613 results for "monedas FC mobile comprar Visité Buyfc26coins.com. Rápido, seguro y económico. La triple corona..6yB2"

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• Tumour sample for patient SA598

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA598

  Dataset EGAD00001009202

• Normal sample for patient SA276

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA276

  Dataset EGAD00001009225

• Normal sample for patient SA279

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA279

  Dataset EGAD00001009226

• Normal sample for patient SA283

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA283

  Dataset EGAD00001009227

• Normal sample for patient SA287

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA287

  Dataset EGAD00001009228

• Tumour sample for patient SA680

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA680

  Dataset EGAD00001009347

• Tumour sample for patient SA681

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA681

  Dataset EGAD00001009348

• Tumour sample for patient SA682

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA682

  Dataset EGAD00001009349

• Normal sample for patient SA289

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA289

  Dataset EGAD00001009367

• Normal sample for patient SA682

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA682

  Dataset EGAD00001009382

• Normal sample for patient SA683

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA683

  Dataset EGAD00001009383

• Tumour sample for patient SA1058

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA1058

  Dataset EGAD00001009673

• Tumour sample for patient SA409

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA409

  Dataset EGAD00001009518

• Tumour sample for patient SA420

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA420

  Dataset EGAD00001009519

• Tumour sample for patient SA296

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA296

  Dataset EGAD00001009520

• Tumour sample for patient SA597

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA597

  Dataset EGAD00001009521

• Tumour sample for patient SA224

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA224

  Dataset EGAD00001009530

• Tumour sample for patient SA228

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA228

  Dataset EGAD00001009533

• Tumour sample for patient SA294

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA294

  Dataset EGAD00001009542

• Normal sample for patient SA1073

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

  Dataset EGAD00001009594

• Normal sample for patient SA211

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA211

  Dataset EGAD00001009545

• Normal sample for patient SA229

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA229

  Dataset EGAD00001009552

• Tumour sample for patient SA291

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA291

  Dataset EGAD00001009360

• Tumour sample for patient SA289

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA289

  Dataset EGAD00001009359

• Tumour sample for patient SA286

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA286

  Dataset EGAD00001009358

• Tumour sample for patient SA280

  Whole genome sequencing of tumour sample for triple negative breast cancer patient SA280

  Dataset EGAD00001009361

• Normal sample for patient SA680

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA680

  Dataset EGAD00001009380

• Normal sample for patient SA681

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA681

  Dataset EGAD00001009381

• Normal sample for patient SA233

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA233

  Dataset EGAD00001009556

• Normal sample for patient SA673

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA673

  Dataset EGAD00001009373

• Normal sample for patient SA678

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA678

  Dataset EGAD00001009378

• Normal sample for patient SA679

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA679

  Dataset EGAD00001009379

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0146_006

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0146_006 for Triple negative breast cancer sample SA535X6XB03099

  Dataset EGAD00001011223

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0142_004

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0142_004 for Triple negative breast cancer sample SA1035X6XB03209

  Dataset EGAD00001011243

• Tumour sample for patient SA1026

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

  Dataset EGAD00001009607

• Normal sample for patient SA533

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA533

  Dataset EGAD00001009571

• Normal sample for patient SA597

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA597

  Dataset EGAD00001009572

• Normal sample for patient SA997

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

  Dataset EGAD00001009573

• 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 SA1058

  Whole genome sequencing of normal sample for triple negative breast cancer patient SA1058

  Dataset EGAD00001009672

• Imaging metabolic heterogeneity in breast cancer using hyperpolarized 13C-MRI

  Higher 13C-lactate labeling was seen in the more aggressive tumors, including all triple negative breast cancers. There was a significant correlation between lactate labeling and expression of the monocarboxylate transporter (MCT1), which mediates tumor cell pyruvate uptake, and a weaker correlation with expression of LDHA, which catalyzes label exchange between the injected pyruvate and the endogenous lactate pool.

