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Airway and parenchyma transcriptomics in a house dust mite model of experimental asthma

Lung transcriptomics studies in asthma have provided valuable information in the whole lung context, however, deciphering the individual contributions of the airway and parenchyma in disease pathogenesis may expedite the development of novel targeted treatment strategies. In this study, we performed transcriptomics on the airway and parenchyma using a house dust mite (HDM)-induced model of experimental asthma that replicates key features of the human disease.

Development of a Symptom-Based Tool for Screening of Children at High Risk of Preschool Asthma

Despite advances in asthma therapeutics, the burden remains highest in preschool children; therefore, it is critical to identify primary care tools that distinguish preschool children at high risk for burdensome disease for further evaluation.

Asthma and allergies in a cohort of adolescents conceived with ART

Research question: Are asthma and allergies more common in adolescents conceived with assisted reproductive technologies (ART) compared with adolescents conceived without?

Azithromycin inhibits mucin secretion, mucous metaplasia, airway inflammation, and airways hyperresponsiveness in mice exposed to house dust mite extract

Excessive production, secretion, and retention of abnormal mucus is a pathological feature of many obstructive airways diseases including asthma. Azithromycin is an antibiotic that also possesses immunomodulatory and mucoregulatory activities, which may contribute to the clinical effectiveness of azithromycin in asthma.

Associations of early-life pet ownership with asthma and allergic sensitization: A meta-analysis of more than 77,000 children from the EU Child Cohort Network

Studies examining associations of early-life cat and dog ownership with childhood asthma have reported inconsistent results. Several factors could explain these inconsistencies, including type of pet, timing, and degree of exposure. Our aim was to study associations of early-life cat and dog ownership with asthma in school-aged children, including the role of type (cat vs dog), timing (never, prenatal, or early childhood), and degree of ownership (number of pets owned), and the role of allergic sensitization.

Clinical significance and applications of oscillometry

Recently, "Technical standards for respiratory oscillometry" was published, which reviewed the physiological basis of oscillometric measures and detailed the technical factors related to equipment and test performance, quality assurance and reporting of results. Here we present a review of the clinical significance and applications of oscillometry.

Parental preconception BMI trajectories from childhood to adolescence and asthma in the future offspring

Recent evidence suggests that parental exposures before conception can increase the risk of asthma in offspring. We investigated the association between parents' preconception body mass index (BMI) trajectories from childhood to adolescence and subsequent risk of asthma in their offspring.

Pertussis immunisation in infancy and atopic outcomes: A protocol for a population-based cohort study using linked administrative data

The burden of IgE-mediated food allergy in Australian born children is reported to be among the highest globally. This illness shares risk factors and frequently coexists with asthma, one of the most common noncommunicable diseases of childhood.

Cord-blood respiratory syncytial virus antibodies and respiratory health in first 5 years of life

To determine the potential longer-term effects of maternal antenatal respiratory syncytial virus (RSV) vaccination, we examined the association between cord-blood RSV-neutralizing antibodies (RSV-NA) and RSV infections in the first 2 years of life, RSV-NA at 3 years, and respiratory health to age 5 years.

Does machine learning have a role in the prediction of asthma in children?

Asthma is the most common chronic lung disease in childhood. There has been a significant worldwide effort to develop tools/methods to identify children's risk for asthma as early as possible for preventative and early management strategies. Unfortunately, most childhood asthma prediction tools using conventional statistical models have modest accuracy, sensitivity, and positive predictive value.