrombin concentrate with plasma exchange in purpura fulminans.

OBJECTIVE: To report successful treatment of three patients admitted with purpura fulminans. DESIGN: Three cases with purpura fulminans: clinical presentation, laboratory findings, treatment, and outcome. SETTING: A seven-bed medical and general surgical Intensive therapy unit in a district general hospital. PATIENTS: Three young patients with clinical and laboratory findings of severe meningococcal sepsis and purpura. INTERVENTIONS: Early replacement therapy with antithrombin concentrate after a single initial plasma exchange, together with conventional antibiotic and supportive treatment. MEASUREMENTS AND MAIN RESULTS: All three cases had abnormal coagulation profile consistent with disseminated intravascular coagulation, adult respiratory distress syndrome, impaired renal function, and severe hemodynamic instability requiring inotropic support. Plasma antithrombin levels were measured in all cases. All patients survived and made a good recovery. CONCLUSIONS: We consider that correction of antithrombin to supranormal levels may have a beneficial effect on survival and outcome in purpura fulminans despite sustained low levels of protein C.

[Pigmentary retinopathy and Coats' vasculopathy]. / Retinopatia pigmentara si vasculopatia Coats.

The paper reports on a clinical case of association between pigmentary retinopathy and Coat's retinal vasculopathy. The study of the clinical syndrome of the case presented and of those described in the literature, shows the possibility that vascular telangiecstases might be the consequence of a hereditary tendency towards a form of latent vasculopathy, that develops towards a known clinical form. The disturbances of a generalized retinal vascular permeability, described for the first time in this context seems to be dependent on the genetic type of pigmentary retinopathy and independent of the peripheral telangiectatic modifications. The association of the two affections is, by the serious complications they generate, a factor of aggravating the visual prognosis.