ASU Scholarship Showcase

More has changed in journal publishing in the past twenty years than the previous four centuries. Digital technologies have transformed the submission, review, production and distribution of scholarly materials, with the result that there has been exponential growth in the number of papers published in an expanding roster of journals—some are mainstream, some highly specialized, some are produced by publishers who have existed since printing began and others are produced by small groups with niche interests.

Quiescin sulfhydryl oxidase 1 (QSOX1) is a highly conserved disulfide bond-generating enzyme that is overexpressed in diverse tumor types. Its enzymatic activity promotes the growth and invasion of tumor cells and alters extracellular matrix composition. In a nude mouse-human tumor xenograft model, tumors containing shRNA for QSOX1 grew significantly more slowly than controls, suggesting that QSOX1 supports a proliferative phenotype in vivo. High throughput screening experiments identified ebselen as an in vitro inhibitor of QSOX1 enzymatic activity. Ebselen treatment of pancreatic and renal cancer cell lines stalled tumor growth and inhibited invasion through Matrigel in vitro. Daily oral treatment with ebselen resulted in a 58% reduction in tumor growth in mice bearing human pancreatic tumor xenografts compared to controls. Mass spectrometric analysis of ebselen-treated QSOX1 mechanistically revealed that C165 and C237 of QSOX1 covalently bound to ebselen. This report details the anti-neoplastic properties of ebselen in pancreatic and renal cancer cell lines. The results here offer a “proof-of-principle” that enzymatic inhibition of QSOX1 may have clinical relevancy.

In order to determine the feasibility of utilizing novel rexinoids for chemotherapeutics and as potential treatments for neurological conditions, we undertook an assessment of the side effect profile of select rexinoid X receptor (RXR) analogs that we reported previously. We assessed pharmacokinetic profiles, lipid and thyroid-stimulating hormone (TSH) levels in rats, and cell culture activity of rexinoids in sterol regulatory element-binding protein (SREBP) induction and thyroid hormone inhibition assays. We also performed RNA sequencing of the brain tissues of rats that had been dosed with the compounds. We show here for the first time that potent rexinoid activity can be uncoupled from drastic lipid changes and thyroid axis variations, and we propose that rexinoids can be developed with improved side effect profiles than the parent compound, bexarotene (1).

Given species inventories of all sites in a planning area, integer programming or heuristic algorithms can prioritize sites in terms of the site's complementary value, that is, the ability of the site to complement (add unrepresented species to) other sites prioritized for conservation. The utility of these procedures is limited because distributions of species are typically available only as coarse atlases or range maps, whereas conservation planners need to prioritize relatively small sites. If such coarse-resolution information can be used to identify small sites that efficiently represent species (i.e., downscaled), then such data can be useful for conservation planning. We develop and test a new type of surrogate for biodiversity, which we call downscaled complementarity. In this approach, complementarity values from large cells are downscaled to small cells, using statistical methods or simple map overlays. We illustrate our approach for birds in Spain by building models at coarse scale (50 × 50 km atlas of European birds, and global range maps of birds interpreted at the same 50 × 50 km grid size), using this model to predict complementary value for 10 × 10 km cells in Spain, and testing how well-prioritized cells represented bird distributions in an independent bird atlas of those 10 × 10 km cells. Downscaled complementarity was about 63–77% as effective as having full knowledge of the 10-km atlas data in its ability to improve on random selection of sites. Downscaled complementarity has relatively low data acquisition cost and meets representation goals well compared with other surrogates currently in use. Our study justifies additional tests to determine whether downscaled complementarity is an effective surrogate for other regions and taxa, and at spatial resolution finer than 10 × 10 km cells. Until such tests have been completed, we caution against assuming that any surrogate can reliably prioritize sites for species representation.

Lack of biodiversity data is a major impediment to prioritizing sites for species representation. Because comprehensive species data are not available in any planning area, planners often use surrogates (such as vegetation communities, or mapped occurrences of a well-inventoried taxon) to prioritize sites. We propose and demonstrate the effectiveness of predicted rarity-weighted richness (PRWR) as a surrogate in situations where species inventories may be available for a portion of the planning area. Use of PRWR as a surrogate involves several steps. First, rarity-weighted richness (RWR) is calculated from species inventories for a q% subset of sites. Then random forest models are used to model RWR as a function of freely available environmental variables for that q% subset. This function is then used to calculate PRWR for all sites (including those for which no species inventories are available), and PRWR is used to prioritize all sites. We tested PRWR on plant and bird datasets, using the species accumulation index to measure efficiency of PRWR. Sites with the highest PRWR represented species with median efficiency of 56% (range 32%–77% across six datasets) when q = 20%, and with median efficiency of 39% (range 20%–63%) when q = 10%. An efficiency of 56% means that selecting sites in order of PRWR rank was 56% as effective as having full knowledge of species distributions in PRWR's ability to improve on the number of species represented in the same number of randomly selected sites. Our results suggest that PRWR may be able to help prioritize sites to represent species if a planner has species inventories for 10%–20% of the sites in the planning area.

