Corrigendum to 'Machine Learning-Based Predictive Models for 90-Day Readmission of Total Joint Arthroplasty Using Comprehensive Electronic Health Records and Patient-Reported Outcome Measures'. [Arthroplasty Today Volume 25, February 2024, 101308].

[This corrects the article DOI: 10.1016/j.artd.

Changes and continuities in gambling careers during the COVID-19 pandemic: a longitudinal qualitative study of regular sports bettors in Britain.

Background: To explore continuities and changes in gambling behaviour during the COVID-19 pandemic and the factors that influenced these among a sample of regular sports bettors.

Methods: A longitudinal qualitative study using in-depth interviews. Sixteen sports bettors living in Britain took part in the first interviews in July-November 2020, and 13 in the follow-up interviews in March-September 2021.

Deep learning and genome-wide association meta-analyses of bone marrow adiposity in the UK Biobank.

Bone marrow adipose tissue is a distinct adipose subtype comprising more than 10% of fat mass in healthy humans. However, the functions and pathophysiological correlates of this tissue are unclear, and its genetic determinants remain unknown. Here, we use deep learning to measure bone marrow adiposity in the femoral head, total hip, femoral diaphysis, and spine from MRI scans of approximately 47,000 UK Biobank participants, including over 41,000 white and over 6300 non-white participants.

Neonates exposed to HIV but uninfected exhibit an altered gut microbiota and inflammation associated with impaired breast milk antibody function.

Background: Infants exposed to HIV but uninfected have altered immune profiles which include heightened systemic inflammation. The mechanism(s) underlying this phenomenon is unknown. Here, we investigated differences in neonatal gut bacterial and viral microbiome and associations with inflammatory biomarkers in plasma.