ASU Scholarship Showcase

Shade plays an important role in designing pedestrian-friendly outdoor spaces in hot desert cities. This study investigates the impact of photovoltaic canopy shade and tree shade on thermal comfort through meteorological observations and field surveys at a pedestrian mall on Arizona State University's Tempe campus. During the course of 1 year, on selected clear calm days representative of each season, we conducted hourly meteorological transects from 7:00 a.m. to 6:00 p.m. and surveyed 1284 people about their thermal perception, comfort, and preferences. Shade lowered thermal sensation votes by approximately 1 point on a semantic differential 9-point scale, increasing thermal comfort in all seasons except winter. Shade type (tree or solar canopy) did not significantly impact perceived comfort, suggesting that artificial and natural shades are equally efficient in hot dry climates. Globe temperature explained 51 % of the variance in thermal sensation votes and was the only statistically significant meteorological predictor. Important non-meteorological factors included adaptation, thermal comfort vote, thermal preference, gender, season, and time of day. A regression of subjective thermal sensation on physiological equivalent temperature yielded a neutral temperature of 28.6 °C. The acceptable comfort range was 19.1 °C-38.1 °C with a preferred temperature of 20.8 °C. Respondents exposed to above neutral temperature felt more comfortable if they had been in air-conditioning 5 min prior to the survey, indicating a lagged response to outdoor conditions. Our study highlights the importance of active solar access management in hot urban areas to reduce thermal stress.

This study investigates the impact of urban form and landscaping type on the mid-afternoon microclimate in semi-arid Phoenix, Arizona. The goal is to find effective urban form and design strategies to ameliorate temperatures during the summer months. We simulated near-ground air temperatures for typical residential neighborhoods in Phoenix using the three-dimensional microclimate model ENVI-met. The model was validated using weather observations from the North Desert Village (NDV) landscape experiment, located on the Arizona State University's Polytechnic campus. The NDV is an ideal site to determine the model's input parameters, since it is a controlled environment recreating three prevailing residential landscape types in the Phoenix metropolitan area (mesic, oasis, and xeric). After validation, we designed five neighborhoods with different urban forms that represent a realistic cross-section of typical residential neighborhoods in Phoenix. The scenarios follow the Local Climate Zone (LCZ) classification scheme after Stewart and Oke. We then combined the neighborhoods with three landscape designs and, using ENVI-met, simulated microclimate conditions for these neighborhoods for a typical summer day. Results were analyzed in terms of mid-afternoon air temperature distribution and variation, ventilation, surface temperatures, and shading. Findings show that advection is important for the distribution of within-design temperatures and that spatial differences in cooling are strongly related to solar radiation and local shading patterns. In mid-afternoon, dense urban forms can create local cool islands. Our approach suggests that the LCZ concept is useful for planning and design purposes.

On-going efforts to understand the dynamics of coupled social-ecological (or more broadly, coupled infrastructure) systems and common pool resources have led to the generation of numerous datasets based on a large number of case studies. This data has facilitated the identification of important factors and fundamental principles which increase our understanding of such complex systems. However, the data at our disposal are often not easily comparable, have limited scope and scale, and are based on disparate underlying frameworks inhibiting synthesis, meta-analysis, and the validation of findings. Research efforts are further hampered when case inclusion criteria, variable definitions, coding schema, and inter-coder reliability testing are not made explicit in the presentation of research and shared among the research community. This paper first outlines challenges experienced by researchers engaged in a large-scale coding project; then highlights valuable lessons learned; and finally discusses opportunities for further research on comparative case study analysis focusing on social-ecological systems and common pool resources. Includes supplemental materials and appendices published in the International Journal of the Commons 2016 Special Issue. Volume 10 - Issue 2 - 2016.

