Predicting the accuracy of multiple sequence alignment algorithms by using computational intelligent techniques

Multiple sequence alignments (MSAs) have become one of the most studied approaches in bioinformatics to perform other outstanding tasks such as structure prediction, biological function analysis or next-generation sequencing. However, current MSA algorithms do not always provide consistent solutions, since alignments become increasingly difficult when dealing with low similarity sequences. As widely known, these algorithms directly depend on specific features of the sequences, causing relevant influence on the alignment accuracy. Many MSA tools have been recently designed but it is not possible to know in advance which one is the most suitable for a particular set of sequences. In this work, we analyze some of the most used algorithms presented in the bibliography and their dependences on several features. A novel intelligent algorithm based on least square support vector machine is then developed to predict how accurate each alignment could be, depending on its analyzed features. This algorithm is performed with a dataset of 2180 MSAs. The proposed system first estimates the accuracy of possible alignments. The most promising methodologies are then selected in order to align each set of sequences. Since only one selected algorithm is run, the computational time is not excessively increased

Hacia un modelo genérico de visualización de traductores dirigidos por la sintaxis

Este trabajo presenta una herramienta de visualización que pretende ayudar a comprender los conceptos de los traductores dirigidos por la sintaxis, proporcionando una representación gráfica de conceptos tan abstractos. La herramienta que se describe consta de una interfaz de visualización y una API. La interfaz de visualización permite a profesores y estudiantes ver una representación gráfica del proceso de ejecución del traductor dirigido por la sintaxis observando detalles como las acciones semánticas ejecutadas o los valores de los atributos de los símbolos. La API permite al usuario anotar una especificación del traductor dirigido por la sintaxis de forma que durante su ejecución genere una traza que permita su posterior visualización con la interfaz. Esta división entre interfaz y API busca que las visualizaciones puedan ser independientes del software utilizado para la generación del traductor, tratando así de sortear alguna de las limitaciones que tienen otras herramientas existentes.In this work, we present a visualization tool aimed at supporting students’ comprehension of syntax directed translators concepts by providing graphical representations of such abstract concepts. The tool is made up of two parts: a visualization interface and an API. The visualization interface provide teachers and students with a graphical representation of the execution process of the syntax directed translator. This representation provide a detailed view of the executed semantic actions and the values of the symbol attributes. The API allows the user to annotate the specification of the syntax directed translator. Thus, its execution generates a trace that will be used by the interface to produce the visualization. This division between the interface and the API supports the independence between the visualizations and the parser generator tool, avoiding some of the limitations identified in other existing tools.Este trabajo ha sido financiado por el Ministerio de Economía y Competitividad (ref. TIN2015-66731-C2-1-R ) y la Comunidad de Madrid, con el proyecto e-Madrid-CM (P2018/TCS-4307) , también cofinanciado por los fondos estructurales (FSE y FEDER)

Monozygotic twins discordant for common variable immunodeficiency reveal impaired DNA demethylation during naı¨ve-to-memory B-cell transition

Common variable immunodeficiency (CVID), the most frequent primary immunodeficiency characterized by loss of B-cell function, depends partly on genetic defects, and epigenetic changes are thought to contribute to its aetiology. Here we perform a high-throughput DNA methylation analysis of this disorder using a pair of CVID-discordant MZ twins and show predominant gain of DNA methylation in CVID B cells with respect to those from the healthy sibling in critical B lymphocyte genes, such as PIK3CD, BCL2L1, RPS6KB2, TCF3 and KCNN4. Individual analysis confirms hypermethylation of these genes. Analysis in naive, unswitched and switched memory B cells in a CVID patient cohort shows impaired ability to demethylate and upregulate these genes in transitioning from naive to memory cells in CVID. Our results not only indicate a role for epigenetic alterations in CVID but also identify relevant DNA methylation changes in B cells that could explain the clinical manifestations of CVID individuals

Activation-induced cytidine deaminase targets SUV4-20-mediated histone H4K20 trimethylation to class-switch recombination sites

