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Fetal and Infant Mortality Review (FIMR) Programs and Infant Mortality Outcomes
No full textInfant mortality is defined as the death of a baby before his or her first birthday. The United States had the highest infant mortality rate (IMR) of any high-income country at 5.4 deaths per 1,000 live births in 2020. Having a substantial number of poor birth outcomes in a community is a multi-faceted problem and often requires an interdisciplinary approach to understand the challenges impacting fetal and/or infant death. One such coordinated approach to address this problem is the Fetal & Infant Mortality Review (FIMR) program.
Despite the proposed function of FIMR programs to combat high infant mortality (IM), there is no published evidence linking the existence of FIMR programs to improved IM outcomes. Existing published research has been useful in clarifying what FIMR is in general terms.
In Chapter 2, a scoping literature review provides a focused approach to determining the relationship between FIMRs and intended outcomes of reduced IM by reviewing the literature for existing studies on FIMR and IM outcomes. Out of 97 screened articles, 12 were empirical articles on FIMR programs, and 7 articles included an evaluation of a FIMR program or process and were included in the review.
In Chapter 3, a quantitative study assesses differences in IMR in communities with an existing FIMR program examining IMR pre- and post FIMR implementation. Results demonstrated a decrease in IMR in communities post-FIMR implementation thus showing that there appears to be an association between FIMR programs and IM outcomes.
In Chapter 4, a qualitative study evaluates the FIMR process, how it works, and what makes it effective or ineffective. Eleven people participated in the virtual one-on-one interviews. A phenomenological approach was used, and findings revealed reported benefits of the FIMR program as well as areas for needed improvement.
This research concluded that more evaluative studies are needed for assessing FIMR program outcomes specific to IM, not solely its processes; and a nationally standardized approach for the operation of FIMRs is needed with room to tailor to specific communities. Findings need to be disseminated widely and used as an opportunity for greater accountability and improvements to FIMR programs
Astrocytic Nik Regulates Local and Systemic Inflammatory and Metabolic Responses
No full textThough NF-��B-inducing kinase (NIK) has well-established roles in inflammatory, immune, and
metabolic regulation on a systemic level, its specific roles in the central nervous system (CNS)
are not well-defined. NIK���s tumor-intrinsic roles in glioblastoma multiforme (GBM) promoting
tumor invasion and growth suggest it could be involved in other neuroinflammatory conditions,
such as stroke and traumatic brain injury, as well as maintain tumor-extrinsic functions in GBM.
Critical in each of these conditions are astrocytes, glial cells of the CNS with diverse immune
and metabolic functions. No study has characterized the function of NIK in astrocytes. Thus, this
thesis aims to examine NIK���s roles in inflammation, immunity, and metabolism within 1) the
CNS overall and 2) specifically through astrocytes ��� critical CNS support cells.
The impact of NIK on GBM survival was investigated via orthotopic implantation of the
syngeneic GL261 GBM model in a total NIK knockout (KO) mouse model. The function of NIK
in astrocytes under basal and lipopolysaccharide-induced inflammatory conditions was explored
with a GFAP-Cre NIK KO mouse model. Output from metabolic cages, transcriptional
regulation of cytokines and metabolic markers in harvested liver and brain tissue, and protein
expression of cytokines in tissue and serum was analyzed in GFAP-Cre NIK KO and control
mice.
Loss of NIK in the GBM tumor microenvironment (TME) increased male mouse survival. With loss of NIK in astrocytes, increased signaling and decreased metabolism was noted both locally and systemically, specific to male mice. After induction of inflammation with LPS, increased astrocytic response and cytokine signaling was identified locally, and decreased tissue inflammation and metabolism systemically, again in male mice.
NIK plays a critical, pro-tumor role within the GBM TME, resulting in increased survival when knocked out. With loss of NIK in astrocytes, systemic homeostasis is impacted, specifically in signaling and metabolic regulation. These effects are significantly more pronounced in males, suggesting a critical sex-specific role of NIK in the CNS and in inflammatory CNS pathologies such as GBM
Soil-Structure Interaction: From Bearing Capacity to Tolerable Movement
No full textThe increasing number of construction projects is anticipated to play a significant role in driving economic growth, emphasizing the importance of sustainable and cost-efficient built-environment and infrastructure projects. Substructure works constitute a substantial portion of the overall construction cost, averaging around 30 to 50%. This range of values rises notably with taller structures. Shallow foundations continue to be the most economical option compared to deep foundations. However, design challenges linked to shallow foundations persist, particularly in calculating the bearing capacity of shallow foundations on clays (ULS) and determining tolerable movement in building structures (SLS).
