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.

In this study, we examine how development status and water scarcity shape people's perceptions of "hard path" and "soft path" water solutions. Based on ethnographic research conducted in four semi-rural/peri-urban sites (in Bolivia, Fiji, New Zealand, and the US), we use content analysis to conduct statistical and thematic comparisons of interview data. Our results indicate clear differences associated with development status and, to a lesser extent, water scarcity. People in the two less developed sites were more likely to suggest hard path solutions, less likely to suggest soft path solutions, and more likely to see no path to solutions than people in the more developed sites. Thematically, people in the two less developed sites envisioned solutions that involve small-scale water infrastructure and decentralized, community-based solutions, while people in the more developed sites envisioned solutions that involve large-scale infrastructure and centralized, regulatory water solutions. People in the two water-scarce sites were less likely to suggest soft path solutions and more likely to see no path to solutions (but no more likely to suggest hard path solutions) than people in the water-rich sites. Thematically, people in the two water-rich sites seemed to perceive a wider array of unrealized potential soft path solutions than those in the water-scarce sites. On balance, our findings are encouraging in that they indicate that people are receptive to soft path solutions in a range of sites, even those with limited financial or water resources. Our research points to the need for more studies that investigate the social feasibility of soft path water solutions, particularly in sites with significant financial and natural resource constraints.

Background: Weight-related stigma is reported frequently by higher body-weight patients in healthcare settings. Bariatric surgery triggers profound weight loss. This weight loss may therefore alleviate patients' experiences of weight-related stigma within healthcare settings. In non-clinical settings, weight-related stigma is associated with weight-inducing eating patterns. Dietary adherence is a major challenge after bariatric surgery.

Objectives: (1) Evaluate the relationship between weight-related stigma and post-surgical dietary adherence; (2) understand if weight loss reduces weight-related stigma, thereby improving post-surgical dietary adherence; and (3) explore provider and patient perspectives on adherence and stigma in healthcare settings.

Design: This mixed methods study contrasts survey responses from 300 postoperative bariatric patients with ethnographic data based on interviews with 35 patients and extensive multi-year participant-observation within a clinic setting. The survey measured experiences of weight-related stigma, including from healthcare professionals, on the Interpersonal Sources of Weight Stigma scale and internalized stigma based on the Weight Bias Internalization Scale. Dietary adherence measures included patient self-reports, non-disordered eating patterns reported on the Disordered Eating after Bariatric Surgery scale, and food frequencies. Regression was used to assess the relationships among post-surgical stigma, dietary adherence, and weight loss. Qualitative analyses consisted of thematic analysis.

Results: The quantitative data show that internalized stigma and general experiences of weight-related stigma predict worse dietary adherence, even after weight is lost. The qualitative data show patients did not generally recognize this connection, and health professionals explained it as poor patient compliance.
Conclusion: Reducing perceptions of weight-related stigma in healthcare settings and weight bias internalization could enhance dietary adherence, regardless of time since patient's weight-loss surgery.

Background: Multiple studies show that obesity and depression tend to cluster in women. An “appearance concern” pathway has been proposed as one basic explanation of why higher weights might lead to depression. The transition to motherhood is a life phase in which women’s body image, weight, and depressive risk are in flux, with average weight increasing overall during this period. Examination of how these factors interact from pre- to post-pregnancy provides a means to test how body image plays a key role, as proposed, in causally shaping women’s depressive risk.

Methods: Tracking 39,915 pregnant women in the Norwegian Mother and Child (MoBA) Cohort Study forward 36 months after their deliveries, we test the moderating and mediating effects of body image concerns on the emergence of new mothers’ depressive symptoms by using a binary logistic regression model with a discrete-time event history approach and mediation analysis with bootstrapping.

Results: For women with high pre-pregnancy body mass index (BMI), weight gain heightens their depressive symptoms over time. Body image concerns mediate the association between weight gain and the development of depressive symptoms regardless of weight status. However, the mediation effect is more evident for women with higher pre-pregnancy BMI. Conversely, better body image is highly protective against the transition to mild or more severe depressive symptoms among new mothers, but only for women who were not classified as obese prior to their pregnancies.

