ASU Scholarship Showcase

Altered thermal regimes under climate change may influence host-parasite interactions and invasive species, both potentially impacting valuable ecosystem services. There is considerable interest in how parasite life cycle rates, growth, and impacts on hosts will change under altered environmental temperatures. Likewise, transformed thermal regimes may reduce natural resistance and barriers preventing establishment of invasive species or alter the range and impacts of established exotic species. The Laurentian Great Lakes are some of the most invaded ecosystems and have been profoundly shaped by exotic species. Invasion by the parasitic sea lamprey (Petromyzon marinus) contributed to major declines in many Great Lakes fish populations. In Lake Superior, substantial progress has been made towards controlling invasive sea lamprey and rehabilitating native fish populations. Surface water temperatures in Lake Superior have been increasing rapidly since 1980 presenting a new challenge for management.

Here we test how thermal changes in Lake Superior have impacted the feeding and growth of the parasitic sea lamprey. Sea lamprey have increased in size corresponding with longer durations of thermal habitat (i.e., longer growing seasons) for their preferred hosts. To compare regional differences in sea lamprey feeding and growth rates, we used a bioenergetics model with temperature estimates from a lake-wide hydrodynamic model hindcast from 1979–2006. Spatial differences in patterns of warming across the lake result in regionally different predictions for increases in sea lamprey feeding rates and size. These predictions were matched by data from adult sea lamprey spawning in streams draining into these different thermal regions. Larger sea lampreys will be more fecund and have increased feeding rates, thus increasing mortality among host fishes. Resource management should consider these climate driven regional impacts when allocating resources to sea lamprey control efforts. Under new and evolving thermal regimes, successful management systems may need to be restructured for changing phenology, growth, and shifts in host-parasite systems towards greater impacts on host populations.

Fungal hyphae are among the most highly polarized cells. Hyphal polarized growth is supported by tip-directed transport of secretory vesicles, which accumulate temporarily in a stratified manner in an apical vesicle cluster, the Spitzenkörper. The exocyst complex is required for tethering of secretory vesicles to the apical plasma membrane. We determined that the presence of an octameric exocyst complex is required for the formation of a functional Spitzenkörper and maintenance of regular hyphal growth in Neurospora crassa. Two distinct localization patterns of exocyst subunits at the hyphal tip suggest the dynamic formation of two assemblies. The EXO-70/EXO-84 subunits are found at the peripheral part of the Spitzenkörper, which partially coincides with the outer macrovesicular layer, whereas exocyst components SEC-5, -6, -8, and -15 form a delimited crescent at the apical plasma membrane. Localization of SEC-6 and EXO-70 to the plasma membrane and the Spitzenkörper, respectively, depends on actin and microtubule cytoskeletons. The apical region of exocyst-mediated vesicle fusion, elucidated by the plasma membrane–associated exocyst subunits, indicates the presence of an exocytotic gradient with a tip-high maximum that dissipates gradually toward the subapex, confirming the earlier predictions of the vesicle supply center model for hyphal morphogenesis.

Cyber-taxonomy of name usage has focused primarily on producing authoritative lists of names or cross-linking names and data across disparate databases. A feature missing from much of this work is the recording and analysis of the context in which a name was used—context which can be critical for understanding not only what name an author used, but to which currently recognized species they actually refer. An experiment on recording contextual information associated with name usage was conducted for the fiddler crabs (genus Uca). Data from approximately one quarter of all publications that mention fiddler crabs, including 95% of those published prior to 1924 and 67% of those published prior to 1976, have currently been recorded in a database. Approaches and difficulties in recording and analyzing the context of name use are discussed. These results are not meant to be a full solution, rather to highlight problems which have not been previously investigated and may act as a springboard for broader approaches and discussion. Some data on the accessibility of the literature, including in particular electronic forms of publication, are also presented. The resulting data has been integrated for general browsing into the website http://www.fiddlercrab.info; the raw data and code used to construct the website is available at https://github.com/msrosenberg/fiddlercrab.info.

Background: Comorbidity among childhood mental health symptoms is common in clinical and community samples and should be accounted for when investigating etiology. We therefore aimed to uncover latent classes of mental health symptoms in middle childhood in a community sample, and to determine the latent genetic and environmental influences on those classes.

