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Rhinovirus-induced asthma exacerbations and risk populations

Asthma exacerbations are heterogeneous conditions that involve the complex interplay between environmental exposures and innate and adaptive immune function

The effects of in utero vitamin D deficiency on airway smooth muscle mass and lung function

In this study, we aimed to uncover the molecular mechanisms contributing to altered lung structure and function.

Genomic responses during acute human anaphylaxis are characterized by upregulation of innate inflammatory gene networks

The aim of this study was to examine the gene response of white blood cells in severe allergic reactions to identify genes that could be targets to new drugs...

In utero exposure to arsenic alters lung development and genes related to immune and mucociliary function in mice

In utero exposure to arsenic via drinking water increases the risk of lower respiratory tract infections during infancy and mortality from bronchiectasis in...

T-cell activation genes differentially expressed at birth in CD4+ T-cells from children who develop IgE food allergy

To show underlying mechanisms, we examined differences in T-cell gene expression in samples at birth and at 1 year in children with and without IgE allergy.

A genomics-based approach to assessment of vaccine safety and immunogenicity in children

This methodology has significant potential to identify covert interactions between inflammatory pathways triggered by vaccination, and as such may be a...

Airway Epithelial Cell Immunity Is Delayed During Rhinovirus Infection in Asthma and COPD

We propose that propensity for viral exacerbations of asthma and COPD relate to delayed expression of epithelial cell innate anti-viral immune genes

Bilateral murine tumor models for characterizing the response to immune checkpoint blockade

This protocol describes bilateral murine tumor models that display a symmetrical yet dichotomous response to immune checkpoint blockade

Network using Michaelis–Menten kinetics: constructing an algorithm to find target genes from expression data

We derived a simple ordinary differential equation-based model using Michaelis–Menten Kinetics to process the microarray data