12289 results for "best fc coin sites reddit Visit Buyfc26coins.com for latest FC 26 coins news..KX6d"

in 37.98 milliseconds.

• Normal sample for patient SA095

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA095

  Dataset EGAD00001009600

• Tumour sample for patient SA400

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA400

  Dataset EGAD00001009576

• Tumour sample for patient SA290

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA290

  Dataset EGAD00001009577

• Tumour sample for patient SA288

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA288

  Dataset EGAD00001009578

• Tumour sample for patient SA299

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA299

  Dataset EGAD00001009579

• Tumour sample for patient SA095

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA095

  Dataset EGAD00001009580

• Tumour sample for patient SA415

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA415

  Dataset EGAD00001009581

• Normal sample for patient SA718

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA718

  Dataset EGAD00001009582

• Normal sample for patient SA720

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA720

  Dataset EGAD00001009583

• Tumour sample for patient SA718

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA718

  Dataset EGAD00001009584

• Tumour sample for patient SA720

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA720

  Dataset EGAD00001009585

• Normal sample for patient SA1017

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1017

  Dataset EGAD00001009586

• Normal sample for patient SA1026

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1026

  Dataset EGAD00001009587

• Normal sample for patient SA1027

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1027

  Dataset EGAD00001009588

• Normal sample for patient SA1028

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1028

  Dataset EGAD00001009589

• Normal sample for patient SA1040

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1040

  Dataset EGAD00001009590

• Normal sample for patient SA1064

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1064

  Dataset EGAD00001009591

• Normal sample for patient SA1065

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1065

  Dataset EGAD00001009592

• Normal sample for patient SA1069

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1069

  Dataset EGAD00001009593

• Normal sample for patient SA1073

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1073

  Dataset EGAD00001009594

• Normal sample for patient SA1074

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1074

  Dataset EGAD00001009595

• Normal sample for patient SA576

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA576

  Dataset EGAD00001009596

• Normal sample for patient SA610

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA610

  Dataset EGAD00001009597

• Normal sample for patient SA992

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA992

  Dataset EGAD00001009598

• Normal sample for patient SA994

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA994

  Dataset EGAD00001009599

• Normal sample for patient SA288

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA288

  Dataset EGAD00001009601

• Normal sample for patient SA299

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA299

  Dataset EGAD00001009602

• Normal sample for patient SA415

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA415

  Dataset EGAD00001009603

• Normal sample for patient SA666

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA666

  Dataset EGAD00001009604

• Tumour sample for patient SA1065

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1065

  Dataset EGAD00001009605

• Tumour sample for patient SA1064

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1064

  Dataset EGAD00001009606

• Tumour sample for patient SA1026

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1026

  Dataset EGAD00001009607

• Tumour sample for patient SA1069

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1069

  Dataset EGAD00001009608

• Tumour sample for patient SA1017

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1017

  Dataset EGAD00001009609

• Tumour sample for patient SA1027

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1027

  Dataset EGAD00001009610

• Tumour sample for patient SA1073

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1073

  Dataset EGAD00001009611

• Tumour sample for patient SA1074

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1074

  Dataset EGAD00001009612

• Tumour sample for patient SA576

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA576

  Dataset EGAD00001009613

• Tumour sample for patient SA1028

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1028

  Dataset EGAD00001009614

• Tumour sample for patient SA1040

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1040

  Dataset EGAD00001009615

• Tumour sample for patient SA992

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA992

  Dataset EGAD00001009616

• Tumour sample for patient SA610

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA610

  Dataset EGAD00001009617

• Normal sample for patient SA416

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA416

  Dataset EGAD00001009618

• Normal sample for patient SA1070

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1070

  Dataset EGAD00001009619

• Tumour sample for patient SA1070

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1070

  Dataset EGAD00001009620

• Tumour sample for patient SA997

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA997

  Dataset EGAD00001009621

• Development of CMT Peds Scale for Children with CMT

  Information about how different forms of CMT affect children is not readily available because there are not good methods to measure impairment of children with CMT. The purpose of this project is to develop and test such a method and to then test this scale to ensure that it is an effective measurement of impairment of CMT in children, that the children tolerate it well, that different investigators using this method obtain similar results and that changes over time with the scale allow measurement of progression of CMT in the children. Primary Objective: To develop and test the CMT Peds scale (CMTPedS) in children with CMT in order to refine the scoring for future natural history and therapeutic trials. Secondary Objective: We propose to test the sensitivity of the CMT Peds Scale in a longitudinal study and compare the CMT Peds Scale with the Children's Quality of Life scale CHQ-PF50. 2000 patients <21 years of age with various forms of CMT will be evaluated at baseline and at subsequent annual follow up visits when possible. This first study release makes available data of n=208 study participants.