This study aims to provide valuable guidelines for designing economical and safe shallow foundation systems that meet LRFD performance criteria, with potential to influence the development of codes and standards. One specific goal is to determine the critical ultimate bearing capacity of shallow foundations on fine-grained soil. Empirical analyses, comparing results of case histories of shallow foundation load tests compiled in the TAMU-SHAL-CLAY-Load Test database to predicted bearing capacities using established theories, along with the comparison of predicted drained and undrained bearing capacities using the information from the database supplemented with data from Houston, Texas soils, revealed that the long-term/drained bearing capacity is more critical for clays with undrained strength greater than 120 kPa, while short-term/undrained bearing capacity is critical for clays with undrained strength less than 120 kPa.
By utilizing information from the database and conducting reliability analysis, geotechnical resistance factors corresponding to a specific probability of failure were proposed for the Ultimate Limit State design of shallow foundations on clays in the LRFD framework. The average of the proposed geotechnical resistance factors yielded a back-calculated FS consistent with those currently adopted in design practice.
Another goal is to determine the tolerable movement of tall building structures for designing foundations, considering the Serviceability Limit State in the LRFD Framework. Numerical simulations, explicitly accounting for soil-structure interaction, were conducted to determine limiting angular distortions to prevent structural damage to buildings on spread footings foundations and mat foundations. The results of these simulations were used to develop plots of normalized differential settlement and normalized stiffness, enabling the prediction of anticipated differential settlement between column locations or obtaining the allowable settlement for buildings on spread footings foundations and mat foundations. Reliability and the probability of exceeding limiting angular distortions were assessed using the Response Surface Method to estimate the implicit performance function, and the surrogate function was analyzed with the First Order Reliability Method. Fragility curves, providing an estimate of the probability of exceedance for a specific limiting angular distortion, were developed using the results of reliability analyses. Finally, a simple method to hand-calculate the maximum settlement of a cluster of spread footings foundation was developed by comparing the deformation behavior of a cluster of spread footings foundation and an equivalent mat foundation through numerical simulations
The Role of Metformin in the Prevention and Treatment of Breast Cancer: Insights From Preclinical Studies
No full textMetformin, a commonly used medication for type II diabetes, has been reported to decrease breast cancer risk. However, results from observational and clinical trials show mixed results, questioning the efficacy of metformin for breast cancer treatment. In addition, determining what patient populations may experience optimal responses to the drug is warranted. Our goal was to improve our understanding of the circumstances under which metformin may exhibit maximal efficacy for breast cancer prevention and treatment. First, we assessed the effectiveness of metformin on tumor outcomes in ovary-intact and ovariectomized rodents. Our findings support metformin treatment being more effective in the postmenopausal setting, having observed prevention of new tumors and reduced tumor burden. The second objective was to elucidate how metformin affects mammary adipose tissue. We have previously shown that metformin reduces M2-like aromatase-expressing macrophages in the tumor border. Here, we investigated if treatment lowered inflammatory markers in tumor-distant mammary tissue. We found a small reduction in inflammatory markers in metformin-treated mammary adipose. However, RNA seq analysis from adipose tissue from treated and control rats showed no changes in gene expression. Our final aim centered on determining the optimal timeframe for metformin treatment during the menopause transition for improved tumor outcomes. We found that metformin treatment in the first four weeks post-ovariectomy was needed to improve tumor outcomes. This work underscores the significance of menopausal status and timing within the menopause transition in influencing the efficacy of metformin for treating mammary tumors and emphasizing the need for a targeted approach to metformin treatment for breast cancers
John Bickham field notebook: AK17501-AK18000.pdf
No full textBound book, each page corresponds to a karyotype slide data.Data pages for AK18001-AK18500 corresponding to unique identifiers of specimens/samples examined for biological research. Specimens are primarily housed at Texas A&M University; Biodiverstiy Research and Teaching Collection
Immediate and Lifelong Consequences of In Utero Exposure to Alcohol: A Systemic and Multi-organ Approach
