14478 results for "PLOS+ONE+Pennsylvania+German+ACS+language+code+pdc+open+access+study"

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• This DAC is the list of persons that, on behalf of the UKBEC consortium, manage the access to the UKBEC data.

  Dac EGAC00001000314

• This agreement governs the terms on which access will be granted to the data generated by the United Kingdom Brain Expression Consortium.

  Dac EGAC00001001408

• Data Access Commitee for Dietrich and Wendisch et al., SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis (Submitted)

  Dac EGAC00001001884

• Data Access Commitee for Dietrich and Wendisch et al., SARS-CoV-2 infection triggers profibrotic macrophage responses and lung fibrosis (Submitted)

  Dac EGAC00001002335

• Institute of Neuropathology - University of Freiburg Medical Center

  The Data Access Committee of the Institute of Neuropathology Freiburg.

  Dac EGAC50000000033

• DAC anti-MPO BCR sequences

  DAC for the requests of access to data of anti-MPO BCR sequences in the EGA repository,

  Dac EGAC50000000446

• DAC for hepatoblastoma sequencing data

  Data Access Committee for sequencing data of hepatoblastoma PDX cell models sequenced under University of Helsinki.

  Dac EGAC50000000548

• NGS-based monitoring of the T cell receptor repertoire in living donor kidney transplant patients undergoing combination cell therapy

  PBMCs from six kidney transplant recipients receiving as part of the Trex001 study autologous Tregs and donor bone marrow and six control patients not receiving either of the two treatments were collected pre-transplant and at one, three and six month post-transplant. Donor reactive T-cells were identified by mixed lymphocyte reactions (MLR) and lineage specific T-cell receptor (TCR) repertoires of native T-cells and proliferating and non-proliferating T-cells from MLRs were determined by next generation sequencing based profiling of the TCR.

  Dataset EGAD50000000302

• DAC for Breast Invasive Lobular Carcinoma CDH1 study

  We developed an artificial intelligence (AI)-model applied to histological images trained using CDH1 biallelic mutations, pathognomonic for breast invasive lobular carcinoma (ILC), as ground truth. We evaluated the performance of the AI-model to predict the presence of CDH1 biallelic mutations and to diagnose ILC. Subsequently, we investigated the molecular underpinning of cases predicted by the model to harbor a CDH1 biallelic mutations but lacking these alterations according to targeted sequencing. We then subjected one ILC lacking CDH1 biallelic mutations and lacking CDH1 promoter methylation to whole genome sequencing (WGS) to determine the molecular basis of its lobular phenotype.

  Dac EGAC50000000333

• WGS data subfolder HFG3FCCXY from multifocal ileal NETs study

  This dataset includes linked-read whole-genome sequencing data (subfolder HFG3FCCXY) for multifocal ileal tumor samples from one patient. Samples were sequenced using the 10x Genomics linked-read whole-genome sequencing (WGS) approach.

  Dataset EGAD00001008496

• WGS data subfolder HF3FKCCXY from multifocal ileal NETs study

  This dataset includes linked-read whole-genome sequencing data (subfolder HF3FKCCXY) for multifocal ileal tumor samples from one patient. Samples were sequenced using the 10x Genomics linked-read whole-genome sequencing (WGS) approach.

  Dataset EGAD00001008492

• Resuscitation Outcomes Consortium (ROC) Controlled Study of the Clinical Effectiveness of Automated Real-Time Feedback on CPR Process Conducted at a Subset of ROC Sites (CPR) (ROC-CPR-BioLINCC)

