ASU Scholarship Showcase

In this synthesis, we hope to accomplish two things: 1) reflect on how the analysis of the new archaeological cases presented in this special feature adds to previous case studies by revisiting a set of propositions reported in a 2006 special feature, and 2) reflect on four main ideas that are more specific to the archaeological cases: i) societal choices are influenced by robustness–vulnerability trade-offs, ii) there is interplay between robustness–vulnerability trade-offs and robustness–performance trade-offs, iii) societies often get locked in to particular strategies, and iv) multiple positive feedbacks escalate the perceived cost of societal change. We then discuss whether these lock-in traps can be prevented or whether the risks associated with them can be mitigated. We conclude by highlighting how these long-term historical studies can help us to understand current society, societal practices, and the nexus between ecology and society.

As part of an international collaboration to compare large-scale commons, we used the Social-Ecological Systems Meta-Analysis Database (SESMAD) to systematically map out attributes of and changes in the Great Barrier Reef Marine Park (GBRMP) in Australia. We focus on eight design principles from common-pool resource (CPR) theory and other key social-ecological systems governance variables, and explore to what extent they help explain the social and ecological outcomes of park management through time. Our analysis showed that commercial fisheries management and the re-zoning of the GBRMP in 2004 led to improvements in ecological condition of the reef, particularly fisheries. These boundary and rights changes were supported by effective monitoring, sanctioning and conflict resolution. Moderate biophysical connectivity was also important for improved outcomes. However, our analysis also highlighted that continued challenges to improved ecological health in terms of coral cover and biodiversity can be explained by fuzzy boundaries between land and sea, and the significance of external drivers to even large-scale social-ecological systems (SES). While ecological and institutional fit in the marine SES was high, this was not the case when considering the coastal SES. Nested governance arrangements become even more important at this larger scale. To our knowledge, our paper provides the first analysis linking the re-zoning of the GBRMP to CPR and SES theory. We discuss important challenges to coding large-scale systems for meta-analysis.

The Montreal Protocol is generally credited as a successful example of international cooperation in response to a global environmental problem. As a result, the production and consumption of ozone-depleting substances has declined rapidly, and it is expected that atmospheric ozone concentrations will return to their normal ranges toward the end of this century. This paper applies the social-ecological system framework and common-pool resource theory to explore the congruence between successful resolution of small-scale appropriation problems and ozone regulation, a large-scale pollution problem. The results of our analysis correspond closely to past studies of the Protocol that highlight the importance of attributes such as a limited number of major industrial producers, advances in scientific knowledge, and the availability of technological substitutes. However, in contrast to previous theoretical accounts that focus on one or a few variables, our analysis suggests that its success may have been the result of interactions between a wider range of SES attributes, many of which are associated with successful small-scale environmental governance. Although carefully noting the limitations of drawing conclusions from the analysis of a single case, our analysis reveals the potential for fruitful interplay between common-pool resource theory and large-scale pollution problems.

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.

The purpose of the United Nations-guided process to establish Sustainable Development Goals is to galvanize governments and civil society to rise to the interlinked environmental, societal, and economic challenges we face in the Anthropocene. We argue that the process of setting Sustainable Development Goals should take three key aspects into consideration. First, it should embrace an integrated social-ecological system perspective and acknowledge the key dynamics that such systems entail, including the role of ecosystems in sustaining human wellbeing, multiple cross-scale interactions, and uncertain thresholds. Second, the process needs to address trade-offs between the ambition of goals and the feasibility in reaching them, recognizing biophysical, social, and political constraints. Third, the goal-setting exercise and the management of goal implementation need to be guided by existing knowledge about the principles, dynamics, and constraints of social change processes at all scales, from the individual to the global. Combining these three aspects will increase the chances of establishing and achieving effective Sustainable Development Goals.

Over the past couple of decades, quality has been an area of increased focus. Multiple models and approaches have been proposed to measure the quality in the construction industry. This paper focuses on determining the quality of one of the types of roofing systems used in the construction industry, i.e., sprayed polyurethane foam roofs (SPF roofs). Thirty-seven urethane-coated SPF roofs that were installed in 2005/2006 were visually inspected to measure the percentage of blisters and repairs three times over a period of four years, six years, and seven years. A repairing criteria was established after a six-year mark based on the data that were reported to contractors as vulnerable roofs. Furthermore, the relation between four possible contributing time-of-installation factors—contractor, demographics, season, and difficulty (number of penetrations and size of the roof in square feet) that could affect the quality of the roof was determined. Demographics and difficulty did not affect the quality of the roofs, whereas the contractor and the season when the roof was installed did affect the quality of the roofs.

Antigen-antibody complexes are central players in an effective immune response. However, finding those interactions relevant to a particular disease state can be arduous. Nonetheless many paths to discovery have been explored since deciphering these interactions can greatly facilitate the development of new diagnostics, therapeutics, and vaccines. In silico B cell epitope mapping approaches have been widely pursued, though success has not been consistent. Antibody mixtures in immune sera have been used as handles for biologically relevant antigens, but these and other experimental approaches have proven resource intensive and time consuming. In addition, these methods are often tailored to individual diseases or a specific proteome, rather than providing a universal platform. Most of these methods are not able to identify the specific antibody’s epitopes from unknown antigens, such as un-annotated neo antigens in cancer. Alternatively, a peptide library comprised of sequences unrestricted by naturally-found protein space provides for a universal search for mimotopes of an antibody’s epitope. Here we present the utility of such a non-natural random sequence library of 10,000 peptides physically addressed on a microarray for mimotope discovery without sequence information of the specific antigen. The peptide arrays were probed with serum from an antigen-immunized rabbit, or alternatively probed with serum pre-absorbed with the same immunizing antigen. With this positive and negative screening scheme, we identified the library-peptides as the mimotopes of the antigen. The unique library peptides were successfully used to isolate antigen-specific antibodies from complete immune serum. Sequence analysis of these peptides revealed the epitopes in the immunized antigen. We present this method as an inexpensive, efficient method for identifying mimotopes of any antibody’s targets. These mimotopes should be useful in defining both components of the antigen-antibody complex.

