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People living with rare diseases (PLWRD) still face huge unmet needs, in part due to the fact that care systems are not sufficiently aligned with their needs and healthcare workforce (HWF) along their care pathways lacks competencies to efficiently tackle rare disease-specific challenges. Level of rare disease knowledge and awareness among the current and future HWF is insufficient.

Computer vision technology is advancing rare disease diagnosis to address unmet needs of the more than 300 million individuals affected globally; one in three rare diseases have a known facial phenotype. 3D face model reconstruction is a key driver of these advances.

The immunological changes underpinning acquisition of remission (also called sustained unresponsiveness) following food immunotherapy remain poorly defined. Limited access to effective therapies and biosamples from treatment responders has prevented progress. Probiotic peanut oral immunotherapy is highly effective at inducing remission, providing an opportunity to investigate immune changes.

Over 400 million people worldwide are living with a rare disease. Next Generation Sequencing identifies potential disease causative genetic variants. However, many are identified as variants of uncertain significance and require functional laboratory validation to determine pathogenicity, and this creates major diagnostic delays.

There are an estimated > 400 million people living with a rare disease globally, with genetic variants the cause of approximately 80% of cases. Next Generation Sequencing (NGS) rapidly identifies genetic variants however they are often of unknown significance.

Since the discovery of MECP2 duplication syndrome (MDS) in 1999, efforts to characterise this disorder have been limited by a lack of large datasets, with small case series often favouring the reporting of certain conditions over others. This study is the largest to date, featuring 134 males and 20 females, ascertained from the international MECP2 Duplication Database (MDBase).

In clinical genetics, establishing an accurate nosology requires analysis of variations in both aetiology and the resulting phenotypes. At the phenotypic level, recognising typical facial gestalts has long supported clinical and molecular diagnosis; however, the objective analysis of facial phenotypic variation remains underdeveloped.

To define clinical common data elements (CDEs) and a mandatory minimum data set (MDS) for genomic studies of cerebral palsy (CP). Method: Candidate data elements were collated following a review of the literature and existing CDEs.

Our goal was to identify genetic risk factors for severe otitis media (OM) in Aboriginal Australians.

Surgical resection of cancer remains the frontline therapy for millions of patients annually, but post-operative recurrence is common, with a relapse rate of around 45% for non-small cell lung cancer. The tumour draining lymph nodes (dLN) are resected at the time of surgery for staging purposes, and this cannot be a null event for patient survival and future response to immune checkpoint blockade treatment. This project investigates cancer surgery, lymphadenectomy, onset of metastatic disease, and response to immunotherapy in a novel model that closely reflects the clinical setting. In a murine metastatic lung cancer model, primary subcutaneous tumours were resected with associated dLNs remaining intact, completely resected or partially resected.