ASU Scholarship Showcase

Background: Cysteine sulfenic acid (Cys-SOH) plays important roles in the redox regulation of numerous proteins. As a relatively unstable posttranslational protein modification it is difficult to quantify the degree to which any particular protein is modified by Cys-SOH within a complex biological environment. The goal of these studies was to move a step beyond detection and into the relative quantification of Cys-SOH within specific proteins found in a complex biological setting--namely, human plasma.

Results: This report describes the possibilities and limitations of performing such analyses based on the use of thionitrobenzoic acid and dimedone-based probes which are commonly employed to trap Cys-SOH. Results obtained by electrospray ionization-based mass spectrometric immunoassay reveal the optimal type of probe for such analyses as well as the reproducible relative quantification of Cys-SOH within albumin and transthyretin extracted from human plasma--the latter as a protein previously unknown to be modified by Cys-SOH.

Conclusions: The relative quantification of Cys-SOH within specific proteins in a complex biological setting can be accomplished, but several analytical precautions related to trapping, detecting, and quantifying Cys-SOH must be taken into account prior to pursuing its study in such matrices.

Background: Carriers of the APOE ε4 allele are at increased risk of developing Alzheimer’s disease (AD), and have been shown to have reduced cerebral metabolic rate of glucose (CMRgl) in the same brain areas frequently affected in AD. These individuals also exhibit reduced plasma levels of apolipoprotein E (apoE) attributed to a specific decrease in the apoE4 isoform as determined by quantification of individual apoE isoforms in APOE ε4 heterozygotes. Whether low plasma apoE levels are associated with structural and functional brain measurements and cognitive performance remains to be investigated.

Methods: Using quantitative mass spectrometry we quantified the plasma levels of total apoE and the individual apoE3 and apoE4 isoforms in 128 cognitively normal APOE ε3/ε4 individuals included in the Arizona APOE cohort. All included individuals had undergone extensive neuropsychological testing and 25 had in addition undergone FDG-PET and MRI to determine CMRgl and regional gray matter volume (GMV).

Results: Our results demonstrated higher apoE4 levels in females versus males and an age-dependent increase in the apoE3 isoform levels in females only. Importantly, a higher relative ratio of apoE4 over apoE3 was associated with GMV loss in the right posterior cingulate and with reduced CMRgl bilaterally in the anterior cingulate and in the right hippocampal area. Additional exploratory analysis revealed several negative associations between total plasma apoE, individual apoE isoform levels, GMV and CMRgl predominantly in the frontal, occipital and temporal areas. Finally, our results indicated only weak associations between apoE plasma levels and cognitive performance which further appear to be affected by sex.

Conclusions: Our study proposes a sex-dependent and age-dependent variation in plasma apoE isoform levels and concludes that peripheral apoE levels are associated with GMV, CMRgl and possibly cognitive performance in cognitively healthy individuals with a genetic predisposition to AD.

Background: We introduced a hypometabolic convergence index (HCI) to characterize in a single measurement the extent to which a person’s fluorodeoxyglucose positron emission tomogram (FDG PET) corresponds to that in Alzheimer’s disease (AD). Apolipoprotein E ε4 (APOE ε4) gene dose is associated with three levels of risk for late-onset AD. We explored the association between gene dose and HCI in cognitively normal ε4 homozygotes, heterozygotes, and non-carriers.

Methods: An algorithm was used to characterize and compare AD-related HCIs in cognitively normal individuals, including 36 ε4 homozygotes, 46 heterozygotes, and 78 non-carriers.

Results: These three groups differed significantly in their HCIs (ANOVA, p = 0.004), and there was a significant association between HCIs and gene dose (linear trend, p = 0.001).

Conclusions: The HCI is associated with three levels of genetic risk for late-onset AD. This supports the possibility of using a single FDG PET measurement to help in the preclinical detection and tracking of AD.