Activation-induced cytidine deaminase (AID) triggers antibody diversification in B cells by catalysing deamination and subsequently mutating immunoglobulin (Ig) genes. Association of AID with RNA Pol II and occurrence of epigenetic changes during Ig gene diversification suggest participation of AID in epigenetic regulation. AID is mutated in hyper-IgM type 2 (HIGM2) syndrome. Here, we investigated the potential role of AID in the acquisition of epigenetic changes. We discovered that AID binding to the IgH locus promotes an increase in H4K20me3. In 293F cells, we demonstrate interaction between co-transfected AID and the three SUV4-20 histone H4K20 methyltransferases, and that SUV4-20H1.2, bound to the IgH switch (S) mu site, is replaced by SUV4-20H2 upon AID binding. Analysis of HIGM2 mutants shows that the AID truncated form W68X is impaired to interact with SUV4-20H1.2 and SUV4-20H2 and is unable to bind and target H4K20me3 to the Smu site. We finally show in mouse primary B cells undergoing class-switch recombination (CSR) that AID deficiency associates with decreased H4K20me3 levels at the Smu site. Our results provide a novel link between SUV4-20 enzymes and CSR and offer a new aspect of the interplay between AID and histone modifications in setting the epigenetic status of CSR sites

MOOC as a Way of Dissemination, Training and Learning of Telecommunication Engineering

In this chapter, the use of massive open online courses (MOOCs) for the dissemination, training capabilities and learning of telecommunication engineering is described taking as example the successful MOOC ‘Ultra- Dense Networks for 5G and its Evolution’ developed under the European innovative training network (ITN) TeamUp5G. MOOCs are usually understood as a way of teaching or learning for massive potential students. Indeed, this is the main goal of any MOOC. However, we also propose its use for training and dissemination. The ITN TeamUp5G is a training network for 15 PhD students of seven different institutions (universities and companies) where the students make research on different interconnected topics for the common goal of Ultra dense networks for 5G. At the same time they researched, they prepared a MOOC to disseminate their most recent advances and their challenges. For the MOOC, they needed to collect their thoughts, organizse their knowledge and establish a common vision of the whole system. The cooperative work, the cross-related meetings and, the preparation of all the materials for the MOOC were very interesting and useful in their training process. The whole experience of designing and creating the MOOC is described in detail along with the challenges and lessons learned.info:eu-repo/semantics/acceptedVersio

Humoral and Cellular Immune Responses After a 3-dose Course of mRNA-1273 COVID-19 Vaccine in Kidney Transplant Recipients: A Prospective Cohort Study.

In kidney transplant recipients, there is discordance between the development of cellular and humoral response after vaccination against SARS-CoV-2. We sought to determine the interplay between the 2 arms of adaptive immunity in a 3-dose course of mRNA-1273 100 μg vaccine. Methods: Humoral (IgG/IgM) and cellular (N- and S-ELISpot) responses were studied in 117 kidney and 12 kidney-pancreas transplant recipients at the following time points: before the first dose, 14 d after the second dose' and before and after the third dose, with a median of 203 and 232 d after the start of the vaccination cycle, respectively. Results: After the second dose, 26.7% of naive cases experienced seroconversion. Before the third dose and in the absence of COVID-19, this percentage increased to 61.9%. After the third dose, seroconversion occurred in 80.0% of patients. Naive patients who had at any time point a detectable positivity for S-ELISpot were 75.2% of the population, whereas patients who maintained S-ELISpot positivity throughout the study were 34.3%. S-ELISpot positivity at 42 d was associated with final seroconversion (odds ratio' 3.14; 95% confidence interval' 1.10-8.96; P = 0.032). Final IgG titer was significantly higher in patients with constant S-ELISpot positivity (P < 0.001). Conclusions: A substantial proportion of kidney transplant recipients developed late seroconversion after 2 doses. Cellular immunity was associated with the development of a stronger humoral respons

Incidence of severe breakthrough SARS-CoV-2 infections in vaccinated kidney transplant and haemodialysis patients