Background: The success of new sequencing technologies and informatic methods for identifying genes has made establishing gene product function a critical rate limiting step in progressing the molecular sciences. We present a method to functionally mine genomes for useful activities in vivo, using an unusual property of a member of the poxvirus family to demonstrate this screening approach.

Results: The genome of Parapoxvirus ovis (Orf virus) was sequenced, annotated, and then used to PCR-amplify its open-reading-frames. Employing a cloning-independent protocol, a viral expression-library was rapidly built and arrayed into sub-library pools. These were directly delivered into mice as expressible cassettes and assayed for an immune-modulating activity associated with parapoxvirus infection. The product of the B2L gene, a homolog of vaccinia F13L, was identified as the factor eliciting immune cell accumulation at sites of skin inoculation. Administration of purified B2 protein also elicited immune cell accumulation activity, and additionally was found to serve as an adjuvant for antigen-specific responses. Co-delivery of the B2L gene with an influenza gene-vaccine significantly improved protection in mice. Furthermore, delivery of the B2L expression construct, without antigen, non-specifically reduced tumor growth in murine models of cancer.

Conclusion: A streamlined, functional approach to genome-wide screening of a biological activity in vivo is presented. Its application to screening in mice for an immune activity elicited by the pathogen genome of Parapoxvirus ovis yielded a novel immunomodulator. In this inverted discovery method, it was possible to identify the adjuvant responsible for a function of interest prior to a mechanistic study of the adjuvant. The non-specific immune activity of this modulator, B2, is similar to that associated with administration of inactivated particles to a host or to a live viral infection. Administration of B2 may provide the opportunity to significantly impact host immunity while being itself only weakly recognized. The functional genomics method used to pinpoint B2 within an ORFeome may be more broadly applicable to screening for other biological activities in an animal.

Background: Immunosignaturing is a new peptide microarray based technology for profiling of humoral immune responses. Despite new challenges, immunosignaturing gives us the opportunity to explore new and fundamentally different research questions. In addition to classifying samples based on disease status, the complex patterns and latent factors underlying immunosignatures, which we attempt to model, may have a diverse range of applications.

Methods: We investigate the utility of a number of statistical methods to determine model performance and address challenges inherent in analyzing immunosignatures. Some of these methods include exploratory and confirmatory factor analyses, classical significance testing, structural equation and mixture modeling.

Results: We demonstrate an ability to classify samples based on disease status and show that immunosignaturing is a very promising technology for screening and presymptomatic screening of disease. In addition, we are able to model complex patterns and latent factors underlying immunosignatures. These latent factors may serve as biomarkers for disease and may play a key role in a bioinformatic method for antibody discovery.

Conclusion: Based on this research, we lay out an analytic framework illustrating how immunosignatures may be useful as a general method for screening and presymptomatic screening of disease as well as antibody discovery.

Background: High-throughput technologies such as DNA, RNA, protein, antibody and peptide microarrays are often used to examine differences across drug treatments, diseases, transgenic animals, and others. Typically one trains a classification system by gathering large amounts of probe-level data, selecting informative features, and classifies test samples using a small number of features. As new microarrays are invented, classification systems that worked well for other array types may not be ideal. Expression microarrays, arguably one of the most prevalent array types, have been used for years to help develop classification algorithms. Many biological assumptions are built into classifiers that were designed for these types of data. One of the more problematic is the assumption of independence, both at the probe level and again at the biological level. Probes for RNA transcripts are designed to bind single transcripts. At the biological level, many genes have dependencies across transcriptional pathways where co-regulation of transcriptional units may make many genes appear as being completely dependent. Thus, algorithms that perform well for gene expression data may not be suitable when other technologies with different binding characteristics exist. The immunosignaturing microarray is based on complex mixtures of antibodies binding to arrays of random sequence peptides. It relies on many-to-many binding of antibodies to the random sequence peptides. Each peptide can bind multiple antibodies and each antibody can bind multiple peptides. This technology has been shown to be highly reproducible and appears promising for diagnosing a variety of disease states. However, it is not clear what is the optimal classification algorithm for analyzing this new type of data.

Results: We characterized several classification algorithms to analyze immunosignaturing data. We selected several datasets that range from easy to difficult to classify, from simple monoclonal binding to complex binding patterns in asthma patients. We then classified the biological samples using 17 different classification algorithms. Using a wide variety of assessment criteria, we found ‘Naïve Bayes’ far more useful than other widely used methods due to its simplicity, robustness, speed and accuracy.

Conclusions: ‘Naïve Bayes’ algorithm appears to accommodate the complex patterns hidden within multilayered immunosignaturing microarray data due to its fundamental mathematical properties.