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- Covalent Labeling (2)
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- Protein Higher-Order Structural Analysis (2)
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Articles 1 - 13 of 13
Full-Text Articles in Physical Sciences and Mathematics
Reactive Chemistries For Protein Labeling, Degradation, And Stimuli Responsive Delivery, Myrat Kurbanov
Reactive Chemistries For Protein Labeling, Degradation, And Stimuli Responsive Delivery, Myrat Kurbanov
Doctoral Dissertations
Reactive chemistries for protein chemical modification play an instrumental role in chemical biology, proteomics, and therapeutics. Depending on the application, the selectivity of these modifications can range from precise modification of an amino acid sequence by genetic manipulation of protein expression machinery to a stochastic modification of lysine residues on the protein surface. Ligand-Directed (LD) chemistry is one of the few methods for targeted modification of endogenous proteins without genetic engineering. However, current LD strategies are limited by stringent amino acid selectivity. To bridge this gap, this thesis focuses on the development of highly reactive LD Triggerable Michael Acceptors (LD-TMAcs) …
Unobtrusive Assessment Of Upper-Limb Motor Impairment Using Wearable Inertial Sensors, Brandon R. Oubre
Unobtrusive Assessment Of Upper-Limb Motor Impairment Using Wearable Inertial Sensors, Brandon R. Oubre
Doctoral Dissertations
Many neurological diseases cause motor impairments that limit autonomy and reduce health-related quality of life. Upper-limb motor impairments, in particular, significantly hamper the performance of essential activities of daily living, such as eating, bathing, and changing clothing. Assessment of impairment is necessary for tracking disease progression, measuring the efficacy of interventions, and informing clinical decision making. Impairment is currently assessed by trained clinicians using semi-quantitative rating scales that are limited by their reliance on subjective, visual assessments. Furthermore, existing scales are often burdensome to administer and do not capture patients' motor performance in home and community settings, resulting in a …
Frontiers In The Self-Assembly Of Charged Macromolecules, Khatcher O. Margossian
Frontiers In The Self-Assembly Of Charged Macromolecules, Khatcher O. Margossian
Doctoral Dissertations
The self-assembly of charged macromolecules forms the basis of all life on earth. From the synthesis and replication of nucleic acids, to the association of DNA to chromatin, to the targeting of RNA to various cellular compartments, to the astonishingly consistent folding of proteins, all life depends on the physics of the organization and dynamics of charged polymers. In this dissertation, I address several of the newest challenges in the assembly of these types of materials. First, I describe the exciting new physics of the complexation between polyzwitterions and polyelectrolytes. These materials open new questions and possibilities within the context …
Deciphering Protein Higher-Order Structure And Interactions Via Diethylpyrocarbonate Labeling-Mass Spectrometry, Xiao Pan
Doctoral Dissertations
The study of protein higher-order structures is vital because it is closely related to the investigation of protein folding, aggregation, interaction and protein therapeutics. Consequently, numerous biochemical and biophysical tools have been developed to study protein higher-order structures in many different situations. The combination of covalent labeling (CL) and mass spectrometry (MS) has emerged as a powerful tool for studying protein structures and offers many advantages over other traditional techniques, such as better structural coverage, high throughput, high sensitivity, and the ability to study proteins in mixtures. This dissertation focuses on diethylpyrocarbonate (DEPC) as an effective CL reagent that can …
Decision-Analytic Models Using Reinforcement Learning To Inform Dynamic Sequential Decisions In Public Policy, Seyedeh Nazanin Khatami
Decision-Analytic Models Using Reinforcement Learning To Inform Dynamic Sequential Decisions In Public Policy, Seyedeh Nazanin Khatami
Doctoral Dissertations
We developed decision-analytic models specifically suited for long-term sequential decision-making in the context of large-scale dynamic stochastic systems, focusing on public policy investment decisions. We found that while machine learning and artificial intelligence algorithms provide the most suitable frameworks for such analyses, multiple challenges arise in its successful adaptation. We address three specific challenges in two public sectors, public health and climate policy, through the following three essays. In Essay I, we developed a reinforcement learning (RL) model to identify optimal sequence of testing and retention-in-care interventions to inform the national strategic plan “Ending the HIV Epidemic in the US”. …
High-Dimensional Feature Selection And Multi-Level Causal Mediation Analysis With Applications To Human Aging And Cluster-Based Intervention Studies, Hachem Saddiki
Doctoral Dissertations
Many questions in public health and medicine are fundamentally causal in that our objective is to learn the effect of some exposure, randomized or not, on an outcome of interest. As a result, causal inference frameworks and methodologies have gained interest as a promising tool to reliably answer scientific questions. However, the tasks of identifying and efficiently estimating causal effects from observed data still pose significant challenges under complex data generating scenarios. We focus on (1) high-dimensional settings where the number of variables is orders of magnitude higher than the number of observations; and (2) multi-level settings, where study participants …
Design Of Resposive Oligomeric And Polymeric Interfaces For Sensing And Controlled Release Applications, . Manisha
Doctoral Dissertations
