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Multi-tiered system of supports, a focus on academic growth for all: a program evaluation dissertation
Get PDFSubmission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo termsThe student, Keeley Schmid, accepted the attached license on 2025-04-24 at 04:57.The student, Keeley Schmid, submitted this Dissertation for approval on 2025-04-24 at 05:09.This Dissertation was approved for publication on 2025-04-28 at 10:33.DSpace SAF Submission Ingestion Package generated from Vireo submission #21940 on 2025-10-19 at 18:18:57Multi-Tiered System of Supports (MTSS), also referred to as Response to Intervention (RtI), is a framework built around the previous No Child Left Behind (2000) and the National Reading Panel (2000) in accordance with the reauthorized (2004) Individuals with Disabilities Education Improvement Act (IDEIA) (Klinger & Edwards, 2006; Lopez & Mendoza, 2013; Otabia et al., 2019; Stahl, 2016). MTSS follows a system-wide continuum approach of high-quality instruction coordinated with evidence-based interventions to support the needs of all students school-wide (Loftus-Rattan et al., 2023; McCart & Miller, 2019). In more recent times, the Every Student Succeeds Act (2015) moved the term from RtI to MTSS to incorporate not only academic outcomes but also social emotional and behavior supports (Otaiba et al., 2019). The purpose of the research study was to conduct a program evaluation on a single school’s Multi-Tiered System of Supports to determine if the program was leading to adequate academic student growth for all learners, including Culturally and Linguistically Diverse students (CLD). The evaluation took place at Thomas Elementary, one of 34 schools in a high performing Chicago suburban school district where 29 of the 31 rated schools were designated commendable or exemplary on the Illinois Report Card (Illinois State Board of Education, 2023). The program evaluation reviewed the fidelity of the system implementation, CLD students’ success in the program, and analyzed staff’s perception of the program, including their perspective on student success. Additionally, the review will provide a rationale for conducting the program evaluation at Thomas Elementary, including a comprehensive review of relevant literature on the historical context of MTSS, the methodology and research design in specific detail, as well as the findings and analysis of the evaluation as well as future recommendations
Efficient machine learning-based modeling for regional reliability analysis of infrastructure systems
No full textSubmission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo termsThe student, Tong Liu, accepted the attached license on 2025-04-25 at 00:46.The student, Tong Liu, submitted this Dissertation for approval on 2025-04-25 at 01:02.This Dissertation was approved for publication on 2025-04-27 at 14:11.DSpace SAF Submission Ingestion Package generated from Vireo submission #21973 on 2025-10-19 at 18:19:10As infrastructure systems grow increasingly interconnected and vulnerable to disruptions from natural hazards and human-induced events, there is a critical need for scalable, adaptive, and physics-consistent modeling techniques. This dissertation investigates the reliability and resilience of structure and infrastructure systems. This work leverages deep learning methodologies, particularly physics-informed neural networks (PINNs) and graph neural networks (GNNs), to enhance infrastructure system analysis, addressing challenges related to system identification, reliability assessment, traffic assignment, dynamic flow forecasting, and infrastructure asset management. By integrating physics-informed constraints, heterogeneous graph representations, and data-driven optimization strategies, this dissertation provides novel solutions that improve computational efficiency, predictive accuracy, and decision-making in complex infrastructure networks. The primary contributions of this dissertation are threefold. First, physics-driven constraints are incorporated into data-driven models to address the limitations of purely data-driven approaches, embedding governing physical laws into the learning process to improve interpretability and robustness. Second, GNN-based frameworks are developed for multi-level regional infrastructure reliability analysis under probabilistic hazard scenarios, demonstrating high scalability and generalization across both in-distribution and out-of-distribution conditions. Third, generalized graph-based models are introduced and validated on diverse transportation applications to evaluate system behavior under disruption and inform equitable infrastructure planning. The research contributions span multiple domains, beginning with PIDynNet, a physics-informed neural network designed for nonlinear structural system identification. The dissertation then presents a rapid seismic reliability assessment framework for highway bridge networks, demonstrating the capability of GNN-based models to predict connectivity loss under