Assisting the implementation of screening for type 1 diabetes by using artificial intelligence on publicly available data.

The type 1 diabetes community is coalescing around the benefits and advantages of early screening for disease risk. To be accepted by healthcare providers, regulatory authorities and payers, screening programmes need to show that the testing variables allow accurate risk prediction and that individualised risk-informed monitoring plans are established, as well as operational feasibility, cost-effectiveness and acceptance at population level. Artificial intelligence (AI) has the potential to contribute to solving these issues, starting with the identification and stratification of at-risk individuals.

Effects of lambing season on nematode faecal egg output in ewes.

In this study, we assessed the occurrence of a periparturient rise (PPR) in winter and spring lambing ewes in Sweden and where nematode egg excretion patterns were investigated mainly for diagnostic purposes. Gastrointestinal nematodes and Haemonchus contortus presence were monitored in parallel in all animals in each experimental group on four farms in samples that were collected mainly when the animals were stabled. Faecal examinations of the same animals were conducted on four sampling occasions between January and June 2018 Each group consisted of 12 crossbreed ewes of similar genotype.

Relationship between Ljungan virus antibodies, HLA-DQ8, and insulin autoantibodies in newly diagnosed type 1 diabetes children.

Environmental factors, including viral infections, may explain an increasing and fluctuating incidence of childhood type 1 diabetes (T1D). Ljungan virus (LV) isolated from bank voles have been implicated, but it is unclear whether LV contributes to islet autoimmunity, progression to clinical onset, or both, of T1D. The aim was to test whether LV antibodies (LVAb) were related to HLA-DQ and islet autoantibodies in newly diagnosed T1D patients (n=676) and controls (n=309).