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accession-icon GSE56530
Data expression of young and senescent human mesenchymal stem cells (hMSC).
  • organism-icon Homo sapiens
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The transcriptome of hMSC in late passages was compared to hMSC in early passages. Both hMSC were obtained from the umbilical vein of three donors, two of hMSC have a normal karyotype (MSC/n) and another has a constitutional paracentric chromosomal inversion (hMSC/inv).

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

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accession-icon GSE68785
Expression data of sandwich cultured primary rat hepatocytes incubated to piperazine designer drugs
  • organism-icon Rattus norvegicus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

The piperazine derivatives most frequently consumed for recreational purposes are 1-benzylpiperazine (BZP), 1-(3,4-methylenedioxybenzyl)piperazine (MDBP), 1-(3-trifluoromethylphenyl)piperazine (TFMPP), and 1-(4-methoxyphenyl)piperazine (MeOPP). Currently it is unclear whether piperazine designer drugs induce mechanisms of hepatotoxicity and, if so, whether they act by a common mechanism.

Publication Title

No associated publication

Sample Metadata Fields

Specimen part

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accession-icon GSE113736
Gene expression profiling of mesenchymal stem cells from bone marrow of multiple myeloma patients and normal donors
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [AltAnalyz probeset-to-Ensembl mapping (huex10st)

Description

A growing body of evidence points to the essential role of bone marrow (BM) tumor microenvironment in Multiple Myeloma (MM) maintenance and progression. Mesenchymal stem cells (MSC) are one of the most important players in this scenario. Through direct and indirect interactions, these cells support MM cells by promoting increase of proliferation, migration, survival, and drug resistance. Additionally, an increasing number of evidence has been demonstrating that MSC from MM patients (MM-MSC) have several abnormalities when compared with their normal counterpart from normal donors (ND-MSC). Therefore, the aimed of our study was to explore the differences between MM-MSC and ND-MSC through gene expression analysis.

Publication Title

Transcriptome Analysis of Mesenchymal Stem Cells from Multiple Myeloma Patients Reveals Downregulation of Genes Involved in Cell Cycle Progression, Immune Response, and Bone Metabolism.

Sample Metadata Fields

Sex, Age, Specimen part, Disease stage, Subject

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accession-icon GSE98582
Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation
  • organism-icon Homo sapiens
  • sample-icon 555 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.

Sample Metadata Fields

Subject, Time

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accession-icon GSE98564
Gene expression biomarkers for neurobehavioral impairment from total sleep deprivation microarray data [D6]
  • organism-icon Homo sapiens
  • sample-icon 199 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Healthy human adults were recruited to a sleep lab at Washington State University and remained there 7 consecutive days. Six received a well-rested Control condition of 10 h Time-In-Bed (TIB) nightly.

Publication Title

Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.

Sample Metadata Fields

Subject, Time

View Samples
accession-icon GSE98565
Gene expression biomarkers for neurobehavioral impairment from total sleep deprivation microarray data [D8]
  • organism-icon Homo sapiens
  • sample-icon 193 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Healthy human adults were recruited to a sleep lab at Washington State University and remained there 7 consecutive days. Six received a well-rested Control condition of 10 h Time-In-Bed (TIB) nightly.

Publication Title

Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.

Sample Metadata Fields

Subject, Time

View Samples
accession-icon GSE98566
Gene expression biomarkers for neurobehavioral impairment from total sleep deprivation microarray data [D9]
  • organism-icon Homo sapiens
  • sample-icon 163 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

Healthy human adults were recruited to a sleep lab at Washington State University and remained there 7 consecutive days. Six received a well-rested Control condition of 10 h Time-In-Bed (TIB) nightly.

Publication Title

Exploring gene expression biomarker candidates for neurobehavioral impairment from total sleep deprivation.

Sample Metadata Fields

Subject, Time

View Samples
accession-icon GSE20489
Microarray characterization of gene expression changes in blood during acute ethanol exposure
  • organism-icon Homo sapiens
  • sample-icon 51 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

As part of the civil aviation safety program to define the adverse effects of ethanol on flying performance, we present results of our DNA microarray analysis of samples from a timecourse study of individuals given ethanol orally, and then evaluated by breathalyzer to monitor blood alcohol content (BAC). At five blood alcohol levels, T1-T5, blood was drawn such that the samples represented 0%, 0.04%, 0.08% BAC, and return to 0.04%, and 0.02% BAC. Microarray analysis showed that changes in gene expression could be detected across the time-course. We verified these expression changes by quantitative polymerase chain reaction (qPCR). Candidate target genes identified from the microarray analysis were clustered by expression change pattern, examined for shared functions and functional network membership. Five coordinately expressed groups were revealed and functional analysis showed shared transcription factor binding sites and functions for members of the clusters. These functions include protein synthesis and modification, expected for changes in gene expression, hematological and immune functions, expected for a blood sample, and pancreatic and hepatic function, expected as response to ethanol. The results provide a first look at changing gene expression patterns in blood during acute increase of ethanol concentration and its depletion due to metabolism or excretion and demonstrate that it is possible to detect significant changes in gene expression using total RNA isolated from whole blood. The analysis approach for this study can be utilized as part of a workflow to identify target genes by timecourse changes in gene expression that may affect pilot performance.

Publication Title

Microarray characterization of gene expression changes in blood during acute ethanol exposure.

Sample Metadata Fields

Sex, Specimen part

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accession-icon GSE16149
Examining smoking-induced differential gene expression changes in buccal mucosa
  • organism-icon Homo sapiens
  • sample-icon 18 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

A tissue like buccal mucosa (from cheek swabs) would be an ideal sample material for rapid, easy collection for testing of biomarkers as an alternative to blood. A limited number of studies, primarily in the smoker/oral cancer literature, address this tissue's efficacy for quantitative PCR or microarray gene expression analysis. In this study both qPCR and microarray analyses were used to evaluate gene expression in buccal cells. An initial study comparing blood and buccal cells from the same individuals looked at relative amounts of four genes. The RNA isolated from buccal cells was degraded but was of sufficient quality to be used with RT-qPCR to detect expression of specific genes. Second, buccal cell RNA was used for microarray-based differential gene expression studies by comparing gene expression between smokers and nonsmokers. The isolation and amplification protocol allowed use of 150-fold less buccal cell RNA than had been reported previously with human microarrays. We report here the finding of a small number of significant gene expression differences between smokers and nonsmokers, using buccal cells as target material. Additionally, Gene Set Enrichment Analysis confirmed that these genes were changing expression in the same pattern as seen in an earlier buccal cell study performed by another group. Our results suggest that in spite of a high degree of RNA degradation, buccal cells from cheek mucosa could be used to detect differential gene expression between smokers and nonsmokers. However the RNA degradation, increase in sample variability and microarray failure rate show that buccal samples should be used with caution as source material in expression studies.

Publication Title

Examining smoking-induced differential gene expression changes in buccal mucosa.

Sample Metadata Fields

Specimen part

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accession-icon GSE1947
Disease mechanisms in peripheral neuropathies due to altered Pmp22 gene dosage or a Pmp22 point mutation
  • organism-icon Mus musculus
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Murine Genome U74A Version 2 Array (mgu74av2)

Description

We compared gene expression at ages P4 and P60 in sciatic nerve of wild type mice and mice with peripheral neuropathies caused by altered Pmp22 gene dosage (homozygous knockout or transgene) or a point mutation (Trembler).

Publication Title

No associated publication

Sample Metadata Fields

No sample metadata fields

View Samples
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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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