Mason Journals (George Mason Univ.)
Not a member yet
3256 research outputs found
Sort by
Optimization of RPPA Protocols for FFPE Tissue: A Comparison of Protein Extraction, Protein Printing, and Total Protein Staining Methods
No full textReverse Phase Protein Array (RPPA) is a technique that microprints proteins from a given sample onto a nitrocellulose coated slide, and utilizes specific antibodies to measure protein expression. These arrays can be constructed using proteins extracted from a variety of sample materials such as formalin-fixed paraffin-embedded (FFPE) tissue. However, there has been debate over the reproducibility of methods used to extract proteins and break formaldehyde cross-links of FFPE tissue for downstream analysis. Currently, the CAPMM lab constructs RPPAs using solid-pin printing, but are in the process of introducing a new inkjet style printing process in addition to a new laser scanning system. The new printing process deposits a smaller amount of total protein per spot on the microarrays, which can make high backgrounds problematic for data analysis. Additionally, the new laser scanning system is not compatible with the current total protein stain, and the high sample background that is frequently observed with FFPE extracted protein can be obstructive for total protein normalization and downstream analysis. These issues require modified protocols for protein extraction, sample printing, and total protein staining. In this experiment, RRPA arrays were constructed using protein from FFPE tissue collected via Laser Capture Microdissection (LCM) to compare the new printing process, extraction buffer, and new total protein stain with current protocols. The results of this experiment showed that the inkjet printing process produces smaller spots, thus reduces total protein printed. Overall, a decreased background was observed in Fast Green vs. SYPRO Ruby Red total protein staining. Finally, reduced background from TCEP vs. Qproteome® buffer extracted protein showed mixed results. These findings will help improve in-house modification of current protocols
Designing payload hardware and interfaces for the Landolt NASA Space Mission
No full textThe NASA Landolt Space Mission aims to put an artificial star in space in geosynchronous orbit, allowing scientists to calibrate ground telescopes to accurately measure the brightness of stars and understand the accelerating expansion of the universe, fundamental properties of stars such as age and radius, and the sizes and habitability of exoplanets. To achieve this, Landolt’s payload includes a laser module, which requires a photodiode printed circuit board (PCB) unit to measure light intensity by producing an electric current. However, as the Landolt Mission takes place outside Earth’s protective atmosphere, the payload components risk exposure to ionizing radiation. As existing photodiode PCB units do not contain radiation-hardened components, we custom-made our own PCB with radiation-hardened components. To visualize the board design, we developed a 3D design of the PCB, and started with making a 3D model of a radiation-hardened LMP7704-SP ceramic flatpack, a type of integrated circuit packaging used when high thermal and electrical performance is required. We gathered its dimensions from Texas Instruments, and developed the model with the FreeCAD software. Specifically, the LMP7704-SP ceramic flatpack acts as an amplifier for the photodiode PCB, by taking in a small signal and enhancing it. Additionally, to ensure all interfaces of the Landolt Mission correspond with one another—like the payload to the spacecraft bus, for example—Interface Control Documents (ICD) must be drafted. ICDs define the functional, electrical, mechanical, and data interfaces between systems to ensure compatibility and integration. The six ICDs are as follows: Payload to Spacecraft Bus, Payload to Launch Services, Payload to Ground Systems, Payload to Ground Calibration, Tech Demos to Payload, and Science Operations Center to Observatories and Archives. We initiated drafting the six ICDs for the six mission interfaces in compliance with the Landolt mission requirements, NASA NPR 7120.8 and NPR 7120.5 guidelines, and the NASA Interface Management documents
Measuring plasma velocities in Coronal loops using Hinode/EIS spectroscopic data to constrain eruption models
No full textMagnetic loops in the outer solar atmosphere (corona) contain plasma heated to approximately 1-6 MK and are fundamental to understanding space weather. Eruptions from these structures can cause significant terrestrial impacts, such as geomagnetic storms and disruptions to communication satellites and power grids. While the long-term goal is to predict these events, current computational models, which utilize conservation of mass, momentum, and energy, first require in-depth observational data to accurately represent the underlying physical processes. The most significant parameters for these models include plasma temperature, density, and, most critically, velocity fields, which are direct indicators of energy transport and instability triggers.
