Matching Items (157)
Filtering by
Description
Attitudes and habits are extremely resistant to change, but a disruption of the magnitude of the COVID-19 pandemic has the potential to bring long-term, massive societal changes. During the pandemic, people are being compelled to experience new ways of interacting, working, learning, shopping, traveling, and eating meals. Going forward, a critical question is whether these experiences will result in changed behaviors and preferences in the long term. This paper presents initial findings on the likelihood of long-term changes in telework, daily travel, restaurant patronage, and air travel based on survey data collected from adults in the United States in Spring 2020. These data suggest that a sizable fraction of the increase in telework and decreases in both business air travel and restaurant patronage are likely here to stay. As for daily travel modes, public transit may not fully recover its pre-pandemic ridership levels, but many of our respondents are planning to bike and walk more than they used to. These data reflect the responses of a sample that is higher income and more highly educated than the US population. The response of these particular groups to the COVID-19 pandemic is perhaps especially important to understand, however, because their consumption patterns give them a large influence on many sectors of the economy.
ContributorsConway, Matthew Wigginton (Author) / Salon, Deborah (Author) / da Silva, Denise Capasso (Author) / Mirtich, Laura Christine (Author)
Created2020-09-03
Description
For cold chain tracking systems, precision and versatility across varying time intervals and temperature ranges remain integral to effective application in clinical, commercial, and academic settings. Therefore, while electronic and chemistry/physics based cold chain tracking mechanisms currently exist, both have limitations that affect their application across various biospecimens and commercial products, providing the initiative to develop a time temperature visual indicator system that resolves challenges with current cold chain tracking approaches. As a result, a permanganate/oxalic acid time temperature visual indicator system for cold chain tracking has been proposed. At thawing temperatures, the designed permanganate/oxalic acid reaction system undergoes a pink to colorless transition as permanganate, Mn(VII), is reduced to auto-catalytic Mn(II), while oxalate is oxidized to CO2. Therefore, when properly stored and vitrified or frozen, the proposed visual indicator remains pink, whereas exposure to thawing conditions will result in an eventual, time temperature dependent, designed color transition that characterizes compromised biospecimen integrity. To design visual indicator systems for targeted times at specific temperatures, absorbance spectroscopy was utilized to monitor permanganate kinetic curves by absorbance at 525 nm. As a result, throughout the outlined research, the following aims were demonstrated: (i) Design and functionality of 1x (0.5 mM KMnO4) visual indicator systems across various time intervals at temperatures ranging from 25°C to -20°C, (ii) Design and functionality of high concentration, 5x, visual indicator systems across varying targeted time intervals at temperatures ranging from 25°C to 0°C, (iii) Pre-activation stability and long-term stability of the proposed visual indicator systems.
ContributorsLjungberg, Emil (Author) / Borges, Chad (Thesis advisor) / Levitus, Marcia (Committee member) / Williams, Peter (Committee member) / Arizona State University (Publisher)
Created2024
Description
Insulator-based dielectrophoresis (iDEP) has attracted considerable attention due to its ability to precisely capture and manipulate nanoparticles and biomolecules. A distinctive approach for effective manipulation of nanometer-sized proteins employing iDEP technique by generating higher electric field (E) and gradient (??2) in the iDEP microfluidic devices is delineated. Strategies to generate higher ??2 in the iDEP devices were outlined using numerical simulations. Intriguingly, the numerical simulation results demonstrated that by decreasing the post-to-post gap in the iDEP microfluidic devices, the ??2 was increased by ⁓12 fold. Furthermore, the inclusion of channel constrictions, such as rectangular constriction or curved constriction into the straight channel iDEP microfluidic device led to a significant increase in ??2. In addition, the inclusion of rectangular constrictions in the straight channel iDEP microfluidic device resulted in a greater increase in ??2 compared to the incorporation of curved constrictions in the same device. Moreover, the straight channel device with horizontal post-to-post gap of 20 μm and vertical post-to-post gap of 10 μm generated the lowest ??2 and the ??2 was uniform across the device. The rectangular constriction device with horizontal and vertical post-to-post gap of 5 μm generated the highest ??2 and the ??2 was non-uniform across the device. Subsequently, suitable candidate devices were fabricated using soft lithography as well as high resolution 3D printing and the DEP behavior of ferritin examined under various experimental conditions. Positive streaming DEP could be observed for ferritin at low frequency in the device generating the lowest ??2, whereas at higher frequency of 10 kHz no DEP trapping characteristics were apparent in the same device. Importantly, in the device geometry resulting in the highest ??2 at 10 kHz, labeled ferritin exhibited pDEPtrapping characteristics. This is an indication that the DEP force superseded diffusion and became the dominant force.
