2163 results for "2025年12月10日300883股价走势分析"

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• Sequencing data for "Replication timing alterations are associated with mutation acquisition during tumour evolution in breast and lung cancer"

  Repli-seq data for "Replication timing alterations are associated with mutation acquisition during tumour evolution in breast and lung cancer"

  Dataset EGAD00001015363

• Genomics of Opioid Pharmacogenomics and Acute/Chronic Postsurgical Pain after Major Surgery in Children

  Pain management after surgery is not optimal, partly due to great interindividual variability in pain perception and coping. This can lead to persistent pain beyond the healing period and disability. Up to two-thirds of the inter-individual variability results from genetic variations in pain perception as well as response to the pain medicine. The investigators aim to identify genomic (genetic/epigenetic), psychological and drug profiles contributing to this variability. Opioids are the mainstay for treatment of postoperative pain in children. Experience dictates that opioids have narrow therapeutic indices and large inter-patient variability in response. This leads to serious side effects like respiratory depression in up to 50% of children undergoing invasive surgery, which can be fatal. It is evident that there are particular children who are more susceptible to suffering side effects and having inadequate pain relief from opioids.It is hypothesized that much of the genetic variability can be explained by gene function which is modulated by a) Single Nucleotide Polymorphisms (SNPs) in genes that encode proteins involved in pain perception, opioid transport/metabolism (pharmacokinetics), and opioid receptor signaling (pharmacodynamics); b) epigenetics which modify gene expression without structural changes to the DNA, and c) genes that influence psychological factors.The purpose of this research study is to identify factors and genes that may be associated with acute and chronic post-surgical pain, and to develop pharmacometric models for response to opioids, like morphine and hydromorphone. While children undergoing different surgeries will be recruited for acute outcomes, children undergoing spine fusion will be followed for 10-12 months for evaluation of psychological and genomic factors affecting chronic post-surgical pain, with a goal of identifying genetic and epigenetic risk models for prediction of acute and chronic post-surgical pain. Although opioids are used every day, some children have bad reactions from their use, like breathing problems, sedation, etc. The investigators want to study factors that may be associated with pain sensitivity, opioid requirements after surgery, their metabolism, efficacy and their side-effects. The investigators expect that the information obtained in this research study will help to develop effective, safer, and tailored treatment options in the future.

  Study phs002105

• CRCbiome: Gut metagenome of Norwegian screening participants using FIT sampling

  The study aims to characterize the gut metagenome of Norwegian screening participants and assess the ability of the gut metagenome to identify those at need for colonoscopy. Background: Colorectal cancer (CRC) screening reduces CRC incidence and mortality. However, current screening methods are either hampered by invasiveness or suboptimal performance, limiting their effectiveness as primary screening methods. To aid in the development of a non-invasive screening test with improved sensitivity and specificity, we have initiated a prospective biomarker study (CRCbiome), nested within a large randomized CRC screening trial in Norway. We aim to develop a microbiome-based classification algorithm to identify advanced colorectal lesions in screening participants testing positive for an immunochemical fecal occult blood test (FIT). We will also examine interactions with host factors, diet, lifestyle and prescription drugs. The prospective nature of the study also enables the analysis of changes in the gut microbiome following the removal of precancerous lesions. Methods: The CRCbiome study recruits participants enrolled in the Bowel Cancer Screening in Norway (BCSN) study, a randomized trial initiated in 2012 comparing once-only sigmoidoscopy to repeated biennial FIT, where women and men aged 50–74 years at study entry are invited to participate. Since 2017, participants randomized to FIT screening with a positive test result have been invited to join the CRCbiome study. Self-reported diet, lifestyle and demographic data are collected prior to colonoscopy after the positive FIT-test (baseline). Screening data, including colonoscopy findings are obtained from the BCSN database. Fecal samples for gut microbiome analyses are collected both before and 2 and 12 months after colonoscopy. Samples are analyzed using metagenome sequencing, with taxonomy profiles, and gene and pathway content as primary measures. CRCbiome data will also be linked to national registries to obtain information on prescription histories and cancer relevant outcomes occurring during the 10 year follow-up period. Discussion: The CRCbiome study will increase our understanding of how the gut microbiome, in combination with lifestyle and environmental factors, influences the early stages of colorectal carcinogenesis. This knowledge will be crucial to develop microbiome-based screening tools for CRC. By evaluating biomarker performance in a screening setting, using samples from the target population, the generalizability of the findings to future screening cohorts is likely to be high.

