MSAViewer:interactive JavaScript visualization of multiple sequence alignments

Summary: The MSAViewer is a quick and easy visualization and analysis JavaScript component for Multiple Sequence Alignment data of any size. Core features include interactive navigation through the alignment, application of popular color schemes, sorting, selecting and filtering. The MSAViewer is ‘web ready’: written entirely in JavaScript, compatible with modern web browsers and does not require any specialized software. The MSAViewer is part of the BioJS collection of components. Availability and Implementation: The MSAViewer is released as open source software under the Boost Software License 1.0. Documentation, source code and the viewer are available at http://msa.biojs.net/. Supplementary information: Supplementary data are available at Bioinformatics online. Contact: [email protected]

Whole Genome Interpretation for a Family of Five.

Although best practices have emerged on how to analyse and interpret personal genomes, the utility of whole genome screening remains underdeveloped. A large amount of information can be gathered from various types of analyses via whole genome sequencing including pathogenicity screening, genetic risk scoring, fitness, nutrition, and pharmacogenomic analysis. We recognize different levels of confidence when assessing the validity of genetic markers and apply rigorous standards for evaluation of phenotype associations. We illustrate the application of this approach on a family of five. By applying analyses of whole genomes from different methodological perspectives, we are able to build a more comprehensive picture to assist decision making in preventative healthcare and well-being management. Our interpretation and reporting outputs provide input for a clinician to develop a healthcare plan for the individual, based on genetic and other healthcare data

Platelet-rich plasma for regeneration of neural feedback pathways around dental implants: a concise review and outlook on future possibilities

published_or_final_versio

Computational Biology and Bioinformatics in Nigeria

Over the past few decades, major advances in the field of molecular biology, coupled with advances in genomic technologies, have led to an explosive growth in the biological data generated by the scientific community. The critical need to process and analyze such a deluge of data and turn it into useful knowledge has caused bioinformatics to gain prominence and importance. Bioinformatics is an interdisciplinary research area that applies techniques, methodologies, and tools in computer and information science to solve biological problems. In Nigeria, bioinformatics has recently played a vital role in the advancement of biological sciences. As a developing country, the importance of bioinformatics is rapidly gaining acceptance, and bioinformatics groups comprised of biologists, computer scientists, and computer engineers are being constituted at Nigerian universities and research institutes. In this article, we present an overview of bioinformatics education and research in Nigeria. We also discuss professional societies and academic and research institutions that play central roles in advancing the discipline in Nigeria. Finally, we propose strategies that can bolster bioinformatics education and support from policy makers in Nigeria, with potential positive implications for other developing countries. © 2014 Fatumo et al.SAF was supported by H3ABioNet NABDA Node, Abuja, Nigeria with NIH Common Fund Award/NHGRI Grant Number U41HG006941 and Genetic Epidemiology Group at Wellcome Trust Sanger Institute.Published versio

Translating the discourse of medical tourism: A catalogue of resources and corpus for translators and researchers

© 2020 The Authors. Published by SKASE Journal of Translation and Interpretation. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: http://www.skase.sk/Volumes/JTI15/pdf_doc/03.pdfThe recent increase in medical tourism in Europe also means more written contents are translated on the web to get to potential clients. Translating cross-border care language is somehow challenging because it implies different agents and linguistic fields making it difficult for translators and researchers to be fully apprehended. We hereby present a catalogue of possible informative resources on medical tourism and an ad hoc corpus based on Spanish medical websites-focused on aesthetics and cosmetics-that were translated into English.Published versio

Olives and olive oil are sources of electrophilic fatty acid nitroalkenes

Extra virgin olive oil (EVOO) and olives, key sources of unsaturated fatty acids in the Mediterranean diet, provide health benefits to humans. Nitric oxide (•NO) and nitrite (NO2-)-dependent reactions of unsaturated fatty acids yield electrophilic nitroalkene derivatives (NO 2-FA) that manifest salutary pleiotropic cell signaling responses in mammals. Herein, the endogenous presence of NO2-FA in both EVOO and fresh olives was demonstrated by mass spectrometry. The electrophilic nature of these species was affirmed by the detection of significant levels of protein cysteine adducts of nitro-oleic acid (NO2-OA-cysteine) in fresh olives, especially in the peel. Further nitration of EVOO by NO2- under acidic gastric digestive conditions revealed that human consumption of olive lipids will produce additional nitro-conjugated linoleic acid (NO2-cLA) and nitro-oleic acid (NO2-OA). The presence of free and protein-adducted NO2-FA in both mammalian and plant lipids further affirm a role for these species as signaling mediators. Since NO2-FA instigate adaptive anti-inflammatory gene expression and metabolic responses, these redox-derived metabolites may contribute to the cardiovascular benefits associated with the Mediterranean diet. © 2014 Fazzari et al

