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.

The World Health Organization recently proposed the inclusion of brominated congeners in addition to chlorinated congeners when computing the toxic equivalency (TEQ) of dioxin-like compounds (DLCs) in assessments of human health risks. In the present study, 12 polybrominated dibenzo-p-dioxins and furans (PBDD/Fs) were analyzed by gas chromatography/high resolution mass spectrometry in the composited, archived biosolids that were collected in 32 U.S. states and the District of Columbia from 94 wastewater treatment plants by the United States Environmental Protection Agency in its 2001 national sewage sludge survey. Two PBDDs and five PBDFs were detected in the biosolids composites at varying frequencies (40–100%) with a total mean concentration of 10,000 ng/kg dry weight (range: 630–42,800), of which 1,2,3,4,6,7,8-hepta-BDF constituted about 95% by mass. Relative to commercial polybrominated diphenyl ether (PBDE) formulations, the ratio of PBDD/Fs to PBDEs in biosolids was 55-times higher (∼0.002% vs ∼0.11%), which indicates potential PBDE transformation or possibly additional sources of PBDD/Fs in the environment. The TEQ contribution of PBDD/Fs was estimated at 162 ng/kg 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) (range: 15–672), which is equivalent to 75% (range: 12–96%) of the total TEQ in biosolids. The TEQ of DLCs released annually to U.S. soils as a result of the land application of biosolids was estimated at 720 g (range: 530–1600 g). Among all known DLCs determined in biosolids, brominated analogs contributed 370% more TEQ than did chlorinated congeners, which indicates the need to include brominated DLCs in the exposure and risk assessment of land-applied biosolids.

Widespread contamination of groundwater by chlorinated ethenes and their biological dechlorination products necessitates the reliable monitoring of liquid matrices; current methods approved by the U.S. Environmental Protection Agency (EPA) require a minimum of 5 mL of sample volume and cannot simultaneously detect all transformative products. This paper reports on the simultaneous detection of six chlorinated ethenes and ethene itself, using a liquid sample volume of 1 mL by concentrating the compounds onto an 85-µm carboxen-polydimenthylsiloxane solid-phase microextraction fiber in 5 min and subsequent chromatographic analysis in 9.15 min. Linear increases in signal response were obtained over three orders of magnitude (∼0.05 to ∼50 µM) for simultaneous analysis with coefficient of determination (R²) values of ≥ 0.99. The detection limits of the method (1.3–6 µg/L) were at or below the maximum contaminant levels specified by the EPA. Matrix spike studies with groundwater and mineral medium showed recovery rates between 79–108%. The utility of the method was demonstrated in lab-scale sediment flow-through columns assessing the bioremediation potential of chlorinated ethene-contaminated groundwater. Owing to its low sample volume requirements, good sensitivity and broad target analyte range, the method is suitable for routine compliance monitoring and is particularly attractive for interpreting the bench-scale feasibility studies that are commonly performed during the remedial design stage of groundwater cleanup projects.

Human societies are unique in the level of cooperation among non-kin. Evolutionary models explaining this behavior typically assume pure strategies of cooperation and defection. Behavioral experiments, however, demonstrate that humans are typically conditional co-operators who have other-regarding preferences. Building on existing models on the evolution of cooperation and costly punishment, we use a utilitarian formulation of agent decision making to explore conditions that support the emergence of cooperative behavior. Our results indicate that cooperation levels are significantly lower for larger groups in contrast to the original pure strategy model. Here, defection behavior not only diminishes the public good, but also affects the expectations of group members leading conditional co-operators to change their strategies. Hence defection has a more damaging effect when decisions are based on expectations and not only pure strategies.

