National Jewish Health

About: National Jewish Health is a healthcare organization based out in Denver, Colorado, United States. It is known for research contribution in the topics: Asthma & T cell. The organization has 883 authors who have published 833 publications receiving 79201 citations. The organization is also known as: National Jewish Medical and Research Center.

Characterization of Mouse γδ T Cell Subsets in the Setting of Type-2 Immunity.

Abstract: Accumulating evidence indicates that γδ T cells are a critical component of type-2 immunity. However, the role of these cells in type-2 immune responses seems to be divergent. γδ T cells are heterogeneous lymphocytes that can be further divided into TCR-Vγ/δ definable subsets. Different subsets have distinct and sometimes opposite function during immune responses. In this chapter, we describe the detailed protocol for characterization of γδ T cell subsets in a mouse model of ovalbumin (OVA)/alum-induced type-2 immunity. Our protocol includes identifying γδ T cell subsets by flow cytometry, functionally inactivating individual subsets in vivo, purifying γδ T cell subsets, and using adoptive cell transfer to explore the role of individual subsets in OVA/alum-induced IgE responses.

Method for treating pulmonary exacerbation and disease progression in subjects having cystic fibrosis

Abstract: The present invention is related to a method for determining pulmonary disease progression severity in a subject having cystic fibrosis and treating the subject according to the severity. The method comprises obtaining a whole blood sample from the subject; detecting the mRNA expression level of each of the following genes: TLR2, ADAM9, PLXND1, CD163, CD36, CD64, CSPG2, IL32, HPSE, HCA112; determining the severity of the pulmonary disease progression based on the subject's combined mRNA expression level of the genes; and treating the subject.

A Distinctive γδ T Cell Repertoire in NOD Mice Weakens Immune Regulation and Favors Diabetic Disease

Abstract: Previous studies in mice and humans suggesting that γδ T cells play a role in the development of type 1 diabetes have been inconsistent and contradictory. We attempted to resolve this for the type 1 diabetes-prone NOD mice by characterizing their γδ T cell populations, and by investigating the functional contributions of particular γδ T cells subsets, using Vγ-gene targeted NOD mice. We found evidence that NOD Vγ4+ γδ T cells inhibit the development of diabetes, and that the process by which they do so involves IL-17 production and/or promotion of regulatory CD4+ αβ T cells (Tregs) in the pancreatic lymph nodes. In contrast, the NOD Vγ1+ cells promote diabetes development. Enhanced Vγ1+ cell numbers in NOD mice, in particular those biased to produce IFNγ, appear to favor diabetic disease. Within NOD mice deficient in particular γδ T cell subsets, we noted that changes in the abundance of non-targeted T cell types also occurred, which varied depending upon the γδ T cells that were missing. Our results indicate that while certain γδ T cell subsets inhibit the development of spontaneous type 1 diabetes, others exacerbate it, and they may do so via mechanisms that include altering the levels of other T cells.

Computational Analysis of RNA-Seq Data from Airway Epithelial Cells for Studying Lung Disease.

Abstract: Airway epithelial cells (AECs) play a central role in the pathogenesis of many lung diseases. Consequently, advancements in our understanding of the underlying causes of lung diseases, and the development of novel treatments, depend on continued detailed study of these cells. Generation and analysis of high-throughput gene expression data provide an indispensable tool for carrying out the type of broad-scale investigations needed to identify the key genes and molecular pathways that regulate, distinguish, and predict distinct pulmonary pathologies. Of the available technologies for generating genome-wide expression data, RNA sequencing (RNA-seq) has emerged as the most powerful. Hence many researchers are turning to this approach in their studies of lung disease. For the relatively uninitiated, computational analysis of RNA-seq data can be daunting, given the large number of methods and software packages currently available. The aim of this chapter is to provide a broad overview of the major steps involved in processing and analyzing RNA-seq data, with a special focus on methods optimized for data generated from AECs. We take the reader from the point of obtaining sequence reads from the lab to the point of making biological inferences with expression data. Along the way, we discuss the statistical and computational considerations one typically confronts during different phases of analysis and point to key methods, software packages, papers, online guides, and other resources that can facilitate successful RNA-seq analysis.

Cooling off the heated controversy of a safer cigarette: heat-not-burn no better than traditional combustion cigarettes

Abstract: In response to overwhelming evidence of harmful effects of cigarette smoking, the tobacco industry launched heat-not-burn cigarettes (HNBC), a hybrid between traditional combustion cigarettes (TCCs) and electronic vaping devices. They marketed HNBC as a less harmful alternative to TCC due to absence of specific toxicants released by burning the tobacco. However, similar to TCC smoke, aerosols released by heating the tobacco (up to 350°C) in HNBC contain nicotine and harmful elements generated by incomplete combustion (pyrolysis) and thermogenic degradation of tobacco. The claims that these by-products are present in amounts too small to be harmful suggest that a threshold concentration for the toxic effects of heated tobacco by-products exists. This assertion requires further elucidation, due to a …