MALDI-TOF MS profiling has been shown to be a rapid and reliable method to characterize pure cultures of bacteria. Currently, there is keen interest in using this technique to identify bacteria in mixtures. Promising results have been reported with two- or three-isolate model systems using biomarker-based approaches. In this work, we applied MALDI-TOF MS-based methods to a more complex model mixture containing six bacteria. We employed: 1) a biomarker-based approach that has previously been shown to be useful in identification of individual bacteria in pure cultures and simple mixtures and 2) a similarity coefficient-based approach that is routinely and nearly exclusively applied to identification of individual bacteria in pure cultures. Both strategies were developed and evaluated using blind-coded mixtures. With regard to the biomarker-based approach, results showed that most peaks in mixture spectra could be assigned to those found in spectra of each component bacterium; however, peaks shared by two isolates as well as peaks that could not be assigned to any individual component isolate were observed. For two-isolate blind-coded samples, bacteria were correctly identified using both similarity coefficient- and biomarker-based strategies, while for blind-coded samples containing more than two isolates, bacteria were more effectively identified using a biomarker-based strategy.

S-cysteinylated albumin and methionine-oxidized apolipoprotein A-I (apoA-I) have been posed as candidate markers of diseases associated with oxidative stress. Here, a dilute-and-shoot form of LC–electrospray ionization–MS requiring half a microliter of blood plasma was employed to simultaneously quantify the relative abundance of these oxidized proteoforms in samples stored at −80 °C, −20 °C, and room temperature and exposed to multiple freeze-thaw cycles and other adverse conditions in order to assess the possibility that protein oxidation may occur as a result of poor sample storage or handling. Samples from a healthy donor and a participant with poorly controlled type 2 diabetes started at the same low level of protein oxidation and behaved similarly; significant increases in albumin oxidation via S-cysteinylation were found to occur within hours at room temperature and days at −20 °C. Methionine oxidation of apoA-I took place on a longer time scale, setting in after albumin oxidation reached a plateau. Freeze–thaw cycles had a minimal effect on protein oxidation. In matched collections, protein oxidation in serum was the same as that in plasma. Albumin and apoA-I oxidation were not affected by sample headspace or the degree to which vials were sealed. ApoA-I, however, was unexpectedly found to oxidize faster in samples with lower surface-area-to-volume ratios. An initial survey of samples from patients with inflammatory conditions normally associated with elevated oxidative stress-including acute myocardial infarction and prostate cancer—demonstrated a lack of detectable apoA-I oxidation. Albumin S-cysteinylation in these samples was consistent with known but relatively brief exposures to temperatures above −30 °C (the freezing point of blood plasma). Given their properties and ease of analysis, these oxidized proteoforms, once fully validated, may represent the first markers of blood plasma specimen integrity based on direct measurement of oxidative molecular damage that can occur under suboptimal storage conditions.

Background: Many studies used the older ActiGraph (7164) for physical activity measurement, but this model has been replaced with newer ones (e.g., GT3X+). The assumption that new generation models are more accurate has been questioned, especially for measuring lower intensity levels. The low-frequency extension (LFE) increases the low-intensity sensitivity of newer models, but its comparability with older models is unknown. This study compared step counts and physical activity collected with the 7164 and GT3X + using the Normal Filter and the LFE (GT3X+N and GT3X+LFE, respectively).

Findings: Twenty-five adults wore 2 accelerometer models simultaneously for 3Âdays and were instructed to engage in typical behaviors. Average daily step counts and minutes per day in nonwear, sedentary, light, moderate, and vigorous activity were calculated. Repeated measures ANOVAs with post-hoc pairwise comparisons were used to compare mean values. Means for the GT3X+N and 7164 were significantly different in 4 of the 6 categories (p < .05). The GT3X+N showed 2041 fewer steps per day and more sedentary, less light, and less moderate than the 7164 (+25.6, -31.2, -2.9 mins/day, respectively). The GT3X+LFE showed non-significant differences in 5 of 6 categories but recorded significantly more steps (+3597 steps/day; p < .001) than the 7164.

Conclusion: Studies using the newer ActiGraphs should employ the LFE for greater sensitivity to lower intensity activity and more comparable activity results with studies using the older models. Newer generation ActiGraphs do not produce comparable step counts to the older generation devices with the Normal filter or the LFE.

Students often self-identify as visual learners and prefer to engage with a topic in an active, hands-on way. Indeed, much research has shown that students who actively engage with the material and are engrossed in the topics retain concepts better than students who are passive receivers of information. However, much of learning life science concepts is still driven by books and static pictures. One concept students have a hard time grasping is how a linear chain of amino acids folds to becomes a 3D protein structure. Adding three dimensional activities to the topic of protein structure and function should allow for a deeper understanding of the primary, secondary, tertiary, and quaternary structure of proteins and how proteins function in a cell. Here, I review protein folding activities and describe using Apps and 3D visualization to enhance student understanding of protein structure.

I teach an upper-level writing course, Genes, Race, Gender, and Society, designed for Life Science majors, in which I utilize a case study to expose students to ethical ways of thinking. Students first work through the topical case study and then are challenged to rethink their responses through the lenses of ethics, taking into account different ethical frameworks. Students then develop their own case study, integrating ethical components. I want to expose my students to this way of thinking because I see technology being driven by the Jurassic Park phenomenon, “Your scientists were so preoccupied with whether or not they could, they didn’t stop to think if they should,” and want future physicians grounded in a sense of how their actions relate to the greater good.