probabilistic seismic scenarios. To improve post-disaster network analysis, a GNN-based shortest distance estimation framework is introduced, enabling scalable and accurate evaluation of roadway network performance under disruption. Furthermore, a curriculum-enhanced graph reinforcement learning model is designed for fast route recommendation in stochastic time-dependent networks, incorporating a graph-based actor-critic architecture and curriculum learning to enhance scalability and generalization. Additionally, a heterogeneous GNN model is introduced for static, dynamic traffic assignment, and multi-class traffic assignment, incorporating virtual links to improve demand propagation and flow estimation. Finally, a GA-GNN optimization framework is introduced to enhance transportation equity in seismic retrofit planning, balancing network resilience with social equity considerations. The dissertation concludes by summarizing key findings and outlining future research directions. Expanding GNN applications to multi-hazard risk assessment can improve infrastructure resilience across various disaster scenarios. Enhancing the generalization capability of GNN models will further improve adaptability to diverse infrastructure topologies and hazard conditions. Additionally, integrating real-time sensor data into GNN-driven frameworks will enable dynamic infrastructure monitoring, proactive risk assessment, and real-time decision-making. By addressing these challenges, future research can extend the impact of deep learning methodologies in infrastructure resilience, fostering the development of smarter, more adaptive, and disaster-resilient infrastructure systems
Framework for automated impact detection and condition assessment of through-plate girder railroad bridges
Get PDFSubmission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo termsThe student, Omobolaji Lawal, accepted the attached license on 2025-04-25 at 17:47.The student, Omobolaji Lawal, submitted this Dissertation for approval on 2025-04-25 at 17:47.This Dissertation was approved for publication on 2025-04-28 at 16:45.DSpace SAF Submission Ingestion Package generated from Vireo submission #21996 on 2025-10-19 at 18:19:21Of the 100,000 railroad bridges in the United States, 50% are over 100 years old. Many of these bridges do not meet the minimum vertical clearance standards, making them susceptible to impact from over-height vehicles. These impacts can cause structural damage, service disruptions, and financial losses, necessitating a systematic approach for rapid detection and condition assessment. This research develops a comprehensive framework for automated impact detection and condition assessment of railroad bridges using artificial intelligence, wireless smart sensors, and structural health monitoring techniques. Focus is placed on through-plate girder bridges, as they represent a common design among bridges that do not meet vertical clearance standards. The first step in this framework is rapid impact detection, achieved through a machine learning-based event classification that distinguishes between impact events and train crossings with high accuracy. The detection step is enhanced by integrating artificial intelligence at the edge, deploying the classification model directly onto a wireless smart sensor platform. This edge computing paradigm eliminates the delays associated with centralized processing, enabling near real-time decision-making for infrastructure monitoring. Beyond detection, the framework incorporates impact severity assessment, a critical step for prioritizing inspections. An artificial neural network model is developed to assess severity using key structural response metrics such as impact impulse, peak acceleration, and spectral energy. Validated with both simulated and field-collected data, this model provides an automated and scalable solution for prioritizing the allocation of limited inspection resources. The final step in the framework is post-impact condition assessment where a neural network-based approach estimates permanent displacements to determine the residual structural integrity of bridges. By systematically integrating these components, this research establishes a robust and automated framework for railroad bridge impact detection and condition assessment. The proposed methodology enhances safety, minimizes operational downtime, and optimizes maintenance resource allocation for aging railroad bridges
Unprepared to collaborate: the state of principal preparation and school counseling in Illinois
