A novel Rac-dependent checkpoint in B cell development controls entry into the splenic white pulp and cell survival

Rac1 and Rac2 GTPases transduce signals from multiple receptors leading to cell migration, adhesion, proliferation, and survival. In the absence of Rac1 and Rac2, B cell development is arrested at an IgD− transitional B cell stage that we term transitional type 0 (T0). We show that T0 cells cannot enter the white pulp of the spleen until they mature into the T1 and T2 stages, and that this entry into the white pulp requires integrin and chemokine receptor signaling and is required for cell survival. In the absence of Rac1 and Rac2, transitional B cells are unable to migrate in response to chemokines and cannot enter the splenic white pulp. We propose that loss of Rac1 and Rac2 causes arrest at the T0 stage at least in part because transitional B cells need to migrate into the white pulp to receive survival signals. Finally, we show that in the absence of Syk, a kinase that transduces B cell antigen receptor signals required for positive selection, development is arrested at the same T0 stage, with transitional B cells excluded from the white pulp. Thus, these studies identify a novel developmental checkpoint that coincides with B cell positive selection

Survey of Surveys (SoS) ‐ Mapping The Landscape of Survey Papers in Information Visualization

Information visualization as a field is growing rapidly in popularity since the first information visualization conference in 1995.However, as a consequence of its growth, it is increasingly difficult to follow the growing body of literature within the field.Survey papers and literature reviews are valuable tools for managing the great volume of previously published research papers,and the quantity of survey papers in visualization has reached a critical mass. To this end, this survey paper takes a quantumstep forward by surveying and classifying literature survey papers in order to help researchers understand the current landscapeof Information Visualization. It is, to our knowledge, the first survey of survey papers (SoS) in Information Visualization. Thispaper classifies survey papers into natural topic clusters which enables readers to find relevant literature and develops thefirst classification of classifications. The paper also enables researchers to identify both mature and less developed researchdirections as well as identify future directions. It is a valuable resource for both newcomers and experienced researchers in andoutside the field of Information Visualization and Visual Analytic