  Data Access NOTE: Please refer to the "Authorized Access" section below for information about how access to the data from this accession differs from many other dbGaP accessions.Objectives: A substudy of the ROC PRIMED trial, the ROC CPR trial sought to investigate whether real-time audio and visual feedback during cardiopulmonary resuscitation (CPR) outside a hospital increases the proportion of participants who achieved prehospital return of spontaneous circulation.Background: Cardiopulmonary resuscitation is an essential link in the chain of survival for treating cardiac arrest. However, performance of CPR is highly variable both outside hospital and in hospital. Interruptions in chest compression, inadequate depth of chest compression, and high rates of ventilation adversely affect blood flow during chest compressions and can hinder resuscitation. Suboptimal CPR, particularly time spent without chest compressions (low chest compression fraction), can reduce survival of cardiac arrest patients.Current technology incorporated into a monitor-defibrillator can assess core components of CPR through the use of an accelerometer and impedance changes across the defibrillation electrodes. This technology can also provide real-time audiovisual feedback so that the rescuer is prompted to perform according to guideline specifications. Use of such feedback increases the likelihood of performing CPR in accordance with guidelines during training and simulation. Participants: There were 1586 participants: 771 treated without feedback and 815 with feedback.Design: CPR feedback was provided through proprietary Q-CPR software operating in the Philips MRx monitor-defibrillator. The feedback feature of the defibrillator includes audible voice prompts and visual messages on the monitor screen that are triggered when measured chest compressions or ventilation deviate from guidelines or are interrupted.The study was conducted in 21 emergency medical service (EMS) agencies at three ROC regions in the U.S. and Canada. Randomized treatment clusters, which ranged from individual emergency medical vehicles to groups of emergency agencies, were assigned to feedback-on or feedback-off treatments. Each cluster remained in its assigned mode for two to seven months, after which it switched to the opposite treatment arm. At the end of those two treatment periods, each cluster was again randomly assigned to feedback-on or feedback-off. This cycle continued for the duration of the study. Each cluster switched treatment arms at least once, and up to four times, during the study. Conclusions: Real-time visual and audible feedback during CPR altered performance to more closely conform with CPR guidelines. Clusters assigned to feedback were associated with increased proportion of time in which chest compressions were provided, increased compression depth, and decreased proportion of compressions with incomplete release. However, frequency of prehospital return of spontaneous circulation did not differ according to feedback status, nor did the presence of a pulse at hospital arrival, survival to discharge, or awake at hospital discharge (Hostler, et al., 2011, PMID: 21296838).

  Study phs003818

• SEER Remote Access Pilot Test Data (2018)

  This is a limited use Surveillance, Epidemiology, and End Results (SEER) file for use in a pilot test of remote data access. The SEER Program of the National Cancer Institute (NCI) is an authoritative source of information on cancer incidence and survival in the United States. SEER currently collects and publishes cancer incidence and survival data from population-based cancer registries covering approximately 34.6 percent of the U.S. population. The SEER Program registries routinely collect data on patient demographics, primary tumor site, tumor morphology and stage at diagnosis, first course of treatment, and follow-up for vital status. The mortality data reported by SEER are provided by the National Center for Health Statistics. The population data used in calculating cancer rates is obtained periodically from the Census Bureau. The SEER research data files include SEER incidence and population data associated by age, sex, race, year of diagnosis, and geographic areas.

