AUETD (Auburn University)
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Effects of Thermal Stress Events and Correlated Response on Thermal Tolerance of the Eastern Oyster (Crassostrea virginica)
Full text linkThe eastern oyster (Crassostrea virginica) is an economically and ecologically important species. There is interest in improving the heat tolerance of this species for both aquaculture and restoration purposes. I examined the effects of induced acquired thermal tolerance (ATT) and genomic selection for Dermo disease resistance on the heat tolerance of this species. In the induced ATT study, oysters were exposed to sublethal heat stress at pre- and post- metamorphosis life stages. After recovery, animals were exposed for 30 days to 25 °C, 36 °C, 38 °C, and 40 °C. In the genomic selection study, genomically selected, phenotypically selected, genomic control, and wild control oyster lines were exposed for 20 days to 23 °C, 28 °C, 36 °C, and 38 °C. We did not see an impact of induced ATT on heat tolerance. However, the genomically selected oysters survived significantly longer at 38 °C than the other lines, indicating a positive relationship between disease tolerance and heat tolerance.
Evaluation of Corn Response to Within-Field Nitrogen Management and the Performance of Tools for In-Season Nitrogen Recommendations in Alabama.
No full textImproving nitrogen (N) use efficiency in corn production requires strategies that account for within-field variability and also the availability of precision agriculture technologies. This study evaluated the corn response to different side-dress N rates across field’s management zones (MZs) in six on-farm trials conducted over two growing seasons (2023–2024) in Alabama. Each field was divided into MZs based on yield maps, soil properties, and topography. A strip-trial design testing three nitrogen rates crossing field management zones was implemented. Tools such as Adapt-N and Atfarm were also tested for their accuracy in prescribing within-field in-season N rates under the Alabama conditions. Variables measured included grain yield, ear length, ear diameter, stalk diameter × plant height, N uptake, and economic metrics such as nitrogen productivity and partial profit. The results showed that corn yield response to N varied across MZs and locations. In 2023, higher rates generally increased yield and profitability, particularly in high-yielding zones. In 2024, drought and heat stress during key growth stages reduced corn yield and limited N uptake which resulted in the farmer rate outperforming higher N rates. Yield components, particularly ear length and ear diameter, were positively correlated with yield; however, the correlation was influenced by both N rate and MZ. The evaluation of Adapt N and Atfarm showed that Adapt N could capture and recommend different N rates that address within-field variability. In contrast, Atfarm recommended uniform N rates regardless of within-field differences in soil type or topography. In most fields, the N rate recommended by both tools was close to the N rate treatment that contributed to the field yield average. These results suggest that the tools performance might be influenced by factors such as calibration, site-specific variability, and integration of local field knowledge. This research highlights the value of zone-specific N management and the potential to refine decision-support tools to improve economic and agronomic outcomes. It underscores the importance of integrating spatial variability, crop development, and environmental conditions when making in-season N application decisions to enhance productivity and sustainability in corn production systems of the southeastern U.S
Exploring Innovative Food Safety Practices for Harvest and Postharvest Handling of Fresh Produce
Full text linkFresh produce has been associated with foodborne outbreaks and recalls due to pathogens such as E. coli O157:H7, Salmonella enterica, and Listeria monocytogenes. To minimize cross-contamination and reduce microbial loads in the final product, it is crucial to improve food safety practices during the harvest and postharvest stages. This project evaluates two innovative approaches to enhance microbial safety in fresh produce handling: the use of nano-textured coatings on harvesting equipment and the application of sanitizers during postharvest washing. The first approach investigates the effectiveness of hydrophobic and superhydrophobic coatings in reducing the transfer of E. coli O157:H7 during a simulated blueberry harvest. The second practice focuses on living lettuce, a popular product known for its intact roots and extended shelf life, by assessing the effectiveness of root washing with sanitizers to control Salmonella enterica. Together, these studies highlight practical interventions that can significantly enhance produce safety, offering valuable guidance for local growers to reduce contamination risks throughout the supply chain
Design and Development of Novel LXRβ Agonists for Alzheimer’s Disease
No full textA progressive neurodegenerative disease, Alzheimer's disease (AD) is identified by the buildup of insoluble protein aggregates, such as Tau and amyloid beta. Amyloid beta (Aβ) and Tau protein processing genetic predispositions are highly correlated with the prevalence of disease. But AD's pathological features can exist separately from one another. Furthermore, individuals who are genetically predisposed to AD may never get it, suggesting that lifestyle decisions and epigenetic factors have a big impact on the onset and course of the disease.
Apolipoprotein E (ApoE) mutations are the single most important genetic risk factor for AD development; the most prevalent ApoE mutations produce three distinct phenotypes: ApoE2, ApoE3, and ApoE4. Commonly known as neutral alleles, ApoE2 and ApoE3 have been shown in some studies to be protective. The ApoE4 allele is the most significant risk factor for the development of AD because it causes the most drastic alteration in cholesterol transport in these patients, which leads to a higher rate of neurovascular dysfunction and blood-brain barrier (BBB) degradation.
