Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: Bronchoalveolar lavage fluid and lung biopsy tissue mNGS in the diagnosis of pulmonary cryptococcosis

PROVIDER: PRJNA1175072 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR31048900.fastq.gz	Fastqsanger.gz
	SRR31049000.fastq.gz	Fastqsanger.gz
	SRR31049100.fastq.gz	Fastqsanger.gz
	SRR31048901.fastq.gz	Fastqsanger.gz
	SRR31049001.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 321

Similar Datasets

Harnessing Bronchoalveolar Lavage Metagenomics for Distinguishing Lung Cancer from Pulmonary Infectious Diseases

Project description:Recent progress in unbiased metagenomic next-generation sequencing (mNGS) allows simultaneous examination of microbial and host genetic material in a single test. Leveraging affordable bronchoalveolar lavage fluid (BALF) mNGS data, we employed machine learning to create a diagnostic approach distinguishing lung cancer from pulmonary infections, conditions prone to misdiagnosis in clinical settings. This prospective study analyzed BALF-mNGS data from lung cancer and pulmonary infection patients, delineating differences in DNA/RNA microbial composition, bacteriophage abundances, and host responses, including gene expression, transposable element levels, immune cell composition, and tumor fraction derived from copy number variation (CNV). Integrating these metrics into a host/microbe metagenomics-driven machine learning model (Model VI) demonstrated robustness, achieving an AUC of 0.87 (95% CI = 0.857-0.883), sensitivity = 73.8%, and specificity = 84.5% in the training cohort, and an AUC of 0.831 (95% CI = 0.819-0.843), sensitivity = 67.1%, and specificity = 94.4% in the validation cohort for distinguishing lung cancer from pulmonary infections. The application of a rule-in and rule-out strategy-based composite predictive model significantly enhances accuracy (ACC) in distinguishing between lung cancer and tuberculosis (ACC=0.913), fungal infection (ACC=0.955), and bacterial infection (ACC=0.836). These findings highlight the potential of cost-effective mNGS-based analysis as a valuable tool for early differentiation between lung cancer and pulmonary infections, offering significant benefits through a single comprehensive testing.

2024-01-08 | GSE252118 | GEO

Identification of pro-fibrotic macrophages populations by scRNA-seq in West Highland white terriers affected with canine idiopathic pulmonary fibrosis

Project description:We used the scRNA-seq to characterize disease-related heterogeneity within cell populations of macrophages/monocytes in the bronchoalveolar lavage fluid from West Highland white terriers either healthy or affected with canine idioapthic pulmonary fibrosis. The disease is still not well understood, occurs in old West Highland white terriers and results from deposition of fibrotic tissue in the lung parenchyma causing respiratory failure.

2020-12-02 | E-MTAB-9623 | biostudies-arrayexpress

Examining gene expression profile from varying preparations of fibrotic lung tissue

Project description:Gene expression of human lung tissue bronchoalveolar lavage (BAL), whole tissue biopsy, and digested single cell suspension of lung tissue from control and ILD samples.

2021-03-08 | GSE166036 | GEO

Proteomic profiling of bronchoalveolar lavage fluid uncovers unique protein clusters linked to survival in idiopathic pulmonary fibrosis and interstitial pneumonia with autoimmune features

Project description:This study aimed to delineate molecular phenotypes of the lung microenvironment across idiopathic interestitial pneumonias, namely interstitial pneumonia with autoimmune features (IPAF)and idiopathic pulmonary fibrosis (IPF) through proteomic analysis of bronchoalveolar lavage fluid (BALF).

2024-05-20 | MSV000094806 | MassIVE

Project description:This study investigated the pulmonary toxicity of Copper oxide nanoparticles (CuO NPs) surface modified with polyethylenimine (PEI) or ascorbate (ASC), was investigated. Rats were exposed nose-only to a fixed exposure concentration of ASC or PEI coated CuO NPs for 5 consecutive days. On day 6 and day 27 post-exposure, pulmonary toxicity markers in bronchoalveolar lavage fluid (BALF) were analyzed and histopathological evaluation of the lungs was performed, along with microarray analyses on whole lung tissue samples.

2020-10-02 | GSE158900 | GEO

Predictive protein biomarker signatures and the corresponding transcriptional cell state changes in human lung fibrosis

Project description:Single cell genomics enables characterization of disease specific cell states, while improvements in mass spectrometry workflows bring the clinical use of body fluid proteomics within sight. However, the correspondence of peripheral protein signatures with cell state changes in diseased organs is currently unknown. Here, we use single cell RNA-seq and proteomics from large patient cohorts of pulmonary fibrosis and establish that predictive protein signatures in body fluids correspond to specific cellular changes in the lung. We determined transcriptional changes in 45 cell types across three patient cohorts and quantified bronchoalveolar lavage fluid and plasma proteins to discover protein signatures and associated cell state changes that were linked to diagnosis, lung function, smoking and injury status. Altered expression of the novel marker of lung health CRTAC1 in alveolar epithelium is robustly reported in patient plasma. With further improvements of this concept and deeper coverage of plasma proteomes, we envision future longitudinal profiling of body fluid signatures coupled to deep learning for non-invasive prediction and monitoring of pathological cell state changes in patient organs.

2020-09-18 | PXD017145 | Pride

Predictive protein biomarker signatures and the corresponding transcriptional cell state changes in human lung fibrosis (Plasma)

Project description:Single cell genomics enables characterization of disease specific cell states, while improvements in mass spectrometry workflows bring the clinical use of body fluid proteomics within reach. However, the correspondence of peripheral protein signatures to changes in cell state in diseased organs is currently unknown. Here, we leverage single cell RNA-seq and proteomics from large patient cohorts of pulmonary fibrosis to establish that predictive protein signatures in body fluids correspond to specific cellular changes in the lung. We determined transcriptional changes in 45 cell types across three patient cohorts and quantified bronchoalveolar lavage fluid and plasma proteins to discover protein signatures and associated cell state changes that were linked to diagnosis, lung function, smoking and injury status. Altered expression of the novel marker of lung health CRTAC1 in alveolar epithelium is robustly reported in patient plasma. With further improvements of this concept and deeper coverage of plasma proteomes, we envision future longitudinal profiling of body fluid signatures coupled to machine learning for non-invasive prediction and monitoring of pathological cell state changes in patient organs.

2020-09-18 | PXD017210 | Pride

Bronchoalveolar Lavage Fluid Microbiota is Associated with the Diagnosis and Prognosis Evaluation of Lung Cancer

Project description:Bronchoalveolar Lavage Fluid Microbiota of Lung Cancer

| PRJEB61420 | ENA

Project description:Lung Microbiota Alterations in Bronchoalveolar Lavage Fluid

| PRJNA1230000 | ENA

Epithelial miR-141 regulates IL-13-induced airway mucus production [single-cell RNA-seq]

Project description:We performed single cell RNA sequencing on bronchial cells from human bronchoalveolar lavage fluid from 4 independent study participants who had asthma and who underwent lung segmental allergen challenge with diluent or allergen (either house duse mite or cat). The goal was to assess total mRNAs in single cell preparations of bronchoalveolar lavage cells.

2020-12-30 | GSE164015 | GEO

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