Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

RNA-sequencing data of macrophages exposed to LPS and/or garlic extract

ABSTRACT: We show here the transcriptional response in RAW 264.7 macrophages treated with LPS and/or a garlic extract (PTSO)

ORGANISM(S): Mus musculus

PROVIDER: GSE178282 | GEO | 2021/11/02

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

RNA-sequencing data of CMT-93 cells exposed to LPS and/or garlic extract

Project description:We show here the transcriptional response in CMT-93 intestinal epithelial cells treated with Trichuris muris antigen and/or a garlic extract (40% PTSO-PTS).

2021-11-02 | GSE178655 | GEO

RNA-sequencing data of macrophages exposed to LPS and/or garlic extract

Project description:RNA-sequencing data of macrophages exposed to LPS and/or garlic extract

| PRJNA738357 | ENA

RNA-sequencing data of CMT-93 cells exposed to LPS and/or garlic extract

Project description:RNA-sequencing data of CMT-93 cells exposed to LPS and/or garlic extract

| PRJNA739909 | ENA

Effects of aged garlic extract (AGE) and FruArg on lipopolysaccharide-induced genetic response in microglial cells using gene expression profiling

Project description:We hypothesized that aged garlic extract, and a pure compound from it, FruArg, can repress the genetic response induced by lipopolysaccharide (LPS). We applied gene expression profiling to understand the potential mechanisms of the protective effects of AGE and FruArg against LPS stress in BV-2 cells. Gene expression profiling showed that AGE repressed the transcriptome alteration induced by LPS. FruArg, as an active compound in AGE, accounted for AGE's protective effects. These results suggest that AGE and FruArg are capable of alleviating oxidative and neuroinflammatory responses stimulated by LPS in BV-2 cells.

2016-10-01 | GSE87531 | GEO

Gene expression of RAW 264.7 cells treated with LPS, ISO, PGE2, LPS PLUS ISO, and LPS PLUS PGE2

Project description:LPS plus ISO and LPS plus PGE2 had non-additive effects on gene expression in RAW 264.7 cells Keywords: time course

2006-06-06 | GSE4964 | GEO

Gene expression of RAW 264.7 cells treated with LPS, IFG, 2MA, LPS PLUS IFG, and LPS PLUS 2MA

Project description:LPS plus IFG and LPS plus 2MA had non-additive effects on gene expression in RAW 264.7 cells Keywords: time course

2006-06-06 | GSE4962 | GEO

RNA-sequencing data of caecum tissue of mice infected with helminths and administered garlic extract

Project description:We show here the transcriptional response in caecum tissue of mice infected with Trichuris muris for 35 days and given either garlic extract treatment or control treatment.

2021-11-02 | GSE178499 | GEO

Identification of Nucleolin-binding proteins in RAW 264.7 macrophages under LPS stimulation

Project description:To identify the potential Nucleolin binding proteins, we performed co-immunoprecipitation assay in 12 h LPS-stimulated RAW 264.7 macrophages.

2023-01-04 | PXD030716 | JPOST Repository

Effect of LPS and LPS-binding protein treatment on RAW 264.4 cells

Project description:All samples were gathered from mouse RAW 264.7 cells (macrophages). Control total RNA was extracted from untreated RAW 264.7 cells cultured for either 1, 2, 4, 8, 16 or 48 hours. Test total RNA was extracted from lipopolysaccharide (100ng/ml) and lipopolysaccharide-binding protein (100pM) treated RAW 264.4 cells cultured for either 1, 2, 4, 8, 16 or 48 hours. This SuperSeries is composed of the following subset Series: GSE1099: Effect of LPS and LPS-binding protein treatment for 1 hour on RAW 264.4 cells GSE1100: Effect of LPS and LPS-binding protein treatment for 2 hours on RAW 264.4 cells GSE1101: Effect of LPS and LPS-binding protein treatment for 4 hours on RAW 264.4 cells GSE1102: Effect of LPS and LPS-binding protein treatment for 8 hours on RAW 264.4 cells GSE1103: Effect of LPS and LPS-binding protein treatment for 16 hours on RAW 264.4 cells GSE1104: Effect of LPS and LPS-binding protein treatment for 48 hours on RAW 264.4 cells Refer to individual Series

2004-03-04 | E-GEOD-1098 | biostudies-arrayexpress

LPS treatment of RAW2647 macrophages

Project description:Macrophages are central players in the immune response and manifest divergent phenotypes to control inflammation and innate immunity. Signaling factors are traditionally recognized as the stimuli governing macrophage functions. In recent years, metabolism’s importance has been reemphasized as critical signaling and regulatory pathways of human diseases and processes, ranging from cancer to aging, often converge on metabolic responses. In this study, we assessed metabolic features that play critical roles in macrophage function. We constructed a genome-scale metabolic network for the RAW 264.7 cell line, an oft-used in vitro model. We determined immunomodulators of activation. Metabolites well-known to be associated with immunoactivation (e.g., glucose and arginine) and immunosuppression (e.g., tryptophan and vitamin D3) were amongst the most critical effectors. Intracellular metabolic mechanisms linked critical suppressive effectors were assessed, identifying a suppressive role for nucleotide synthesis. Furthermore, we demonstrate how metabolic mechanisms of macrophage activation can be identified by analyzing multi-omic data of LPS-stimulated RAW cells in the context of our predictions. Our study demonstrates metabolism’s role in regulating macrophage activation may be greater than previously anticipated. The RAW 264.7 (ATTC) cell line was stimulated for 24 hours with LPS. Treated cells were washed twice with Dulbecco’s PBS and harvested for high-throughput analyses. Labeled cDNA was prepared as described (Jones et al. 2010). A mixture Cy3-labeled control cDNA and Cy5-labeled were hybridized to Agilent Mouse GE 4x44K v2 Microarray (Agilent Technologies) and processed. Image analysis and intra-chip normalization were performed with Feature Extraction 9.5.3.1 (Agilent). Data were analyzed with MeV (tm4.org) or with custom python scripts

2012-01-24 | E-GEOD-35237 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data