  Study phs002012

• The Thrifty Microbiome: The Role of the Gut Microbiota in Obesity in the Amish

  Emerging evidence that the gut microbiota may contribute in important ways to human health and disease has led us and others to hypothesize that both symbiotic and pathological relationships between gut microbes and their host may be key contributors to obesity and the metabolic complications of obesity. Our "Thrifty Microbiome Hypothesis" poses that gut microbiota play a key role in human energy homeostasis. Specifically, constituents of the gut microbial community may introduce a survival advantage to its host in times of nutrient scarcity, promoting positive energy balance by increasing efficiency of nutrient absorption and improving metabolic efficiency and energy storage. However, in the presence of excess nutrients, fat accretion and obesity may result, and in genetically predisposed individuals, increased fat mass may result in preferential abdominal obesity, ectopic fat deposition (liver, muscle), and metabolic complications of obesity (insulin resistance, hypertension, hyperlipidemia). Furthermore, in the presence of excess nutrients, a pathological transition of the gut microbial community may occur, causing leakage of bacterial products into the intestinal lymphatics and portal circulation, thereby inducing an inflammatory state, further aggravating metabolic syndrome traits and accelerating atherosclerosis. This pathological transition and the extent to which antimicrobial leakage occurs and causes inflammatory and other maladaptive sequelae of obesity may also be influenced by host factors, including genetics. In the proposed study, we will directly test the Thrifty Microbiome Hypothesis by performing detailed genomic and functional assessment of gut microbial communities in intensively phenotyped and genotyped human subjects before and after intentional manipulation of the gut microbiome. To address these hypotheses, five specific aims are proposed: (1) enroll three age- and sex-matched groups from the Old Order Amish: (i) 50 obese subjects (BMI > 30 kg/m2) with metabolic syndrome, (ii) 50 obese subjects (BMI > 30 kg/m2) without metabolic syndrome, and (iii) 50 non-obese subjects (BMI < 25 kg/m2) without metabolic syndrome and characterize the architecture of the gut microbiota from the subjects enrolled in this study by high-throughput sequencing of 16S rRNA genes; (2) characterize the gene content (metagenome) to assess the metabolic potential of the gut microbiota in 75 subjects to determine whether particular genes or pathways are correlated with disease phenotype; (3) characterize the transcriptome in 75 subjects to determine whether differences in gene expression in the gut microbiota are correlated with disease phenotype, (4) determine the effect of manipulation of the gut microbiota with antibiotics on energy homeostasis, inflammation markers, and metabolic syndrome traits in 50 obese subjects with metabolic syndrome and (5) study the relationship between gut microbiota and metabolic and cardiovascular disease traits, weight change, and host genomics in 1,000 Amish already characterized for these traits and in whom 500K Affymetrix SNP chips have already been completed. These studies will provide our deepest understanding to date of the role of gut microbes in terms of 'who's there?', 'what are they doing?', and 'how are they influencing host energy homeostasis, obesity and its metabolic complications? PUBLIC HEALTH RELEVANCE: This study aims to unravel the contribution of the bacteria that normally inhabit the human gastrointestinal tract to the development of obesity, and its more severe metabolic consequences including cardiovascular disease, insulin resistance and Type II diabetes. We will take a multidisciplinary approach to study changes in the structure and function of gut microbial communities in three sets of Old Order Amish patients from Lancaster, Pennsylvania: obese patients, obese patients with metabolic syndrome and non-obese individuals. The Old Order Amish are a genetically closed homogeneous Caucasian population of Central European ancestry ideal for genetic studies. These works have the potential to provide new mechanistic insights into the role of gut microflora in obesity and metabolic syndrome, a disease that is responsible for significant morbidity in the adult population, and may ultimately lead to novel approaches for prevention and treatment of this disorder.

  Study phs000258

• HiDEF-seq single-molecule sequencing of single-strand mismatches and damage

  Our study sought to resolve, with single-molecule fidelity, the mismatches and damage events that precede DNA mutations. Using a novel single-molecule, long-read sequencing method (HiDEF-seq) we detect base substitutions when present in either one or both DNA strands. We also detect cytosine deamination, a common type of DNA damage, with single-molecule fidelity. This study profiled 134 samples from diverse tissues, including from individuals with cancer predisposition syndromes. These samples revealed single-strand mismatch and damage signatures. Since double-strand DNA mutations are only the endpoint of the mutation process, our approach enables new studies of how mutations arise in a variety of contexts, especially in cancer and aging.

  Dataset EGAD50000000460

• Offspring Sex Impacts DNA Methylation and Gene Expression in Placentae from Women with Diabetes during Pregnancy

  Exposure to diabetes in utero is known to increase the offspring's likelihood of developing metabolic disease in adulthood, but the mechanisms involved are unknown. It has been proposed that early exposure to hyperglycemia and elevated insulin levels may lead to malprogramming of the fetus leading to the subsequent development of diabetes and obesity. Epigenetic modifications of the genome including DNA methylation, provide a plausible mechanism that allows for permanent propagation of gene activity states from one generation of cells to the next. The placenta, a fetal tissue easily accessible for study, is a complex organ that is essential in regulating fetal growth. The changes in placental nutrient transport associated with diabetes during pregnancy (DDP) have significant effects on the developing fetus, indicating that the placenta plays a critical role in fetal programming. The aim of our study was to investigate whether exposure to DDP alters genome-wide DNA methylation in the placenta obtained from term pregnancies resulting in differentially methylated loci of metabolically relevant genes and downstream changes in RNA and protein expression.

  Study phs001535

• The Genetic Basis of Progression in Multiple Sclerosis

  This study examined the genetic determinants of multiple sclerosis (MS) severity in an international cohort of people with MS assembled by the International Multiple Sclerosis Genetics Consortium (IMSGC) and the MultipleMS Consortium. A total of 12,584 people with MS of European ancestry were included in the main genome-wide association study (GWAS). Participants were enriched for older individuals with longer disease duration (mean age 51.7 years and mean disease duration 18.2 years). All individuals were whole-genome genotyped on the Illumina Global Screen Array (GSAMD-24v2-0). Imputation was performed using the Haplotype Reference Consortium reference panel. The primary outcome was the age-related MS severity score. All individuals had at least 1 expanded disability status scale (EDSS) measure. When multiple EDSS scores were available, the last one was selected to calculate the age-related MS severity score.Of those 12,584 people with MS, this data release includes 4,623 participants recruited from non-European sites in the US, Canada and Australia. This release includes individual-level genotype and phenotype files necessary to replicate our GWAS of MS severity, including covariates.