ContributorsMAHMUD, SAMIRA (Author) / Ros, Alexandra (Thesis advisor) / Borges, Chad (Committee member) / Mills, Jeremy (Committee member) / Arizona State University (Publisher)
Created2024
Description
Background: Eosinophilic esophagitis (EoE) is an increasingly prevalent allergic disease characterized by eosinophilic inflammation and symptoms of esophageal dysfunction. Diagnosis and monitoring require repeated, invasive endoscopic esophageal biopsies to assess levels of eosinophilic inflammation. Recently, the minimally invasive esophageal string test (EST) has been used collect protein in mucosal secretions as a surrogate for tissue biopsies in monitoring disease activity. From the string, assessment of the eosinophil-associated proteins major basic protein-1 (MBP-1) and eotaxin-3 (Eot3) is used to assess disease activity; however, this requires measurement in a reference laboratory, for which the turnaround time for results exceeds the time required for histopathologic assessment of endoscopic biopsies. In addition, MBP-1 and Eot3 are not markers unique to eosinophils. These obstacles can be overcome by targeting eosinophil peroxidase (EPX), an eosinophil-specific protein, using a rapid point-of-care test. Currently, EPX is measured by a labor-intensive enzyme-linked immunosorbent assay (ELISA), but we sought to optimize a rapid point-of-care test to measure EPX in EST segments.
Methods: We extracted protein from residual EST segments and measured EPX levels by ELISA and a lateral flow assay (LFA).
Results: EPX levels measured by LFA strongly correlated with those quantified by ELISA
(rs = 0.90 {95% CI: 0.8283, 0.9466}). The EPX LFA is comparable to ELISA for measuring EPX levels in ESTs.
Conclusions: The EPX LFA can provide a way to rapidly test EPX levels in ESTs in clinical settings and may serve as a valuable tool to facilitate diagnosis and monitoring of EoE.
ContributorsDao, Adelyn (Author) / Lake, Douglas (Thesis director) / Borges, Chad (Committee member) / Wright, Benjamin (Committee member) / Barrett, The Honors College (Contributor) / School of Molecular Sciences (Contributor) / School of Life Sciences (Contributor)
Created2024-05
Description
Predicting nonlinear dynamical systems has been a long-standing challenge in science. This field is currently witnessing a revolution with the advent of machine learning methods. Concurrently, the analysis of dynamics in various nonlinear complex systems continues to be crucial. Guided by these directions, I conduct the following studies. Predicting critical transitions and transient states in nonlinear dynamics is a complex problem. I developed a solution called parameter-aware reservoir computing, which uses machine learning to track how system dynamics change with a driving parameter. I show that the transition point can be accurately predicted while trained in a sustained functioning regime before the transition. Notably, it can also predict if the system will enter a transient state, the distribution of transient lifetimes, and their average before a final collapse, which are crucial for management. I introduce a machine-learning-based digital twin for monitoring and predicting the evolution of externally driven nonlinear dynamical systems, where reservoir computing is exploited. Extensive tests on various models, encompassing optics, ecology, and climate, verify the approach’s effectiveness. The digital twins can extrapolate unknown system dynamics, continually forecast and monitor under non-stationary external driving, infer hidden variables, adapt to different driving waveforms, and extrapolate bifurcation behaviors across varying system sizes. Integrating engineered gene circuits into host cells poses a significant challenge in synthetic biology due to circuit-host interactions, such as growth feedback. I conducted systematic studies on hundreds of circuit structures exhibiting various functionalities, and identified a comprehensive categorization of growth-induced failures. I discerned three dynamical mechanisms behind these circuit failures. Moreover, my comprehensive computations reveal a scaling law between the circuit robustness and the intensity of growth feedback. A class of circuits with optimal robustness is also identified. Chimera states, a phenomenon of symmetry-breaking in oscillator networks, traditionally have transient lifetimes that grow exponentially with system size. However, my research on high-dimensional oscillators leads to the discovery of ’short-lived’ chimera states. Their lifetime increases logarithmically with system size and decreases logarithmically with random perturbations, indicating a unique fragility. To understand these states, I use a transverse stability analysis supported by simulations.
