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accession-icon GSE5110
48h Immobilization in human
  • organism-icon Homo sapiens
  • sample-icon 10 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Our results suggest that 48h of immobilization increases expression of mRNA for components of the UPP and MT function while decreasing mRNA and protein for components involved in ECM integrity. We hypothesized that 48h of immobilization would increase gene expression and respective protein products for components of the ubiquitin proteasome pathway (UPP).

Publication Title

Analysis of human skeletal muscle after 48 h immobilization reveals alterations in mRNA and protein for extracellular matrix components.

Sample Metadata Fields

Treatment

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accession-icon GSE154028
High fat diet inhibits EV-Mediated angiogenisis
  • organism-icon Sus scrofa
  • sample-icon 11 Downloadable Samples
  • Technology Badge Icon Porcine Gene 1.0 ST Array (porgene10st)

Description

Mesenchymal stem cell-derived extracellular vesicles (EVs) have been shown to promote angiogenesis in the ischemic myocardium. This study examines the difference in vascular density, myocardial perfusion, molecular signaling, and gene expression between normal diet (ND) and high fat diet (HFD) groups at baseline and following intra-myocardial injection of EVs

Publication Title

Effects of High Fat Versus Normal Diet on Extracellular Vesicle-Induced Angiogenesis in a Swine Model of Chronic Myocardial Ischemia.

Sample Metadata Fields

Sex, Specimen part, Treatment

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accession-icon SRP044164
Transcriptome impact of acute deletion of Gata3 in murine pro-T cells
  • organism-icon Mus musculus
  • sample-icon 36 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2500

Description

The purpose of the study was to determine what genes in DN2 pro-T cells are immediately regulated by the transcription factor GATA-3, either as activation targets or as repression targets. To do this, two pairs of Gata3-floxed and control pro-T cells were generated and analyzed by RNA-seq within the first day of deletion of the Gata3 gene. Pro-T cells were generated by differentiation in vitro on OP9-DL1 monolayers of fetal liver-derive precursors from wildtype or Gata3-floxed mice, and the Gata3 gene was acutely deleted by transduction with Cre retroviral vector. Within 20 hr after transduction, samples of acutely Gata3-deleted and control DN2 cells were sorted and RNA prepared for RNA-seq analysis. High-throughput sequencing of the samples was carried out. Experimental Gata3 deleted samples in both cases were Gata3-floxed, ROSA26R-EYFP samples infected with Cre retrovirus and sorted for EYFP+ (Cre-activated) DN2 phenotype. Control for experiment 1: wildtype (C57BL/6) DN2 pro-T cells generated in parallel, also treated with Cre retrovirus but sorted only for DN2 phenotype. Control for experiment 2: same genotype as experimental, but infected with a GFP+ empty retroviral vector and sorted for GFP+ DN2 phenotype. Overall design: Two pairs of RNA-seq samples of DN2 pro-T cells were generated for comparison, each pair consisting of a Gata3-deleted sample plus a stage-matched control.

Publication Title

GATA-3 dose-dependent checkpoints in early T cell commitment.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE33425
Human MAIT and CD8++ cell development
  • organism-icon Homo sapiens
  • sample-icon 17 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Human MAIT and CD8αα cells develop from a pool of type-17 precommitted CD8+ T cells.

Sample Metadata Fields

Specimen part, Disease, Disease stage

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accession-icon GSE33424
Expression data from human cord blood CD161++/CD161+/CD161- CD8+ T cell subsets
  • organism-icon Homo sapiens
  • sample-icon 9 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We used microarray to compare gene expression between CD161++/CD161+/CD161-CD8+ T cells from human cord blood.

Publication Title

Human MAIT and CD8αα cells develop from a pool of type-17 precommitted CD8+ T cells.

Sample Metadata Fields

Specimen part

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accession-icon GSE33374
Expression data from healthy human CD161++CD8aa and CD161++CD8ab T cells
  • organism-icon Homo sapiens
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

We used microarrays to compare gene expression between healthy human CD161++CD8aa and CD161++CD8ab T cells.

Publication Title

Human MAIT and CD8αα cells develop from a pool of type-17 precommitted CD8+ T cells.

