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Researchers have made a world-first discovery on how to prevent severe respiratory infections in babies.
To introduce a disease prognosis framework enabled by a robust classification scheme derived from patient-specific transcriptomic response to stimulation.
We employed a systems biology approach to delineate upper airway gene network patterns underlying asthma exacerbation phenotypes in children.
CFTR-dependent imbalance of macrophage phenotypes and functions could contribute to the exaggerated inflammatory response seen in CF lung disease
The co-exposure responses in the Th2high BN incorporated type I interferon/Th1, alternative macrophage activation/Th2 and Th17 signatures
Our findings suggest that the proportion of degranulated basophils can also be associated with recurrent exacerbations
To complement early allergic sensitization, monitoring NPM composition may enable early detection and intervention in high-risk children
Our data demonstrate that CD8+XCR1neg DCs possess a unique pattern of endocytic receptors and a restricted TLR profile that is particularly enriched for TLR5
Here, we review the basic concepts in bioinformatics and genomic data analysis and illustrate the application of these tools to further our understanding of lung diseases
Anya Deborah Pat Jones Strickland Holt BSc MSc PhD PhD PhD, DSc, FRCPath, FRCPI, FAA Honorary Research Associate Head, Pregnancy and Early Life