Phenotype-loci associations in networks of patients with rare disorders: application to assist in the diagnosis of novel clinical cases

Copy number variations (CNVs) are genomic structural variations (deletions, duplications, or translocations) that represent the 4.8–9.5% of human genome variation in healthy individuals. In some cases, CNVs can also lead to disease, being the etiology of many known rare genetic/genomic disorders. Despite the last advances in genomic sequencing and diagnosis, the pathological effects of many rare genetic variations remain unresolved, largely due to the low number of patients available for these cases, making it difficult to identify consistent patterns of genotype–phenotype relationships. We aimed to improve the identification of statistically consistent genotype–phenotype relationships by integrating all the genetic and clinical data of thousands of patients with rare genomic disorders (obtained from the DECIPHER database) into a phenotype–patient–genotype tripartite network. Then we assessed how our network approach could help in the characterization and diagnosis of novel cases in clinical genetics. The systematic approach implemented in this work is able to better define the relationships between phenotypes and specific loci, by exploiting large-scale association networks of phenotypes and genotypes in thousands of rare disease patients. The application of the described methodology facilitated the diagnosis of novel clinical cases, ranking phenotypes by locus specificity and reporting putative new clinical features that may suggest additional clinical follow-ups. In this work, the proof of concept developed over a set of novel clinical cases demonstrates that this network-based methodology might help improve the precision of patient clinical records and the characterization of rare syndromes

Reconstruction of a genome-scale metabolic model of streptomyces albus j1074: improved engineering strategies in natural product synthesis

This research was funded by the European Union’s Horizon 2020 Research and Innovation Programme under Grant Agreement number 814650, and Programa Severo Ochoa de Ayudas Predoctorales para la investigación y docencia from Principado de Asturias (grant BP19-058 to P.M.-C.)

The EGR2 gene is involved in axonal Charcot-Marie-Tooth disease

[EN] Background and purpose: A three-generation family affected by axonal Charcot-Marie-Tooth disease (CMT) was investigated with the aim of discovering genetic defects and to further characterize the phenotype. Methods: The clinical, nerve conduction studies and muscle magnetic resonance images of the patients were reviewed. A whole exome sequencing was performed and the changes were investigated by genetic studies, in silico analysis and luciferase reporter assays. Results: A novel c.1226G>A change (p.R409Q) in the EGR2 gene was identified. Patients presented with a typical, late-onset axonal CMT phenotype with variable severity that was confirmed in the ancillary tests. The in silico studies showed that the residue R409 is an evolutionary conserved amino acid. The p.R409Q mutation, which is predicted as probably damaging, would alter the conformation of the protein slightly and would cause a decrease of gene expression. Conclusions: This is the first report of an EGR2 mutation presenting as an axonal CMT phenotype with variable severity. This study broadens the phenotype of the EGR2-related neuropathies and suggests that the genetic testing of patients suffering from axonal CMT should include the EGR2 gene.This collaborative joint project is awarded by IRDiRC and funded by the Instituto de Salud Carlos III (ISCIII) - Subdireccion General de Evaluacion y Fomento de la Investigacion within the framework of the National R+D+I Plan (Grants IR11/TREAT-CMT, PI12/00946 and PI12/00453), co-funded with FEDER funds. C.E. has a "Miguel Servet' contract funded by the ISCIII and Centro de Investigacion Principe Felipe (CIPF) (Grant no. CPII14/00002). We are also grateful to Itziar Llopis for sample management.Sevilla, T.; Sivera, R.; Martínez-Rubio, D.; Lupo, V.; Chumillas, M.; Calpena-Corpas, E.; Dopazo, J.... (2015). The EGR2 gene is involved in axonal Charcot-Marie-Tooth disease. European Journal of Neurology. 22(12):1548-1555. https://doi.org/10.1111/ene.1278215481555221