17515 results for "the best way to get coins in fc 26 Navštivte Buyfc26coins.com Společnost známá transparentními transakcemi..CQ2q"

in 19.62 milliseconds.

• Methylation data

  To ellucidate methylation activity in mRCC, methylation data was generated as part of the EuroTarget study

  Dataset EGAD50000002295

• Targeted resequencing of Acute Myeloid Leukemia patients with an acquired inv(3)(q21q26) or t(3;3)(q21;q26).

  Targeted resequencing on the specific regions chr3:126036241-130672290 and chr3:157712147-175694147 in hg19 centered on the chromosomal regions 3q21 and 3q26 respectively. The focus lies on the detection of the exact breakpoints in Acute Myeloid Leukemia (AML) patients having acquired a inv(3)(q21q26) or t(3;3)(q21;q26). This dataset contains all information to detect all structural variants contained within these regions, including the 3q-aberrations inducing the overexpression of the proto-oncogene EVI1.

  Dataset EGAD00001000727

• Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis

  This dataset contains raw sequencing files associated with the paper "Neutrophils and emergency granulopoiesis drive immune suppression and an extreme response endotype during sepsis" (https://doi.org/10.1038/s41590-023-01490-5). It is composed of two experiments, which are as follows: 1. Single-cell profiling of whole blood leukocytes: This experiment comprises sequencing files generated using the BD Rhapsody single-cell multi-omics profiling (RNA + protein) platform. This platform was used to profile the whole blood leukocyte population in a cohort of sepsis patients, cardiac surgery controls and healthy controls. There are 48 samples and four files per sample: two paired-end FASTQ files (R1 and R2) corresponding to the RNA-seq library, and two paired-end FASTQ files (R1 and R2) corresponding to the protein profiling (ADT-based AbSeq) library. 2. Single-cell profiling of circulating HSPCs: This experiment comprises sequencing files generated using the 10X single-cell multi-omics (RNA-seq + ATAC-seq) profiling platform. This platform was used to profile circulating HSPCs in a cohort of sepsis patients and healthy controls. There are 5 samples (or plexes), each of which consists of a pool of individuals for whom cells were multiplexed and sequenced as a single sample. There are four files per sample: two paired-end FASTQ files (R1 and R2) corresponding to the RNA-seq library, and two paired-end FASTQ files (R1 and R2) corresponding to the ATAC-seq library. Because these samples consists of multiplexed pools, index files are also provided. These can be used for sample deconvolution using the Cell Ranger pipeline. NOTE: Due to EGA's constrains in the number of files permitted per sample, index files (I1 and I2) for the HSPC data set are provided as a separate experiment named "FASTQ index files (I1 and I2) for deconvolution of 10X single-cell multiomics libraries".

  Dataset EGAD00001010927

• PARK7/DJ-1 deficiency modulates microglial activation in response to LPS-induced inflammation

  Starting point is one patient from which iPSC cells are created, some received a genome correction to be called iCtrl from those two batches (DJ1 and iCtrl). 3 independent differentiation to Microglia cells were done, named R1, R2 and R3. On top, growing conditions were either untreated or LPS, leading to the 12 samples.

  Dataset EGAD50000000291

• Kids First and INCLUDE: Down Syndrome, Heart Defects, and Acute Lymphoblastic Leukemia

  This project is a collaboration with the trans-NIH INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE (INCLUDE) Project, which seeks to improve health and quality-of-life for individuals with Down syndrome, and NHLBI's TransOmics for Precision Medicine (TOPMed) program, which seeks to apply omics technologies to improve scientific understanding of the fundamental biological processes that underlie heart, lung, blood, and sleep (HLBS) disorders. The data is also available at the INCLUDE Data Hub. Down syndrome (DS), which occurs due to trisomy 21, is one of the strongest risk factors for both congenital heart disease (CHD) and acute leukemia. For instance, children with DS have a 2000-fold increased risk of atrioventricular septal defects (AVSD) and a 20-fold increased risk of acute lymphoblastic leukemia (ALL). An important and innovative aspect of the Kids First program is understanding the overlap between structural birth defects and childhood cancer. Notably, the background of DS predisposes children to both of these phenotypes, however, the genomic architecture of risk remains largely undiscovered. In this joint Kids First/TOPMed/INCLUDE project, we are currently including >2,000 samples for whole-genome sequencing, including: 1) paired germline-tumor samples from children with DS-ALL; and 2) samples from families with DS-CHD. This work will advance our understanding of the developmental pathways that may lead to both structural birth defects and childhood cancer. The objectives of this study are to determine the genetic variants underlying AVSD and ALL risk in children with DS. Therefore, the aims of our study are: 1) compare whole-genome sequencing (WGS) data between children with documented DS-AVSD and children with DS who have structurally normal hearts to identify genetic variants that perturb heart development; and 2) compare WGS data between children with documented DS-ALL and children (from Aim 1) with DS who do not have a known history of ALL. We will also examine associations between germline mutations and somatic genomic features. This study will address the fundamental question of why children with DS have an elevated risk of AVSD and ALL. Insights into the genes that drive DS-AVSD and DS-ALL may have implications for improved genetic counseling, surveillance, clinical management, and treatment strategies for these children. Additionally, our findings may inform targeted therapies or interventions for children without DS who are at risk for structural birth defects and cancer. Additional Pediatric Cardiac Genetics Consortium (PCGC) data from children affected with Down syndrome and congenital heart disease are accessible through two separate dbGaP studies: phs001138 (Kids First) and phs001194 (TOPMed).

