1,720,966 research outputs found
Interactive alkaptonuria database: investigating clinical data to improve patient care in a rare disease
Alkaptonuria (AKU) is an ultrarare autosomal recessive disorder (MIM 203500) that is caused byby a complex set of mutations in homogentisate 1,2-dioxygenasegene and consequent accumulation of homogentisic acid (HGA), causing a significant protein oxidation. A secondary form of amyloidosis was identified in AKU and related to high circulating serum amyloid A (SAA) levels, which are linked with inflammation and oxidative stress and might contribute to disease progression and patients' poor quality of life. Recently, we reported that inflammatory markers (SAA and chitotriosidase) and oxidative stress markers (protein thiolation index) might be disease activity markers in AKU. Thanks to an international network, we collected genotypic, phenotypic, and clinical data from more than 200 patients with AKU. These data are currently stored in our AKU database, named ApreciseKUre. In this work, we developed an algorithm able to make predictions about the oxidative status trend of each patient with AKU based on 55 predictors, namely circulating HGA, body mass index, total cholesterol, SAA, and chitotriosidase. Our general aim is to integrate the data of apparently heterogeneous patients with AKUAKU by using specific bioinformatics tools, in order to identify pivotal mechanisms involved in AKU for a preventive, predictive, and personalized medicine approach to AKU.-Cicaloni, V., Spiga, O., Dimitri, G. M., Maiocchi, R., Millucci, L., Giustarini, D., Bernardini, G., Bernini, A., Marzocchi, B., Braconi, D., Santucci, A. Interactive alkaptonuria database: investigating clinical data to improve patient care in a rare disease
ApreciseKUre: an approach of Precision Medicine in a Rare Disease
Abstract Background Alkaptonuria (AKU; OMIM:203500) is a classic Mendelian genetic disorder described by Garrod already in 1902. It causes urine to turn black upon exposure to air and also leads to ochronosis as well as early osteoarthritis. Main body of the abstract Our objective is the implementation of a Precision Medicine (PM) approach to AKU. We present here a novel ApreciseKUre database facilitating the collection, integration and analysis of patient data in order to create an AKU-dedicated “PM Ecosystem” in which genetic, biochemical and clinical resources can be shared among registered researchers. In order to exploit the ApreciseKUre database, we developed an analytic method based on Pearson’s correlation coefficient and P value that generates as refreshable correlation matrix. A complete statistical analysis is obtained by associating every pair of parameters to examine the dependence between multiple variables at the same time. Short conclusions Employing this analytic approach, we showed that some clinically used biomarkers are not suitable as prognostic biomarkers in AKU for a more reliable patients’ clinical monitoring. We believe this database could be a good starting point for the creation of a new clinical management tool in AKU, which will lead to the development of a deeper knowledge network on the disease and will advance its treatment. Moreover, our approach can serve as a personalization model paradigm for other inborn errors of metabolism or rare diseases in general
Multi-Omics Model Applied to Cancer Genetics
In this review, we focus on bioinformatic oncology as an integrative discipline that incorporates knowledge from the mathematical, physical, and computational fields to further the biomedical understanding of cancer. Before providing a deeper insight into the bioinformatics approach and utilities involved in oncology, we must understand what is a system biology framework and the genetic connection, because of the high heterogenicity of the backgrounds of people approaching precision medicine. In fact, it is essential to providing general theoretical information on genomics, epigenomics, and transcriptomics to understand the phases of multi-omics approach. We consider how to create a multi-omics model. In the last section, we describe the new frontiers and future perspectives of this field
Going Beyond Counting First Authors in Author Co-citation Analysis
The present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
We provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Structural investigation of Rett-inducing MeCP2 mutations
X-ray structure of methyl-CpG binding domain (MBD) of MeCP2, an intrinsically disordered protein (IDP) involved in Rett syndrome, offers a rational basis for defining the spatial distribution for most of the sites where mutations responsible of Rett syndrome, RTT, occur. We have ascribed pathogenicity for mutations of amino acids bearing positively charged side chains, all located at the protein-DNA interface, as positive charge removal cause reduction of the MeCP2-DNA adduct lifetime. Pathogenicity of the frequent proline replacements, outside the DNA contact moiety of MBD, can be attributed to the role of this amino acid for maintaining both unfolded states for unbound MeCP2 and, at the same time, to favor some higher conformational order for stabilizing structural determinants required by protein activity. These hypotheses can be extended to transcription repressor domain, TRD, the other MeCP2-DNA interaction site and, in general, to all the IDP that interact with nucleic acids
Dispelling the Myths Behind First-author Citation Counts
We conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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