We use Spain’s Equality Law to test for the existence of agency problems between party leaders and their constituents. The law mandates a 40 percent female quota on electoral lists in towns with populations above 5,000. Using pre- and postquota data by party and municipality, we implement a triple-difference design. We find that female quotas resulted in slightly better electoral results for the parties that were most affected by the quota. Our evidence shows that party leaders were not maximizing electoral results prior to the quota, suggesting the existence of agency problems that hinder female representation in political institutions.

Reliable estimates of the impacts and costs of biological invasions are critical to developing credible management, trade and regulatory policies. Worldwide, forests and urban trees provide important ecosystem services as well as economic and social benefits, but are threatened by non-native insects. More than 450 non-native forest insects are established in the United States but estimates of broad-scale economic impacts associated with these species are largely unavailable. We developed a novel modeling approach that maximizes the use of available data, accounts for multiple sources of uncertainty, and provides cost estimates for three major feeding guilds of non-native forest insects. For each guild, we calculated the economic damages for five cost categories and we estimated the probability of future introductions of damaging pests. We found that costs are largely borne by homeowners and municipal governments. Wood- and phloem-boring insects are anticipated to cause the largest economic impacts by annually inducing nearly $1.7 billion in local government expenditures and approximately $830 million in lost residential property values. Given observations of new species, there is a 32% chance that another highly destructive borer species will invade the U.S. in the next 10 years. Our damage estimates provide a crucial but previously missing component of cost-benefit analyses to evaluate policies and management options intended to reduce species introductions. The modeling approach we developed is highly flexible and could be similarly employed to estimate damages in other countries or natural resource sectors.

Purpose: PET (positron emission tomography) imaging researches of functional metabolism using fluorodeoxyglucose ([superscript 18]F-FDG) of animal brain are important in neuroscience studies. FDG-PET imaging studies are often performed on groups of rats, so it is desirable to establish an objective voxel-based statistical methodology for group data analysis.

Material and Methods: This study establishes a statistical parametric mapping (SPM) toolbox (plug-ins) named spmratIHEP for voxel-wise analysis of FDG-PET images of rat brain, in which an FDG-PET template and an intracranial mask image of rat brain in Paxinos & Watson space were constructed, and the default settings were modified according to features of rat brain. Compared to previous studies, our constructed rat brain template comprises not only the cerebrum and cerebellum, but also the whole olfactory bulb which made the later cognitive studies much more exhaustive. And with an intracranial mask image in the template space, the brain tissues of individuals could be extracted automatically. Moreover, an atlas space is used for anatomically labeling the functional findings in the Paxinos & Watson space. In order to standardize the template image with the atlas accurately, a synthetic FDG-PET image with six main anatomy structures is constructed from the atlas, which performs as a target image in the co-registration.

Results: The spatial normalization procedure is evaluated, by which the individual rat brain images could be standardized into the Paxinos & Watson space successfully and the intracranial tissues could also be extracted accurately. The practical usability of this toolbox is evaluated using FDG-PET functional images from rats with left side middle cerebral artery occlusion (MCAO) in comparison to normal control rats. And the two-sample t-test statistical result is almost related to the left side MCA.

Conclusion: We established a toolbox of SPM8 named spmratIHEP for voxel-wise analysis of FDG-PET images of rat brain.

Theory suggests that human behavior has implications for disease spread. We examine the hypothesis that individuals engage in voluntary defensive behavior during an epidemic. We estimate the number of passengers missing previously purchased flights as a function of concern for swine flu or A/H1N1 influenza using 1.7 million detailed flight records, Google Trends, and the World Health Organization's FluNet data. We estimate that concern over “swine flu,” as measured by Google Trends, accounted for 0.34% of missed flights during the epidemic. The Google Trends data correlates strongly with media attention, but poorly (at times negatively) with reported cases in FluNet. Passengers show no response to reported cases. Passengers skipping their purchased trips forwent at least $50 M in travel related benefits. Responding to actual cases would have cut this estimate in half. Thus, people appear to respond to an epidemic by voluntarily engaging in self-protection behavior, but this behavior may not be responsive to objective measures of risk. Clearer risk communication could substantially reduce epidemic costs. People undertaking costly risk reduction behavior, for example, forgoing nonrefundable flights, suggests they may also make less costly behavior adjustments to avoid infection. Accounting for defensive behaviors may be important for forecasting epidemics, but linking behavior with epidemics likely requires consideration of risk communication.

