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Medication Use in Type 1 Diabetes and the Association with Socioeconomic Disadvantage: Analysis of a National Linked Dataset

To explore trends in the receipt of commonly prescribed medications (beyond insulin) in people with type 1 diabetes in Australia, including polypharmacy, and to investigate socioeconomic disparities across these trends.

Socioeconomic status and diabetes technology use in youth with type 1 diabetes: a comparison of two funding models

Technology use, including continuous glucose monitoring (CGM) and insulin pump therapy, is associated with improved outcomes in youth with type 1 diabetes (T1D). In 2017 CGM was universally funded for youth with T1D in Australia. In contrast, pump access is primarily accessed through private health insurance, self-funding or philanthropy.

Lifting the wellbeing of adolescents and young adults with type 1 diabetes: A feasibility study of the LIFT app

Adolescents and young adults with type 1 diabetes have an increased risk of psychological distress. To address this, psychological support provided asynchronously via an app may be feasible. Our study aimed to explore feasibility and safety of the LIFT wellbeing app.

Acceptance and Commitment Therapy (ACT) intervention in adolescents with type 1 diabetes: A pilot and feasibility study

A considerable proportion of patients with type 1 diabetes (T1D) experience emotional problems due to the continual demands of the disease, which may persist throughout life without appropriate support. The aim of this study was to assess the feasibility and acceptability of an Acceptance and Commitment Therapy (ACT) intervention and provide early indications of its capacity to impact psychosocial outcomes for adolescents with T1D. 

WALLABY pilot survey: Public release of H i data for almost 600 galaxies from phase 1 of ASKAP pilot observations

We present WALLABY pilot data release 1, the first public release of H i pilot survey data from the Wide-field ASKAP L-band Legacy All-sky Blind Survey (WALLABY) on the Australian Square Kilometre Array Pathfinder.

A surge in serum mucosal cytokines associated with seroconversion in children at risk for type 1 diabetes

Autoantibodies to pancreatic islet antigens identify young children at high risk of type 1 diabetes. On a background of genetic susceptibility, islet autoimmunity is thought to be driven by environmental factors, of which enteric viruses are prime candidates.

An Assessment of Clinical Continuous Glucose Monitoring Targets for Older and High-Risk People Living with Type 1 Diabetes

To assess relationships between continuous glucose monitoring (CGM) time in range (TIR), 70-180 mg/dL, time below range (TBR), <70 mg/dL, time above range (TAR), >180 mg/dL, and glucose coefficient of variation (CV) in relation to currently recommended clinical CGM targets for older people, which recommend reduced TIR and TBR targets relative to the general type 1 diabetes population. 

Complete Genomes of Three Pseudomonas aeruginosa Bacteriophages, Kara-mokiny 1, Kara-mokiny 2, and Kara-mokiny 3

Here, we present the complete genome sequence of Pseudomonas aeruginosa phages Kara-mokiny 1, Kara-mokiny 2, and Kara-mokiny 3. These phages have lytic capabilities against P. aeruginosa and belong to the myovirus morphotype. The genomes of Kara-mokiny 1 and Kara-mokiny 2 are 67,075 bp while that of Kara-mokiny 3 is 66,019 bp long.

Driving with Type 1 Diabetes: Real-World Evidence to Support Starting Glucose Level and Frequency of Monitoring During Journeys

There is limited evidence supporting the recommendation that drivers with insulin-treated diabetes need to start journeys with glucose >90 mg/dL. Glucose levels of drivers with type 1 diabetes were monitored for 3 weeks using masked continuous glucose monitoring (CGM).

3DFAACTS-SNP: using regulatory T cell-specific epigenomics data to uncover candidate mechanisms of type 1 diabetes (T1D) risk

Genome-wide association studies (GWAS) have enabled the discovery of single nucleotide polymorphisms (SNPs) that are significantly associated with many autoimmune diseases including type 1 diabetes (T1D). However, many of the identified variants lie in non-coding regions, limiting the identification of mechanisms that contribute to autoimmune disease progression.