Get PDFSubmission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2025-10-19 without embargo termsThe student, Jessica Mulder, accepted the attached license on 2025-04-28 at 14:03.The student, Jessica Mulder, submitted this Dissertation for approval on 2025-04-28 at 14:16.This Dissertation was approved for publication on 2025-04-28 at 16:03.DSpace SAF Submission Ingestion Package generated from Vireo submission #22039 on 2025-10-19 at 18:19:32School counselors play a critical role in the academic, social-emotional, and postsecondary success of students. In order for school counselors to be effective in these roles, school principals need to understand what school counselors do, and how to best support them. The purpose of this explanatory sequential mixed methods study was to understand the reasons behind Illinois Principal Preparation Programs' decisions to include or exclude content on school counseling and the ASCA National Model within their curriculum. Fifteen of the twenty three ISBE approved Illinois Principal Preparation Programs were surveyed to determine if they include information on school counseling and/or the ASCA model in their curriculum. Follow-up interviews were conducted with four program directors (two whose schools do include school counseling and two whose schools do not) to better understand the reasons for including/excluding school counseling content in the curriculum. Analysis indicates that school counseling may not be included at schools because it isn’t required by the ISBE code that outlines requirements for Principal Preparation Programs. Some programs that do include content are including it as part of MTSS curriculum and student support services. Analysis seems to indicate that programs who also have a school counseling program and/or have former school counselors in their Principal Preparation faculty are more likely to include school counseling content in their curriculum
Single-molecule dynamics of GPCR signal transducers
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Jonathan Deutsch, accepted the attached license on 2025-02-04 at 16:39.The student, Jonathan Deutsch, submitted this Dissertation for approval on 2025-02-04 at 17:18.This Dissertation was approved for publication on 2025-02-11 at 11:48.DSpace SAF Submission Ingestion Package generated from Vireo submission #21631 on 2025-10-19 at 19:14:11G protein-coupled receptors (GPCRs) transduce extracellular signals across the plasma membrane by coupling to heterotrimeric G proteins and arrestins. G proteins activate intracellular signaling cascades, while arrestins primarily attenuate G protein signaling and facilitate GPCR internalization and trafficking. Advances in structural biology have significantly improved our understanding of the molecular mechanisms underlying GPCR signal transduction by capturing distinct conformational states adopted by G proteins and arrestins along their activation pathways. However, a full understanding of GPCR-mediated signaling requires elucidating the dynamic interconversions between these metastable states and the conformational energy landscapes that govern them. In this work, I use single-molecule Förster resonance energy transfer (smFRET) imaging to investigate the dynamics of G proteins and arrestins during key stages of their activation by GPCRs. Chapter 2 focuses on the movements of the G protein α-helical domain, which undergoes displacement upon receptor coupling to facilitate nucleotide exchange and G protein activation. I show that these dynamics are affected by the agonist bound in the receptor's orthosteric pocket, suggesting a previously unrecognized role for the G protein in shaping ligand efficacy. Chapter 3 explores the autoinhibitory C-tail dynamics of a non-visual β-arrestin, identifying an intermediate conformational state that enables its recruitment to receptors with minimal or no C-terminal phosphorylation. Together, these single-molecule studies provide new insights into how both the initiation and termination of GPCR signaling are fine-tuned through the allosteric modulation of its transducer proteins’ structural dynamics
Evolution of transmission mode in a temperate virus of Pseudomonas aeruginosa and its effects on the host
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Laura Suttenfield, accepted the attached license on 2025-03-01 at 23:02.The student, Laura Suttenfield, submitted this Dissertation for approval on 2025-03-01 at 23:15.This Dissertation was approved for publication on 2025-03-06 at 10:28.DSpace SAF Submission Ingestion Package generated from Vireo submission #21655 on 2025-10-19 at 19:14:19Bacteria are known for the infections they produce; that they are themselves infected is not often considered. This thesis considers the latent, lysogenic phase of a temperate virus DMS3 of the opportunistic pathogen Pseudomonas aeruginosa. In Chapter 1, I review the existing literature on how lysogeny contributes to viral fitness. In Chapter 2, we attempt to test this with deep sequencing of semi-random insertion sites. In Chapter 3, we find that spontaneous induction in lysogens causes divergent evolutionary resolutions. In Chapter 4, we take this approach to whole populations to test the way that infected and uninfected P. aeruginosa evolves in the presence of an antibiotic which can induce the lysogen. We find substantial evidence that this temperate virus impacts the evolution of its pathogen host
Process-induced strain engineering in two dimensional semiconductors
