ASU Scholarship Showcase

Biomarkers encompass a wide range of different measurable indicators, representing a tangible link to physiological changes occurring within the body. Accessibility, sensitivity, and specificity are significant factors in biomarker suitability. New biomarkers continue to be discovered, and questions over appropriate selection and assessment of their usefulness remain. If traditional markers of inflammation are not sufficiently robust in their specificity, then perhaps alternative means of detection may provide more information. Epigenetic drift (epigenetic modifications as they occur as a direct function with age), and its ancillary elements, including platelets, secreted microvesicles (MVs), and microRNA (miRNA), may hold enormous predictive potential. The majority of epigenetic drift observed in blood is independent of variations in blood cell composition, addressing concerns affecting traditional blood-based biomarker efficacy. MVs are found in plasma and other biological fluids in healthy individuals. Altered MV/miRNA profiles may also be found in individuals with various diseases. Platelets are also highly reflective of physiological and lifestyle changes, making them extremely sensitive biomarkers of human health. Platelets release increased levels of MVs in response to various stimuli and under a plethora of disease states, which demonstrate a functional effect on other cell types.

Cancer therapy selects for cancer cells resistant to treatment, a process that is fundamentally evolutionary. To what extent, however, is the evolutionary perspective employed in research on therapeutic resistance and relapse? We analyzed 6,228 papers on therapeutic resistance and/or relapse in cancers and found that the use of evolution terms in abstracts has remained at about 1% since the 1980s. However, detailed coding of 22 recent papers revealed a higher proportion of papers using evolutionary methods or evolutionary theory, although this number is still less than 10%. Despite the fact that relapse and therapeutic resistance is essentially an evolutionary process, it appears that this framework has not permeated research. This represents an unrealized opportunity for advances in research on therapeutic resistance.

The urban heat island (UHI) phenomenon is a significant worldwide problem caused by rapid population growth and associated urbanization. The UHI effect exacerbates heat waves during the summer, increases energy and water consumption, and causes the high risk of heat-related morbidity and mortality. UHI mitigation efforts have increasingly relied on wisely designing the urban residential environment such as using high albedo rooftops, green rooftops, and planting trees and shrubs to provide canopy coverage and shading. Thus, strategically designed residential rooftops and their surrounding landscaping have the potential to translate into significant energy, long-term cost savings, and health benefits. Rooftop albedo, material, color, area, slope, height, aspect and nearby landscaping are factors that potentially contribute. To extract, derive, and analyze these rooftop parameters and outdoor landscaping information, high resolution optical satellite imagery, LIDAR (light detection and ranging) point clouds and thermal imagery are necessary. Using data from the City of Tempe AZ (a 2010 population of 160,000 people), we extracted residential rooftop footprints and rooftop configuration parameters from airborne LIDAR point clouds and QuickBird satellite imagery (2.4 m spatial resolution imagery). Those parameters were analyzed against surface temperature data from the MODIS/ASTER airborne simulator (MASTER). MASTER images provided fine resolution (7 m) surface temperature data for residential areas during daytime and night time. Utilizing these data, ordinary least squares (OLS) regression was used to evaluate the relationships between residential building rooftops and their surface temperature in urban environment. The results showed that daytime rooftop temperature was closely related to rooftop spectral attributes, aspect, slope, and surrounding trees. Night time temperature was only influenced by rooftop spectral attributes and slope.

This study examines the spatial and temporal patterns of the surface urban heat island (SUHI) intensity in the Phoenix metropolitan area and the relationship with land use land cover (LULC) change between 2000 and 2014. The objective is to identify specific regions in Phoenix that have been increasingly heated and cooled to further understand how LULC change influences the SUHI intensity. The data employed include MODerate-resolution Imaging Spectroradiometer (MODIS) land surface temperature (LST) 8-day composite June imagery, and classified LULC maps generated using 2000 and 2014 Landsat imagery. Results show that the regions that experienced the most significant LST changes during the study period are primarily on the outskirts of the Phoenix metropolitan area for both daytime and nighttime. The conversion to urban, residential, and impervious surfaces from all other LULC types has been identified as the primary cause of the UHI effect in Phoenix. Vegetation cover has been shown to significantly lower LST for both daytime and nighttime due to its strong cooling effect by producing more latent heat flux and less sensible heat flux. We suggest that urban planners, decision-makers, and city managers formulate new policies and regulations that encourage residential, commercial, and industrial developers to include more vegetation when planning new construction.

This paper reviews how remotely sensed data have been used to understand the impact of urbanization on global environmental change. We describe how these studies can support the policy and science communities’ increasing need for detailed and up-to-date information on the multiple dimensions of cities, including their social, biological, physical, and infrastructural characteristics. Because the interactions between urban and surrounding areas are complex, a synoptic and spatial view offered from remote sensing is integral to measuring, modeling, and understanding these relationships. Here we focus on three themes in urban remote sensing science: mapping, indices, and modeling. For mapping we describe the data sources, methods, and limitations of mapping urban boundaries, land use and land cover, population, temperature, and air quality. Second, we described how spectral information is manipulated to create comparative biophysical, social, and spatial indices of the urban environment. Finally, we focus how the mapped information and indices are used as inputs or parameters in models that measure changes in climate, hydrology, land use, and economics.

Background: Medical and public health scientists are using evolution to devise new strategies to solve major health problems. But based on a 2003 survey, medical curricula may not adequately prepare physicians to evaluate and extend these advances. This study assessed the change in coverage of evolution in North American medical schools since 2003 and identified opportunities for enriching medical education.