Conclusions: These findings support a role for body image concerns in the etiology of depressive symptoms during the transition to motherhood. The findings suggest body image interventions before or during pregnancy could help reduce risks of depression in the early postpartum period and well beyond.

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.

Food and water shortages are two of the greatest challenges facing humans in the coming century. While our theoretical understanding of how humans become vulnerable to and cope with hunger is relatively well developed, anthropological research on parallel problems in the water domain is limited. By carefully considering well-established propositions derived from the food literature against what is known about water, our goal in this essay is to advance identifying, theorizing, and testing a broader anthropology of resource insecurity. Our analysis focuses on (1) the causes of resource insecurity at the community level, (2) “coping” responses to resource insecurity at the household level, and (3) the effect of insecurity on emotional well-being and mental health at the individual level. Based on our findings, we argue that human experiences of food and water insecurity are sufficiently similar to facilitate a broader theory of resource insecurity, including in how households and individuals cope. There are also important differences between food and water insecurity, including the role of structural factors (such as markets) in creating community-level vulnerabilities. These suggest food and water insecurity may also produce household struggles and individual suffering along independent pathways.

The impact of undergraduate research experiences (UREs) is supported by evidence from physical and life science fields, especially when student-apprentices work in traditional laboratories. Within social sciences specifically, some excellent student outcomes associated with UREs adhere to non–lab-based modalities like course-based research experiences (CUREs). Here, the authors evaluate the laboratory-based undergraduate research experiences (LUREs) as a potentially valuable approach for incorporating social science undergraduates in research. Using comparative analysis of survey data from students completing three types of social science-based UREs (n = 235), individual research experiences (IREs), CUREs, or LUREs, students perceived gains overall regardless of the type of experience, with some indication that LUREs are the most effective.

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.

Many population centers in the American West rely on water from the Colorado River Basin, which has faced shortages in recent years that are anticipated to be exacerbated by climate change. Shortages to urban water supplies related to climate change will not be limited to cities dependent on the Colorado River. Considering this, addressing sustainable water governance is timely and critical for cities, states, and regions facing supply shortages and pollution problems. Engaging in sustainability transitions of these hydro-social systems will increase the ability of such systems to meet the water needs of urban communities. In this paper, we identify historical transitions in water governance and examine their context for three sites in the Colorado River Basin (Denver, Colorado, Las Vegas, Nevada, and Phoenix, Arizona) to provide insight for intentional transitions towards sustainable, or “water sensitive” cities. The comparative historical approach employed allows us to more fully understand differences in present-day water governance decisions between the sites, identify past catalysts for transitions, and recognize emerging patterns and opportunities that may impact current and future water governance in the Colorado River Basin and beyond.

The 1918 influenza pandemic was a major epidemiological event of the twentieth century resulting in at least twenty million deaths worldwide; however, despite its historical, epidemiological, and biological relevance, it remains poorly understood. Here we examine the relationship between annual pneumonia and influenza death rates in the pre-pandemic (1910–17) and pandemic (1918–20) periods and the scaling of mortality with latitude, longitude and population size, using data from 66 large cities of the United States. The mean pre-pandemic pneumonia death rates were highly associated with pneumonia death rates during the pandemic period (Spearman ρ = 0.64–0.72; P<0.001). By contrast, there was a weak correlation between pre-pandemic and pandemic influenza mortality rates. Pneumonia mortality rates partially explained influenza mortality rates in 1918 (ρ = 0.34, P = 0.005) but not during any other year. Pneumonia death counts followed a linear relationship with population size in all study years, suggesting that pneumonia death rates were homogeneous across the range of population sizes studied. By contrast, influenza death counts followed a power law relationship with a scaling exponent of ∼0.81 (95%CI: 0.71, 0.91) in 1918, suggesting that smaller cities experienced worst outcomes during the pandemic. A linear relationship was observed for all other years. Our study suggests that mortality associated with the 1918–20 influenza pandemic was in part predetermined by pre-pandemic pneumonia death rates in 66 large US cities, perhaps through the impact of the physical and social structure of each city. Smaller cities suffered a disproportionately high per capita influenza mortality burden than larger ones in 1918, while city size did not affect pneumonia mortality rates in the pre-pandemic and pandemic periods.