  Study phs002929

• Pharmacokinetics and Pharmacogenomics of Ribociclib in Race-Based Cohorts (LEANORA)

  Underrepresented populations' participation in clinical trials remains limited, and the potential impact of genomic variants on drug metabolism remains elusive. This study aimed to assess the pharmacokinetics (PK) and pharmacogenomics (PGx) of ribociclib in self-identified Black women with hormone receptor positive (HR+)/human epidermal growth factor receptor 2-negative (HER2) advanced breast cancer. LEANORA (NCT04657679) was a prospective, observational, multicenter cohort study involving 14 Black women. PK and PGx were evaluated using tandem mass spectrometry and PharmacoScan microarray. CYP3A5*3, CYP3A5*6, and CYP3A5*7 variants were genotyped and CYP3A5 phenotypes were constructed from these data. We observed 7 poor metabolizers (PM), 6 intermediate metabolizers (IM), and one normal metabolizer (NM). The area under the curve of plasma concentration versus time curve (AUC) of ribociclib did not differ between PMs (39,230 hr*ng/mL) and IM/NMs (43,546 hr*ng/mL; P=0.38). The incidence of adverse events (AEs) was also similar. We found no association between CYP3A5 genotype and ribociclib exposure. Continued efforts are needed to include diverse populations in clinical trials to ensure equitable treatment outcomes.

  Study phs003770

• Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer

  Circulating tumor DNA (ctDNA)-based minimal residual disease (MRD) monitoring shows promise for risk stratification and decision-making in cancer patients. However, factors like background noise from non-tumor DNA, clonal haematopoiesis, and non-shedding tumors may complicate manual interpretation and limit its clinical application. In this proof-of-concept study in advanced non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), we developed an algorithm that automatically classifies serial cell-free DNA (cfDNA) samples, thereby enabling reliable and reproducible interpretation, and preventing time-consuming manual interpretation in approximately 75% of patients. Importantly, application of the algorithm allowed early risk stratification and decision-making, specifically identifying approximately 35% of patients with short-term clinical benefit and approximately 25% of patients who may potentially benefit from treatment escalation. Simultaneous serum tumor marker (STM) monitoring further improved risk stratification and decision-making in our study, enabling accurate identification of all patients with a clinical benefit of at least one year.

  Study EGAS50000001554

• Preeclampsia InterPregGen Consortium: Whole Genome Sequencing of 100 unrelated Uzbeks (DNA samples from the Institute of Immunology, Uzbek Academy of Sciences, Tashkent, Uzbekistan; Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology, Tashkent, Uzbekistan)

  Preeclampsia (PE) is a syndrome affecting pregnant mothers and fetus/babies characterised by hypertension and proteinuria, and is a leading cause of maternal and fetal death and of premature births worldwide. The InterPregGen Consortium was funded by a European Framework 7 (FP7) grant and grew out of the WTCCC3 GWAS comparing ~2000 UK PE mothers with ~6000 common UK controls. The EGAS00001000416 study data is whole genome sequencing of 100 unrelated Uzbeks in order to impute genotypes into PE cases and controls from Uzbekistan and to provide genetic data and infrastructure for future genetic studies in Uzbekistan and Central Asia more generally and to fill a gap in worldwide information as Central Asia is not adequately represented in available genomic data. This study is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators in Tashkent, Uzbekistan at the Institute of Immunology, Uzbek Academy of Sciences and at the Republic Specialized Scientific Practical Medical Centre of Obstetrics and Gynecology

  Study EGAS00001000416

• Preeclampsia InterPregGen Consortium: Whole Genome Sequencing of 100 unrelated Kazakhs (DNA samples from the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan; Gulnara Svyatova, Principal Investigator

