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.

Background:
Data assimilation refers to methods for updating the state vector (initial condition) of a complex spatiotemporal model (such as a numerical weather model) by combining new observations with one or more prior forecasts. We consider the potential feasibility of this approach for making short-term (60-day) forecasts of the growth and spread of a malignant brain cancer (glioblastoma multiforme) in individual patient cases, where the observations are synthetic magnetic resonance images of a hypothetical tumor.

Results:
We apply a modern state estimation algorithm (the Local Ensemble Transform Kalman Filter), previously developed for numerical weather prediction, to two different mathematical models of glioblastoma, taking into account likely errors in model parameters and measurement uncertainties in magnetic resonance imaging. The filter can accurately shadow the growth of a representative synthetic tumor for 360 days (six 60-day forecast/update cycles) in the presence of a moderate degree of systematic model error and measurement noise.

Conclusions:
The mathematical methodology described here may prove useful for other modeling efforts in biology and oncology. An accurate forecast system for glioblastoma may prove useful in clinical settings for treatment planning and patient counseling.

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.`

Perchloroethylene (PCE) is a highly utilized solvent in the dry cleaning industry because of its cleaning effectiveness and relatively low cost to consumers. According to the 2006 U.S. Census, approximately 28,000 dry cleaning operations used PCE as their principal cleaning agent. Widespread use of PCE is problematic because of its adverse impacts on human health and environmental quality. As PCE use is curtailed, effective alternatives must be analyzed for their toxicity and impacts to human health and the environment. Potential alternatives to PCE in dry cleaning include dipropylene glycol n-butyl ether (DPnB) and dipropylene glycol tert-butyl ether (DPtB), both promising to pose a relatively smaller risk. To evaluate these two alternatives to PCE, we established and scored performance criteria, including chemical toxicity, employee and customer exposure levels, impacts on the general population, costs of each system, and cleaning efficacy. The scores received for PCE were 5, 5, 3, 5, 3, and 3, respectively, and DPnB and DPtB scored 3, 1, 2, 2, 4, and 4, respectively. An aggregate sum of the performance criteria yielded a favorably low score of “16” for both DPnB and DPtB compared to “24” for PCE. We conclude that DPnB and DPtB are preferable dry cleaning agents, exhibiting reduced human toxicity and a lesser adverse impact on human health and the environment compared to PCE, with comparable capital investments, and moderately higher annual operating costs.

We designed and evaluated an active sampling device, using as analytical targets a family of pesticides purported to contribute to honeybee colony collapse disorder. Simultaneous sampling of bulk water and pore water was accomplished using a low-flow, multi-channel pump to deliver water to an array of solid-phase extraction cartridges. Analytes were separated using either liquid or gas chromatography, and analysis was performed using tandem mass spectrometry (MS/MS). Achieved recoveries of fipronil and degradates in water spiked to nominal concentrations of 0.1, 1, and 10 ng/L ranged from 77 ± 12 to 110 ± 18%. Method detection limits (MDLs) were as low as 0.040–0.8 ng/L. Extraction and quantitation of total fiproles at a wastewater-receiving wetland yielded concentrations in surface water and pore water ranging from 9.9 ± 4.6 to 18.1 ± 4.6 ng/L and 9.1 ± 3.0 to 12.6 ± 2.1 ng/L, respectively. Detected concentrations were statistically indistinguishable from those determined by conventional, more laborious techniques (p > 0.2 for the three most abundant fiproles). Aside from offering time-averaged sampling capabilities for two phases simultaneously with picogram-per-liter MDLs, the novel methodology eliminates the need for water and sediment transport via in situ solid phase extraction.

The Future of Wastewater Sensing workshop is part of a collaboration between Arizona State University Center for Nanotechnology in Society in the School for the Future of Innovation in Society, the Biodesign Institute’s Center for Environmental Security, LC Nano, and the Nano-enabled Water Treatment (NEWT) Systems NSF Engineering Research Center. The Future of Wastewater Sensing workshop explores how technologies for studying, monitoring, and mining wastewater and sewage sludge might develop in the future, and what consequences may ensue for public health, law enforcement, private industry, regulations and society at large. The workshop pays particular attention to how wastewater sensing (and accompanying research, technologies, and applications) can be innovated, regulated, and used to maximize societal benefit and minimize the risk of adverse outcomes, when addressing critical social and environmental challenges.