  Study EGAS00001004118

• Extracorporeal Life Support Survival in a Pediatric Hematopoietic Cellular Transplant Recipient with Presumed Graft Versus Host Disease-Related Fulminant Myocarditis

  We report the case of a 15-year-old female with hypodiploid pre-B acute lymphoblastic leukemia status post allogeneic hematopoietic stem cell transplantation (HCT) from a matched unrelated male donor who presented on transplant day +75 with cardiac arrest due to ventricular fibrillation associated with fulminant myocarditis. Using conventional diagnostics, an exhaustive search for microbial pathogens in the heart biopsy as well as nasopharynx, blood, urine, and endotracheal aspirate was performed but did not uncover a candidate pathogen. The family consented to a research study for the use of unbiased next-generation genomic sequencing for pathogen identification in the myocardial biopsy. DNA sequencing was performed on 1.5 x 108 sequencing pairs and no microbial pathogens were identified. Interestingly, a significant component of Y-chromosomal human DNA was identified, suggesting infiltration of at least 10 donor leukocytes per host cell. This finding is grossly consistent with the lymphocyte:myocyte ratio in the biopsy according to visual inspection at 40x magnification. This case merits discussion due to (1) her survival after 17 days of veno-arterial extracorporeal life support (ECLS) and (2) the possibility of cardiotropic graft versus host disease (GVHD).

  Study phs001336

• BARIA baseline first 100 individuals transcriptomes

  Prevalence of obesity and associated diseases, including type 2 diabetes mellitus, dyslipidaemia and non-alcoholic fatty liver disease (NAFLD), are increasing. Underlying mechanisms, especially in humans, are unclear. Bariatric surgery provides the unique opportunity to obtain biopsies and portal vein blood-samples. Methods The BARIA Study aims to assess how microbiota and their metabolites affect transcription in key tissues and clinical outcome in obese subjects and how baseline anthropometric and metabolic characteristics determine weight loss and glucose homeostasis after bariatric surgery. We phenotype patients undergoing bariatric surgery (predominantly laparoscopic Roux-en-Y gastric bypass), before weight loss, with biometrics, dietary and psychological questionnaires, mixed meal test (MMT) and collect fecal-samples and intra-operative biopsies from liver, adipose tissues and jejunum. We aim to include 1500 patients. A subset (approximately 25%) will undergo intra-operative portal vein blood-sampling. Fecal-samples are analyzed with shotgun metagenomics and targeted metabolomics, fasted and postprandial plasma-samples are subjected to metabolomics, and RNA is extracted from the tissues for RNAseq-analyses. Data will be integrated using state-of-the-art neuronal networks and metabolic modeling. Patient follow-up will be ten years.

  Study EGAS00001005704

• De novo assembly of 150 Danish genomes reveals rich structural complexity

  Most known genetic variation in human genomes has been called from comparison of short reads to the reference genome, an approach biased against finding complex variation. We sequenced 150 individuals from 50 parent-offspring trios with multiple insert-size libraries to very high coverage. We show that each genome could be independently de novo assembled into a small number of high-quality scaffolds (median N50 > 21 Mb), each of quality comparable to long read assemblies while being very cost-effective. We show that our variant call set from comparing de novo assemblies is far more complete in terms of complex variation than previous studies. Importantly, even the complex 4-5 Mb extended MHC region was assembled and resolved into haplotypes, revealing >700kb novel sequence in this important region of the genome, and major parts of the Y chromosome including some palindromes were assembled with high accuracy. Finally, we show that our variant call-set allows for the genotyping of many more complex variants when used as a reference-panel for imputation into SNP-chip data or into previously resequenced genomes.

  Study EGAS00001002108

• RNA-Seq Data From Early Stage Triple Negative Breast Cancer Tumors Treated With TVEC and Chemotherapy (MCC18621)

  This study is a phase 1/phase 2 trial testing the combination of talimogene laherparepvec (TVEC) and neoadjuvant chemotherapy for the treatment of stage II-III triple negative breast cancer. The trial demonstrated that the addition of TVEC to neoadjuvant chemotherapy was feasible, and resulted in a pathological complete response (pCR) rate of 45.9%, residual cancer burden (RCB) 0-1 rate of 65%, and event free survival of 89%. The macrodissected formalin-fixed paraffin-embedded (FFPE) samples were from 50 patients treated across two phases at different timepoints (pre-treatment, 6th week of treatment, and surgical resection). RNA-Seq data is provided along with clinical classifiers.

  Study phs003199

• 10x Single Cell Gene Expression Library TENX069

  10x Single Cell Gene Expression library TENX069 for Triple negative breast cancer patient-derived xenograft SA609X4XB03083

  Dataset EGAD00001011211

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0148_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0148_001 for Triple negative breast cancer patient-derived xenograft SA535X4XB02498

  Dataset EGAD00001011221

• 10x Single Cell Gene Expression Library SCRNA10X_SA_CHIP0189_001

  10x Single Cell Gene Expression library SCRNA10X_SA_CHIP0189_001 for Triple negative breast cancer patient-derived xenograft SA535X7XB03448

  Dataset EGAD00001011226