D978085c-ca94-4dfd-be48-a8fa268c487e - samples
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PROVIDER: EGAD00001004348 | EGA |
REPOSITORIES: EGA
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Project description:Using our newly designed C. acetobutylicum arrays we analyzed the mRNA changes during a time course experiment (up to 66 h) paying special attention on the study of the late timepoints. Keywords: time course Samples were taken from a Bioflow II reactor at 6, 7, 8, 9, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 44, 48, 54, 58, and 66 hrs after bioreactor inoculation. Two slides per timepoint were hybridized on a dye swap configuration. The control mRNA was generated by combining samples taken at 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 44, 48, 54, 58, and 66 hrs after bioreactor inoculation. For timepoints 6, 8, 14, 32, 38, 66 our internal quality control check suggested a larger than normal variation of the intensities in the control channel and a third slide was hybridized. The discarded slides are GSM141189, GSM141203, GSM141222, GSM141229 and GSM141242.
2010-05-25 | E-GEOD-6094 | biostudies-arrayexpress
Project description:A miRNA microarray was performed from HCV infected patient serum samples of bothe genotype 1b and genotype 3a, which are prevalent in India, with the aim of identifying a set of miRNAs which are uniquely differentially expressed during HCV infection. miR-320c, miR-483-5p, miR-134 and miR-198 were found to be upregulated in the patient samples as compared to the controls and are currenty being validated.
2013-11-01 | GSE41829 | GEO
Project description:The overall goal of the study was to determine if serum or serum EV microRNAs added prognostic value to current clinical nomograms for prostate cancer. Serum was collected from 203 patients with biopsy-proven prostate cancer. EVs were isolated from the 132 serum samples. RNA was isolated from these serum and serum EV samples, and 61 microRNAs were quantified per sample on a custom qPCR plate. The microRNA data was normalized using NormFinder. The normalized microRNA data was then compared to adverse pathology and prostate biopsy Gleason grade group.
2023-09-22 | GSE228371 | GEO
Project description:BACKGROUND: MicroRNAs negatively regulate gene expression and play a pivotal role in the pathogenesis of human type 2 diabetes mellitus (T2DM). As the domestic cat presents a spontaneous animal model for human T2DM, the purpose of this study was to investigate whether microRNAs are detectable in feline serum and whether microRNA expression profiles differ between healthy and diabetic cats. METHODS: Total RNA was extracted from 400 µl serum of healthy lean (HL) and newly diagnosed diabetic (D) cats. MicroRNA microarrays representing 1079 distinct mouse miRNA targets were used to measure miRNA expression in samples from eight HL and eight D cats. RESULTS: By microarray, 227 distinct microRNAs were identified. Nineteen miRNAs were differentially expressed in diabetic cats, but only two reached statistical significance after correction for multiple comparisons. In qRT-PCR, miR-122* was found to be upregulated in diabetic cats more than 40-fold compared to HL cats, while miR-193b was upregulated about 10-fold. MiR-483* showed a 6- fold increase in diabetic cats compared to HL cats. CONCLUSIONS: Small volumes of serum samples yield sufficient material to detect altered microRNA expression profiles in diabetic cats. The domestic cat may be considered a useful animal model for studying miRNAs involved in human T2DM.
2013-04-11 | GSE37177 | GEO
Project description:Using our newly designed C. acetobutylicum arrays we analyzed the mRNA changes during a time course experiment (up to 66 h) paying special attention on the study of the late timepoints. Keywords: time course
2008-07-21 | GSE6094 | GEO
Project description:MicroRNA-198 an inhibitor of keratinocyte migration
| PRJNA165845 | ENA
Project description:The investigation includes findings from our clinical trial, monitoring individualized response to pneumococcal vaccination, where we have carried out integrative profiling assessment of saliva pre and post vaccination in a single individual. This is to our knowledge the most extensive saliva-centered omics dataset on an individual, covering 100 timepoints over the course of one year. The time span covers a healthy period as well as comprehensive monitoring of innate and adaptive immune responses following pneumococcal vaccination. Protein and RNA from saliva were produced at each timepoint (100 timepoints), and mass spectrometry proteomics and RNA-sequencing were carried out for all samples in non-targeted comprehensive profiling. Specifically, a single individual (male, 38) was profiled over multiple timepoints during healthy periods, as well as post treatment with pneumococcal vaccine (PPSV23). Initially pre-immunization samples, including a 24 hour period with hourly sampling (samples P1052515H07-P1052615H08), were collected to provide a comparative baseline. A subsequent 24-hour time course was performed, with again hourly samples taken pre and post vaccination (P1060715H07-P1060815H06). The PPSV23 pneumococcal vaccine was admistered inbetween timepoints at approximately 10.30am, prior to datapoint P1060715H11. Following the vaccination, and after the 24 hour monitoring, daily samples were taken for about a month (up to sample P1070715H08), to capture innate and adaptive responses in saliva. Two more weekly samples followed, with then monthly samples till the end of the investigation. Omics sample analysis includes: RNA-sequencing of total RNA, small RNA sequencing in saliva extracellular vesicles and saliva mass spectrometry proteomics. Note on sample naming: The sample identifier/name P1MMDDYYHhh corresponds to: patient index:P1, date MMDDYY and hour hh preceded by H using 24 hour enumeration.