  Study EGAS50000000170

• UK10K_OBESITY_SCOOP

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches.The SCOOP samples are part of the Obesity group and will undergo exome sequencing. Severe Childhood Onset Obesity Project (SCOOP) is a sub-cohort of the Genetics Of Obesity Study (GOOS) cohort established by Sadaf Farooqi and Steve O’Rahilly at the University of Cambridge over the last 12 years. The GOOS cohort contains >4,000 patients of diverse geographic origin, many of whom have monogenic and syndromic forms of obesity, and includes patients that are offspring of consanguineous union. SCOOP is a subset of >1500 UK Caucasian patients with severe, early onset obesity (all patients have a BMI Standard Deviation Score (SDS) > 3 and obesity onset before the age of 10 years), in whom all known monogenic causes of obesity have been excluded. GWAS data on the SCOOP cohort will be available (WTCCC2 independent study) at the time of the start of this study. Data from this cohort has demonstrated that the prevalence of the common obesity risk alleles in FTO, MC4R and NEGR1 are amongst the highest within SCOOP, demonstrating its value also in the study of genetic variants with an impact on more common obesity. For further information with regard to this cohort please contact Sadaf Farooqi (isf20@medschl.cam.ac.uk).

  Study EGAS00001000124

• RNA_Seq_in_Patients_with_Primordial_Dwarfism

  Transcriptome studies in patients with rare genetic diseases can potentially aid in theinterpretation of likely causal genetic variation through identification of altered transcriptabundance and/or structure. RNA-Seq is the most sensitive assay for both investigatingtranscript structure and abundanceThe primary aim of this pilot project is to investigate to what degree integrating exome-Seqand RNA-Seq data on the same individual can accelerate the identification of causal allelesfor rare genetic diseases. There are two main strands to this: (i) identifying which variantsdiscovered in exome-seq appear to be having a functional impact on transcripts, and (ii)identifying transcript outliers, especially among known causal genes, that may not necessarilyhave a causal variant identified from exome sequencing. The latter may identify the presenceof causal variants that lie far from coding regions (e.g. the formation of cryptic splice sitesdeep within introns, or loss of long range regulatory elements), which can be confirmed withfurther targeted genetic assays. Just over 50% of all disease-causing variants recorded in theHuman Gene Mutation Database (HGMD) affect transcript structure and abundance (e.g.nonsense SNVs, essential splice site SNVs, frameshifting indels, CNVs).This pilot project will study RNA from lymphoblastoid cell-lines from 12 patients withprimordial dwarfism syndromes, for 10 of these samples we have previously generate exomedata as part of our collaboration with the group of Prof Andrew Jackson. The two remainingsamples are positive controls where the causal mutation is known, and is known to affecttranscript structure and/or abundance.Primordial dwarfism is a prime candidate for these RNA-seq studies because all knowncausal mutations to date have key roles in DNA replication and thus, unsurprisingly, theproducts of the causal genes are typically ubiquitously expressed.Each RNA will be sequenced, with two technical replicates (independent RT-PCR and libraries) persample, and each replicate run in 1/2 of a HiSeq lane using 100bp paired reads. Samples preparation was as follows :The cells were grown to confluency, then pellets frozen at -80. RNA samples were prepared using the Qiagen RNeasy kit, then nanodropped and analyzed using the bioanalyzer to determine concentration and purity.This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001000283

• PDX_HTA2.0_Guergen2022

  GeneChip HTA 2.0 data of primary renal cell carcinoma (RCC) and RCC metastases related to Guergen et al, Front Oncol 12:2022 889789. Microarrays were normalized individually using the SCAN method from the R package SCAN.UPC (version 2.34.0). Probe sets were summarized on the Entrez GeneID level using the annotation provided by BrainArray (version 25).

  Dataset EGAD00010002392

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 12)

  The dataset contains whole genome sequencing data of 17 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 46 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000000441

• HIV-phyloTSI: PANGEA (PCR amplicon)

  This dataset includes sample numbers TSI_0426 to TSI_0527 for the PANGEA (PCR amplicon) cohort of the study. Samples were generated by pooling four overlapping PCR amplicons (see Gall et al 2012, DOI: 10.1128/JCM.01516-12). The sequencing was conducted using the Illumina NovaSeq system. Each sample has a BAM file, and its associated reference file.

  Dataset EGAD50000001308

• Spatial and temporal transcriptome analysis on human skeletal muscle regeneration

  Skeletal muscle carries a unique ability for adaptation as well as regeneration that highly depends on a supportive cellular microenvironment. Here we show that spatial and single-cell transcriptomic analysis in human skeletal muscle is a unique approach to illuminate cellular interactions in the microenvironment.

  Dataset EGAD50000000263

• Visium Spatial transcriptomics

  This study consists of the spatial transcriptomics data generated by : Visium CytAssist Spatial Gene Expression for FFPE (10x) for steatotic liver disease-associated hepatocellular carcinoma (SLD-HCC) (n=7) and non-SLD-HCC (n=5) The goal of this data is to compare SLD-HCC vs non-SLD-HCC as well as response to immunotherapy

  Dataset EGAD50000001506