Although insulin resistance in skeletal muscle is well-characterized, the role of circulating whole blood in the metabolic syndrome phenotype is not well understood. We set out to test the hypothesis that genes involved in inflammation, insulin signaling and mitochondrial function would be altered in expression in the whole blood of individuals with metabolic syndrome. We further wanted to examine whether similar relationships that we have found previously in skeletal muscle exist in peripheral whole blood cells. All subjects (n=184) were Latino descent from the Arizona Insulin Resistance registry. Subjects were classified based on the metabolic syndrome phenotype according to the National Cholesterol Education Program’s Adult Treatment Panel III. Of the 184 Latino subjects in the study, 74 were classified with the metabolic syndrome and 110 were without. Whole blood gene expression profiling was performed using the Agilent 4x44K Whole Human Genome Microarray. Whole blood microarray analysis identified 1,432 probes that were altered in expression ≥1.2 fold and P<0.05 after Benjamini-Hochberg in the metabolic syndrome subjects. KEGG pathway analysis revealed significant enrichment for pathways including ribosome, oxidative phosphorylation and MAPK signaling (all Benjamini-Hochberg P<0.05). Whole blood mRNA expression changes observed in the microarray data were confirmed by quantitative RT-PCR. Transcription factor binding motif enrichment analysis revealed E2F1, ELK1, NF-kappaB, STAT1 and STAT3 significantly enriched after Bonferroni correction (all P<0.05). The results of the present study demonstrate that whole blood is a useful tissue for studying the metabolic syndrome and its underlying insulin resistance although the relationship between blood and skeletal muscle differs.

At the end of the dark ages, anatomy was taught as though everything that could be known was known. Scholars learned about what had been discovered rather than how to make discoveries. This was true even though the body (and the rest of biology) was very poorly understood. The renaissance eventually brought a revolution in how scholars (and graduate students) were trained and worked. This revolution never occurred in K-12 or university education such that we now teach young students in much the way that scholars were taught in the dark ages, we teach them what is already known rather than the process of knowing. Citizen science offers a way to change K-12 and university education and, in doing so, complete the renaissance. Here we offer an example of such an approach and call for change in the way students are taught science, change that is more possible than it has ever been and is, nonetheless, five hundred years delayed.

The lack of lipidome analytical tools has limited our ability to gain new knowledge about lipid metabolism in microalgae, especially for membrane glycerolipids. An electrospray ionization mass spectrometry-based lipidomics method was developed for Nannochloropsis oceanica IMET1, which resolved 41 membrane glycerolipids molecular species belonging to eight classes. Changes in membrane glycerolipids under nitrogen deprivation and high-light (HL) conditions were uncovered. The results showed that the amount of plastidial membrane lipids including monogalactosyldiacylglycerol, phosphatidylglycerol, and the extraplastidic lipids diacylglyceryl-O-4′-(N, N, N,-trimethyl) homoserine and phosphatidylcholine decreased drastically under HL and nitrogen deprivation stresses. Algal cells accumulated considerably more digalactosyldiacylglycerol and sulfoquinovosyldiacylglycerols under stresses. The genes encoding enzymes responsible for biosynthesis, modification and degradation of glycerolipids were identified by mining a time-course global RNA-seq data set. It suggested that reduction in lipid contents under nitrogen deprivation is not attributable to the retarded biosynthesis processes, at least at the gene expression level, as most genes involved in their biosynthesis were unaffected by nitrogen supply, yet several genes were significantly up-regulated. Additionally, a conceptual eicosapentaenoic acid (EPA) biosynthesis network is proposed based on the lipidomic and transcriptomic data, which underlined import of EPA from cytosolic glycerolipids to the plastid for synthesizing EPA-containing chloroplast membrane lipids.

Background: Modern advances in sequencing technology have enabled the census of microbial members of many natural ecosystems. Recently, attention is increasingly being paid to the microbial residents of human-made, built ecosystems, both private (homes) and public (subways, office buildings, and hospitals). Here, we report results of the characterization of the microbial ecology of a singular built environment, the International Space Station (ISS). This ISS sampling involved the collection and microbial analysis (via 16S rRNA gene PCR) of 15 surfaces sampled by swabs onboard the ISS. This sampling was a component of Project MERCCURI (Microbial Ecology Research Combining Citizen and University Researchers on ISS). Learning more about the microbial inhabitants of the “buildings” in which we travel through space will take on increasing importance, as plans for human exploration continue, with the possibility of colonization of other planets and moons.