ContributorsKong, Lingwei (Author) / Lai, Ying-Cheng (Thesis advisor) / Tian, Xiaojun (Committee member) / Papandreou-Suppappola, Antonia (Committee member) / Alkhateeb, Ahmed (Committee member) / Arizona State University (Publisher)
Created2023
Description
Alzheimer’s Disease (AD) is the most common form of dementia affecting the population over the age of 65. AD is characterized clinically by increasing difficulty with memory and language, resulting in a loss of independence. This is due to the presence of two characteristic protein aggregates in the brain: extracellular amyloid plaques and intracellular neurofibrillary tangles (NFTs). Utilizing multiplexed immunofluorescence and dimensional reduction analysis the types of cells present in the hippocampus, the region of the brain most affected by AD, can be explored. Understanding the kinds of cell subtypes present, the mechanism behind how AD develops can be explored. Multiplexed IF was performed on human hippocampus FFPE tissues to detect a total of 37 proteins. Dimensional reduction analysis was performed to identify the four major cell types in the brain: neurons, oligodendrocytes, astrocytes, and microglia. After identifying each cell type, further dimensional reduction analysis was performed within each cell type to identify cell subtypes. A total of 21 neuron, 41 oligodendrocyte, 20 astrocyte, and 22 microglia subtypes were identified. The location of cell subtypes in each region of the hippocampal formation was found to match previous reports, further validating the findings of this project.
ContributorsEllison, Mischa A (Author) / Guo, Jia (Thesis advisor) / Borges, Chad (Committee member) / Mastroeni, Diego (Committee member) / Arizona State University (Publisher)
Created2024
Description
With needs for carbon sequestration and sustainable chemical feedstocks increasing formate stands out as a real possibility in addressing these growing problems. One of the principal issues with positioning formate as the central compound of a bioeconomy is establishing a sustainable and reliable method for producing it. The goal of this project was to take the first steps towards engineering a formate production cell factory in Chlamydomonas reinhardtii by introducing the biosynthetic pathway necessary for the creation of molybdenum cofactor which would later be used as an integral part of the function of a formate dehydrogenase enzyme capable of reducing carbon dioxide to make formate. I was able to get some seemingly successful transformants but unable to confidently confirm whether or not these transformants hardboard the molybdenum cofactor synthesis genes.
ContributorsNikkel, Zachary (Author) / Redding, Kevin (Thesis director) / Ghirlanda, Giovanna (Committee member) / Borges, Chad (Committee member) / Barrett, The Honors College (Contributor) / School of Molecular Sciences (Contributor)
Created2022-05
Description
A notable challenge when assembling synthetic gene circuits is that modularity often fails to function as intended. A crucial underlying reason for this modularity failure is the existence of competition for shared and limited gene expression resources. By designing a synthetic cascading bistable switches (Syn-CBS) circuit in a single strain with two coupled self-activation modules to achieve successive cell fate transitions, nonlinear resource competition within synthetic gene circuits is unveiled. However, in vivo it can be seen that the transition path was redirected with the activation of one switch always prevailing over that of the other, contradictory to coactivation theoretically expected. This behavior is a result of resource competition between genes and follows a ‘winner-takes-all’ rule, where the winner is determined by the relative connection strength between the two modules. Despite investigation demonstrating that resource competition between gene modules can significantly alter circuit deterministic behaviors, how resource competition contributes to gene expression noise and how this noise can be controlled is still an open issue of fundamental importance in systems biology and biological physics. By utilizing a two-gene circuit, the effects of resource competition on protein expression noise levels can be closely studied. A surprising double-edged role is discovered: the competition for these resources decreases noise while the constraint on resource availability adds its own term of noise into the system, denoted “resource competitive” noise. Noise reduction effects are then studied using orthogonal resources. Results indicate that orthogonal resources are a good strategy for eliminating the contribution of resource competition to gene expression noise.
Noise propagation through a cascading circuit has been considered without resource competition. It has been noted that the noise from upstream genes can be transmitted downstream. However, resource competition’s effects on this cascading noise have yet to be studied. When studied, it is found that resource competition can induce stochastic state
switching and perturb noise propagation. Orthogonal resources can remove some of the resource competitive behavior and allow for a system with less noise.
