Bronchiectasis, due to its highly heterogenous nature, requires an individualised approach to therapy. Patients experience symptoms and exacerbations driven by a combination of impaired mucociliary clearance, airway inflammation and airway infection. Treatment of bronchiectasis aims to enhance airway clearance and to address the underlying causes of inflammation and infection susceptibility. Bronchiectasis has multiple causes and so the pathophysiology leading to individual symptoms and exacerbations are different between individuals. Standardised investigations are recommended by international guidelines to identify the underlying causes of bronchiectasis. The process of identifying the underlying biology within an individual is called "endotyping" and is an emerging concept across chronic diseases. Endotypes that have a specific treatment are referred to as "treatable traits" and a treatable traits approach to managing patients with bronchiectasis in a holistic and evidence-based manner is the key to improved outcomes. Bronchiectasis is an area of intense research. Endotyping allows identification of subsets of patients to allow medicines to be tested differently in the future where trials, rather than trying to achieve a "one size fits all" solution, can test efficacy in subsets of patients where the treatment is most likely to be efficacious.
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http://dx.doi.org/10.1183/20734735.0119-2021 | DOI Listing |
J Autism Dev Disord
January 2025
Institutes for Behavior Resources, Inc, 2104 Maryland Ave., Baltimore, MD, 21218, USA.
We aimed to compare sleep problems in autistic and non-autistic adults with co-occurring depression and anxiety. The primary research question was whether autism status influences sleep quality, after accounting for the effects of depression and anxiety. We hypothesized that autistic adults would report higher levels of depression, anxiety, and sleep problems compared to non-autistic adults, after controlling for these covariates.
View Article and Find Full Text PDFAllergy
January 2025
Department of Pediatrics and Adolescent Medicine, Juntendo University Graduate School of Medicine, Tokyo, Japan.
Background: IgE-mediated food allergy is accompanied by mucosal mast cell (MMC) hyperplasia in the intestinal mucosa. Intestinal MMC numbers correlate with the severity of food allergy symptoms. However, the mechanisms by which MMCs proliferate excessively are poorly understood.
View Article and Find Full Text PDFAlzheimers Dement
January 2025
Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Xicheng District, Beijing, China.
Alzheimer's disease (AD) is a degenerative disease characterized by progressive cognitive dysfunction. The strong link between nutrition and the occurrence and progression of AD pathology has been well documented. Poor nutritional status accelerates AD progress by potentially aggravating amyloid beta (Aβ) and tau deposition, exacerbating oxidative stress response, modulating the microbiota-gut-brain axis, and disrupting blood-brain barrier function.
View Article and Find Full Text PDFAlzheimers Dement
January 2025
Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Introduction: Malnutrition correlates with neuropsychiatric symptoms (NPSs) in Alzheimer's disease (AD); however, the potential mechanism underlying this association remains unclear.
Methods: Baseline and longitudinal associations of nutritional status with NPSs were analyzed in 374 patients on the AD continuum and 61 healthy controls. Serum biomarkers, behavioral tests, cerebral neurotransmitters, and differentially gene expression were evaluated in standard and malnourished diet-fed transgenic APPswe/PSEN1dE9 (APP/PS1) mice.
Int J Chron Obstruct Pulmon Dis
January 2025
Department of Cardiology, Respiratory Medicine and Intensive Care, University Hospital Augsburg, Augsburg, Germany.
Background: Chronic obstructive pulmonary disease (COPD) affects breathing, speech production, and coughing. We evaluated a machine learning analysis of speech for classifying the disease severity of COPD.
Methods: In this single centre study, non-consecutive COPD patients were prospectively recruited for comparing their speech characteristics during and after an acute COPD exacerbation.
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