Faculty and Staff

In spring 2013, the presenters developed a survey on academic library streaming video and distributed it broadly through various discussion and mailing lists.

This is the first large-scale and most comprehensive effort to date to collect data on streaming video funding, licensing, acquisition, and hosting in academic libraries. Its results will provide benchmark data for future explorations of this rapidly expanding approach to video in academic libraries.

Streaming video is becoming a common occurrence on many campuses today. Its fast growth is due in part to the steady growth of online classes and programs. Technology has also played a role in this growth as alternatives for ingesting and accessing content have expanded. Multiple options are now available including in-house approaches, cloud storage, and third party vendors.

This survey collected data on how academic institutions address the day-to-day operations related to streaming video as well as perceived directions for future action.

Survey questions addressed selection and acquisition of video in both hard copy and streaming formats, funding for acquisitions, current and planned hosting interfaces, cataloging and access, and current practice and policy on digitization of hard copy titles for streaming. This session reviews the instrument used, and provides a preliminary look at some of the key data collected.

Background: Cancer diagnosis in both dogs and humans is complicated by the lack of a non-invasive diagnostic test. To meet this clinical need, we apply the recently developed immunosignature assay to spontaneous canine lymphoma as clinical proof-of-concept. Here we evaluate the immunosignature as a diagnostic for spontaneous canine lymphoma at both at initial diagnosis and evaluating the disease free interval following treatment.

Methods: Sera from dogs with confirmed lymphoma (B cell n = 38, T cell n = 11) and clinically normal dogs (n = 39) were analyzed. Serum antibody responses were characterized by analyzing the binding pattern, or immunosignature, of serum antibodies on a non-natural sequence peptide microarray. Peptides were selected and tested for the ability to distinguish healthy dogs from those with lymphoma and to distinguish lymphoma subtypes based on immunophenotype. The immunosignature of dogs with lymphoma were evaluated for individual signatures. Changes in the immunosignatures were evaluated following treatment and eventual relapse.

Results: Despite being a clonal disease, both an individual immunosignature and a generalized lymphoma immunosignature were observed in each dog. The general lymphoma immunosignature identified in the initial set of dogs (n = 32) was able to predict disease status in an independent set of dogs (n = 42, 97% accuracy). A separate immunosignature was able to distinguish the lymphoma based on immunophenotype (n = 25, 88% accuracy). The individual immunosignature was capable of confirming remission three months following diagnosis. Immunosignature at diagnosis was able to predict which dogs with B cell lymphoma would relapse in less than 120 days (n = 33, 97% accuracy).

Conclusion: We conclude that the immunosignature can serve as a multilevel diagnostic for canine, and potentially human, lymphoma.