Ontology highlight
ABSTRACT:
PROVIDER: PRJEB28053 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR2722610_1.fastq.gz | Fastqsanger.gz | |||
| ERR2722610_2.fastq.gz | Fastqsanger.gz | |||
| ERR2722620_1.fastq.gz | Fastqsanger.gz | |||
| ERR2722620_2.fastq.gz | Fastqsanger.gz | |||
| ERR2722630_1.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 168 |
Similar Datasets
Project description:Subjects are children from Kilifi District Hospital, Kenya, recruited in 2001 malaria season. total RNA extracted from PaxGene tubes, total RNA and Stratagene Universal reference RNA underwent linear amplification (Message Amp, Ambion). Amplified RNA directly labelled Cy5 and Cy3 and hybridised to 'lymphochip' arrays (print run - lc36n). Scanned on Axon 4000B scanner using GenePix 4.0 software. Clinical sample ID provided in 'Disease State Description' corresponds with Sample ID in Table 1 "Clinical Information for the micro-array samples" in the associated publication.
2005-07-06 | E-SMDB-2669 | biostudies-arrayexpress
Project description:Subjects are children from Kilifi District Hospital, Kenya, recruited in 2001 malaria season. total RNA extracted from PaxGene tubes, total RNA and Stratagene Universal reference RNA underwent linear amplification (Message Amp, Ambion). Amplified RNA directly labelled Cy5 and Cy3 and hybridised to 'lymphochip' arrays (print run - lc36n). Scanned on Axon 4000B scanner using GenePix 4.0 software. Clinical sample ID provided in 'Disease State Description' corresponds with Sample ID in Table 1 "Clinical Information for the micro-array samples" in the associated publication. A disease state experiment design type is where the state of some disease such as infection, pathology, syndrome, etc is studied. Keywords: disease_state_design
2005-07-09 | GSE2900 | GEO
Project description:high throughput sequencing of the metagenome of mexican children
2020-03-16 | GSE143207 | GEO
Project description:Genome wide DNA methylation profiling of isolated monocyte samples from healthy Kenyan children, the same children during an episode of acute malaria, healthy Kenyan adults, and healthy adults from the United States. The Illumina Infinium MethylationEPIC BeadChip microarray was used to obtain DNA methylation profiles across approximately 860,000 CpGs in negatively selected monocyte samples. Samples included monocytes from 8 children from western Kenya obtained while healthy and matching samples from the same 8 Kenyan children obtained during an episode of acute uncomplicated Plasmodium falciparum malaria, 8 healthy malaria-immune adults from western Kenya, and 8 healthy malaria-naive adults from the US. Abstract -- Background: Age-related changes in adaptive and innate immune cells have been associated with a decline in effective immunity and chronic, low-grade inflammation. Epigenetic, transcriptional, and functional changes in monocytes occur with aging, though most studies to date have focused on differences between young adults and the elderly in populations with European ancestry; few data exist regarding changes that occur in circulating monocytes during the first few decades of life or in African populations. We analyzed DNA methylation profiles, cytokine production, and inflammatory gene expression profiles in monocytes from young adults and children from western Kenya. Results: We identified several hypo- and hyper-methylated CpG sites in monocytes from Kenyan young adults vs. children that replicated findings in the current literature of differential DNA methylation in monocytes from elderly persons vs. young adults across diverse populations. Differentially methylated CpG sites were also noted in gene regions important to inflammation and innate immune responses. Monocytes from Kenyan young adults vs. children displayed increased production of IL-8, IL-10, and IL-12p70 in response to TLR4 and TLR2/1 stimulation as well as distinct inflammatory gene expression profiles. Conclusions: These findings complement previous reports of age-related methylation changes in isolated monocytes and provide novel insights into the role of age-associated changes in innate immune functions.
2021-03-11 | GSE157611 | GEO
Project description:The study aimed to define transcriptional signatures for detection of active TB (TB) compared to latent TB infection (LTBI) as well as to other diseases (OD) with similar clinical phenotypes in patients with and without HIV in a paediatric cohort from Kenya Transcriptional signatures were identified that distinguished active TB from LTBI, active TB from other diseases, and active TB from both LTBI and other diseases in HIV+/- patients. Children were recruited from 2 hospitals in Coast Province, Kenya (n=157) who were either HIV+ or HIV - with either active TB (culture confirmed), active TB (culture negative), LTBI or OD. Blood was collected into PAX gene tubes (PreAnalytiX). Total RNA integrity was assessed using an Agilent 2100 Bioanalyzer (Agilent, Palo Alto, CA). Labeled cRNA was hybridized to Illumina Human HT-12 Beadchips. Data were analysed in R.
2014-05-01 | E-GEOD-39939 | biostudies-arrayexpress
Project description:In a prior report, we observed two distinct lung microbiomes in healthy subjects that we termed â??pneumotypesâ??: pneumotypeSPT, characterized by high bacterial load and supraglottic predominant taxa (SPT) such as the anaerobes Prevotella and Veillonella; and pneumotypeBPT, with low bacterial burden and background predominant taxa (BPT) found in the saline lavage and bronchoscope. Here, we determined the prevalence of these two contrasting lung microbiome types, in a multi-center study of healthy subjects. We confirmed that a lower airway microbiome enriched with upper airway microbes (pneumotypeSPT) was present in ~45% of healthy individuals. Cross-sectional Multicenter cohort. BAL of 49 healthy subjects from three cohort had their lower airway microbiome assessed by 16S rDNA sequencing and microbial gene content (metagenome) was computationally inferred from taxonomic assignments. The amplicons from total 100 samples are barcoded; the barcode and other clinical characteristics (e.g. inflammatory biomarkers and metabolome data) for each sample are provided in the 'Pneumotype.sep.Map.A1.txt' file.
2016-03-29 | E-GEOD-74395 | biostudies-arrayexpress