Rapid advances in genomic technologies to screen, diagnose, and treat newborns will significantly increase the number of conditions in newborn screening (NBS). We previously identified four factors that delay and/or complicate NBS expansion: 1) variability in screening panels persists; 2) the short duration of pilots limits information about interventions and health outcomes; 3) recent recommended uniform screening panel (RUSP) additions are expanding the definition of NBS; and 4) the RUSP nomination and evidence review process has capacity constraints. In this paper, we developed a use case for each factor and suggested how model(s) could be used to evaluate changes and improvements. The literature on models was reviewed from a range of disciplines including system sciences, management, artificial intelligence, and machine learning. The results from our analysis highlighted that there is at least one model which could be applied to each of the four factors that has delayed and/or complicate NBS expansion. In conclusion, our paper supports the use of modeling to address the four challenges in the expansion of NBS.

Atypical B cells (atBCs) are a distinct B-cell population and represent approximately 5% of B cells in peripheral blood (PB) of healthy adult individuals. However, in adults these cells are expanded in conditions of chronic infections, inflammation, primary immunodeficiencies, autoimmune diseases, and aging. Their immunophenotype is characterized by the lack of CD21 expression and the hallmark human memory B-cell marker CD27. In this study, we investigated the immunophenotype of atBCs in different pediatric pathological conditions and correlated their expansion with the children\'s clinical diagnosis. We were able to retrospectively evaluate 1,571 consecutive PB samples, corresponding to 1,180 pediatric patients, by using a 9-color flow-cytometric panel. The results, compared with a pediatric healthy cohort, confirmed an expansion of atBCs in patient samples with percentages greater than 5% of total B cells. Four subpopulations with different expressions of IgM and IgD were discriminated: IgM+IgD+, IgM+-only, IgD+-only, and IgM-IgD-. IgG+ atBCs were predominant in the IgM- IgD- subpopulation. Moreover, the study highlighted some features of atBCs, such as a low CD38 expression, a heterogeneity of CD24, a high expression of CD19 and a large cell size. We also demonstrated that an increase of atBCs in a pediatric cohort is correlated with immunodeficiencies, autoimmune, inflammatory, and hematological disorders, consistent with previous studies mainly performed in adults. Furthermore, our flow cytometric clustering analysis corroborated the recent hypothesis of an alternative B origin for atBCs.