Lipids are transported by ApoE as protein complexes, for example, High-Density Lipoprotein (HDL), Low-Density Lipoprotein (LDL), Very Low-Density Lipoprotein (VLDL), and others, which differ in size, density, and function. Astrocytes, a non-neuronal cell type that performs a variety of regulatory tasks, such as maintaining the blood-brain barrier, forming myelin, controlling nutrition, and eliminating toxic metabolites like Tau and Aβ, are the cells in the brain that express APOE the most. Patients with atherosclerotic plaques are the target of current therapeutic applications that modulate ApoE. These applications encourage the removal of lipids from peripheral tissues and return them to the liver for further elimination. This process, called reverse cholesterol transport (RCT), raises HDL cholesterol while lowering LDL cholesterol.
Liver X receptors (LXRs) are attractive targets in the paradigm of RCT-mediated therapeutic benefit because they can directly alter ApoE regulation and improve related deficits in AD patients. Through RCT mechanisms, LXRs transcriptionally regulate a number of genes linked to lipid metabolism, energy regulation, and cholesterol clearance. Systemic toxicities like steatosis and neutropenia have prevented LXR-specific agonists from receiving FDA approval, despite their promising results in various transgenic animal models of atherosclerosis and AD. The challenge of achieving therapeutic specificity among the variability of LXR isoforms and function to stop undesired off-target activity in healthy tissue types exacerbates this problem.
Therefore, in order to obtain structure-activity relationships and mechanical details that identify novel ligands with improved therapeutic efficacy, our computational design for novel LXR compounds has focused on profiling selective ligand interactions between the two isoforms of these receptors
Experimental Characterization and Modeling of the Aging Behavior of the Lithium-ion Batteries Considering Kinetic-diffusion Limitation and Graphite-silicon Blended Anode
No full textFundamental understanding of the electrochemical, thermal and mechanical behaviors of the lithium ion batteries during aging is crucial for securing lifespan and safety by the cost-effective and efficient design of cell and the system thereof. The emergence of silicon (Si) and graphite-silicon (C-Si) blended anodes impact cell-level performance which adds the difficulty in experimental and modeling characterization. In this work, we have firstly developed a highly accurate and dynamic isothermal calorimeter that enables the measurement of heat generation rate (HGR) of the cylindrical and pouch type cell. The electrical and thermal behaviors as a function of the aging cycle are recorded for different temperature conditions. Then, a reduced-order electrochemical-thermal model (ETM) platform is developed, which is highlighted by three microcells considering the geometry of a cylindrical cell. The numbers of microcells and numerical mesh elements are optimized with respect to the simulation accuracy and computational speed. During operations, it can be observed that a temperature gradient arises in the radial direction, resulting in a decrease in local resistance and an increase in reaction rate at the high-temperature core location.
To model the electrochemical and thermal behaviors in a C-Si blended anode, a mechanical stress-driven composite anode model implemented on the ETM platform is developed, which considers hydrostatic diffusion-induced stress on particle level and biaxial stress on electrode level. The competing lithiation and delithiation mechanisms between C and Si particles are described by the Butler-Volmer equation, driven by the stress. The effects of particle-level mechanical stress on the electrode potential, hysteresis and cell-level HGR are further justified. The results show that the stress within anode particles is dependent upon not only Li+ concentration but also concentration gradient. The hydrostatic stress within silicon particles is notably larger than graphite, which drives a silicon-dominated reaction in low-SOC range, and consequently causes a voltage hysteresis and a HGR peak majorly at low SOC.
Based on the established ETM, two major challenges in characterizing battery aging mechanisms are addressed. The first one is the kinetic-diffusion limitation of the solid electrolyte interphase (SEI) generation. A physics-based methodology is proposed considering a two-stage process, with a Piecewise Kinetic-Diffusion (PKD) control mechanism of the SEI formation in the electrochemical degradation model. The kinetic and diffusion limits are separately determined by calculating the molar fluxes of Li+ and ethylene carbonate (EC) solvent as two reactant species for SEI, which are compared at the reaction interphase to identify the limiting mechanism. The simulation results are validated with both calendar and cycle life data, under different SOCs, temperatures, and charging profiles. The PKD method more accurately captures the temperature and SOC dependency of capacity and voltage fade, as compared to the conventional methods.
The second challenge is the degradation mechanism of the C-Si two-particle anode system. In this work, the stress-induced overpotential (SIO) is considered to be the factor that differentiates the electrochemical degradation rate between C and Si particles, which leads to a faster aging of the Si particles due to its mechanical properties and high utilization during lithiation. The proposed model is validated against the experimental aging data, which provide detailed analysis on the individual contribution of C and Si component on the overall cell-level aging and thermal behavior.
