Marine and atmospheric transport modeling supporting nuclear preparedness in Norway: Recent achievements and remaining challenges.

Numerical transport models are important tools for nuclear emergency decision makers in that they rapidly provide early predictions of dispersion of released radionuclides, which is key information to determine adequate emergency protective measures. They can also help us understand and describe environmental processes and can give a comprehensive assessment of transport and transfer of radionuclides in the environment. Transport of radionuclides in air and ocean is affected by a number of different physico-chemical processes.

SARS-CoV-2-specific CD8 T cells from people with long COVID establish and maintain effector phenotype and key TCR signatures over 2 years.

Long COVID occurs in a small but important minority of patients following COVID-19, reducing quality of life and contributing to healthcare burden. Although research into underlying mechanisms is evolving, immunity is understudied. SARS-CoV-2-specific T cell responses are of key importance for viral clearance and COVID-19 recovery.

Adaptation of FDMT to include process-based models and consider regional aspects following radionuclide deposition events.

Experience from earlier nuclear accidents has clearly shown the need for maintaining and developing appropriate modelling capabilities. Dealing with complex issues such as human exposure following a nuclear accident necessitates the implementation of a set of interconnected models such as FDMT. FDMT is an integrated module within the two main European decision support systems for radiological emergency preparedness, ARGOS and JRODOS, to simulate the transfer of radionuclides along terrestrial food chains and to predict their activity concentrations in foodstuffs.

A study of particle dry deposition parameterizations in an atmospheric radioactive preparedness model: Application to the Chernobyl case.

Parameterization of dry deposition is key for modelling of atmospheric transport and deposition of radioactive particles. Still, very simple parameterizations are often encountered in radioactive preparedness models such as the SNAP model (SNAP=Severe Nuclear Accident Program) of the Norwegian Meteorological Institute. In SNAP a constant dry deposition velocity (=0.

Identification of distinct subgroups of Sjögren's disease by cluster analysis based on clinical and biological manifestations: data from the cross-sectional Paris-Saclay and the prospective ASSESS cohorts.

Background: Sjögren's disease is a heterogenous autoimmune disease with a wide range of symptoms-including dryness, fatigue, and pain-in addition to systemic manifestations and an increased risk of lymphoma. We aimed to identify distinct subgroups of the disease, using cluster analysis based on subjective symptoms and clinical and biological manifestations, and to compare the prognoses of patients in these subgroups.

Methods: This study included patients with Sjögren's disease from two independent cohorts in France: the cross-sectional Paris-Saclay cohort and the prospective Assessment of Systemic Signs and Evolution of Sjögren's Syndrome (ASSESS) cohort.