17225 results for "free coins in fc 26 Visit Buyfc26coins.com for latest FC 26 coins news..xwWa"

in 17.32 milliseconds.

• FEGA and European GDI: working together to improve human health

  The Federated EGA is a global resource for discovery of and access to sensitive human omics and associated data consented for secondary use, through a network of human data repositories to accelerate biomedical research and improve human health. The Federated EGA network was launched in September 2022 with five inaugural nodes, and since 2023 seven operational nodes can share data across national borders in adherence to European and national laws. A few weeks after FEGA's official launch, in November 2022, the European Genomic Data Infrastructure (GDI) project was kicked-off . This European Commission co-funded project, coordinated by ELIXIR, is aimed to deliver federated, sustainable and secure data infrastructure to access genomic and related phenotypic and clinical data across Europe. This project supports the aim of the 1+MG initiative (25 EU countries, Norway and UK) to enable personalised medicine and health through a shared framework and infrastructure for securely accessing and integrating high quality genomic data and other health data across borders.1+MG will be an integral component of the European Health Data Space (EHDS) for secondary use (Healthdata@EU) as an authorised participant. How are Federated EGA and GDI similar? Given their shared visions, the Federated EGA and European GDI networks have a lot in common. To begin, they share the same overall goal of establishing networks of “nodes” that host sensitive human data within a jurisdiction and connecting these nodes in a global network to support data discovery and promote human genome data access for research and healthcare. FEGA and GDI are both initially focused on enabling access to human genomic data, while FEGA ambition is to expand the scope to clinical research data and other omics data in the future. FEGA and GDI are both built on open and interoperable software solutions, a subset of which are based on the LocalEGA components. FEGA and GDI implementation solutions are based on international community standards, for example those developed by the Global Alliance for Genomics and Health, which contributes to making them interoperable. Both FEGA and GDI allow for the nodes to make use of any solution that is fully compatible. As illustrated in Figure 1, a final key point is the significant overlap of institutions involved in envisioning and operating FEGA and GDI nodes, with the clear wish to keep them interoperable in the future. What distinguishes Federated EGA from GDI? Despite being largely similar, there are some differences between the FEGA and GDI networks, which we aim to clarify in this post. The first difference is the governance model that the nodes will operate to comply with national laws and GDPR. In the FEGA network, nodes have taken inspiration from the EGA data access model, where the infrastructure is a data processor of the hosted data and data controllership remains with the originating Data Access Committees (i.e. Data controllers) for each dataset. On the other hand, in the GDI network the controllership of datasets will be transferred to a 1+MG European Digital Infrastructure Consortium (EDIC) legal entity created by the Member States (MS), who will make data access decisions, with data holders having veto powers for their datasets. Importantly, FEGA nodes have the flexibility to choose another model to fit with their data protection framework, including becoming data controllers for their datasets. The second difference is the inclusion criteria for data. While FEGA nodes are designed to accept almost any type of omics data in need of control access (e.g. genomics, transcriptomics, genotyping, single cells sequencing, patient-tracked metagenomics), GDI nodes are initially, but not only, focused on accepting whole genome and exome sequencing data and affiliated data from sources such as (i) the Genome of Europe use case of the 1+MG initiative which specifically aims to fulfil the mission of building “a European network of national genomic reference cohorts of at least 500,000 citizens”) (ii) data collection of other types of genomic data identified by countries through the 1+MG dashboard and (iii) genomic data coming from data holders which would need to fulfil EHDS requirements. The third difference is the maturity of the software stacks. The FEGA network provides a set of software for data and metadata submission, storage, permissions management, and file distribution (the LocalEGA package). GDI is building a complete set of open source reference for the five functionalities covering the full data life cycle (a few more compared to the LocalEGA) including federated processing (analytics, AI/ML), which is still under active development. Notably, one of the GDI functionalities - storage and interfaces - can be satisfied by using the LocalEGA storage solution, highlighting the ability of FEGA and GDI to be interoperable. In both FEGA and GDI, nodes are allowed to use alternative solutions as long as they are fully interoperable with the networks. Figure 1 provides a simple overview of these described commonalities and differences. Figure1: schematic overview of the main commonalities and difference among a FEGA and a GDI node Can the same institute run a FEGA and a GDI node at the same time? The answer is Yes! We believe this is entirely possible and encouraged. As long as 1+MG requirements are continuously fulfilled in the implementation. The same trained personnel could operate the infrastructure and leverage the same national funding to run a FEGA and a GDI node. Several European nodes, especially GDI vanguard nodes like Norway, Sweden, Finland and Spain are following this model. The idea is that a lot of the work can be reused, given the overlapping scope and the interoperable technology. Thus, the hosted datasets can be discovered via the two catalogues, perhaps accessible under the same or different governance models. From a FEGA node perspective, the GDI datasets could simply be a subset of the datasets hosted in the FEGA node, which have their specific governance as any other. What's next? So, the amazing teams of people building the Federated EGA network and the European GDI network are working together to create infrastructures able to provide secure access to human genomic and associated data around Europe. Because we all know how much human genomics can improve healthcare and precision medicine. And we all want to collaborate to make it happen. This article has been reviewed collectively by members of the EGA and the GDI coordination team.