The experimentally validated modeling analysis is dedicated to develop a deeper physical understanding of reaction kinetics, mass and charge transport within the battery. This work may provide guidelines for the development of battery management system, cooling circuit, and the design of electrode materials and fast-charging algorithms, all of which are closely linked to the electrical, thermal, and mechanical behavior of batteries over their lifespan
Examining the Relationship Between Caregiver Acceptance and Children’s Prosocial Behavior with Multiple Dimensions of Sleep as Moderators
Full text linkThis study explored how sleep might influence the relationship between caregiver acceptance and prosocial behavior in early adolescence. Using a diverse sample and objective sleep data, the study first tested whether sleep changed the strength of this relationship. Results did not support moderation, meaning caregiver acceptance was associated with greater prosocial behavior regardless of how well adolescents slept.
However, several sleep variables did serve as partial mediators. Longer sleep duration, earlier bedtimes, and more consistent sleep schedules helped explain how caregiver acceptance was associated with higher prosocial behavior. These indirect effects remained significant or marginally significant after accounting for factors like sex, puberty, and family income. In contrast, sleep quality measures such as efficiency and latency were not related to prosocial behavior and did not serve as mediators.
Overall, the findings suggest that supportive caregiving may help adolescents develop healthier sleep patterns, which in turn promote kindness, empathy, and cooperation. Interventions that focus on both emotional support and sleep routines may be especially effective in encouraging positive social development
Impact of natural and artificial light treatments on welfare and behavior in commercial broilers
No full textIn recent years, consumer driven interest has led to the addition of windows in broiler houses to allow for natural light during rearing. However, the effects of natural light on broiler welfare and behavior remain largely unknown. This project aimed to evaluate the impact of natural light (NL) versus artificial light (AL) on broiler fear responses, welfare indicators, behavior, and spatial distribution throughout a 56-day grow-out period. A total of 704 mixed-sex Ross 708 chicks were randomly assigned to 16 rooms (44 birds/room), with 8 rooms per light treatment: AL provided via 5000K LED lighting, or NL delivered through windows supplemented with 5000K LED. Three fear tests were performed – novel object (at 14 and 35 days), response to observer (at 14 and 35 days), and novel environment (at 55 days), alongside welfare assessments including footpad dermatitis, hock burn, gait score, and latency to lie at 55 days. Behavioral observations were conducted via scan sampling every 30 minutes over a 24-hour period on days 5, 12, 33, and 54. Behavioral observations and birds’ distribution were conducted for 8 rooms total (4 per treatment group). Bird distribution in NL rooms was evaluated by counting the number of birds on sunlit versus shaded sides during the photophase. Fear response and welfare data were analyzed using PROC MIXED or PROC GLIMMIX, while behavioral and distribution data were analyzed using repeated measures PROC GLIMMIX (SAS 9.4). Results indicated that NL birds were quicker to approach the novel object (mean latency 69.9 s vs. 181.4 s, P<0.01) and were more willing to enter the 1-meter zone around the object (P=0.03), though no treatment differences were observed in the response to observer, novel environment tests, or most welfare parameters, except for footpad dermatitis, which was lower in NL birds (P=0.03). For behavioral observation, an interaction was noted for walking and sitting. Treatment has an effect as NL birds performed more walking and other locomotion activities (P<0.05), while AL birds showed more sitting behavior (P<0.05). Age significantly influenced all behavioral categories except running, environmental pecking and frolicking. Additionally, birds preferred the sunlit side over the shaded side in NL rooms (P<0.05). Overall, natural light exposure promoted more active behaviors and improved some welfare indicators such as footpad health but did not significantly affect leg health or fear responses
Omics Analyses of Sulfur Starvation Response in Pseudomonas aeruginosa: Linking Oxidative Stress to Iron Homeostasis
No full textInorganic sulfur, primarily in the form of sulfate, is the preferred sulfur source utilized by bacteria. However, sulfate availability in terrestrial environments is severely limited, comprising less than 1–5% of the total available sulfur, with the majority existing in organic (organosulfur) forms. Consequently, soil bacteria have evolved strategies to utilize a diverse range of organosulfur compounds. Previous nutritional studies have established that sulfate limitation triggers extensive metabolic reprogramming characterized predominantly by the upregulation of sulfur-scavenging genes. Particularly, sulfur deprivation also consistently induces the expression of antioxidant genes, yet the underlying mechanisms remain poorly understood.