No full textPrenatal alcohol exposure (PAE) has an estimated prevalence of ~8 to15% in North America, making it the largest single cause of neurodevelopment disabilities and growth deficits. There is increasing recognition that Fetal Alcohol Spectrum Disorders (FASDs) is a ���whole-body��� disease, impacting the health of the individual immediately in utero and persistently throughout the lifespan, likely due to epigenetic alterations and stem cell reprogramming. To gain a better understanding of the more immediate consequences of PAE, I first characterize the consequences of PAE on the placental transcriptome, correlating these changes to observed differences in fetal growth and placental blood flow in a murine model. Secondly, I utilize a murine neural stem cell (NSC) culture model equivalent to mid-1st to 2nd trimester in humans to study the adaptive role of ethanol sensitive Gag-Like Proteins (GLPs) in NSCs. In addition, I also focus on the lifelong impact of PAE, characterizing baseline health differences in young adult (5 mo) PAE rats and identifying an association of a pro-inflammatory state of mesenteric adipose tissue and liver with changes in behavior. Subsequently, I examine transcriptomic differences in the enteric organs (mesenteric adipose tissue and liver) that occur as a response to a health stressor (cerebrovascular ischemic stroke), correlating differences in response to observed impaired recovery post-stroke. Overall, this dissertation focuses on examining PAEinduced (mal)adaptations at different critical time points in development and in life
Dynamic Covalent Polymer Networks for Additive Manufacturing and Supersonic Impact
No full textThe use of dynamic covalent bonds enables self-healing, shape morphing, and energy dissipation in materials. During the past decade, significant progress has been made in advancing both network chemistry and structural design. Diels-Alder (DA) ���click��� reactions introduce room-temperature stability and thermal response to the polymer networks. This thesis explores the roles of temperature and stress in the unique behavior of DA dynamic polymer (DAP) materials for their use in additive manufacturing and supersonic impact. In the second chapter, we report highly conductive nanocomposites made of DAP networks containing branched multi-wall carbon nanotubes (b-CNTs). The ability of liquified DAP to wet, infiltrate, and chemically stabilize bCNTs at increased temperature, and then ���lock��� well-dispersed nanotubes upon cooling via the ���click��� DA reaction results in a low percolation threshold of 0.04 wt% b-CNTs. Moreover, the nanocomposites exhibit controlled network plasticity for permanent shape reconfiguration at solid state via Joule-heating-induced dynamic bond exchanges, and these transformations can be triggered selectively at different locations in printed multi-material hybrid constructs, enabling spatiotemporal control of the material's permanent shape. In the third chapter, we demonstrate that large puncture healing of ultra-thin DAP dynamic networks under supersonic impact by microprojectiles outperforms that of traditional glassy polymers, while showing energy absorption comparable to those materials. Post-mortem microscopies reveal efficient puncture healing that is likely enabled by stress- and temperature-induced viscoelastic responses of DAP networks. The progression of impact events was observed using in-situ imaging with a nanosecond, microscale resolution, while the recovery of DA bonds after the impact was confirmed by infrared nanospectroscopy. In the fourth chapter, we present a procedure design for manufacturing DAP microspheres and analyze their high-strain-rate deformation behaviors under supersonic impacts against a rigid substrate. The dynamic responses of these microspheres are associated with the viscoelastic and viscoplastic characteristics of the microspheres as well as interfacial adhesion. Unlike traditional polymers, the interfacial adhesion properties are governed by the thermomechanical responses of DAP networks, due to temperature- and stress-sensitive DA bonds. The role of thermomechanical network responses in microsphere impacts was unveiled by in-situ observations, post-mortem morphological analysis, and finite element analysis simulations
Machine Learning for Design Space Exploration
No full textDesign space exploration is a crucial, yet time-intensive aspect of the silicon design lifecycle. With the increasing focus on domain-specific architectures, companies are engaged in evaluating, developing, and verifying a growing number of designs [1]. Performance architects face the challenge of identifying the optimal design within an ever-expanding design space, compounded by the complexity of modern microarchitecture designs. Architects perform design space exploration (DSE) after the microarchitecture has been finalized. DSE typically entails utilizing a scatter approach, where architects explore different configurations of parameters believed to return optimal performance numbers. This is guided by their intuition, borne out of extensive experience in the field from having designed numerous processors. Alternatively, they may perform parameter sweeps, fixing certain values, while experimenting with a subset of parameters to observe the outcomes. Architects must optimize for a wide suite of workloads, including SPEC [2], where each benchmark exhibits a unique program structure and flow, leading to an exponential design space. Additionally, cycle accurate simulators such as ChampSim [3], although faster than EDA flows and RTL models, can still take hours to run a configuration over many benchmarks. Another key issue of any simulation is the serial nature of how processors work, with running simulations, either a RTL or a C/C++ model, requires a serial processing of the instructions to simulate on the hardware. The combination of time consuming simulations with a large number of workloads makes design space exploration a costly and time consuming process.