Sample Metadata Fields

Specimen part, Disease, Disease stage

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accession-icon SRP092402
A blood RNA signature for predicting the treatment outcome in the Tuberculosis Treatment Response Cohort
  • organism-icon Homo sapiens
  • sample-icon 909 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Identification of blood biomarkers that prospectively predict Mycobacterium tuberculosis treatment response. Overall design: There are a total of 914 samples used in this design. This involves samples from 100 cases and 38 controls. Most of the samples have 2 technical replicates where as 2 samples have 4. Samples from the TB cases have been collected on the start day of TB treatment and on 1,4 and 24 weeks after treatment as well. For some subjects we also have samples after the subject has been cured. The case or TB Subjects have been categorized by the nature of their response as definite,probable or possible cure. The day of cure is presented in the time to negativity column. Also provided in the metadata are the MGIT -Mycobacteria Growth Indicator Tube and XPERT (cartridge based nucleic acid amplification test, automated diagnostic test that can identify Mycobacterium tuberculosis (MTB)) values at the various times of sample collection for all TB Subjects.

Publication Title

Host blood RNA signatures predict the outcome of tuberculosis treatment.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Subject, Time

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accession-icon GSE42806
Gene expression profiling in tibial muscular dystrophy and control skeletal muscle
  • organism-icon Homo sapiens
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Tibial muscular dystrophy (TMD) is a late onset, autosomal dominant distal myopathy that results from mutations in the two last domains of titin. The cascade of molecular events leading from the causative Titin mutations to the preterm death of muscle cells in TMD is largely unknown. To identify these components, we used gene expression profiling of muscle biopsies from TMD patients and healthy controls.

Publication Title

Gene expression profiling in tibial muscular dystrophy reveals unfolded protein response and altered autophagy.

Sample Metadata Fields

Sex, Specimen part, Disease, Disease stage, Subject

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accession-icon SRP071965
A blood RNA signature for tuberculosis disease risk: a prospective cohort study
  • organism-icon Homo sapiens
  • sample-icon 330 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Identification of blood biomarkers that prospectively predict progression of Mycobacterium tuberculosis infection to tuberculosis disease might lead to interventions that combat the tuberculosis epidemic. We aimed to assess whether global gene expression measured in whole blood of healthy people allowed identification of prospective signatures of risk of active tuberculosis disease. RESULTS:Between July 6, 2005, and April 23, 2007, we enrolled 6363 from the ACS study and 4466 from independent South African and Gambian cohorts. 46 progressors and 107 matched controls were identified in the ACS cohort. A 16 gene signature of risk was identified. The signature predicted tuberculosis progression with a sensitivity of 66·1% (95% CI 63·2–68·9) and a specificity of 80·6% (79·2–82·0) in the 12 months preceding tuberculosis diagnosis. The risk signature was validated in an untouched group of adolescents (p=0·018 for RNA sequencing and p=0·0095 for qRT-PCR) and in the independent South African and Gambian cohorts (p values <0·0001 by qRT-PCR) with a sensitivity of 53·7% (42·6–64·3) and a specificity of 82·8% (76·7–86) in 12 months preceding tuberculosis. Interpretation: The whole blood tuberculosis risk signature prospectively identified people at risk of developing active tuberculosis, opening the possibility for targeted intervention to prevent the disease. Overall design: In this prospective cohort study, we followed up healthy, South African adolescents aged 12–18 years from the adolescent cohort study (ACS) who were infected with M tuberculosis for 2 years. We collected blood samples from study participants every 6 months and monitored the adolescents for progression to tuberculosis disease. A prospective signature of risk was derived from whole blood RNA sequencing data by comparing participants who developed active tuberculosis disease (progressors) with those who remained healthy (matched controls). After adaptation to multiplex qRT-PCR, the signature was used to predict tuberculosis disease in untouched adolescent samples and in samples from independent cohorts of South African and Gambian adult progressors and controls. Participants of the independent cohorts were household contacts of adults with active pulmonary tuberculosis disease.

Publication Title

A blood RNA signature for tuberculosis disease risk: a prospective cohort study.

Sample Metadata Fields

Sex, Age, Specimen part, Race, Subject

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accession-icon GSE28418
Expression data from mouse tissues and MEFs: insights into the physiological activation of p53-p66Shc pathway
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Oxidative stress activates a specific p53 transcriptional response that regulates cellular senescence and aging.

Sample Metadata Fields

Age, Specimen part

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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