  Blog fega-and-gdi

• NHLBI TOPMed: Children's Health Study (CHS) Effects of Air Pollution on the Development of Obesity in Children (Meta-AIR)

  The Effects of Air Pollution on the Development of Obesity in Children (Meta-AIR) study was proposed to study a subset of the Children's Health Study (CHS) participants representing the extremes of long-term traffic-related air pollution exposure occurring in Southern California CHS communities. The primary aim of the Meta-AIR study was to investigate whether lifetime exposure to air pollution increases risk for obesity and metabolic dysfunction at 17-18 years of age. A total of 56 Hispanic White participants (16 asthma cases and 40 controls) were included in the TOPMed project.

  Study phs001604

• Functional Analysis of Genetic Variants in African Americans with Breast Cancer

  The goal of this study is to identify and characterize novel genetic variants associated with a predisposition to breast cancer (BCa) in African Americans (AAs) using a family case-family control study design. Variants of unknown clinical significance (VUS) were characterized using bioinformatics tools. Future studies will further characterize select VUSs using in vitro genomic editing methods and functional assays to determine the functional consequences. The targeted sequencing data is made available for 85 actionable cancer genes. These genes have been previously classified with deleterious mutation(s) and whose phenotype results in a specific, defined medical recommendation(s).

  Study phs002977

• Proteomic predictors of individualized nutrient-specific insulin secretion in health and disease

  Population level variation and molecular mechanisms behind insulin secretion in response to carbohydrate, protein, and fat remain uncharacterized despite ramifications for personalized nutrition. We now define prototypical insulin secretion dynamics in response to the three macronutrients in islets from 140 cadaveric donors, including those diagnosed with type 2 diabetes. We leverage the insulin response heterogeneity and use transcriptomics and proteomics to identify molecular pathways of specific nutrient responsiveness. Surprisingly, we find robust insulin secretion to fatty acid stimulus in ~8% of donors, challenging the idea that fat has negligible effects on insulin release. Distinct islet proteomes with differences in metabolic signalling networks convey this hyper-responsiveness to fat relative to carbohydrate. By comparing human islets to human embryonic stem cell-derived islet clusters, we show that, unlike glucose-responsiveness, fat hyper-responsiveness is equivalent and may be a hallmark of functionally immature cells. Our study represents the first comparison of dynamic responses to nutrients and multi-omics analysis in human insulin secreting cells. Responses of different people’s islets to carbohydrate, protein, and fat lay the groundwork for personalized nutrition.