Results: Sterile swabs were used to sample 15 surfaces onboard the ISS. The sites sampled were designed to be analogous to samples collected for (1) the Wildlife of Our Homes project and (2) a study of cell phones and shoes that were concurrently being collected for another component of Project MERCCURI. Sequencing of the 16S rRNA genes amplified from DNA extracted from each swab was used to produce a census of the microbes present on each surface sampled. We compared the microbes found on the ISS swabs to those from both homes on Earth and data from the Human Microbiome Project.

Conclusions: While significantly different from homes on Earth and the Human Microbiome Project samples analyzed here, the microbial community composition on the ISS was more similar to home surfaces than to the human microbiome samples. The ISS surfaces are OTU-rich with 1,036–4,294 operational taxonomic units (OTUs per sample). There was no discernible biogeography of microbes on the 15 ISS surfaces, although this may be a reflection of the small sample size we were able to obtain.

Our previous studies show reduced abundance of the β-subunit of mitochondrial H+-ATP synthase (β-F1-ATPase) in skeletal muscle of obese individuals. The β-F1-ATPase forms the catalytic core of the ATP synthase, and it is critical for ATP production in muscle. The mechanism(s) impairing β-F1-ATPase metabolism in obesity, however, are not completely understood. First, we studied total muscle protein synthesis and the translation efficiency of β-F1-ATPase in obese (BMI, 36±1 kg/m²) and lean (BMI, 22±1 kg/m²) subjects. Both total protein synthesis (0.044±0.006 vs 0.066±0.006%·h^-1) and translation efficiency of β-F1-ATPase (0.0031±0.0007 vs 0.0073±0.0004) were lower in muscle from the obese subjects when compared to the lean controls (P<0.05). We then evaluated these same responses in a primary cell culture model, and tested the specific hypothesis that circulating non-esterified fatty acids (NEFA) in obesity play a role in the responses observed in humans. The findings on total protein synthesis and translation efficiency of β-F1-ATPase in primary myotubes cultured from a lean subject, and after exposure to NEFA extracted from serum of an obese subject, were similar to those obtained in humans. Among candidate microRNAs (i.e., non-coding RNAs regulating gene expression), we identified miR-127-5p in preventing the production of β-F1-ATPase. Muscle expression of miR-127-5p negatively correlated with β-F1-ATPase protein translation efficiency in humans (r = – 0.6744; P<0.01), and could be modeled in vitro by prolonged exposure of primary myotubes derived from the lean subject to NEFA extracted from the obese subject. On the other hand, locked nucleic acid inhibitor synthesized to target miR-127-5p significantly increased β-F1-ATPase translation efficiency in myotubes (0.6±0.1 vs 1.3±0.3, in control vs exposure to 50 nM inhibitor; P<0.05). Our experiments implicate circulating NEFA in obesity in suppressing muscle protein metabolism, and establish impaired β-F1-ATPase translation as an important consequence of obesity.

Online communities are becoming increasingly important as platforms for large-scale human cooperation. These communities allow users seeking and sharing professional skills to solve problems collaboratively. To investigate how users cooperate to complete a large number of knowledge-producing tasks, we analyze Stack Exchange, one of the largest question and answer systems in the world. We construct attention networks to model the growth of 110 communities in the Stack Exchange system and quantify individual answering strategies using the linking dynamics on attention networks. We identify two answering strategies. Strategy A aims at performing maintenance by doing simple tasks, whereas strategy B aims at investing time in doing challenging tasks. Both strategies are important: empirical evidence shows that strategy A decreases the median waiting time for answers and strategy B increases the acceptance rate of answers. In investigating the strategic persistence of users, we find that users tends to stick on the same strategy over time in a community, but switch from one strategy to the other across communities. This finding reveals the different sets of knowledge and skills between users. A balance between the population of users taking A and B strategies that approximates 2:1, is found to be optimal to the sustainable growth of communities.