Nature has designed magnificent responsive systems by constructing several interacting molecular level networks for the recognition and propagation of chemical and biochemical information. One of the eminent characteristics of these systems is their capability to quickly transduce molecular scale recognition events into macroscopic or visually observable responses. Inspired by these systems present in nature, we became interested in developing artificial responsive systems with similar capabilities. This dissertation will feature four such systems that employ amphiphilic oligomers and polymers which were chosen as the scaffolds because of their high thermodynamic stability, low critical aggregation concentrations, convenient handles to incorporate functional group …
Structural Analysis Of Protein Therapeutics Using Covalent Labeling – Mass Spectrometry, Patanachai Limpikirati
Structural Analysis Of Protein Therapeutics Using Covalent Labeling – Mass Spectrometry, Patanachai Limpikirati
Doctoral Dissertations
Using mass spectrometry (MS) to obtain information about a higher order structure of protein requires that a protein’s structural properties are encoded into the mass of that protein. Covalent labeling (CL) with reagents that can irreversibly modify solvent accessible amino acid side chains is an effective way to encode structural information into the mass of a protein, as this information can be read-out in a straightforward manner using standard MS-based proteomics techniques. The differential reactivity of proteins under two or more conditions can be used to distinguish protein topologies, conformations, and/or binding sites. CL-MS methods have been effectively used for …
Protein Detection And Structural Characterization By Mass Spectrometry Using Supramolecular Assemblies And Small Molecules, Bo Zhao
Doctoral Dissertations
Mass spectrometry (MS) has played an increasingly prominent role in proteomics and structure biology because it shows superior capabilities in identification, quantification and structural characterization of proteins. To realize its full potential in protein analysis, significant progress has been made in developing innovative techniques and reagents that can couple to MS detection. This dissertation demonstrates the use of polymeric supramolecular assemblies for enhanced protein detection in complex biological mixtures by MS. An amphiphilic random co-polymer scaffold is developed to form functional supramolecular assemblies for protein/ peptide enrichment. The influences of charge density and functional group pKa on host-guest interactions …
Game-Assisted Rehabilitation For Post-Stroke Survivors, Hee-Tae Jung
Game-Assisted Rehabilitation For Post-Stroke Survivors, Hee-Tae Jung
Doctoral Dissertations
Stroke is a leading cause of permanent impairments among its survivors. Although patients need to go through intensive, longitudinal rehabilitation to regain function before the stroke, patients show poor engagement and adherence to rehabilitation therapies which hampers their recovery. As a means to enhance stroke survivors' motivation, engagement, and adherence to intensive and longitudinal rehabilitation, the use of games in stroke rehabilitation has received attention from research and clinical communities. In order to realize this, it is important to take a holistic, end-to-end research approach that encompasses 1) the development of game technologies that are not only entertaining but also …
Model-Based Guidance For Human-Intensive Processes, Stefan Christov
Model-Based Guidance For Human-Intensive Processes, Stefan Christov
Doctoral Dissertations
Human-intensive processes (HIPs), such as medical processes involving coordination among doctors, nurses, and other medical staff, often play a critical role in society. Despite considerable work and progress in error reduction, human errors are still a major concern for many HIPs. To address this problem of human errors in HIPs, this thesis investigates two approaches for online process guidance, i.e., for guiding process performers while a process is being executed. Both approaches rely on monitoring a process execution and base the guidance they provide on a detailed formal process model that captures the recommended ways to perform the corresponding HIP. …
Evaluating Predictors Of An Individual’S Dietary Intake Latent Value Under Different Mixed Models, Shuli Yu
Evaluating Predictors Of An Individual’S Dietary Intake Latent Value Under Different Mixed Models, Shuli Yu
Doctoral Dissertations
The accurate estimation of an individual’s usual dietary intake is important since the estimates are essential to uncover the diet-disease relationships. This study explores a more accurate method to estimate an individual’s latent value of usual dietary intake when it is repeatedly measured using a 24-hour dietary recall (24HR) and seven day dietary recall (7DDR), accounting for random measurement error and bias. The performance of the (empirical) predictor of subject’s latent value obtained under the finite population mixed model (FPMM) framework is compared with those obtained under the usual mixed model and the measurement error model through a simulation study. …
Ligand-Receptor Interactions For Supramolecular Disassembly With Applications In Screening And Drug Delivery, Diego Amado Torres
Ligand-Receptor Interactions For Supramolecular Disassembly With Applications In Screening And Drug Delivery, Diego Amado Torres
Doctoral Dissertations
Proteins have the capacity to bind specific sets of compounds known as ligands, these are small molecules with a recurrent theme in their molecular design that is a characteristic exploited here to (i) identify particular affinities of small molecules for proteins with the aim of using them as ligands, inhibitors, or targeting moieties in more complex systems by means of a methodology that screens small molecules based on protein affinity; (ii) decorate a self-assembling supramolecular system at different positions, making it responsive to a complementary protein with the aim of exploring differences in disassembly and sensitivity of the release of …