Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging of ZP1609 and Amyloid Beta

The revolutionary development of soft ionization techniques like matrix-assisted laser desorption/ionization (MALDI) has opened up the possibilities for mass spectrometry (MS) in protein detection, identification, and sequencing. The ability of MALDI MS to acquire images of intact tissue sections offer an additional dimension of analysis where location information can be attained. Visualization of biological systems help to unravel the complexities of cells, drug pathways, and disease pathology. However, the capabilities of MALDI MS imaging are often being questioned, as signals are typically biased towards the most abundant component within a complex sample. Within biological tissue samples, the most abundant components are salts and lipids making it difficult for compounds such as proteins and peptides to ionize and be detected. In this thesis, sample preparation techniques are investigated to help improve the detection sensitivity of MALDI MSI for proteins and peptides through investigation of ZP1609 and the amyloid ß (Aß) protein. ZP1609 is an antiarrhythmic drug designed to protect against cardiac ischemia-reperfusion injury, and Aß oligomers are strongly correlated with Alzheimer’s disease (AD) pathology. Both of which are considered lower abundance compounds within samples analyzed, and therefore ideal candidates for the work described herein. This thesis presents MALDI MS capabilities in the detection of noncovalent complexes by distinguishing variations in in vitro Aß composition for different sample preparatory procedures. Furthermore, a reduction in ion suppression effects by salts and lipids was demonstrated with increased MALDI MSI detection sensitivity for the target peptide. Most noticeably, an additional acidification protocol generated images of greater detection sensitivity, and spatial resolution. Introduction of solid-phase extraction (SPE) by means of magnetic bead application was designed to improve the extraction of proteins from tissue sections. The C18 functionalized magnetic beads provided signal enhancement capabilities for varying concentrations of Aß1-42 samples, however difficulties were encountered when applied for MALDI MSI analysis. Nonetheless, the application of SPE for targeted analyte extraction prior to MALDI MS analysis was beneficial in improving detection sensitivity of Aß proteins with and without the presence of contaminants from tissue sections

Improved Ballast Recovery in Water Treatment

SUEZ Environnement’s Densadeg XRC™ is a high throughput water clarification unit capable of removing total suspended solids (TSS) with the aid of a high density ballast material. The ballast material is separated from the waste solids through a hydrocyclone and recycled into the system. Separation is inefficient and the unit experiences loss of ballast at 7 to 14 lbs per million gallons of treated water through the overflow of the hydrocyclone. Currently, ballast must be added at the loss rate to maintain the proper concentration to remove TSS. This requires that water treatment plants must provide storage space for ballast material, manpower to add the ballast, and a method to measure ballast concentration. To recover ballast material, a scale model of the overflow of the hydrocyclone was constructed and an angled pipe was added to settle the ballast into a collection sump. The effects of angle and linear flow velocity in the settling pipe were tested in a Design of Experiment (DOE) analysis to determine the critical process parameters. The maximum linear velocity in the settling pipe to settle ballast was also determined and used as the design criteria for the pilot scale. The results of this study will provide a basis for engineers from SUEZ to begin a long-term study of the economic impacts of using this ballast recovery method. Success in this project will allow SUEZ to provide this solution as an addition to the existing and future Densadeg XRC™ units.https://scholarscompass.vcu.edu/capstone/1088/thumbnail.jp

Growing Pains or Confidence? CEO Relative Age, Stress, and Firm Performance

CEOs face tremendous stress at work. Motivated by the psychological literature that self-efficacy helps people overcome stress, we examine if the self-efficacy of CEOs alleviates their stress and improves their firms’ performance. Using CEOs’ relative age, i.e., age in kindergarten due to state-level eligibility cutoff date, as a proxy for the CEOs’ self-efficacy, we find that CEOs with higher self-efficacy generate better firm performance, especially in high-stress situations such as industry downturn, expansion into a new sector, mergers and acquisitions, and innovation. While existing literature documents negative impacts of CEO overconfidence, our findings suggest that the confidence of CEOs can be beneficial to their firms

Connections between Pre-service Teachers’ Mathematical Dispositions and Self-efficacy for Teaching Mathematics

Mathematical dispositions (MD) and self-efficacy for teaching mathematics (SEFTM) are important elements of teachers‟ beliefs that significantly influence their behaviors and educational practices in the classroom. This study looked at relationships between pre-service teachers‟ (PSTs) MD and their SEFTM in connection with other descriptors related to their progress through the teacher education program and prior mathematical experiences. Survey data were collected from 238 PSTs at a midsized university in the US. Results include the finding that PSTs‟ intended grade-level and subject approximately mirror their MD and SEFTM: those planning to be elementary school (generalist) teachers were slightly behind both middle and high school teachers, who had more positive MD, while both elementary and middles school PSTs were slightly behind high school-level mathematics content PSTs, who had the greatest SEFTM. Additionally, MD was a strong predictor of SEFTM, and both MD and SEFTM appear to be mediated by the influence upon PSTs of their prior mathematics teachers. Implications for teacher education and avenues for further research into these associations are offered

Does stroke location predict walk speed response to gait rehabilitation?

