Clonal populations of lineage-uncommitted pluripotent mesenchymal stem cells have been identified in prenatal avians and rodents. These cells reside in the connective tissue matrices of many organs and tissues. They demonstrate extended capabilities for selfrenewal and the ability to differentiate into multiple separate tissues within the mesodermal germ line. This study was designed to determine whether such cells are present in the connective tissues of postnatal mammals. This report describes a cell clone derived by isolation from postnatal rat connective tissues, cryopreservation, extended propagation, and serial dilution clonogenic analysis. In the undifferentiated state, this clone demonstrates a high nuclear-to-cytoplasmic ratio and extended capacity for self-renewal. Subsequent morphological, histochemical, and immunochemical analysis after the induction of differentiation revealed phenotypic markers characteristic of multiple cell types of mesodermal origin, such as skeletal muscle, smooth muscle, fat cells, cartilage, and bone. These results indicate that this clone consists of pluripotent mesenchymal stem cells. This report demonstrates that clonal populations of reserve stem cells are present in mammals after birth. Potential roles for such cells in the maintenance, repair, and regeneration of mesodermal tissues are discussed.

Visualizations can add value to raw library data. Tools that programmatically make such visualizations interactive can further increase the value of this data, by giving librarians visual tools to analyze their data sets. To demonstrate these benefits, Kingsborough Community College Library built SeeCollections (http://b7jl.org/seecollections), a web application that visualizes our libraries' collections of books and ebooks. This article discusses the how SeeCollections gathers data from Kingsborough's discovery layer API (Application Programming Interface), and transforms this data to create visualizations for the web. SeeCollections is a lightweight, proof-of-concept data application based on a vendor API. API data is often accessible in academic libraries, but is frequently underutilized. SeeCollections was built to demonstrate the immediate value of these API data sources to Kingsborough librarians, by providing a visual interface to discovery layer data. Keeping in mind the broader literature on data visualization, this article will explore how SeeCollections was built.

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