In this study, we provide such observational constraints by measuring plasma velocities within manually identified coronal loops. We use extreme-ultraviolet spectroscopic data from the EUV Imaging Spectrometer (EIS) on the Hinode satellite. By creating and using our very own Python-based analysis tool, developed with the help of the EISPAC module, we interpret Doppler shifts in the spectroscopic data to derive line-of-sight plasma velocities across a temperature range of 500,000 to 6,000,000 Kelvin. These measurements are designed to be inputted into existing theoretical models to test and refine our understanding of the heating and eruption mechanisms in these loops. The results of our velocity measurements, categorized by loop structure, loop position, and plasma formation temperature, will be presented, providing an important dataset for benchmarking magnetohydrodynamic (MHD) simulations
Characterization of a Peptide Amphiphile Hydrogel Model System
No full textOrganic phase change materials (PCM) release large quantities of heat during phase changes and can store significant amounts of thermal energy. Unlike inorganic PCMs, which are commonly used to store thermal energy in buildings, organic PCMs show potential for biomedical applications. Current PCMs, including fatty acids or paraffins, can be difficult to synthesize, exhibit low tunability, or display poor physical properties. One prospective PCM, peptide-amphiphiles (PA), may show enhanced tunability and a simplified synthesis. Experimental PAs contained a lipid tail bound to a short peptide containing between 0 and 5 leucine residues. PAs were synthesized using an automated peptide synthesizer, purified by HPLC, and their purity was confirmed by MALDI-MS analysis. The efficacy of PAs as PCMs can be evaluated by determining the critical gelation concentration (CGC), or the concentration of peptide required to form a hydrogel, using a dilution assay. Based on preliminary data, it is anticipated that the CGC will be between 4 and 10% weight. To observe the influence of pH and the number of leucine residues on micelle formation, a fluorescence-based critical micelle concentration (CMC) assay was conducted using the micelle sensitive dye 1,6-diphenyl-1,3,5-hexatriene. Increased pH and peptide length decreased the CMC. Compiling CGC and CMC data will provide valuable information about the effect of modifying the quantity of leucine residues on PA properties and the ability of PAs to act as PCMs. These tunable PA hydrogels could be applied in biomedical settings to improve drug delivery or wound healing
Improving Heart Transplant Outcomes via Statistical Modeling of Mortality
No full textEach year, the Organ Procurement and Transplant Network (OPTN) transplants only about one-third of potential donor hearts, often due to concerns about organ function or difficulties matching organs to suitable patients in time. To address this underutilization and improve post-transplant outcomes, a logistic regression model trained on data from the Scientific Registry of Transplant Recipients (SRTR) was used to predict one-year post-transplant mortality. A Cox proportional hazards model was also fit to estimate patient mortality risk while on the waitlist. This model was integrated into a discrete-event simulation model reflecting OPTN allocation policies, using SRTR patient and organ data from 2006–2018. The simulated allocation policy would determine the highest priority candidate whose risk from waiting exceeded the risk of post-transplant one-year mortality. The simulation showed approximately a 33% increase in hearts transplanted per donor and a 90% reduction in average waiting time. These results suggest that predictive modeling can help optimize heart allocation and could be incorporated into current organ evaluation workflows to speed up and improve matching decisions
Evaluating the Impact of Traffic Control Measures on the Severity of School Zone Crashes in Virginia
No full textVirginia crash data is a detailed collection of records managed by the Virginia Department of Motor Vehicles (DMV) which documents all the crashes within the state from 2017-present. It includes information about crash location, time, severity of crash, and other details to support traffic safety improvements. This analysis focuses on crashes happening in a school zone because of its relevance to my daily life. This research examines the potential impact of traffic control type (excluding traffic lanes) on the severity of crash within the school zone. To analyze the severity of crashes occurring within school zones, the variable crash severity is treated as an ordinal dependent variable. A ranked logistic regression model is utilized in STATA to evaluate different types of traffic control (excluding traffic lanes) and the likelihood of reducing severe crashes. Control variables such as: time, road condition, weather, etc. will also be included to improve model accuracy.
This study aims to identify the relationship between traffic control measure and the crashes severity in school zones. While results are still being finalized, the findings will be beneficial in informing better traffic safety strategies which will protect young pedestrians and student drivers
Special Education Teacher Preparation and Inclusive Postsecondary Education: Effects of a Peer Mentorship Field Experience
No full textStudents with intellectual and developmental disabilities (SWIDD) often require academic, employment, and social support to be successful in inclusive postsecondary education programs. One way to provide support in these areas is via peer mentorship. In addition to SWIDD obtaining the support they need; peer mentors also benefit from the relationships that are established. This qualitative case study examined the impacts of a peer mentorship program associated with an inclusive postsecondary education program on Special Education Teacher Candidates (SETCs). The program existed as a service-learning portion of a course focused on secondary special education. Key findings included: 1) SETCs developed a better sense of disability; 2) learned to see SWIDD as peers; and 3) made connections to the importance of transition planning for students even while in elementary school. Based on the findings of this study, those who prepare special education teachers should consider providing SETCs with opportunities to work with SWIDD in inclusive postsecondary education settings. 
2024 State of the Art Leadership Awards
No full textThe Journal of Inclusive Postsecondary Education would like to recognize the following awardees for their contributions to the field. Each honoree received their award at the 2024 State of the Art Conference in Inclusive Postsecondary Education, held in Chapel Hill, North Carolina