Methods: The sample comprised representative cohorts of twins. A questionnaire-based assessment of mental health symptoms was used in latent class analyses. Data on 3223 twins (1578 boys and 1645 girls) with a mean age of 7.5 years were analyzed. The sample was predominantly non-Hispanic Caucasian (92.1%).

Results: Latent class models delineated groups of children according to symptom profiles–not necessarily clinical groups but groups representing the general population, most with scores in the normative range. The best-fitting models suggested 9 classes for both girls and boys. Eight of the classes were very similar across sexes; these classes ranged from a ‘‘Low Symptom’’ class to a ‘‘Moderately Internalizing & Severely Externalizing’’ class. In addition, a ‘‘Moderately Anxious’’ class was identified for girls but not boys, and a ‘‘Severely Impulsive & Inattentive’’ class was identified for boys but not girls. Sex-combined analyses implicated moderate genetic influences for all classes. Shared environmental influences were moderate for the ‘‘Low Symptom’’ and ‘‘Moderately Internalizing & Severely Externalizing’’ classes, and small to zero for other classes.

Conclusions: We conclude that symptom classes are largely similar across sexes in middle childhood. Heritability was moderate for all classes, but shared environment played a greater role for classes in which no one type of symptom predominated.

The best-response dynamics is an example of an evolutionary game where players update their strategy in order to maximize their payoff. The main objective of this paper is to study a stochastic spatial version of this game based on the framework of interacting particle systems in which players are located on an infinite square lattice. In the presence of two strategies, and calling a strategy selfish or altruistic depending on a certain ordering of the coefficients of the underlying payoff matrix, a simple analysis of the nonspatial mean-field approximation of the spatial model shows that a strategy is evolutionary stable if and only if it is selfish, making the system bistable when both strategies are selfish. The spatial and nonspatial models agree when at least one strategy is altruistic. In contrast, we prove that in the presence of two selfish strategies and in any spatial dimension, only the most selfish strategy remains evolutionary stable. The main ingredients of the proof are monotonicity results and a coupling between the best-response dynamics properly rescaled in space with bootstrap percolation to compare the infinite time limits of both systems.

Vision and Change in Undergraduate Biology Education outlined five core concepts intended to guide undergraduate biology education: 1) evolution; 2) structure and function; 3) information flow, exchange, and storage; 4) pathways and transformations of energy and matter; and 5) systems. We have taken these general recommendations and created a Vision and Change BioCore Guide—a set of general principles and specific statements that expand upon the core concepts, creating a framework that biology departments can use to align with the goals of Vision and Change. We used a grassroots approach to generate the BioCore Guide, beginning with faculty ideas as the basis for an iterative process that incorporated feedback from more than 240 biologists and biology educators at a diverse range of academic institutions throughout the United States. The final validation step in this process demonstrated strong national consensus, with more than 90% of respondents agreeing with the importance and scientific accuracy of the statements. It is our hope that the BioCore Guide will serve as an agent of change for biology departments as we move toward transforming undergraduate biology education.

The purpose of this study was to examine in which way adding more indicators or a covariate influences the performance of latent class analysis (LCA). We varied the sample size (100 ≤ N ≤ 2000), number, and quality of binary indicators (between 4 and 12 indicators with conditional response probabilities of [0.3, 0.7], [0.2, 0.8], or [0.1, 0.9]), and the strength of covariate effects (zero, small, medium, large) in a Monte Carlo simulation study of 2- and 3-class models. The results suggested that in general, a larger sample size, more indicators, a higher quality of indicators, and a larger covariate effect lead to more converged and proper replications, as well as fewer boundary parameter estimates and less parameter bias. Furthermore, interactions among these study factors demonstrated how using more or higher quality indicators, as well as larger covariate effect size, could sometimes compensate for small sample size. Including a covariate appeared to be generally beneficial, although the covariate parameters themselves showed relatively large bias. Our results provide useful information for practitioners designing an LCA study in terms of highlighting the factors that lead to better or worse performance of LCA.

