Tracking Persistent Symptoms in Scotland (TraPSS): a longitudinal prospective cohort study of COVID-19 recovery after mild acute infection.

Background: COVID-19 disease results in disparate responses between individuals and has led to the emergence of long coronavirus disease (Long-COVID), characterised by persistent and cyclical symptomology. To understand the complexity of Long-COVID, the importance of symptom surveillance and prospective longitudinal studies is evident.

Methods: A 9-month longitudinal prospective cohort study was conducted within Scotland (n=287), using a mobile app to determine the proportion of recovered individuals and those with persistent symptoms and common symptoms, and associations with gender and age.

Impact of physical activity and exercise training on health-related quality of life in older adults: an umbrella review.

Health-related quality of life (HRQoL) is inversely associated with all-cause mortality in older adults and may be improved with physical activity and exercise training. The objective of this umbrella review was to determine the impact of physical activity and exercise training on HRQoL in younger-old (average age ≤ 75 years) and older-old (average age > 75 years) adults. Our umbrella review (CRD42023481145) included 39 systematic reviews (21/39 with meta-analysis) including 113 unique individual studies of 13391 unique participants.

More absolute moderate-to-vigorous physical activity is associated with better health-related quality of life in outpatients with an acquired brain injury.

Health-related quality of life (HRQoL) is a patient-perceived measure of physical, social, and emotional health. Acquired brain injury (ABI) occurs due to damage to the brain after birth. Individuals with an ABI typically present with reduced HRQoL and require additional support to maintain their HRQoL.

Artificial intelligence-guided design of lipid nanoparticles for pulmonary gene therapy.

Ionizable lipids are a key component of lipid nanoparticles, the leading nonviral messenger RNA delivery technology. Here, to advance the identification of ionizable lipids beyond current methods, which rely on experimental screening and/or rational design, we introduce lipid optimization using neural networks, a deep-learning strategy for ionizable lipid design. We created a dataset of >9,000 lipid nanoparticle activity measurements and used it to train a directed message-passing neural network for prediction of nucleic acid delivery with diverse lipid structures.