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Complement is an important part of the immune system. It is initiated through three different pathways known as the classical, lectin, and alternative pathway.
In this study, using a mouse model, we determined whether vitamin D deficiency in utero and during early life modulated the severity of asthma.
In the majority of people, functional differences are observed between the two cerebral hemispheres: language production is typically subserved by the left...
Otitis media (OM) is a common childhood disease characterised by middle ear inflammation following infection
Concerns about the risk of inducing immune deviation-associated "neonatal tolerance" as described in mice have restricted the widespread adoption...
Post-acute sequelae of COVID-19 (PASC), or long COVID, are a public health concern. While most recover from SARS-CoV-2 infections within weeks, some experience persistent symptoms. Here, we quantified the association between repeated SARS-CoV-2 infections and the risk of hospital-diagnosed PASC.
To explore Aboriginal families' experiences of recognising clinical deterioration and raising their concerns within the Paediatric ESCALATION system to identify enablers and barriers to family involvement.
Digital interventions have emerged as promising tools to support mental well-being in diabetes. This review aimed to evaluate the effectiveness of digital health interventions in improving mental health outcomes among adults with diabetes, as well as assess the methodological quality of relevant studies and provide a commentary on research gaps and future directions.
Few studies have explored associations between indexes incorporating both breastfeeding and complementary feeding and future risk of overweight/obesity. The aim of this study was to explore associations between a previously developed Infant Diet Score (IDS; higher score reflecting better alignment with breastfeeding and complementary feeding guidelines in the first year of life), and the risk of overweight and/or obesity in childhood.
To map and systematise existing research on the use of artificial intelligence (AI) in mental health-based diabetes care contexts, identify trends and potential gaps in the literature, examine methodological limitations and highlight future research directions.