ContributorsGoetz, Hanah Elizabeth (Author) / Tian, Xiaojun (Thesis advisor) / Wang, Xiao (Committee member) / Lai, Ying-Cheng (Committee member) / Arizona State University (Publisher)
Created2022
Description
Most drugs work by binding to receptors on the cell surface. These receptors can then carry the message into the cell and have a wide array of results. However, studying how fast the binding is can be difficult. Current methods involve extracting the receptor and labeling them, but both these steps have issues. Previous works found that binding on the cell surface is accompanied with a small change in cell size, generally an increase. They have also developed an algorithm that can track these small changes without a label using a simple bright field microscope. Here, this relationship is further explored by comparing edge tracking results to a more widely used method, surface plasmon resonance. The kinetic constants found from the two methods are in agreement. No corrections or manipulations were needed to create agreement. The Bland-Altman plots shows that the error between the two methods is about 0.009 s-1. This is about the same error between cells, making it a non-dominant source of error.
ContributorsHunt, Ashley (Author) / Tao, Nongjian (Thesis advisor) / Ros, Alexandra (Committee member) / Borges, Chad (Committee member) / Arizona State University (Publisher)
Created2018
Description
Measuring molecular interaction with membrane proteins is critical for understanding cellular functions, validating biomarkers and screening drugs. Despite the importance, developing such a capability has been a difficult challenge, especially for small molecules binding to membrane proteins in their native cellular environment. The current mainstream practice is to isolate membrane proteins from the cell membranes, which is difficult and often lead to the loss of their native structures and functions. In this thesis, novel detection methods for in situ quantification of molecular interactions with membrane proteins are described.
First, a label-free surface plasmon resonance imaging (SPRi) platform is developed for the in situ detection of the molecular interactions between membrane protein drug target and its specific antibody drug molecule on cell surface. With this method, the binding kinetics of the drug-target interaction is quantified for drug evaluation and the receptor density on the cell surface is also determined.
Second, a label-free mechanically amplification detection method coupled with a microfluidic device is developed for the detection of both large and small molecules on single cells. Using this method, four major types of transmembrane proteins, including glycoproteins, ion channels, G-protein coupled receptors (GPCRs) and tyrosine kinase receptors on single whole cells are studied with their specific drug molecules. The basic principle of this method is established by developing a thermodynamic model to express the binding-induced nanometer-scale cellular deformation in terms of membrane protein density and cellular mechanical properties. Experiments are carried out to validate the model.
Last, by tracking the cell membrane edge deformation, molecular binding induced downstream event – granule exocytosis is measured with a dual-optical imaging system. Using this method, the single granule exocytosis events in single cells are monitored and the temporal-spatial distribution of the granule fusion-induced cell membrane deformation are mapped. Different patterns of granule release are resolved, including multiple release events occurring close in time and position. The label-free cell membrane deformation tracking method was validated with the simultaneous fluorescence recording. And the simultaneous cell membrane deformation detection and fluorescence recording allow the study of the propagation of the granule release-induced membrane deformation along cell surfaces.
First, a label-free surface plasmon resonance imaging (SPRi) platform is developed for the in situ detection of the molecular interactions between membrane protein drug target and its specific antibody drug molecule on cell surface. With this method, the binding kinetics of the drug-target interaction is quantified for drug evaluation and the receptor density on the cell surface is also determined.
Second, a label-free mechanically amplification detection method coupled with a microfluidic device is developed for the detection of both large and small molecules on single cells. Using this method, four major types of transmembrane proteins, including glycoproteins, ion channels, G-protein coupled receptors (GPCRs) and tyrosine kinase receptors on single whole cells are studied with their specific drug molecules. The basic principle of this method is established by developing a thermodynamic model to express the binding-induced nanometer-scale cellular deformation in terms of membrane protein density and cellular mechanical properties. Experiments are carried out to validate the model.
Last, by tracking the cell membrane edge deformation, molecular binding induced downstream event – granule exocytosis is measured with a dual-optical imaging system. Using this method, the single granule exocytosis events in single cells are monitored and the temporal-spatial distribution of the granule fusion-induced cell membrane deformation are mapped. Different patterns of granule release are resolved, including multiple release events occurring close in time and position. The label-free cell membrane deformation tracking method was validated with the simultaneous fluorescence recording. And the simultaneous cell membrane deformation detection and fluorescence recording allow the study of the propagation of the granule release-induced membrane deformation along cell surfaces.
ContributorsZhang, Fenni (Author) / Tao, Nongjian (Thesis advisor) / Chae, Junseok (Committee member) / Borges, Chad (Committee member) / Jing, Tianwei (Committee member) / Wang, Shaopeng (Committee member) / Arizona State University (Publisher)
Created2018