Important antibiotics in human medicine have been used for many decades in animal agriculture for growth promotion and disease treatment. Several publications have linked antibiotic resistance development and spread with animal production. Aquaculture, the newest and fastest growing food production sector, may promote similar or new resistance mechanisms. This review of 650+ papers from diverse sources examines parallels and differences between land-based agriculture of swine, beef, and poultry and aquaculture. Among three key findings was, first, that of 51 antibiotics commonly used in aquaculture and agriculture, 39 (or 76%) are also of importance in human medicine; furthermore, six classes of antibiotics commonly used in both agriculture and aquaculture are also included on the World Health Organization’s (WHO) list of critically important/highly important/important antimicrobials. Second, various zoonotic pathogens isolated from meat and seafood were observed to feature resistance to multiple antibiotics on the WHO list, irrespective of their origin in either agriculture or aquaculture. Third, the data show that resistant bacteria isolated from both aquaculture and agriculture share the same resistance mechanisms, indicating that aquaculture is contributing to the same resistance issues established by terrestrial agriculture. More transparency in data collection and reporting is needed so the risks and benefits of antibiotic usage can be adequately assessed.

A meta-analysis was conducted to inform the epistemology, or theory of knowledge, of contaminants of emerging concern (CECs). The CEC terminology acknowledges the existence of harmful environmental agents whose identities, occurrences, hazards, and effects are not sufficiently understood. Here, data on publishing activity were analyzed for 12 CECs, revealing a common pattern of emergence, suitable for identifying past years of peak concern and forecasting future ones: dichlorodiphenyltrichloroethane (DDT; 1972, 2008), trichloroacetic acid (TCAA; 1972, 2009), nitrosodimethylamine (1984), methyl tert-butyl ether (2001), trichloroethylene (2005), perchlorate (2006), 1,4-dioxane (2009), prions (2009), triclocarban (2010), triclosan (2012), nanomaterials (by 2016), and microplastics (2022 ± 4). CECs were found to emerge from obscurity to the height of concern in 14.1 ± 3.6 years, and subside to a new baseline level of concern in 14.5 ± 4.5 years. CECs can emerge more than once (e.g., TCAA, DDT) and the multifactorial process of emergence may be driven by inception of novel scientific methods (e.g., ion chromatography, mass spectrometry and nanometrology), scientific paradigm shifts (discovery of infectious proteins), and the development, marketing and mass consumption of novel products (antimicrobial personal care products, microplastics and nanomaterials). Publishing activity and U.S. regulatory actions were correlated for several CECs investigated.

Processed municipal sewage sludges (MSS) are an abundant, unwanted by-product of wastewater treatment, increasingly applied to agriculture and forestry for inexpensive disposal and soil conditioning. Due to their high organic carbon and lipid contents, MSS not only is rich in carbon and nutrients but also represents a “sink” for recalcitrant, hydrophobic, and potentially bioaccumulative compounds. Indeed, many organics sequestered and concentrated in MSS meet the US Environmental Protection Agency’s definition of being persistent, bioaccumulative, and toxic (PBT). In a strategic effort, our research team at the Biodesign Institute has created the National Sewage Sludge Repository (NSSR), a large repository of digested MSSs from 164 wastewater treatment plants from across the USA, as part of the Human Health Observatory (H2O) at Arizona State University (ASU). The NSSR likely represents the largest archive of digested MSS specimens in the USA. The present study summarizes key findings gleaned thus far from analysis of NSSR samples. For example, we evaluated the content of toxicants in MSS and computed estimates of nationwide inventories of mass produced chemicals that become sequestrated in sludge and later are released into the environment during sludge disposal on land. Ongoing efforts document co-occurrence of a variety of PBT compounds in both MSS and human samples, while also identifying a large number of potentially harmful MSS constituents for which human exposure data are still lacking. Finally, we summarize future opportunities and invite collaborative use of the NSSR by the research community. The H2O at ASU represents a new resource and research tool for environmental scientists and the larger research community. As illustrated in this work, this repository can serve to (i) identify and prioritize emerging contaminants, (ii) provide spatial and temporal trends of contaminants, (iii) inform and evaluate the effectiveness of environmental policy-making and regulations, and (iv) approximate, ongoing exposures and body burdens of mass-produced chemicals in human society.

