ASU Scholarship Showcase

Attitudes and habits are extremely resistant to change, but a disruption of the magnitude of the COVID-19 pandemic has the potential to bring long-term, massive societal changes. During the pandemic, people are being compelled to experience new ways of interacting, working, learning, shopping, traveling, and eating meals. Going forward, a critical question is whether these experiences will result in changed behaviors and preferences in the long term. This paper presents initial findings on the likelihood of long-term changes in telework, daily travel, restaurant patronage, and air travel based on survey data collected from adults in the United States in Spring 2020. These data suggest that a sizable fraction of the increase in telework and decreases in both business air travel and restaurant patronage are likely here to stay. As for daily travel modes, public transit may not fully recover its pre-pandemic ridership levels, but many of our respondents are planning to bike and walk more than they used to. These data reflect the responses of a sample that is higher income and more highly educated than the US population. The response of these particular groups to the COVID-19 pandemic is perhaps especially important to understand, however, because their consumption patterns give them a large influence on many sectors of the economy.

Cities in the Global South face rapid urbanization challenges and often suffer an acute lack of infrastructure and governance capacities. Smart Cities Mission, in India, launched in 2015, aims to offer a novel approach for urban renewal of 100 cities following an area‐based development approach, where the use of ICT and digital technologies is particularly emphasized. This article presents a critical review of the design and implementation framework of this new urban renewal program across selected case‐study cities. The article examines the claims of the so‐called “smart cities” against actual urban transformation on‐ground and evaluates how “inclusive” and “sustainable” these developments are. We quantify the scale and coverage of the smart city urban renewal projects in the cities to highlight who the program includes and excludes. The article also presents a statistical analysis of the sectoral focus and budgetary allocations of the projects under the Smart Cities Mission to find an inherent bias in these smart city initiatives in terms of which types of development they promote and the ones it ignores. The findings indicate that a predominant emphasis on digital urban renewal of selected precincts and enclaves, branded as “smart cities,” leads to deepening social polarization and gentrification. The article offers crucial urban planning lessons for designing ICT‐driven urban renewal projects, while addressing critical questions around inclusion and sustainability in smart city ventures.`

The number and variety of connectivity estimation methods is likely to continue to grow over the coming decade. Comparisons between methods are necessary to prune this growth to only the most accurate and robust methods. However, the nature of connectivity is elusive with different methods potentially attempting to identify different aspects of connectivity. Commonalities of connectivity definitions across methods upon which base direct comparisons can be difficult to derive. Here, we explicitly define “effective connectivity” using a common set of observation and state equations that are appropriate for three connectivity methods: dynamic causal modeling (DCM), multivariate autoregressive modeling (MAR), and switching linear dynamic systems for fMRI (sLDSf). In addition while deriving this set, we show how many other popular functional and effective connectivity methods are actually simplifications of these equations. We discuss implications of these connections for the practice of using one method to simulate data for another method. After mathematically connecting the three effective connectivity methods, simulated fMRI data with varying numbers of regions and task conditions is generated from the common equation. This simulated data explicitly contains the type of the connectivity that the three models were intended to identify. Each method is applied to the simulated data sets and the accuracy of parameter identification is analyzed. All methods perform above chance levels at identifying correct connectivity parameters. The sLDSf method was superior in parameter estimation accuracy to both DCM and MAR for all types of comparisons.

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.

Accessibility is increasingly used as a metric when evaluating changes to public transport systems. Transit travel times contain variation depending on when one departs relative to when a transit vehicle arrives, and how well transfers are coordinated given a particular timetable. In addition, there is necessarily uncertainty in the value of the accessibility metric during sketch planning processes, due to scenarios which are underspecified because detailed schedule information is not yet available. This article presents a method to extend the concept of "reliable" accessibility to transit to address the first issue, and create confidence intervals and hypothesis tests to address the second.

There is a need for indicators of transportation-land use system quality that are understandable to a wide range of stakeholders, and which can provide immediate feedback on the quality of interactively designed scenarios. Location-based accessibility indicators are promising candidates, but indicator values can vary strongly depending on time of day and transfer wait times. Capturing this variation increases complexity, slowing down calculations. We present new methods for rapid yet rigorous computation of accessibility metrics, allowing immediate feedback during early-stage transit planning, while being rigorous enough for final analyses. Our approach is statistical, characterizing the uncertainty and variability in accessibility metrics due to differences in departure time and headway-based scenario specification. The analysis is carried out on a detailed multi-modal network model including both public transportation and streets. Land use data are represented at high resolution. These methods have been implemented as open-source software running on commodity cloud infrastructure. Networks are constructed from standard open data sources, and scenarios are built in a map-based web interface. We conclude with a case study, describing how these methods were applied in a long-term transportation planning process for metropolitan Amsterdam.

Background: Carriers of the APOE ε4 allele are at increased risk of developing Alzheimer’s disease (AD), and have been shown to have reduced cerebral metabolic rate of glucose (CMRgl) in the same brain areas frequently affected in AD. These individuals also exhibit reduced plasma levels of apolipoprotein E (apoE) attributed to a specific decrease in the apoE4 isoform as determined by quantification of individual apoE isoforms in APOE ε4 heterozygotes. Whether low plasma apoE levels are associated with structural and functional brain measurements and cognitive performance remains to be investigated.

Methods: Using quantitative mass spectrometry we quantified the plasma levels of total apoE and the individual apoE3 and apoE4 isoforms in 128 cognitively normal APOE ε3/ε4 individuals included in the Arizona APOE cohort. All included individuals had undergone extensive neuropsychological testing and 25 had in addition undergone FDG-PET and MRI to determine CMRgl and regional gray matter volume (GMV).

