ASU Scholarship Showcase

Five immunocompetent C57BL/6-cBrd/cBrd/Cr (albino C57BL/6) mice were injected with GL261-luc2 cells, a cell line sharing characteristics of human glioblastoma multiforme (GBM). The mice were imaged using magnetic resonance (MR) at five separate time points to characterize growth and development of the tumor. After 25 days, the final tumor volumes of the mice varied from 12 mm³ to 62 mm³, even though mice were inoculated from the same tumor cell line under carefully controlled conditions. We generated hypotheses to explore large variances in final tumor size and tested them with our simple reaction-diffusion model in both a 3-dimensional (3D) finite difference method and a 2-dimensional (2D) level set method. The parameters obtained from a best-fit procedure, designed to yield simulated tumors as close as possible to the observed ones, vary by an order of magnitude between the three mice analyzed in detail. These differences may reflect morphological and biological variability in tumor growth, as well as errors in the mathematical model, perhaps from an oversimplification of the tumor dynamics or nonidentifiability of parameters. Our results generate parameters that match other experimental in vitro and in vivo measurements. Additionally, we calculate wave speed, which matches with other rat and human measurements.

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.`

Gompertz’s empirical equation remains the most popular one in describing cancer cell population growth in a wide spectrum of bio-medical situations due to its good fit to data and simplicity. Many efforts were documented in the literature aimed at understanding the mechanisms that may support Gompertz’s elegant model equation. One of the most convincing efforts was carried out by Gyllenberg and Webb. They divide the cancer cell population into the proliferative cells and the quiescent cells. In their two dimensional model, the dead cells are assumed to be removed from the tumor instantly. In this paper, we modify their model by keeping track of the dead cells remaining in the tumor. We perform mathematical and computational studies on this three dimensional model and compare the model dynamics to that of the model of Gyllenberg and Webb. Our mathematical findings suggest that if an avascular tumor grows according to our three-compartment model, then as the death rate of quiescent cells decreases to zero, the percentage of proliferative cells also approaches to zero. Moreover, a slow dying quiescent population will increase the size of the tumor. On the other hand, while the tumor size does not depend on the dead cell removal rate, its early and intermediate growth stages are very sensitive to it.

MicroRNAs (miRNAs) are short non-coding RNAs that regulate gene output at the post-transcriptional level by targeting degenerate elements primarily in 3′untranslated regions (3′UTRs) of mRNAs. Individual miRNAs can regulate networks of hundreds of genes, yet for the majority of miRNAs few, if any, targets are known. Misexpression of miRNAs is also a major contributor to cancer progression, thus there is a critical need to validate miRNA targets in high-throughput to understand miRNAs' contribution to tumorigenesis. Here we introduce a novel high-throughput assay to detect miRNA targets in 3′UTRs, called Luminescent Identification of Functional Elements in 3′UTRs (3′LIFE). We demonstrate the feasibility of 3′LIFE using a data set of 275 human 3′UTRs and two cancer-relevant miRNAs, let-7c and miR-10b, and compare our results to alternative methods to detect miRNA targets throughout the genome. We identify a large number of novel gene targets for these miRNAs, with only 32% of hits being bioinformatically predicted and 27% directed by non-canonical interactions. Functional analysis of target genes reveals consistent roles for each miRNA as either a tumor suppressor (let-7c) or oncogenic miRNA (miR-10b), and preferentially target multiple genes within regulatory networks, suggesting 3′LIFE is a rapid and sensitive method to detect miRNA targets in high-throughput.

Cognitive theories in visual attention and perception, categorization, and memory often critically rely on concepts of similarity among objects, and empirically require measures of “sameness” among their stimuli. For instance, a researcher may require similarity estimates among multiple exemplars of a target category in visual search, or targets and lures in recognition memory. Quantifying similarity, however, is challenging when everyday items are the desired stimulus set, particularly when researchers require several different pictures from the same category. In this article, we document a new multidimensional scaling database with similarity ratings for 240 categories, each containing color photographs of 16–17 exemplar objects. We collected similarity ratings using the spatial arrangement method. Reports include: the multidimensional scaling solutions for each category, up to five dimensions, stress and fit measures, coordinate locations for each stimulus, and two new classifications. For each picture, we categorized the item's prototypicality, indexed by its proximity to other items in the space. We also classified pairs of images along a continuum of similarity, by assessing the overall arrangement of each MDS space. These similarity ratings will be useful to any researcher that wishes to control the similarity of experimental stimuli according to an objective quantification of “sameness.”