Nanoscale zero-valent iron (nZVI) is a strong nonspecific reducing agent that is used for in situ degradation of chlorinated solvents and other oxidized pollutants. However, there are significant concerns regarding the risks posed by the deliberate release of engineered nanomaterials into the environment, which have triggered moratoria, for example, in the United Kingdom. This critical review focuses on the effect of nZVI injection on subsurface microbial communities, which are of interest due to their important role in contaminant attenuation processes. Corrosion of ZVI stimulates dehalorespiring bacteria, due to the production of H₂ that can serve as an electron donor for reduction of chlorinated contaminants. Conversely, laboratory studies show that nZVI can be inhibitory to pure bacterial cultures, although toxicity is reduced when nZVI is coated with polyelectrolytes or natural organic matter. The emerging toolkit of molecular biological analyses should enable a more sophisticated assessment of combined nZVI/biostimulation or bioaugmentation approaches. While further research on the consequences of its application for subsurface microbial communities is needed, nZVI continues to hold promise as an innovative technology for in situ remediation of pollutants It is particularly attractive. for the remediation of subsurface environments containing chlorinated ethenes because of its ability to potentially elicit and sustain both physical–chemical and biological removal despite its documented antimicrobial properties.

Using liquid chromatography tandem mass spectrometry, we determined the first nationwide inventories of 13 perfluoroalkyl substances (PFASs) in U.S. biosolids via analysis of samples collected by the U.S. Environmental Protection Agency in the 2001 National Sewage Sludge Survey. Perfluorooctane sulfonate [PFOS; 403 +/- 127 ng/g dry weight (dw)] was the most abundant PFAS detected in biosolids composites representing 32 U.S. states and the District of Columbia, followed by perfluorooctanoate [PFOA; 34 +/- 22 ng/g dw] and perfluorodecanoate [PFDA; 26 +/- 20 ng/g dw]. Mean concentrations in U.S. biosolids of the remaining ten PFASs ranged between 2 and 21 ng/g dw. Interestingly, concentrations of PFOS determined here in biosolids collected prior to the phase-out period (2002) were similar to levels reported in the literature for recent years. The mean load of Sigma PFASs in U.S. biosolids was estimated at 2749-3450 kg/year, of which about 1375-2070 kg is applied on agricultural land and 467-587 kg goes to landfills as an alternative disposal route. This study informs the risk assessment of PFASs by furnishing national inventories of PFASs occurrence and environmental release via biosolids application on land.

Background: Buffering to achieve pH control is crucial for successful trichloroethene (TCE) anaerobic bioremediation. Bicarbonate (HCO3−) is the natural buffer in groundwater and the buffer of choice in the laboratory and at contaminated sites undergoing biological treatment with organohalide respiring microorganisms. However, HCO3− also serves as the electron acceptor for hydrogenotrophic methanogens and hydrogenotrophic homoacetogens, two microbial groups competing with organohalide respirers for hydrogen (H2). We studied the effect of HCO3− as a buffering agent and the effect of HCO3−-consuming reactions in a range of concentrations (2.5-30 mM) with an initial pH of 7.5 in H2-fed TCE reductively dechlorinating communities containing Dehalococcoides, hydrogenotrophic methanogens, and hydrogenotrophic homoacetogens.

Results: Rate differences in TCE dechlorination were observed as a result of added varying HCO3− concentrations due to H2-fed electrons channeled towards methanogenesis and homoacetogenesis and pH increases (up to 8.7) from biological HCO3− consumption. Significantly faster dechlorination rates were noted at all HCO3− concentrations tested when the pH buffering was improved by providing 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid (HEPES) as an additional buffer. Electron balances and quantitative PCR revealed that methanogenesis was the main electron sink when the initial HCO3− concentrations were 2.5 and 5 mM, while homoacetogenesis was the dominant process and sink when 10 and 30 mM HCO3− were provided initially.

Conclusions: Our study reveals that HCO3− is an important variable for bioremediation of chloroethenes as it has a prominent role as an electron acceptor for methanogenesis and homoacetogenesis. It also illustrates the changes in rates and extent of reductive dechlorination resulting from the combined effect of electron donor competition stimulated by HCO3− and the changes in pH exerted by methanogens and homoacetogens.

Predicting the timing of a castrate resistant prostate cancer is critical to lowering medical costs and improving the quality of life of advanced prostate cancer patients. We formulate, compare and analyze two mathematical models that aim to forecast future levels of prostate-specific antigen (PSA). We accomplish these tasks by employing clinical data of locally advanced prostate cancer patients undergoing androgen deprivation therapy (ADT). While these models are simplifications of a previously published model, they fit data with similar accuracy and improve forecasting results. Both models describe the progression of androgen resistance. Although Model 1 is simpler than the more realistic Model 2, it can fit clinical data to a greater precision. However, we found that Model 2 can forecast future PSA levels more accurately. These findings suggest that including more realistic mechanisms of androgen dynamics in a two population model may help androgen resistance timing prediction.