Results: Our results demonstrated higher apoE4 levels in females versus males and an age-dependent increase in the apoE3 isoform levels in females only. Importantly, a higher relative ratio of apoE4 over apoE3 was associated with GMV loss in the right posterior cingulate and with reduced CMRgl bilaterally in the anterior cingulate and in the right hippocampal area. Additional exploratory analysis revealed several negative associations between total plasma apoE, individual apoE isoform levels, GMV and CMRgl predominantly in the frontal, occipital and temporal areas. Finally, our results indicated only weak associations between apoE plasma levels and cognitive performance which further appear to be affected by sex.

Conclusions: Our study proposes a sex-dependent and age-dependent variation in plasma apoE isoform levels and concludes that peripheral apoE levels are associated with GMV, CMRgl and possibly cognitive performance in cognitively healthy individuals with a genetic predisposition to AD.

Nitrogen availability and cell density each affects growth and cellular astaxanthin content of Haematococcus pluvialis, but possible combined effects of these two factors on the content and productivity of astaxanthin, especially under outdoor culture conditions, is less understood. In this study, the effects of the initial biomass densities IBDs of 0.1, 0.5, 0.8, 1.5, 2.7, 3.5, and 5.0 g L-1 DW and initial nitrogen concentrations of 0, 4.4, 8.8, and 17.6 mM nitrate on growth and cellular astaxanthin content of H. pluvialis Flotow K-0084 were investigated in outdoor glass column photobioreactors in a batch culture mode. A low IBD of 0.1 g L-1 DW led to photo-bleaching of the culture within 1-2 days. When the IBD was 0.5 g L-1 and above, the rate at which the increase in biomass density and the astaxanthin content on a per cell basis was higher at lower IBD. When the IBD was optimal (i.e., 0.8 g L-1), the maximum astaxanthin content of 3.8% of DW was obtained in the absence of nitrogen, whereas the maximum astaxanthin productivity of 16.0 mg L-1 d(-1) was obtained in the same IBD culture containing 4.4 mM nitrogen. The strategies for achieving maximum Haematococcus biomass productivity and for maximum cellular astaxanthin content are discussed.

Major progress has been made in the past decade towards understanding of the biosynthesis of red carotenoid astaxanthin and its roles in stress response while exploiting microalgae-based astaxanthin as a potent antioxidant for human health and as a coloring agent for aquaculture applications. In this review, astaxanthin-producing green microalgae are briefly summarized with Haematococcus pluvialis and Chlorella zofingiensis recognized to be the most popular astaxanthin-producers. Two distinct pathways for astaxanthin synthesis along with associated cellular, physiological, and biochemical changes are elucidated using H. pluvialis and C. zofingiensis as the model systems. Interactions between astaxanthin biosynthesis and photosynthesis, fatty acid biosynthesis and enzymatic defense systems are described in the context of multiple lines of defense mechanisms working in concert against photooxidative stress. Major pros and cons of mass cultivation of H. pluvialis and C. zofingiensis in phototrophic, heterotrophic, and mixotrophic culture modes are analyzed. Recent progress in genetic engineering of plants and microalgae for astaxanthin production is presented. Future advancement in microalgal astaxanthin research will depend largely on genome sequencing of H pluvialis and C. zofingiensis and genetic toolbox development. Continuous effort along the heterotrophic-phototrophic culture mode could lead to major expansion of the micro algal astaxanthin industry.

Background: Microalgae are promising feedstock for production of lipids, sugars, bioactive compounds and in particular biofuels, yet development of sensitive and reliable phylotyping strategies for microalgae has been hindered by the paucity of phylogenetically closely-related finished genomes.

Results: Using the oleaginous eustigmatophyte Nannochloropsis as a model, we assessed current intragenus phylotyping strategies by producing the complete plastid (pt) and mitochondrial (mt) genomes of seven strains from six Nannochloropsis species. Genes on the pt and mt genomes have been highly conserved in content, size and order, strongly negatively selected and evolving at a rate 33% and 66% of nuclear genomes respectively. Pt genome diversification was driven by asymmetric evolution of two inverted repeats (IRa and IRb): psbV and clpC in IRb are highly conserved whereas their counterparts in IRa exhibit three lineage-associated types of structural polymorphism via duplication or disruption of whole or partial genes. In the mt genomes, however, a single evolution hotspot varies in copy-number of a 3.5 Kb-long, cox1-harboring repeat. The organelle markers (e.g., cox1, cox2, psbA, rbcL and rrn16_mt) and nuclear markers (e.g., ITS2 and 18S) that are widely used for phylogenetic analysis obtained a divergent phylogeny for the seven strains, largely due to low SNP density. A new strategy for intragenus phylotyping of microalgae was thus proposed that includes (i) twelve sequence markers that are of higher sensitivity than ITS2 for interspecies phylogenetic analysis, (ii) multi-locus sequence typing based on rps11_mt-nad4, rps3_mt and cox2-rrn16_mt for intraspecies phylogenetic reconstruction and (iii) several SSR loci for identification of strains within a given species.

Conclusion: This first comprehensive dataset of organelle genomes for a microalgal genus enabled exhaustive assessment and searches of all candidate phylogenetic markers on the organelle genomes. A new strategy for intragenus phylotyping of microalgae was proposed which might be generally applicable to other microalgal genera and should serve as a valuable tool in the expanding algal biotechnology industry.