Serum Amyloid A (SAA) is an acute phase protein complex consisting of several abundant isoforms. The N- terminus of SAA is critical to its function in amyloid formation. SAA is frequently truncated, either missing an arginine or an arginine-serine dipeptide, resulting in isoforms that may influence the capacity to form amyloid. However, the relative abundance of truncated SAA in diabetes and chronic kidney disease is not known.

Methods: Using mass spectrometric immunoassay, the abundance of SAA truncations relative to the native variants was examined in plasma of 91 participants with type 2 diabetes and chronic kidney disease and 69 participants without diabetes.

Results: The ratio of SAA 1.1 (missing N-terminal arginine) to native SAA 1.1 was lower in diabetics compared to non-diabetics (p = 0.004), and in males compared to females (p<0.001). This ratio was negatively correlated with glycated hemoglobin (r = −0.32, p<0.001) and triglyceride concentrations (r = −0.37, p<0.001), and positively correlated with HDL cholesterol concentrations (r = 0.32, p<0.001).

Conclusion: The relative abundance of the N-terminal arginine truncation of SAA1.1 is significantly decreased in diabetes and negatively correlates with measures of glycemic and lipid control.

We present a novel paradigm to identify shared and unique brain regions underlying non-semantic, non-phonological, abstract, audio-visual (AV) memory vs. naming using a longitudinal functional magnetic resonance imaging experiment. Participants were trained to associate novel AV stimulus pairs containing hidden linguistic content. Half of the stimulus pairs were distorted images of animals and sine-wave speech versions of the animal's name. Images and sounds were distorted in such a way as to make their linguistic content easily recognizable only after being made aware of its existence. Memory for the pairings was tested by presenting an AV pair and asking participants to verify if the two stimuli formed a learned pairing. After memory testing, the hidden linguistic content was revealed and participants were tested again on their recollection of the pairings in this linguistically informed state. Once informed, the AV verification task could be performed by naming the picture. There was substantial overlap between the regions involved in recognition of non-linguistic sensory memory and naming, suggesting a strong relation between them. Contrasts between sessions identified left angular gyrus and middle temporal gyrus as key additional players in the naming network. Left inferior frontal regions participated in both naming and non-linguistic AV memory suggesting the region is responsible for AV memory independent of phonological content contrary to previous proposals. Functional connectivity between angular gyrus and left inferior frontal gyrus and left middle temporal gyrus increased when performing the AV task as naming. The results are consistent with the hypothesis that, at the spatial resolution of fMRI, the regions that facilitate non-linguistic AV associations are a subset of those that facilitate naming though reorganized into distinct networks.

The number and variety of connectivity estimation methods is likely to continue to grow over the coming decade. Comparisons between methods are necessary to prune this growth to only the most accurate and robust methods. However, the nature of connectivity is elusive with different methods potentially attempting to identify different aspects of connectivity. Commonalities of connectivity definitions across methods upon which base direct comparisons can be difficult to derive. Here, we explicitly define “effective connectivity” using a common set of observation and state equations that are appropriate for three connectivity methods: dynamic causal modeling (DCM), multivariate autoregressive modeling (MAR), and switching linear dynamic systems for fMRI (sLDSf). In addition while deriving this set, we show how many other popular functional and effective connectivity methods are actually simplifications of these equations. We discuss implications of these connections for the practice of using one method to simulate data for another method. After mathematically connecting the three effective connectivity methods, simulated fMRI data with varying numbers of regions and task conditions is generated from the common equation. This simulated data explicitly contains the type of the connectivity that the three models were intended to identify. Each method is applied to the simulated data sets and the accuracy of parameter identification is analyzed. All methods perform above chance levels at identifying correct connectivity parameters. The sLDSf method was superior in parameter estimation accuracy to both DCM and MAR for all types of comparisons.