Methods: In 2013, curriculum deans for all North American medical schools were invited to rate curricular coverage and perceived importance of 12 core principles, the extent of anticipated controversy from adding evolution, and the usefulness of 13 teaching resources. Differences between schools were assessed by Pearson’s chi-square test, Student’s t-test, and Spearman’s correlation. Open-ended questions sought insight into perceived barriers and benefits.

Results: Despite repeated follow-up, 60 schools (39%) responded to the survey. There was no evidence of sample bias. The three evolutionary principles rated most important were antibiotic resistance, environmental mismatch, and somatic selection in cancer. While importance and coverage of principles were correlated (r = 0.76, P < 0.01), coverage (at least moderate) lagged behind importance (at least moderate) by an average of 21% (SD = 6%). Compared to 2003, a range of evolutionary principles were covered by 4 to 74% more schools. Nearly half (48%) of responders anticipated igniting controversy at their medical school if they added evolution to their curriculum. The teaching resources ranked most useful were model test questions and answers, case studies, and model curricula for existing courses/rotations. Limited resources (faculty expertise) were cited as the major barrier to adding more evolution, but benefits included a deeper understanding and improved patient care.

Conclusion: North American medical schools have increased the evolution content in their curricula over the past decade. However, coverage is not commensurate with importance. At a few medical schools, anticipated controversy impedes teaching more evolution. Efforts to improve evolution education in medical schools should be directed toward boosting faculty expertise and crafting resources that can be easily integrated into existing curricula.

Deforestation in Myanmar has recently attracted much attention worldwide. This study examined spatio-temporal patterns of deforestation and forest carbon flux in Myanmar from 2001 to 2010 and environmental impacts at the regional scale using land products of the Moderate Resolution Imaging Spectroradiometer (MODIS). The results suggest that the total deforestation area in Myanmar was 21,178.8 km², with an annual deforestation rate of 0.81%, and that the total forest carbon release was 20.06 million tons, with an annual rate of 0.37%. Mangrove forests had the highest deforestation and carbon release rates, and deciduous forests had both the largest deforestation area and largest amount of carbon release. During the study period, the south and southwestern regions of Myanmar, especially Ayeyarwady and Rakhine, were deforestation hotspots (i.e., the highest deforestation and carbon release rates occurred in these regions). Deforestation caused significant carbon release, reduced evapotranspiration (ET), and increased land surface temperatures (LSTs) in deforested areas in Myanmar during the study period. Constructive policy recommendations are put forward based on these research results.

Land-use mapping is critical for global change research. In Central Arizona, U.S.A., the spatial distribution of land use is important for sustainable land management decisions. The objective of this study was to create a land-use map that serves as a model for the city of Maricopa, an expanding urban region in the Sun Corridor of Arizona. We use object-based image analysis to map six land-use types from ASTER imagery, and then compare this with two per-pixel classifications. Our results show that a single segmentation, combined with intermediary classifications and merging, morphing, and growing image-objects, can lead to an accurate land-use map that is capable of utilizing both spatial and spectral information. We also employ a moving-window diversity assessment to help with analysis and improve post-classification modifications.

Background: Lizards are evolutionarily the most closely related vertebrates to humans that can lose and regrow an entire appendage. Regeneration in lizards involves differential expression of hundreds of genes that regulate wound healing, musculoskeletal development, hormonal response, and embryonic morphogenesis. While microRNAs are able to regulate large groups of genes, their role in lizard regeneration has not been investigated.

Results: MicroRNA sequencing of green anole lizard (Anolis carolinensis) regenerating tail and associated tissues revealed 350 putative novel and 196 known microRNA precursors. Eleven microRNAs were differentially expressed between the regenerating tail tip and base during maximum outgrowth (25 days post autotomy), including miR-133a, miR-133b, and miR-206, which have been reported to regulate regeneration and stem cell proliferation in other model systems. Three putative novel differentially expressed microRNAs were identified in the regenerating tail tip.

Conclusions: Differentially expressed microRNAs were identified in the regenerating lizard tail, including known regulators of stem cell proliferation. The identification of 3 putative novel microRNAs suggests that regulatory networks, either conserved in vertebrates and previously uncharacterized or specific to lizards, are involved in regeneration. These findings suggest that differential regulation of microRNAs may play a role in coordinating the timing and expression of hundreds of genes involved in regeneration.

Introduction: Abundance of immune cells has been shown to have prognostic and predictive significance in many tumor types. Beyond abundance, the spatial organization of immune cells in relation to cancer cells may also have significant functional and clinical implications. However there is a lack of systematic methods to quantify spatial associations between immune and cancer cells.

Methods: We applied ecological measures of species interactions to digital pathology images for investigating the spatial associations of immune and cancer cells in breast cancer. We used the Morisita-Horn similarity index, an ecological measure of community structure and predator–prey interactions, to quantify the extent to which cancer cells and immune cells colocalize in whole-tumor histology sections. We related this index to disease-specific survival of 486 women with breast cancer and validated our findings in a set of 516 patients from different hospitals.

Results: Colocalization of immune cells with cancer cells was significantly associated with a disease-specific survival benefit for all breast cancers combined. In HER2-positive subtypes, the prognostic value of immune-cancer cell colocalization was highly significant and exceeded those of known clinical variables. Furthermore, colocalization was a significant predictive factor for long-term outcome following chemotherapy and radiotherapy in HER2 and Luminal A subtypes, independent of and stronger than all known clinical variables.

Conclusions: Our study demonstrates how ecological methods applied to the tumor microenvironment using routine histology can provide reproducible, quantitative biomarkers for identifying high-risk breast cancer patients. We found that the clinical value of immune-cancer interaction patterns is highly subtype-specific but substantial and independent to known clinicopathologic variables that mostly focused on cancer itself. Our approach can be developed into computer-assisted prediction based on histology samples that are already routinely collected.