  Dataset EGAD50000000519

• Paired DNA and RNA sequencing uncovers common and rare genomic variants regulating gene expression in the human retina

  In this study, we uncovered common and rare genomic variants shaping retinal expression profiles. This includes 1,483,595 significant cis-expression quantitative trait loci (eQTLs) impacting 9,959 and 3,699 genes in NSR and RPE, respectively, with associated genomic variants enriched to cis-candidate regulatory elements and notable shared eGenes between NSR and RPE. We also detected 1051 expression outliers and prioritised 299 rare non-coding single-nucleotide, structural variants or copy number variants as plausible drivers for 28% of outlier events. This study increases understanding of gene expression regulation in the human retina.

  Study EGAS50000001443

• Ibrutinib induces a global chromatin reorganisation in chronic lymphocytic leukaemia

  Chronic lymphocytic leukaemia (CLL) is the most common haematological malignancy in developed countries. Ibrutinib (PCI-32765), a specific and irreversible inhibitor of Bruton's Tyrosine Kinase (BTK) represents a major step forward in the treatment of CLL. We have undertaken a detailed analysis of the changes happening to the chromatin structure in CLL cells from patients continuously receiving oral doses of ibrutinib. ChIP-seq has been performed for H3K4me3, H3K27ac, H3K27me3 and EZH2 . We observed that Ibrutinib-dependent lymphocytosis correlates with a global and transient recruitment of EZH2 to active cis-regulatory elements and increased H3K27me3.

  Study EGAS00001002827

• DNA from colon cancer samples and matched normal samples was hybridized on Human 660W-Quad SNP arrays and sequenced in Illumina HiScanSQ.

  DNA from colon cancer samples and matched normal samples was hybridized on Human 660W-Quad SNP arrays and sequenced in Illumina HiScanSQ. The objective of the study was to introduce methodology for the detection of genomic copy number alterations (CNAs) using high-throughput sequencing data. The samples in this study allow the comparison of the results from the seqCNA R package with those from other methods that detect copy number alterations (CNAs) in tumoural samples, either using SNP-array data or high-throughput sequencing data.

  Study EGAS00001000558

• Alternative lengthening of telomeres in childhood neuroblastoma from genome to proteome

  Telomere maintenance by telomerase activation or alternative lengthening of telomeres (ALT) is a major determinant of poor outcome in neuroblastoma. Here, we screen for ALT in primary and relapsed neuroblastomas and characterize its features using multi-omics profiling. We aim to deepen the knowledge about the biology and clinical features of ALT-positive neuroblastomas by enriching ALT tumors in the study cohort independent of ATRX mutation status. Using a combination of genomic, transcriptomic and proteomic profiling, we provide evidence that this subgroup is clinically and molecularly distinct.

  Study EGAS00001004349

• T-cell reconstitution after reduced dose ATLG induction in kidney transplant recipients

  Pre-sensitized kidney transplant recipients have a higher risk for rejection following kidney transplantation and therefore receive a lymphodepletional induction therapy with anti human T-lymphocyte globulin (ATLG). The time course of lymphocyte reconstitution with regards to overall and donor-reactive T-cell receptor (TCR) specificity remains elusive. In this study we aimed to describe the TCR repertoire in a reduced dose ATLG regimen making it possible to evaluate shifts in the shape of the immune repertoire and to detect the reappearance of donor-reactive T-cells following reduced lymphodepletional induction therapy.

  Study EGAS00001005941

• Discovery and capture of novel dynamic DNA methylation in human sperm with preferential links to altered folate metabolism

  The sperm DNA methylation landscape is unique and critical for offspring health. If gamete-derived DNA methylation escapes reprogramming in early embryos, epigenetic defects in sperm may be transmitted to the next generation. Current techniques to assess sperm DNA methylation show bias towards CpG dense regions and do not target areas of dynamic methylation, those predicted to be environmentally sensitive and tunable regulatory elements. Thus, this study aim to assess variation in human sperm DNA methylation and design a targeted capture panel to interrogate the human sperm methylome.

  Study EGAS00001003617