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Yue Zhang, accepted the attached license on 2025-03-04 at 16:53.The student, Yue Zhang, submitted this Dissertation for approval on 2025-03-04 at 17:02.This Dissertation was approved for publication on 2025-03-07 at 10:50.DSpace SAF Submission Ingestion Package generated from Vireo submission #21661 on 2025-10-19 at 19:14:21Atomically thin, two-dimensional (2D) electronic materials such as transition metal dichalcogenides (TMDs) represent the ultimate thickness limit in scaling down integrated circuits. This paradigm shift facilitates the heterogeneous integration of 2D electronic devices into the current silicon-based CMOS technology library. A key challenge is understanding CMOS process compatibility with 2D materials, and what new fabrication capabilities are enabled by applying common CMOS processes on 2D devices. In particular, there is a knowledge gap in how thin film stress, commonly found across thin film deposition processes, interacts with 2D few-layers and how the van der Waals interface affects strain transfer during CMOS processes. In this dissertation, we show that CMOS process-induced stress applies a controllable strain when evaporating thin films on 2D monolayers and heterobilayers. We use thin film evaporation as an example, and selectively deposit lithographically-patterned thin film magnesium oxide (MgO), known as stressors, onto 2D monolayers and heterobilayers with e-beam evaporation. By tracking the changes in Raman signature modes in monolayer MoS₂ and WSe₂, we qualitatively estimate the strain, and the result is independently verified with the photoluminescence emission peak mode. Importantly, engineering the mechanical boundary condition enables the application of complex, spatially heterogeneous strain and strain gradients that are designable. This new ability has two impacts. In the monolayer, we demonstrate inducing up to 0.8% complex strain distribution that is challenging for polymer-based strain engineering methods. In the artificially stacked MoS₂/WS₂ heterobilayer, for the top layer, the MgO stressor applies a uniform, ~1% strain while the bottom layer is unaffected, creating layer-dependent strain, or heterostrain. The patterned stressor strategy allows direct device integration for strained 2D materials. As a demonstration, we start with a monolayer MoS₂ transistor, and repeatedly deposit the MgO stressor while measuring the carrier transport at different stressor thicknesses. While the stressor is below the critical thickness (~150 nm), the device conductivity linearly improves due to the enhancement of electron carrier mobility: at ~0.4% strain, we observe over 60% electron mobility enhancement. Compared to similar studies with polymer-based strain engineering methods, our strategy has a similar enhancement strength, while manifesting the integration of highly strained 2D systems into other solid devices. Finally, we show that the patterned stressor helps access polarizations in the 2D valleytronics. Specifically, 2D TMDs such as MoS₂ and WSe₂ host rich valley physics but do not allow valley polarizations due to lattice symmetry. We show that the patterned stressor effectively engineers the material inversion and rotational symmetry and yields robust valley polarization. Since valley polarization is determined by the lattice symmetry, the polarization must be sensitive to the directionality of strain and strain gradient. We use the patterned stressor to systematically test the valley polarization dependence on strain directionality and show that the valley polarization turns on and off at different directions of strain gradient, forming a two-fold rotational symmetry. Our results provide a practical route to generate strong, robust, and localized valley polarizations, a prerequisite for all practical valleytronic devices. Therefore, the stressor technique is well suited for further explorations in 2D valleytronics, such as valley carrier transport, trapping, and decoherence. Overall, engineering process-induced stress provides opportunities to fine-tune the electronic properties of 2D materials with strain, and directly incorporate strained 2D systems into the current CMOS architecture. More broadly, highly localized strain and strain gradients enable unprecedented quantum functional devices made of 2D monolayers and heterostructures. Deterministically designing and applying strain with thin film stressors accelerates the integration of diverse strain-enabled multifunctional 2D devices into CMOS circuits, defined as "more than Moore" in technology roadmaps
The impact of strain and chemical functionalization on two-dimensional materials
