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Suppressing recurrence in Sonic Hedgehog subgroup medulloblastoma using the OLIG2 inhibitor CT-179

OLIG2-expressing tumor stem cells have been shown to drive recurrence in Sonic Hedgehog (SHH)-subgroup medulloblastoma (MB) and patients urgently need specific therapies to target this tumor cell population.

Mental health assessment of transgender youth - Should standardised psychological measures be scored by norms of birth-registered sex?

Standardised psychometric measures are used in mental health care and research settings to identify risk, assist diagnosis, and assess symptom severity. Standardised scoring of these measures involves transforming respondents' raw scores using binary sex norms. However, scoring manuals offer no guidance as to appropriate scoring methods for trans and non-binary respondents.

Aboriginal and Torres Strait Islander community experiences and recommendations for health and medical research: a mixed methods study

To describe Aboriginal and Torres Strait Islander communities' processes, positioning and experiences of health and medical research and their recommendations.

Normative values for lung, bronchial sizes, and bronchus-artery ratios in chest CT scans: from infancy into young adulthood

To estimate the developmental trends of quantitative parameters obtained from chest computed tomography (CT) and to provide normative values on dimensions of bronchi and arteries, as well as bronchus-artery (BA) ratios from preschool age to young adulthood.

Impact of Parent-Reported Antibiotic Allergies on Pediatric Antimicrobial Stewardship Programs

Antimicrobial stewardship (AMS) is crucial for optimizing antimicrobial use and restraining emergence of antimicrobial resistance. The overall increase in reported antibiotic allergies in children can pose a significant barrier to AMS, but its impact on clinical AMS care in children has not been addressed.

Feasibility of home-based urine collection in children under 5 years in the ORIGINS birth cohort study: mixed method protocol and sample completion results

Urine is an attractive biospecimen for nutritional status and population health surveys. It is an excellent non-invasive alternative to blood for appropriate biomarkers in young children and is suitable for home-based collection, enabling representative collections across a population. However, the bulk of literature in this population is restricted to collection in primary care settings.

Developmental queer and trans actualizations: A clear pathway to promoting health and well-being for sexually and gender diverse youth

Minority stress models and trauma-focused approaches have predominated our understanding and responses to health disparities among sexually and gender diverse (SGD) young people for more than 30 years. While the impacts and root causes of adversities are undoubtedly critical for promoting SGD health and well-being, it is important to highlight strengths-based narratives of the lives of SGD youth.

Physical activity behaviors in trans and gender diverse adults: a scoping review

There is currently limited data regarding the physical activity behaviors of trans and gender diverse people (including binary and non-binary identities; henceforth trans). The aim of this review was to synthesize the existing literature in this area, with a focus on physical activity behaviors as they relate to health (e.g. health benefits, risks of adverse health outcomes). 

Understanding wellbeing from the perspective of youth with chronic conditions: A group concept mapping approach

Promoting wellbeing for youth is a global health priority and young people with chronic conditions demonstrate disproportionately low wellbeing compared to their peers. However, wellbeing is variably defined, and little is understood as to what wellbeing means for this population. The aim of this study was to develop a conceptualisation of wellbeing that is rooted in the perspectives of young people with chronic conditions. 

Machine learning techniques to predict diabetic ketoacidosis and HbA1c above 7% among individuals with type 1 diabetes — A large multi-centre study in Australia and New Zealand

Type 1 diabetes and diabetic ketoacidosis (DKA) have a significant impact on individuals and society across a wide spectrum. Our objective was to utilize machine learning techniques to predict DKA and HbA1c>7 %.