Publications by authors named "A D Anderson"

Interferon (IFN)-α is the earliest cytokine signature observed in individuals at risk for type 1 diabetes (T1D), but the effect of IFN-α on the antigen repertoire of HLA Class I (HLA-I) in pancreatic β-cells is unknown. Here we characterize the HLA-I antigen presentation in resting and IFN-α-exposed β-cells and find that IFN-α increases HLA-I expression and expands peptide repertoire to those derived from alternative mRNA splicing, protein cis-splicing and post-translational modifications. While the resting β-cell immunopeptidome is dominated by HLA-A-restricted peptides, IFN-α largely favors HLA-B and only marginally upregulates HLA-A, translating into increased HLA-B-restricted peptide presentation and activation of HLA-B-restricted CD8 T cells.

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Background: Identification of rheumatoid arthritis (RA) in primary care is challenging and often delayed. Anti-cyclic citrullinated peptide (anti-CCP) antibody testing of people presenting to primary care with new-onset musculoskeletal symptoms without synovitis could help address this; those testing positive are at increased risk of developing RA.

Aim: To explore how primary care clinicians currently identify and refer patients with suspected RA, and the behaviours required to implement a prediction model for guiding targeted anti-CCP testing for non-specific musculoskeletal symptoms in primary care.

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Objective: To estimate limb loss prevalence in the United States (US) by etiology and anatomical position and the trends of limb loss over 40 years.

Design: We used the National Inpatient Sample, Healthcare Cost and Utilization Project to estimate current and future limb loss prevalence in the US and by anatomical location. Prevalence estimates were based on the incidence and duration of the disease.

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Background: Skeletal muscle echo intensity (EI) is associated with functional outcomes in older adults, but resistance training interventions have shown mixed results. Texture analysis has been proposed as a novel approach for assessing muscle quality, as it captures spatial relationships between pixels. It is unclear whether texture analysis is able to track changes following resistance training.

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