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Hyunchul Kim, accepted the attached license on 2025-04-14 at 13:12.The student, Hyunchul Kim, submitted this Dissertation for approval on 2025-04-14 at 15:17.This Dissertation was approved for publication on 2025-04-18 at 16:33.DSpace SAF Submission Ingestion Package generated from Vireo submission #21767 on 2025-10-19 at 19:14:43Two-dimensional (2D) materials, such as graphene and transition metal dichalcogenides (TMDCs), have emerged as promising candidates for flexible electronics, optoelectronics, and energy storage devices due to their exceptional electronic, optical, and mechanical properties. This dissertation investigates strain engineering and chemical functionalization of 2D materials, focusing on their impacts on electrical properties, surface energy, and device performance. Conventional silicon-based electronics face intrinsic challenges, including short-channel effects, high leakage currents, and limited mechanical flexibility, which restrict their scalability and adaptability for next-generation technologies. Similarly, organic semiconductors offer mechanical flexibility but suffer from low electron mobility and poor scalability. To overcome these limitations, 2D materials provide unique opportunities due to their atomic thinness, high elastic strain limits, and tunable electronic structures. This dissertation explores strain engineering as a tool to precisely modulate band structures, work functions, and carrier mobilities in 2D materials. It demonstrates the fabrication of a stretchable MoS2 transistor based on wrinkled 2D heterostructures, showcasing its mechanical flexibility and strain-tunable band gap without compromising performance. Raman and photoluminescence studies confirm strain-induced band gap modulations and threshold voltage shifts, enabling applications in wearable electronics. This study further explores the effects of strain on work function (WF) shifts in 2D materials using Kelvin Probe Force Microscopy (KPFM). The results reveal strain-tunable WF modulations in materials such as WSe2, WS2, and MoS2. The observed modulations exhibit distinct trends across materials, reflecting differences in their band structures and providing valuable insights into the development of straintronics based on 2D materials. Additionally, this work examines surface energy modulation of hydrogenated and fluorinated graphene through contact angle measurements and Fowkes’ theory. Results highlight how volatile organic compound (VOC) adsorption affects wettability, while chemical functionalization enables hydrophilic-to-hydrophobic transitions, supporting applications in biosensing, anti-corrosion coatings, and selective adsorption systems. This dissertation offers a comprehensive analysis of the effects of mechanical strain, chemical functionalization, and substrate interactions on the physical properties of 2D materials and their device performance. By integrating experimental observations with theoretical modeling, it establishes a framework for designing functional 2D interfaces tailored for quantum devices, energy-efficient electronics, and bio-integrated systems
Effects of dietary supplementation with Bacillus spp. on immune response, intestinal health outcomes, and the nasal, otic, and fecal microbiota of healthy adult dogs
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Sofia Wilson, accepted the attached license on 2025-04-16 at 17:06.The student, Sofia Wilson, submitted this Dissertation for approval on 2025-04-16 at 17:19.This Dissertation was approved for publication on 2025-04-21 at 16:53.DSpace SAF Submission Ingestion Package generated from Vireo submission #21803 on 2025-10-19 at 19:14:59Dietary supplementation with “biotics,” which include probiotics, prebiotics, synbiotics, and postbiotics, is a strategy used to modify the intestinal microbiota and promote host health. Although biotics are commonly incorporated into pet products, questions remain regarding appropriate biotic selection, mechanisms of action, optimum inclusion levels, and safety. Bacillus spp. are spore-forming bacteria able to survive in extreme conditions, such as the acidic stomach, and vegetative cells exhibit high metabolic activity associated with production of enzymes and antimicrobial compounds. However, questions remain regarding the mechanisms by which Bacillus spores and vegetative cells exert their benefits. Therefore, the purpose of this dissertation was to evaluate the probiotic potential of select Bacillus strains and their effects on the gut microbiome of dogs and assess their role in supporting gut health and immunity. The first aim was to determine the apparent total tract macronutrient digestibility (ATTD) of diets supplemented with fibers or biotics and to evaluate their effects on the fecal characteristics, metabolites, microbiota, and immunoglobulin (Ig) A concentrations of dogs. Adult female Beagle dogs (n=12; age=6.2 ± 1.6 yr; body weight=9.5 ± 1.1 kg) were used in a replicated 3×3 Latin square design to test three treatments: 1) control diet based on rice, chicken meal, tapioca starch, and cellulose + a placebo treat (CT); 2) diet based on rice, chicken meal, garbanzo beans, and cellulose + a placebo treat (GB); 3) diet based on rice, chicken meal, garbanzo beans, and a functional fiber/prebiotic blend + a probiotic-containing treat (GBPP). The probiotic treat contained Bacillus subtilis and Bacillus amyloliquefaciens [2 × 109 colony-forming units (CFU)/d]. In