Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium [100_nm_TiO2_NP]

ABSTRACT: In this study, using advanced microscopy, in vivo/in vitro omics experiments and in silico molecular modelling, the long-lasting response to a single exposure of different lung cell types to nanomaterial was determined. The information was further used to build a predictive algorithm that would allow identification of nanomaterials that have the potential to induce inflammation.

ORGANISM(S): Mus musculus

PROVIDER: GSE157851 | GEO | 2020/09/12

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium [15_nm_TiO2_NP]

Project description:In this study, using advanced microscopy, in vivo/in vitro omics experiments and in silico molecular modelling, the long-lasting response to a single exposure of different lung cell types to nanomaterial was determined. The information was further used to build a predictive algorithm that would allow identification of nanomaterials that have the potential to induce inflammation.

2020-09-12 | GSE157847 | GEO

Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium [Tube_TiO2_NP]

2020-09-12 | GSE157855 | GEO

Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium [DQ_TiO2_NP]

2020-09-12 | GSE157854 | GEO

Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium [Cube_TiO2_NP]

2020-09-12 | GSE157853 | GEO

Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium

Project description:We are daily exposed to a multitude of health hazardous airborne particulate matter with notable deposition in the fragile alveolar region of our lungs. Hence, there is a great need for identification and prediction of material-associated diseases, currently hindered due to the lack of in-depth understanding of causal relationships, in particular between acute exposures and chronic symptoms. By applying advanced microscopies and omics to in vitro and in vivo systems, together with in silico molecular modelling, we have here determined that the long-lasting response to a single exposure can originate from the interplay between the newly discovered nanomaterial quarantining and nanomaterial cycling between different lung cell types. This new insight finally allows us to predict the spectrum of lung inflammation associated with materials of interest using only in vitro measurements and in silico modelling potentially relating outcomes to material properties for large number of materials thus boosting safe-by-design-based material development. Because of its profound implications for animal-free predictive toxicology, our work paves the way to a more efficient and hazard-free introduction of numerous new advanced materials into our lives.

2020-08-31 | GSE146036 | GEO

Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium

Project description:This SuperSeries is composed of the SubSeries listed below.

2020-09-12 | GSE157856 | GEO

Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium

Project description:Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium

| PRJNA662967 | ENA

Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium

Project description:Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium

| PRJNA609104 | ENA

Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium [100_nm_TiO2_NP]

Project description:Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium [100_nm_TiO2_NP]

| PRJNA662964 | ENA

Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium [DQ_TiO2_NP]

Project description:Chronic Inflammation Prediction for Inhaled Particles, the Impact of Material Cycling and Quarantining in the Lung Epithelium [DQ_TiO2_NP]

| PRJNA662972 | ENA

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

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