Development of START, a novel multimedia-based symptom appraisal tool for autoimmune rheumatic diseases.

Objectives: To facilitate earlier diagnosis of autoimmune rheumatic diseases (ARDs), we aimed to 1) develop START, a novel multimedia-based symptom appraisal tool for ARDs and 2) pilot test START among established ARD cases and non-ARD controls.

Methods: We developed START using a social cognitive theory-based theoretical framework and consensus-based lists of ARDs and manifestations from our previous work. START was revised through reviews by an expert panel of rheumatologists and cognitive debriefing interviews (CDIs) with patients newly referred for assessment of ARDs.

Hematopoietic stem cell transplantation as rescue therapy for refractory autoimmune retinopathy: a case report.

Autoimmune retinopathy (AIR) is a rare, potentially blinding retinal disease that remains a challenging condition to manage when resistant to conventional immune-modulatory approaches. We report clinical and electrophysiological improvement in a 49-year-old patient who underwent an autologous hematopoietic stem cell transplant (aHSCT) for thymoma-associated AIR after experiencing progressive disease despite receiving periocular and systemic steroids, mycophenolate mofetil, baricitinib, tacrolimus, bortezomib, rituximab, plasmapheresis, and intravenous immunoglobulin. The aHSCT had two stages: (i) peripheral blood stem cell harvest following mobilization with cyclophosphamide and granulocyte colony-stimulating factor, and (ii) conditioning regimen with plasmapheresis, rituximab, cyclophosphamide, and anti-thymocyte globulin high-dose therapy, followed by autologous hematopoietic cell infusion of 5.

Machine learning outperforms humans in microplastic characterization and reveals human labelling errors in FTIR data.

Microplastics are ubiquitous and appear to be harmful, however, the full extent to which these inflict harm has not been fully elucidated. Analysing environmental sample data is challenging, as the complexity in real data makes both automated and manual analysis either unreliable or time-consuming. To address challenges, we explored a dense feed-forward neural network (DNN) for classifying Fourier transform infrared (FTIR) spectroscopic data.

Food Allergy Prevalence in Two Population-Based UK Cohorts Born 12 Years Apart.

Background: Adverse food reactions include food allergy (FA; immune-mediated) and food intolerances (non-immune-mediated). FA are classified into IgE- and non-IgE-mediated FA. There is limited information available about changes in FA prevalence over time.