each 28-day period, a 22-day diet adaptation was followed by a 5-day fecal collection phase. ATTD of dry matter (DM), organic matter, and energy were lower (P<0.001) and DM fecal output was higher (P<0.01) in dogs fed GBPP than CT or GB, whereas ATTD of crude protein was higher (P<0.001) in dogs fed CT and GBPP than GB. ATTD of fat was higher (P<0.001) and wet fecal output was lower (P<0.01) in dogs fed CT than GB or GBPP. Fecal DM% was higher (P<0.001) in dogs fed CT than GBPP or GB, and higher in dogs fed GBPP than GB. Fecal short-chain fatty acid concentrations were higher (P<0.001) in dogs fed GB than CT or GBPP, and higher in dogs fed GB than GBPP. Fecal IgA concentrations were higher (P<0.01) in dogs fed GB than CT. Fecal microbiota populations were affected by diet, with alpha diversity being higher (P<0.01) in dogs fed GB than CT, and beta diversity shifting following dietary fiber and biotic supplementation. The relative abundance of 24 bacterial genera were altered in dogs fed GB or GBPP than CT. Finally, serum triglyceride concentrations were lower in dogs fed GB than GBPP or CT. The second aim was to determine the effects of Bacillus coagulans GBI-30, 6086 on ATTD and the hematology, Ig concentrations, and fecal characteristics, metabolites, and microbiota populations of healthy adult dogs. Adult English Pointer dogs (n=12; age=5.9±2.5 yr; body weight=26.6±6.1 kg) were fed the same diet, but supplemented with B. coagulans or a placebo via gelatin capsules in a replicated 3×3 Latin square design. Capsules were administered daily before each feeding, with the following treatments tested: 1) basal diet + placebo (control; 250 mg maltodextrin); 2) basal diet + B. coagulans (low dose; 5 × 108 colony-forming units CFU/d); and 3) basal diet + B. coagulans (high dose; 2.5 × 109 CFU/d). In each 28-day period, a 22-day diet adaptation was followed by a 5-day sample collection phase. B. coagulans supplementation did not affect ATTD, food intake, fecal metabolites, immunoglobulin concentrations, or hematology, but did lower fecal scores (P<0.05; firmer stools). Using qPCR, fecal Faecalibacterium spp. abundance was greater (P<0.05) and fecal Bacteroides spp., Bifidobacterium spp., and Ruminococcus gnavus abundances tended to be greater (P<0.10) in dogs fed the low B. coagulans dose than those fed the placebo. Using 16S rRNA sequencing, the relative abundance of nasal Staphylococcus spp. tended to differ (P<0.10) between dogs supplemented with the low and high dose of B. coagulans. Within the pinnae, the relative abundances of Bifidobacterium spp. and Dubosiella spp. were greater (P<0.05) in dogs fed the low dose of B. coagulans than controls, while Allobaculum stercoricanis and Sutterella spp. abundances were lower (P<0.05) in dogs supplemented with the high dose of B. coagulans than controls. The third aim was to determine the effects of B. coagulans GBI-30, 6086 on the fecal scores, pH, DM percentage, and microbiota populations of dogs following an abrupt diet change. Adult English Pointer dogs (n=12; age=5.9±2.5 yr; body weight=26.6±6.1 kg) were used in a replicated 3×3 Latin square design and fed commercial diets containing no probiotics or prebiotics. The following treatments were administered orally in gelatin capsules before each daily feeding: 1) placebo control (250 mg maltodextrin/day); 2) B. coagulans (low dose; 5 × 108 CFU/day); and 3) B. coagulans (high dose; 2.5 × 109 CFU/day). An extruded kibble diet was fed for 28 days. Dogs were then abruptly switched to a canned diet and fed for 14 days, with fecal samples collected before and 2, 6, 10, and 14 days after diet change. The abrupt diet change reduced (P<0.0001) fecal DM content, increased (P<0.0001) fecal scores and pH, and reduced (P<0.0001) fecal bacterial species richness and phylogenetic diversity. Diet change also increased (P<0.001) fecal Bacteroidota, Fusobacteriota, and Proteobacteria, decreased (P<0.001) fecal Firmicutes, and altered about 40 fecal bacterial genera relative abundances. Diet-induced changes were not greatly impacted by B. coagulans, but fecal scores tended to be lower (i.e., firmer stools; P<0.10), fecal E. coli and Faecalibacterium abundances were greater (P<0.05), and fecal bacterial phylogenic diversity was higher (P<0.05) in dogs supplemented with the low dose than placebo-supplemented dogs. The final aim was to evaluate the fecal characteristics, microbiota populations, fecal IgA and calprotectin concentrations, as well as serum chemistry, hematology, and immune function of dogs supplemented with B. subtilis and B. amyloliquefaciens. Adult English Pointer dogs (n=20; age=5.0 ± 2.3 yr; BW=24.4 ± 3.8 kg) were used in a double-blind, placebo-controlled crossover design. Dogs were allotted to the placebo (n = 10; 3-4 g/d of maltodextrin) or probiotic group (n = 10; 3-4 g/d of probiotic powder, 2 × 108 CFU/g) and fed to maintain BW for 28 days. Fecal scores tended to be higher (P<0.10; i.e., looser stools) and fecal DM content was lower (P<0.05) in dogs consuming the probiotic than those consuming the