2020-01-31 | GSE108664 | GEO
Project description:Purpose: There is a quest for novel non-invasive diagnostic markers for the detection of breast cancer. The goal of this study is to identify circulating microRNA signatures using a cohort of Asian Chinese breast cancer patients, and to compare microRNA profiles between tumour and serum samples. Experimental design: MicroRNAs from paired breast cancer tumours, normal tissue and serum samples derived from 32 patients were comprehensively profiled using microarrays (1300 microRNAs against tumour and normal tissues) or LNA RT-PCR panels (742 microRNAs against serum samples). Serum samples from healthy individuals (n=22) were also employed as normal controls. Significant serum microRNAs, identified by logistic regression, were validated in an independent set of serum samples from patients (n=82) and healthy controls (n=53). Results: The 20 most significant microRNAs differentially expressed in breast cancer tumours included miR-21, miR-10b, and miR-145, previously shown to be dysregulated in breast cancer. Interestingly, 16 of the 20 most significant microRNAs differentially expressed in serum samples were novel. MiR-1, miR-92a, miR-133a and miR-133b were identified as the most important diagnostic markers, and were successfully validated; receiver operating characteristic curves derived from combinations of these microRNAs exhibited areas under the curves of 0.944-0.946. Only seven microRNAs were overexpressed in both tumours and serum, suggesting that microRNAs may be released into the serum selectively. Conclusion: The clinical employment of microRNA signatures as a non-invasive diagnostic strategy is promising, but should be further validated for different subtypes of breast cancers.
2013-09-06 | GSE41922 | GEO
Project description:The investigation includes findings from our clinical trial, monitoring individualized response to pneumococcal vaccination, where we have carried out integrative profiling on peripheral blood mononuclear cells (PBMCs) and saliva pre and post vaccination in a single individual. This is to our knowledge the most extensive saliva-centered omics dataset on an individual, covering 100 timepoints over the course of one year. The time span covers a healthy period as well as comprehensive monitoring of innate and adaptive immune responses following pneumococcal vaccination. Protein and RNA from saliva and PBMCs were produced at each timepoint (100 timepoints for saliva, 25 for PBMCs), and mass spectrometry proteomics and RNA-sequencing were carried out for all samples in non-targeted comprehensive profiling. Specifically, a single individual (male, 38) was profiled over multiple timepoints during healthy periods, as well as post treatment with pneumococcal vaccine (PPSV23). Initially pre-immunization samples, including a 24 hour period with hourly sampling (samples P1052515H07-P1052615H08), were collected to provide a comparative baseline. A subsequent 24-hour time course was performed, with again hourly samples taken pre and post vaccination (P1060715H07-P1060815H06). The PPSV23 pneumococcal vaccine was admistered inbetween timepoints at approximately 10.30am, prior to datapoint P1060715H11. Following the vaccination, and after the 24 hour monitoring, daily samples were taken for about a month (up to sample P1070715H08), to capture innate and adaptive responses in saliva. Two more weekly samples followed, with then monthly sample till the end of the investigation. Concurrently, weekly or monthly PBMC samples were taken. Omics sample analysis includes: RNA-sequencing of total RNA in saliva and PBMCs. small RNA sequencing in saliva. Proteomics in saliva and PBMCs. small RNA from extracellular vesicles in saliva. Note on sample naming: The sample identifier/name P1MMDDYYHhh corresponds to: patient index:P1, date MMDDYY and hour hh preceded by H using 24hour enumeration. Overall the study produced 100 timepoints for saliva in the span of a year, as well as 30 PBMC samples.
2020-01-31 | GSE108665 | GEO
Project description:The investigation includes findings from our clinical trial, monitoring individualized response to pneumococcal vaccination, where we have carried out integrative profiling assessment of saliva pre and post vaccination in a single individual. This is to our knowledge the most extensive saliva-centered omics dataset on an individual, covering 100 timepoints over the course of one year. The time span covers a healthy period as well as comprehensive monitoring of innate and adaptive immune responses following pneumococcal vaccination. Protein and RNA from saliva were produced at each timepoint (100 timepoints), and mass spectrometry proteomics and RNA-sequencing were carried out for all samples in non-targeted comprehensive profiling. Specifically, a single individual (male, 38) was profiled over multiple timepoints during healthy periods, as well as post treatment with pneumococcal vaccine (PPSV23). Initially pre-immunization samples, including a 24 hour period with hourly sampling (samples P1052515H07-P1052615H08), were collected to provide a comparative baseline. A subsequent 24-hour time course was performed, with again hourly samples taken pre and post vaccination (P1060715H07-P1060815H06). The PPSV23 pneumococcal vaccine was admistered inbetween timepoints at approximately 10.30am, prior to datapoint P1060715H11. Following the vaccination, and after the 24 hour monitoring, daily samples were taken for about a month (up to sample P1070715H08), to capture innate and adaptive responses in saliva. Two more weekly samples followed, with then monthly sample till the end of the investigation. Omics sample analysis includes: RNA-sequencing of total RNA, small RNA sequencing in saliva extracellular vesicles and saliva mass spectrometry proteomics. Note on sample naming: The sample identifier/name P1MMDDYYHhh corresponds to: patient index:P1, date MMDDYY and hour hh preceded by H using 24 hour enumeration.
2020-01-31 | GSE108666 | GEO