A major conundrum in evolution is that, despite natural selection, polymorphism is still omnipresent in nature: Numerous species exhibit multiple morphs, namely several abundant values of an important trait. Polymorphism is particularly prevalent in asymmetric traits, which are beneficial to their carrier in disruptive competitive interference but at the same time bear disadvantages in other aspects, such as greater mortality or lower fecundity. Here we focus on asymmetric traits in which a better competitor disperses fewer offspring in the absence of competition. We report a general pattern in which polymorphic populations emerge when disruptive selection increases: The stronger the selection, the greater the number of morphs that evolve. This pattern is general and is insensitive to the form of the fitness function. The pattern is somewhat counterintuitive since directional selection is excepted to sharpen the trait distribution and thereby reduce its diversity (but note that similar patterns were suggested in studies that demonstrated increased biodiversity as local selection increases in ecological communities). We explain the underlying mechanism in which stronger selection drives the population towards more competitive values of the trait, which in turn reduces the population density, thereby enabling lesser competitors to stably persist with reduced need to directly compete. Thus, we believe that the pattern is more general and may apply to asymmetric traits more broadly. This robust pattern suggests a comparative, unified explanation to a variety of polymorphic traits in nature.

Background: Increasing our understanding of the factors affecting the severity of the 2009 A/H1N1 influenza pandemic in different regions of the world could lead to improved clinical practice and mitigation strategies for future influenza pandemics. Even though a number of studies have shed light into the risk factors associated with severe outcomes of 2009 A/H1N1 influenza infections in different populations (e.g., [1-5]), analyses of the determinants of mortality risk spanning multiple pandemic waves and geographic regions are scarce. Between-country differences in the mortality burden of the 2009 pandemic could be linked to differences in influenza case management, underlying population health, or intrinsic differences in disease transmission [6]. Additional studies elucidating the determinants of disease severity globally are warranted to guide prevention efforts in future influenza pandemics.

In Mexico, the 2009 A/H1N1 influenza pandemic was characterized by a three-wave pattern occurring in the spring, summer, and fall of 2009 with substantial geographical heterogeneity [7]. A recent study suggests that Mexico experienced high excess mortality burden during the 2009 A/H1N1 influenza pandemic relative to other countries [6]. However, an assessment of potential factors that contributed to the relatively high pandemic death toll in Mexico are lacking. Here, we fill this gap by analyzing a large series of laboratory-confirmed A/H1N1 influenza cases, hospitalizations, and deaths monitored by the Mexican Social Security medical system during April 1 through December 31, 2009 in Mexico. In particular, we quantify the association between disease severity, hospital admission delays, and neuraminidase inhibitor use by demographic characteristics, pandemic wave, and geographic regions of Mexico.

Methods: We analyzed a large series of laboratory-confirmed pandemic A/H1N1 influenza cases from a prospective surveillance system maintained by the Mexican Social Security system, April-December 2009. We considered a spectrum of disease severity encompassing outpatient visits, hospitalizations, and deaths, and recorded demographic and geographic information on individual patients. We assessed the impact of neuraminidase inhibitor treatment and hospital admission delay (≤ > 2 days after disease onset) on the risk of death by multivariate logistic regression.

Results: Approximately 50% of all A/H1N1-positive patients received antiviral medication during the Spring and Summer 2009 pandemic waves in Mexico while only 9% of A/H1N1 cases received antiviral medications during the fall wave (P < 0.0001). After adjustment for age, gender, and geography, antiviral treatment significantly reduced the risk of death (OR = 0.52 (95% CI: 0.30, 0.90)) while longer hospital admission delays increased the risk of death by 2.8-fold (95% CI: 2.25, 3.41).

Conclusions: Our findings underscore the potential impact of decreasing admission delays and increasing antiviral use to mitigate the mortality burden of future influenza pandemics.