placebo, but fecal IgA and calprotectin concentrations did not differ between treatments. Serum metabolites and hematology data were all within normal reference ranges, although eosinophils (counts and % of total white blood cells) were lower (P<0.05) in probiotic-supplemented dogs than those in the control group. Immune cells isolated from probiotic-supplemented dogs produced greater (P<0.05) tumor necrosis factor-alpha (TNF-α) than those from control dogs when cells were stimulated with zymosan, an agonist of toll-like receptor 2. Concentrations of serum lipopolysaccharide-binding protein (LBP), interleukin (IL)-1β, and IL-6 did not differ between treatment groups, however serum C-reactive protein (CRP) concentrations were higher (P<0.05) in dogs supplemented with the probiotic than those in the control group. Fecal microbial composition, evaluated by alpha and beta diversity indices, was not significantly impacted by probiotic supplementation, although the Shannon Diversity Index tended (P<0.10) to be higher in placebo-supplemented dogs. The relative abundances of fecal microbiota measured by 16S rRNA sequencing were not greatly affected by probiotic supplementation, although the relative abundance of fecal Blautia was lower (P<0.05) in dogs supplemented with the probiotic than those fed the placebo. Our findings indicate that while B. coagulans, B. subtilis, and B. amyloliquefaciens can be safely supplemented to healthy dogs, their probiotic effects on GI health and immunity appear to be dose, species, or strain dependent. B. coagulans minimally impacted immune parameters, with a greater impact on stool quality and fecal microbial composition when dogs were fed a low dose of (5 × 108 CFU/d). However, few benefits were observed in dogs consuming the high dose of B. coagulans (2.5 × 109 CFU/d). Conversely, B. subtilis and B. amyloliquefaciens provided limited intestinal health benefits and reduced stool quality, although spores modulated innate immune responses in healthy dogs. Bacillus inclusion in canine diets did not substantially impact nutrient digestibility, whereas legume-based dietary fibers, with or without prebiotics and probiotics, were shown to reduce ATTD, and abruptly transitioning dogs from a kibble to canned diet negatively influenced fecal characteristics. Overall, diet and macronutrient composition were shown to influence fecal characteristics and drastically shift the fecal microbiota, regardless of Bacillus supplementation. Therefore, the probiotic potential of Bacillus spp. may be enhanced if supplemented in combination with prebiotics or as a multi-strain Bacillus probiotic mixture to offer complementary benefits to gut health and immunity by providing support for a more diverse range of microbes
The control of polymer architecture and composition through kinetic studies
No full textSubmission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2027-05-01The student, Keelee McCleary-Petersen, accepted the attached license on 2025-04-16 at 19:02.The student, Keelee McCleary-Petersen, submitted this Dissertation for approval on 2025-04-16 at 19:08.This Dissertation was approved for publication on 2025-04-20 at 16:09.DSpace SAF Submission Ingestion Package generated from Vireo submission #21807 on 2025-10-19 at 19:15:01The architecture and composition of polymers greatly affects the material properties, ultimately determining the types of applications that the polymers can be used for. Thus, the development of new synthetic strategies for controlling the architecture and composition of polymers can open the doors for the design of next-generation materials. Chapter 1 gives an overview of the types of polymers that will be discussed in this dissertation, as well as an overview of each of the methods that will be used to control the architecture and composition of the synthesized polymers. Chapter 2 first introduces a new synthetic method for obtaining shaped bottlebrush polymers using a simultaneous graft-from and graft-through reaction via ring-opening metathesis polymerization (ROMP) or ring-opening polymerization (ROP). Chapter 3 then dives into examining a phenomenon we observed where the rate of macromonomer polymerization via ROMP depends on the polymeric chain more than the norbornene anchor group. Next, Chapter 4 describes a new method developed to synthesize Janus bottlebrush polymers via sequential graft-to reaction then graft-from ROP in a one-pot polymerization, using mostly commercially available reagents, that only require a simple two-step purification process. Lastly, Chapter 5 discusses kinetic studies that were performed for the copolymerization between two different di-epoxides with a diamine to gain a molecular insight into the compositional structure of the resulting copolymers. Throughout the chapters of this dissertation, kinetic studies were used to evaluate reaction progress, reaction compatibility, polymer architecture and polymer composition, showcasing how vital and extensive polymerization kinetics can be utilized, depending on the needs of the project