Design space exploration in microprocessor design is an ideal candidate for the application of machine learning, considering the lengthy simulation times and the complexity of the optimization problem at hand. The rise of machine learning presents an opportunity to apply these optimization and techniques towards design space exploration. These techniques aim to teach models to find correlations through training on large amounts of data. This not only assists less experienced individuals in finding optimal solutions but also complements the expertise of seasoned architects. The proposed work aims to explore the use of machine learning for simulation predictions to shorten the total simulation time. The results can then be used to train optimization algorithms to find an optimal configuration within a design space exploration
Advanced Autonomous Algorithms for Versatile Terrain Navigation and Multirobot Coverage Control
No full textThe primary objective of this research is to develop robust autonomous navigation and multirobot coverage control algorithms with broad applicability. To achieve this objective, this dissertation delves into three core topics: 1) terrain-aware path planning, 2) real-time stair detection, and 3) multi-robot coverage control. To address the challenges associated with autonomous navigation using vision-based terrain classification, a novel technique, the uncertainty rejection filter, is introduced. This filter, when combined with a neural networks-based terrain classification model, enhances the reliability of autonomous navigation by identifying uncertain regions and assigning appropriate traversal costs. Simulations and field tests demonstrate the effectiveness of this path-planning scheme. This dissertation also presents a real-time stair detection algorithm based on a decision boundary-aware model. Leveraging a support vector machine trained on RGB images, the algorithm outperforms existing models. Lastly, novel algorithms for multi-robot coverage control are proposed for both homogeneous and heterogeneous systems. A centralized approach incorporating agent dropout and reinsertion processes improves overall coverage, while a decentralized version achieves desired outcomes without a central computer. These algorithms exhibit improved coverage performance in diverse non-convex environments. Additionally, a user interface is introduced to enable users to define target areas for coverage by the proposed algorithms. Field experiments showcase the successful integration of the user interface with the coverage control algorithms
An Empirical Investigation of Afghanistan���s Organizational Culture
No full textThe purpose of this study was to examine Afghanistan culture using Geert Hofstede's Value Survey Module (VSM-2013). This research aimed to uncover and interpret the VSM profiles for Afghanistan, particularly focusing on differences across gender, ethnicities, languages, and religions in relation to Hofstede���s six cultural dimensions: power distance (PD), individualism���collectivism (IC), masculinity���femininity (MF), uncertainty avoidance (UA), long-term���short-term orientation (LSO), and indulgence���restraint (IR). Survey data were collected from 2,071 students across 15 universities in five provinces ���Kabul, Kandahar, Herat, Balkh, and Nangarhar. After ensuring the reliability and validity of the data, the study employed two main analytical techniques: Multivariate Analysis of Variance (MANOVA) to explore cultural variances across groups (e.g., gender, ethnicity, language, and religion) and Hofstede���s Classic VSM-2013 technique to compute VSM indices for Afghanistan as well as those groups. The results revealed insightful distinctions and similarities in cultural dimensions among Afghan men and women, as well as across various ethnic, linguistic, and religious groups. The study's findings are particularly valuable for addressing the need for empirical evidence on Afghanistan���s national culture. Understanding these cultural contexts is critical for the effective management of human resources in Afghanistan