  Study phs002330

• PCNSL single cell dataset

  Mononuclear cells were isolated as cell suspensions by dissociation in a BD Horizon™ Dri Tumor & Tissue Dissociation Reagent (BD Biosciences) using a gentleMACS dissociator (Miltenyi Biotec). A totalseq-C antibody cocktail (Biolegend) was used, and the cell suspensions were diluted to a concentration of 1,000 cells/μL. Library sequencing was performed using the DNBSEQ-G400 (MGI Tech), Illumina HiSeq 2000, or Illumina NovaSeq 6000 5 (Illumina). The FASTQ files were aligned to the 10x provided reference genome using 10x Genomics Cell Ranger software v7.1.0 to create unique molecular identifier count tables of gene expression of the samples.

  Dataset EGAD50000000685

• Overrepresentation of genetic variation in the AnkyrinG interactome is related to a range of neurological disorders

  Upon the discovery of numerous genes involved in the pathogenesis of neurodevelopmental disorders, several studies showed that a significant proportion of these genes converge on common pathways and protein networks. Here, we used a reversed approach, by screening the well-characterized AnkyrinG protein-protein interaction network, implicated in a variety of neurodevelopmental disorders, for genetic variation in a large cohort of 1009 cases with neurodevelopmental disorder. We identified a significant enrichment of de novo potentially disease-causing variants in this network, confirming that this protein network plays an important role in the emergence of several neurodevelopmental disorders.

  Study EGAS00001004326

• Human NXPE1 mediates variation in sialic acid O-acetylation in Colon Tissue

  Sialylation, and its modifications, have important consequences for development, differentiation and immune system regulation in nearly all human tissues. An accounting of all the genes responsible for modifying sialic acids is incomplete, with only one pathway for O-acetylation being well-defined in humans. Using whole genome sequencing of normal human colorectal tissue we identify a haplotype on chromosome 11 that is associated with differences in mild periodic acid Schiff staining (mPAS), a marker of acetylation of sialic acids. Of the genes in this region, only SNPs from NXPE1 correlate perfectly in a validation data set. NXPE1 protein expression by IHC also correlates with mPAS staining patterns in homozygous, as well as heterozygous colon crypts that have undergone spontaneous gain of the mPAS phenotype. Manipulation of NXPE1 expression with CRISPR-Cas9 causes changes to modified sialic acid levels in both 2D cell line and 3D normal colon organoid models. These findings suggest NXPE1 may cause O-acetylation of sialic acids in colorectal tissue, potentially defining NXPE as a new family of sialic acid-modifying genes.

  Study EGAS00001007704

• Whole genome sequencing of patients with or at risk for HCC

  Liver cancer is a major cause of cancer mortality worldwide. Screening individuals at high risk, including those with cirrhosis and viral hepatitis, provides an avenue for improved survival, but current screening methods are inadequate. In this study, we used whole-genome cell-free DNA (cfDNA) fragmentome analyses to evaluate 724 individuals from the United States, the European Union, or Hong Kong with hepatocellular carcinoma (HCC) or who were at average or high-risk for HCC. Using a machine learning model that incorporated multifeature fragmentome data, the sensitivity for detecting cancer was 88% in an average-risk population at 98% specificity and 85% among high-risk individuals at 80% specificity. We validated these results in an independent population. cfDNA fragmentation changes reflected genomic and chromatin changes in liver cancer, including from transcription factor binding sites. These findings provide a biological basis for changes in cfDNA fragmentation in patients with liver cancer and provide an accessible approach for noninvasive cancer detection.

  Study EGAS00001007249

• Pediatric CNS tumor classification by DNA-methylation dataset

  In this study nanopore sequencing was applied to obtain sparse DNA methylation profiles from pediatric CNS tumor samples. A neural network was used to classify the tumor based on the obtained methylation profile.

  Dataset EGAD00010002599