While expert groups often make recommendations on a range of non-controversial as well as controversial issues, little is known about how the level of expert consensus-the level of expert agreement-influences perceptions of the recommendations. This research illustrates that for non-controversial issues expert groups that exhibit high levels of agreement are more persuasive than expert groups that exhibit low levels of agreement. This effect is mediated by the perceived entitativity-the perceived cohesiveness or unification of the group-of the expert group. But for controversial issues, this effect is moderated by the perceivers' implicit assumptions about the group composition. When perceivers are provided no information about a group supporting the Affordable Care Act-a highly controversial piece of U.S. legislation that is divided by political party throughout the country-higher levels of agreement are less persuasive than lower levels of agreement because participants assume there were more democrats and fewer republicans in the group. But when explicitly told that the group was half republicans and half democrats, higher levels of agreement are more persuasive.

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.

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.

Background: Tissue-specific RNA plasticity broadly impacts the development, tissue identity and adaptability of all organisms, but changes in composition, expression levels and its impact on gene regulation in different somatic tissues are largely unknown. Here we developed a new method, polyA-tagging and sequencing (PAT-Seq) to isolate high-quality tissue-specific mRNA from Caenorhabditis elegans intestine, pharynx and body muscle tissues and study changes in their tissue-specific transcriptomes and 3’UTRomes.

Results: We have identified thousands of novel genes and isoforms differentially expressed between these three tissues. The intestine transcriptome is expansive, expressing over 30% of C. elegans mRNAs, while muscle transcriptomes are smaller but contain characteristic unique gene signatures. Active promoter regions in all three tissues reveal both known and novel enriched tissue-specific elements, along with putative transcription factors, suggesting novel tissue-specific modes of transcription initiation. We have precisely mapped approximately 20,000 tissue-specific polyadenylation sites and discovered that about 30% of transcripts in somatic cells use alternative polyadenylation in a tissue-specific manner, with their 3’UTR isoforms significantly enriched with microRNA targets.

Conclusions: For the first time, PAT-Seq allowed us to directly study tissue specific gene expression changes in an in vivo setting and compare these changes between three somatic tissues from the same organism at single-base resolution within the same experiment. We pinpoint precise tissue-specific transcriptome rearrangements and for the first time link tissue-specific alternative polyadenylation to miRNA regulation, suggesting novel and unexplored tissue-specific post-transcriptional regulatory networks in somatic cells.

Background: 3′untranslated regions (3′UTRs) are poorly understood portions of eukaryotic mRNAs essential for post-transcriptional gene regulation. Sequence elements in 3′UTRs can be target sites for regulatory molecules such as RNA binding proteins and microRNAs (miRNAs), and these interactions can exert significant control on gene networks. However, many such interactions remain uncharacterized due to a lack of high-throughput (HT) tools to study 3′UTR biology. HT cloning efforts such as the human ORFeome exemplify the potential benefits of genomic repositories for studying human disease, especially in relation to the discovery of biomarkers and targets for therapeutic agents. Currently there are no publicly available human 3′UTR libraries. To address this we have prepared the first version of the human 3′UTRome (h3′UTRome v1) library. The h3′UTRome is produced to a single high quality standard using the same recombinational cloning technology used for the human ORFeome, enabling universal operating methods and high throughput experimentation. The library is thoroughly sequenced and annotated with simple online access to information, and made publicly available through gene repositories at low cost to all scientists with minimal restriction.

Results: The first release of the h3′UTRome library comprises 1,461 human 3′UTRs cloned into Gateway® entry vectors, ready for downstream analyses. It contains 3′UTRs for 985 transcription factors, 156 kinases, 171 RNA binding proteins, and 186 other genes involved in gene regulation and in disease. We demonstrate the feasibility of the h3′UTRome library by screening a panel of 87 3′UTRs for targeting by two miRNAs: let-7c, which is implicated in tumorigenesis, and miR-221, which is implicated in atherosclerosis and heart disease. The panel is enriched with genes involved in the RAS signaling pathway, putative novel targets for the two miRNAs, as well as genes implicated in tumorigenesis and heart disease.

Conclusions: The h3′UTRome v1 library is a modular resource that can be utilized for high-throughput screens to identify regulatory interactions between trans-acting factors and 3′UTRs, Importantly, the library can be customized based on the specifications of the researcher, allowing the systematic study of human 3′UTR biology.