Introduction: Given the increased COVID-19 observed in kidney transplant recipients (KTRs) and haemodialysis patients, several studies have tried to establish the efficacy of mRNA vaccines in these populations by evaluating their humoral and cellular responses. However, there is currently no information on clinical protection (deaths and hospitalizations), a gap that this study aims to fill. Methods: Observational prospective study involving 1,336 KTRs and haemodialysis patients from three dialysis units affiliated to Hospital Clínic of Barcelona, Spain, vaccinated with two doses of mRNA-1273 (Moderna) or BNT162b2 (Pfizer-BioNTech) SARS-CoV-2 mRNA vaccines. The outcomes measured were SARS-CoV-2 infection diagnosed by a positive RT-PCR fourteen days after the second vaccine dose, hospital admissions derived from infection, and a severe COVID-19 composite outcome, defined as either ICU admission, invasive and non-invasive mechanical ventilation, or death. Results: Six per cent (18/302) of patients on haemodialysis were infected, of whom four required hospital admission (1.3%), only one (0.3%) had severe COVID-19, and none of them died. In contrast, 4.3% (44/1034) of KTRs were infected, and presented more hospital admissions (26 patients, 2.5%), severe COVID-19 (11 patients, 1.1%) or death (4 patients, 0.4%). KTRs had a significantly higher risk of hospital admission than HD patients, and this risk increased with age and male sex (HR 3.37 and 4.74, respectively). Conclusions: The study highlights the need for booster doses in KTRs. In contrast, the haemodialysis population appears to have an adequate clinical response to vaccination, at least up to four months from its administration

Impacts of biomedical hashtag-based Twitter campaign: #DHPSP utilization for promotion of open innovation in digital health, patient safety, and personalized medicine

The open innovation hub Digital Health and Patient Safety Platform (DHPSP) was recently established with the purpose to invigorate collaborative scientific research and the development of new digital products and personalized solutions aiming to improve human health and patient safety. In this study, we evaluated the effectiveness of a Twitter-based campaign centered on using the hashtag #DHPSP to promote the visibility of the DHPSP initiative. Thus, tweets containing #DHPSP were monitored for five weeks for the period 20.10.2020–24.11.2020 and were analyzed with Symplur Signals (social media analytics tool). In the study period, a total of 11,005 tweets containing #DHPSP were posted by 3020 Twitter users, generating 151,984,378 impressions. Analysis of the healthcare stakeholder-identity of the Twitter users who used #DHPSP revealed that the most of participating user accounts belonged to individuals or doctors, with the top three user locations being the United States (501 users), the United Kingdom (155 users), and India (121 users). Analysis of co-occurring hashtags and the full text of the posted tweets further revealed that the major themes of attention in the #DHPSP Twitter-community were related to the coronavirus disease 2019 (COVID-19), medicine and health, digital health technologies, and science communication in general. Overall, these results indicate that the #DHPSP initiative achieved high visibility and engaged a large body of Twitter users interested in the DHPSP focus area. Moreover, the conducted campaign resulted in an increase of DHPSP member enrollments and website visitors, and new scientific collaborations were formed. Thus, Twitter campaigns centered on a dedicated hashtag prove to be a highly efficient tool for visibility-promotion, which could be successfully utilized by healthcare-related open innovation platforms or initiatives

The International Natural Product Sciences Taskforce (INPST) and the power of Twitter networking exemplified through #INPST hashtag analysis

Background: The development of digital technologies and the evolution of open innovation approaches have enabled the creation of diverse virtual organizations and enterprises coordinating their activities primarily online. The open innovation platform titled "International Natural Product Sciences Taskforce" (INPST) was established in 2018, to bring together in collaborative environment individuals and organizations interested in natural product scientific research, and to empower their interactions by using digital communication tools. Methods: In this work, we present a general overview of INPST activities and showcase the specific use of Twitter as a powerful networking tool that was used to host a one-week "2021 INPST Twitter Networking Event" (spanning from 31st May 2021 to 6th June 2021) based on the application of the Twitter hashtag #INPST. Results and Conclusion: The use of this hashtag during the networking event period was analyzed with Symplur Signals (https://www.symplur.com/), revealing a total of 6,036 tweets, shared by 686 users, which generated a total of 65,004,773 impressions (views of the respective tweets). This networking event's achieved high visibility and participation rate showcases a convincing example of how this social media platform can be used as a highly effective tool to host virtual Twitter-based international biomedical research events