Objectives Recovery of independent ambulation after stroke is a major goal. However, which rehabilitation regimen best benefits each individual is unknown and decisions are currently made on a subjective basis. Predictors of response to specific therapies would guide the type of therapy most appropriate for each patient. Although lesion topography is a strong predictor of upper limb response, walking involves more distributed functions. Earlier studies that assessed the cortico-spinal tract (CST) were negative, suggesting other structures may be important. Experimental Design: The relationship between lesion topography and response of walking speed to standard rehabilitation was assessed in 50 adult-onset patients using both volumetric measurement of CST lesion load and voxel-based lesion–symptom mapping (VLSM) to assess non-CST structures. Two functional mobility scales, the functional ambulation category (FAC) and the modified rivermead mobility index (MRMI) were also administered. Performance measures were obtained both at entry into the study (3–42 days post-stroke) and at the end of a 6-week course of therapy. Baseline score, age, time since stroke onset and white matter hyperintensities score were included as nuisance covariates in regression models. Principal Observations: CST damage independently predicted response to therapy for FAC and MRMI, but not for walk speed. However, using VLSM the latter was predicted by damage to the putamen, insula, external capsule and neighbouring white matter. Conclusions Walk speed response to rehabilitation was affected by damage involving the putamen and neighbouring structures but not the CST, while the latter had modest but significant impact on everyday functions of general mobility and gait

Detection of Amyloid Beta (Aβ) Oligomeric Composition Using Matrix-Assisted Laser Desorption Ionization Mass Spectrometry (MALDI MS).

The use of MALDI MS as a fast and direct method to detect the Aβ oligomers of different masses is examined in this paper. Experimental results suggest that Aβ oligomers are ionized and detected as singly charged ions, and thus, the resulting mass spectrum directly reports the oligomer size distribution. Validation experiments were performed to verify the MS data against artifacts. Mass spectra collected from modified Aβ peptides with different propensities for aggregation were compared. Generally, the relative intensities of multimers were higher from samples where oligomerization was expected to be more favorable, and vice versa. MALDI MS was also able to detect the differences in oligomeric composition before and after the incubation/oligomerization step. Such differences in sample composition were also independently confirmed with an in vitro Aβ toxicity study on primary rat cortical neurons. An additional validation was accomplished through removal of oligomers from the sample using molecular weight cutoff filters; the resulting MS data correctly reflected the removal at the expected cutoff points. The results collectively validated the ability of MALDI MS to assess the monomeric/multimeric composition of Aβ samples

Predicting speech fluency and naming abilities in aphasic patients

There is a need to identify biomarkers that predict degree of chronic speech fluency/language impairment and potential for improvement after stroke. We previously showed that the Arcuate Fasciculus lesion load (AF-LL), a combined variable of lesion site and size, predicted speech fluency in patients with chronic aphasia. In the current study, we compared lesion loads of such a structural map (i.e., AF-LL) with those of a functional map [i.e., the functional gray matter lesion load (fGM-LL)] in their ability to predict speech fluency and naming performance in a large group of patients. The fGM map was constructed from functional brain images acquired during an overt speaking task in a group of healthy elderly controls. The AF map was reconstructed from high-resolution diffusion tensor images also from a group of healthy elderly controls. In addition to these two canonical maps, a combined AF-fGM map was derived from summing fGM and AF maps. Each canonical map was overlaid with individual lesion masks of 50 chronic aphasic patients with varying degrees of impairment in speech production and fluency to calculate a functional and structural lesion load value for each patient, and to regress these values with measures of speech fluency and naming. We found that both AF-LL and fGM-LL independently predicted speech fluency and naming ability; however, AF lesion load explained most of the variance for both measures. The combined AF-fGM lesion load did not have a higher predictability than either AF-LL or fGM-LL alone. Clustering and classification methods confirmed that AF lesion load was best at stratifying patients into severe and non-severe outcome groups with 96% accuracy for speech fluency and 90% accuracy for naming. An AF-LL of greater than 4 cc was the critical threshold that determined poor fluency and naming outcomes, and constitutes the severe outcome group. Thus, surrogate markers of impairments have the potential to predict outcomes and can be used as a stratifier in experimental studies

MOPO-LSI: A User Guide

MOPO-LSI is an open-source Multi-Objective Portfolio Optimization Library for Sustainable Investments. This document provides a user guide for MOPO-LSI version 1.0, including problem setup, workflow and the hyper-parameters in configurations