Asthma phenotypes and T-bet protein expression in cells treated with Fluticasone Furoate/Vilanterol.

Asthma is a complex disease with diverse clinical manifestations ranging from mild to severe. Despite existing guidelines for asthma recognition and treatment, still a proportion of patients stay uncontrolled. Combinational therapy which comprises inhaled corticosteroids (ICS) and a long acting B2 adrenreceptor agonist (LABA) has been suggested to control asthma. In this study T-bet expression was attested in CD4 T cells treated with Fluticasone Furoate (FF), Vilanterol (V) and FF/V combination in severe asthmatic patients compared to patients with moderate asthma and healthy controls using Immunocytochemistry (ICC). First, CD4 T cells were isolated from PBMCs of 12 patients and controls using CD4 T cell isolation kit. Subsequently, isolated CD4 T cells were cultured with FF, V and FF/V for 1 h. To accomplish ICC, cells were incubated with anti-T-bet antibody, and then stained with HRP-bound secondary antibody. T-bet expression was evaluated using light microscopy. Statistical analyses were performed using R 3.5.2 software and visualized by ggplot2 3.1.0 package. Significant increasing in T-bet expression was seen in CD4 T cells from patients with moderate asthma treated with FF and FF/V. Suggesting conclusion would be distinct mechanisms responsible for severe asthma and moderate asthma in the patients and the needs for novel therapies. Further molecular studies in different asthma phenotypes would be instructive for asthma treatment.

Computer-aided intelligent system for diagnosing pediatric asthma.

Asthma is a lung chronic inflammatory disorder estimated between 1.4% and 27.1% in different area of the world. Result of various studies show that asthma is usually underdiagnosed especially in developing countries, because of limitations on access to medical specialists and laboratory facilities. In this paper, we report on the development and evaluation of a novel patient-based fuzzy system that promotes the diagnosis method of asthma. The design of this application addresses five critical issues included: 1) modular representation of asthma diagnostic variables regard to patients' perception of the disease, 2) algorithmic approaches conducting inference of diagnosing based on patient's response to questions, 4) front-end mechanism for capturing data from patient, 5) output for both patient and physician regard to asthma possibility. for the system output score (0-10) the efficacy of this system calculated in the study sample included 139 asthmatic patients and 139 non-asthmatic patients (age range 6-18) reinforce the sensitivity of 88% and specificity of 100% for cut off value 0.7.