  Study phs001553

• Mapping Genes for Mammographic Density

  We recruited 1,521 women from the Old Order Amish (OOA) population of Lancaster County, Pennsylvania, with the primary goal of identifying genetic factors that influence mammographic density. All women were between the ages of 40 and 88 years, with a mean of 54 years. Additional study design details, including eligibility criteria, are described elsewhere (Douglas et al., 2008). The present-day OOA of Lancaster County are the descendants of approximately 550 individuals from central Western Europe who immigrated to the U.S. in the early eighteenth century. All living individuals derive from a single, 14-generation pedigree (Lee et al., 2010). Although the OOA are a genetically closed founder population, allele frequencies and LD profiles are remarkably similar between the OOA and U.S. participants in the International HapMap project (HapMap CEU) for common SNPs (MAF>/=5%) (Van Hout et al., 2010). We recently completed genome-wide linkage and association analyses of mammographic density, including dense and non-dense areas of the breast and the ratio of dense to total area of the breast. Summary-level data from our GWAS are available here and through the Marker of DEnsity (MODE) Consortium.

  Study phs000604

• Establishing stable brain tumor stem cell lines and translational research for new treatments

  Choroid plexus carcinomas (CPCs) have dismal prognoses with limited clinical options. A lack of characterized cell lines has hindered the development of new treatment strategies. Here, we perform whole genome sequencing analyses of two cell lines established from CPCs. Whole genome sequencing (WGS),was performed in CCHE-45 and NGT131 cell lines. Both cell lines harbored pathogenic TP53 point mutations; CCHE-45 additionally displayed TP53 loss. Furthermore, alterations of the NOTCH and WNT pathways were also detected in both cell lines. Two protein-coding gene fusions, BZW2-URGCP, and CTTNBP2-ERBB4, mutations of two oncodrivers, GBP-4 and KRTAP-12-2, and several copy number alterations were observed in CCHE-45, but not NGT131. The discovered difference's importance and implications highlight the possible diversity of choroid plexus carcinoma and call for additional research to fully understand disease pathogenesis. Whole genome sequencing revealed that the two choroid plexus carcinoma cell lines shared TP53 mutations and other common pathway alterations and activation of NOTCH and WNT pathways. Noticeable differences were also observed. These cell lines can serve as valuable models to propose new treatments in these rare but deadly brain tumors.

  Study JGAS000657

• Investigation of molecular diagnosis by molecular biological analysis using next-generation sequencer for actionable endocrine diseases (including neoplastic diseases)

  Fructose-1,6-bisphosphatase (FBPase) deficiency, caused by an FBP1 mutation, is an autosomal recessive disorder characterized by hypoglycemic lactic acidosis. Due to the rarity of FBPase deficiency, the mechanism by which the mutations cause enzyme activity loss still remains unclear. Here we identify compound heterozygous missense mutations of FBP1, c.491G>A (p.G164D) and c.581T>C (p.F194S), in an adult patient with hypoglycemic lactic acidosis. The G164D and F194S FBP1 mutants exhibit decreased FBP1 protein expression and a loss of FBPase enzyme activity. The biochemical phenotypes of all previously reported FBP1 missense mutations in addition to G164D and F194S are classified into three functional categories. Type 1 mutations are located at pivotal residues in enzyme activity motifs and have no effects on protein expression. Type 2 mutations structurally cluster around the substrate binding pocket and are associated with decreased protein expression due to protein misfolding. Type 3 mutations are likely nonpathogenic. These findings demonstrate a key role of protein misfolding in mediating the pathogenesis of FBPase deficiency, particularly for Type 2 mutations. This study provides important insights that certain patients with Type 2 mutations may respond to chaperone molecules.

  Study JGAS000625