  Preeclampsia (PE) is a syndrome affecting pregnant mothers and fetus/babies characterised by hypertension and proteinuria, and is a leading cause of maternal and fetal death and of premature births worldwide. The InterPregGen Consortium was funded by a European Framework 7 (FP7) grant and grew out of the WTCCC3 GWAS comparing ~2000 UK PE mothers with ~6000 common UK controls. The EGAS00001000417 study data is whole genome sequencing of 100 unrelated Kazakhs in order to impute genotypes into PE cases and controls from Kazakhstan and to provide genetic data and infrastructure for future genetic studies in Kazakhstan and Central Asia more generally and to fill a gap in worldwide information as Central Asia is not adequately represented in available genomic data. This study is one component of the InterPregGen FP7 project. DNA samples for this component were collected by InterPregGen Consortium collaborators at the Scientific Center of Obstetrics, Gynecology and Perinatology, Almaty, Kazakhstan (Gulnara Svyatova, Principal Investigator)

  Study EGAS00001000417

• Single Cell Analysis Program - Transcriptome (SCAP-T)

  This initiative is part of the Single Cell Analysis Program (SCAP) and is funded through the NIH Common Fund (See http://nihroadmap.nih.gov/), which supports cross-cutting programs that are expected to have exceptionally high impact. Common Fund initiatives address key roadblocks in biomedical research that impede basic scientific discovery and its translation into improved human health. In addition, these programs capitalize on emerging opportunities to catalyze progress across multiple biomedical fields. Single cell analysis has recently emerged as an important field of research because technologies have improved in sensitivity and throughput sufficiently to begin measuring and understanding heterogeneity in complex biological systems and correlating it with changes in biological function and disease processes. By profiling individual cells it is possible to resolve rare cells, transient cell states, and the influence of organization and environment on such cells and states, which cannot be described by ensemble measurements. The long-term goal of the SCAP is to accelerate this move towards personalizing health to the cellular level by understanding the link between cell heterogeneity, tissue function and emergence of disease through the discovery, development and translation of innovative approaches which will dramatically change the way cells are characterized. The SCAP will focus on research, which will systematically measure, analyze and model cell-to-cell variation, and identify crucial differences and rare biological states, which may have important functional consequences. Under SCAP, there are three studies to evaluate the cellular heterogeneity using transcriptional profiling of single cells (U01): University of Pennsylvania: Role of single cell mRNA variation in systems associated electrically excitable cells University of Southern California: Evaluation of cellular heterogeneity using patchclamp and RNA-seq of single cells University of California at San Diego: Single cell sequencing and in situ mapping of RNA transcripts in human brains The SCAP has been designed as a five-year program with several components: (1) the collection, analysis and sharing of comprehensive expression datasets to understand the role of heterogeneity in tissues and systemically and identify critical parameters and states; (2) the discovery of new, innovative tools for spatiotemporal imaging, manipulation, analysis and modeling of a biologically relevant population of cells with minimal perturbation; (3) milestone-driven validation and translation of technologies for characterizing single cells in situ meeting the needs of end-users; and (4) development and coordination of a multidisciplinary research community through workshops and other collective endeavors. Further details about the NIH SCAP-T program can be found here http://commonfund.nih.gov/singlecell/. The SCAP-T data sets include the detailed phenotype information, experimental protocols, QC information, RNA-sequencing data and NGS results from human heart and human brain cells. The first data release includes 697 single cells from human brain and heart. The second data release includes an additional 978 single cells from human brain and heart. The third data release includes an additional 1631 single cells from human brain and heart. The fourth data release is a correction to this study, but adds no new cells. The fifth data release includes an additional 2984 single cells from human brain and heart. The sixth data release includes an additional 944 single cells from human brain and heart. The seventh data release includes an additional 1977 single cells from human brain and heart. The SCAP-T data portal provides a customized interface for users to quickly identify and retrieve files by phenotypes, and data properties such as sequencing facility or coverage for all of these 9231 single cells. For more information about the SCAP-T study and the data portal, please visit http://www.scap-t.org.

  Study phs000833

• METABRIC data access committee

  Dac EGAC00001000484

• Saliba Lab Data Access Committee

  DAC for data generated by Saliba Lab at Helmholtz institute for RNA-based Infection Research, Würzburg, Germany

  Dac EGAC50000000152

• Cardiac fibroblast DAC

  DAC for reviewing requests to access data on cardiac fibroblasts as described by Aguado-Alvaro et al (Nature Communications, 2025)

  Dac EGAC50000000479