A fundamental problem in computational biophysics is to deduce the function of a protein from the structure. Many biological macromolecules such as enzymes, molecular motors or membrane transport proteins perform their function by cycling between multiple conformational states. Understanding such conformational transitions, which typically occur on the millisecond to second time scale, is central to understanding protein function. Molecular dynamics (MD) computer simulations have become an important tool to connect molecular structure to function, but equilibrium MD simulations are rarely able to sample on time scales longer than a few microseconds – orders of magnitudes shorter than the time scales of interest. A range of different simulation methods have been proposed to overcome this time-scale limitation. These include calculations of the free energy landscape and path sampling methods to directly sample transitions between known conformations. All these methods solve the problem to sample infrequently occupied but important regions of configuration space. Many path-sampling algorithms have been applied to the closed – open transition of the enzyme adenylate kinase (AdK), which undergoes a large, clamshell-like conformational transition between an open and a closed state. Here we review approaches to sample macromolecular transitions through the lens of AdK. We focus our main discussion on the current state of knowledge – both from simulations and experiments – about the transition pathways of ligand-free AdK, its energy landscape, transition rates and interactions with substrates. We conclude with a comparison of the discussed approaches with a view towards quantitative evaluation of path-sampling methods.

We introduce and solve a ‘null model’ of stochastic metastatic colonization. The model is described by a single parameter θ: the ratio of the rate of cell division to the rate of cell death for a disseminated tumour cell in a given secondary tissue environment. We are primarily interested in the case in which colonizing cells are poorly adapted for proliferation in the local tissue environment, so that cell death is more likely than cell division, i.e. θ < 1. We quantify the rare event statistics for the successful establishment of a metastatic colony of size N. For N ≫ 1, we find that the probability of establishment is exponentially rare, as expected, and yet the mean time for such rare events is of the form ∼ log (N)/(1 − θ) while the standard deviation of colonization times is ∼1/(1 − θ). Thus, counter to naive expectation, for θ < 1, the average time for establishment of successful metastatic colonies decreases with decreasing cell fitness, and colonies seeded from lower fitness cells show less stochastic variation in their growth. These results indicate that metastatic growth from poorly adapted cells is rare, exponentially explosive and essentially deterministic. These statements are brought into sharper focus by the finding that the temporal statistics of the early stages of metastatic colonization from low-fitness cells (θ < 1) are statistically indistinguishable from those initiated from high-fitness cells (θ > 1), i.e. the statistics show a duality mapping (1 − θ) → (θ − 1). We conclude our analysis with a study of heterogeneity in the fitness of colonising cells, and describe a phase diagram delineating parameter regions in which metastatic colonization is dominated either by low or high fitness cells, showing that both are plausible given our current knowledge of physiological conditions in human cancer.

Objective: Although the adverse effects of chronic pain on work productivity and daily life pursuits are clear, the within-person dynamics of pain, goal cognition, and engagement in work-related and lifestyle goals remain uncharted. This study investigated the impact of pain intensity (assessed on 3 occasions each day) and goal-related schematic thinking (ratings of importance, planning, and goal pursuit opportunities, assessed only in the morning) on afternoon and evening work and lifestyle goal pursuit.

Methods: A community sample of working adults with chronic pain (N = 131) were screened and interviewed about their work and lifestyle goals and completed a 21-day telephonic diary. Hierarchical linear modeling was used to estimate within-person and between-person effects.

Results: At the within-person level, morning pain intensity was inversely related to schematic cognition concerning work and lifestyle goals, whereas, at the between-person level, morning pain intensity varied positively with schematic thinking about work goals as well with afternoon lifestyle goal pursuit. At both the between- and within- analytic levels, morning goal schemas were positively associated with the pursuit of each type of goal in the afternoon and again in the evening. Moreover, positive carry-over effects of morning goal schemas on next day afternoon goal pursuit were observed.

Conclusions: Whereas morning pain intensity exhibited inconsistent effects across analytic levels, morning goal-related schematic thinking consistently predicted goal pursuit across analytic levels, type of goal, and time of day. These findings have implications for treatment and prevention of pain’s potentially deleterious effects on workplace and lifestyle goals.