To address this knowledge gap, we employed an integrative omics approach combining RNA sequencing (RNA-seq), label-free proteomics, fluorometric assays, and computational network inference analyses, using the opportunistic pathogen Pseudomonas aeruginosa PAO1 cultured in sulfur-free media (SFM) as our experimental model. As expected, RNA-seq and proteomics datasets revealed pronounced overexpression of genes and proteins associated with scavenging and assimilation of organosulfur compounds (ssu, msu, and sfn operons), alongside antioxidant genes encoding organic hydroperoxide resistance protein (Ohr), 1-Cys peroxiredoxin (LsfA), and iron-dependent superoxide dismutase (SodB).
Surprisingly, we uncovered a previously unreported response: sulfur starvation significantly downregulated numerous iron-acquisition pathways, including siderophore biosynthesis (pyoverdine, pyochelin operons), heme uptake clusters (has, phu), and genes related to xenosiderophore transport. Concomitantly, sulfur-deprived cells displayed significant upregulation of iron-storage proteins (BfrB, Dps, PA4880), indicative of an Fe-replete cellular state. Quantitative Fe measurements using inductively coupled plasma optical emission spectroscopy (ICP-OES) demonstrated a significantly diminished iron uptake capacity in sulfur-starved cells, aligning with our omics findings. Complementary quantitative HPLC analyses further corroborated these results by revealing decreased extracellular concentrations of pyoverdine siderophore.
To understand the oxidative stress dynamics under sulfur deprivation, we employed fluorometric reactive oxygen species (ROS) assays using 2',7'-dichlorofluorescein diacetate (DCFH-DA), revealing a sustained, time-dependent increase in ROS levels in sulfur-starved cells. Additionally, the assessment of intracellular labile Fe using Calcein-AM fluorescence demonstrated a biphasic response, with an initial rise in intracellular Fe at early starvation (2.5 h), followed by a notable decline below control levels at later time points (5–7.5 h). While initially perplexing, this biphasic iron response is consistent with the physiological adaptations observed, namely downregulated iron uptake and increased iron sequestration, which collectively diminish intracellular unincorporated Fe levels over time. Time-course proteomics provided additional insights, demonstrating a progressive, sustained elevation of antioxidant proteins (Ohr, LsfA, SodB), and Fe-storage proteins (BfrB, PA4880, PA0962), underscoring their crucial roles in mitigating oxidative damage through prolonged sulfur limitation.
To complement our experimental findings, we conducted a computational analysis to elucidate the regulatory circuitry underpinning the sulfur starvation response. This approach was necessitated by the observed differential expression of key regulatory elements, including siderophore biosynthesis regulators (pvdS), and the iron-responsive small RNAs (PrrF). Leveraging our transcriptomic dataset, we employed GENIE3, a machine-learning-based network inference tool, to construct gene regulatory networks aimed at identifying key transcription factors and regulatory hubs involved in mediating the sulfur deprivation response. Our computational analyses identified MexL as a putative regulatory hub, potentially orchestrating gene expression changes associated with sulfur limitation. Although the predictive accuracy of our inferred network was constrained by the limited sample size and suboptimal precision-recall metrics, MexL emerged as a biologically relevant candidate due to its well-established regulatory roles. Specifically, MexL is known to influence phenazine biosynthesis pathways and the expression of the MexJK-OprM efflux pump system, both significantly altered under sulfur-starved conditions in our omics analyses. Therefore, despite methodological limitations, the identification of MexL as a central regulator is both plausible and biologically compelling. Nonetheless, these computational predictions should be interpreted cautiously and require rigorous experimental validation.
Overall, our integrative analyses support a model wherein sulfur deprivation triggers Fe dyshomeostasis in Pseudomonas aeruginosa, initially elevating intracellular Fe pools and subsequently activating Fe-storage mechanisms to mitigate Fe-induced oxidative stress. This adaptive response offers a mechanistic explanation for the induction of antioxidant genes consistently observed during sulfate limitation, shedding light on a longstanding puzzle regarding oxidative stress responses under sulfur scarcity. Additionally, our study also reveals that sulfur starvation significantly suppresses multiple virulence determinants, including quorum-sensing regulators, RND-type efflux pumps, phenazine biosynthetic enzymes, and hydrolytic proteases, many of which are established targets of the ferric uptake regulator (Fur) and iron-responsive PrrF small RNAs.
In conclusion, our findings position sulfur availability as a central modulator of Fe metabolism, oxidative stress responses, and virulence gene expression in P. aeruginosa. These mechanistic insights significantly advance our understanding of bacterial adaptation to sulfur-limiting environments and highlight sulfur metabolism as a promising therapeutic target. Exploiting bacterial sulfur dependency could represent an innovative nutritional immunity strategy, potentially addressing limitations associated with traditional Fe-targeted interventions that inadvertently risk enhancing bacterial virulence
HEADS-UP and Beyond: Extension-Led Interventions for Weather-Related Disaster Readiness in Vulnerable Communities in Alabama
Full text linkRural communities in Alabama face high risks from weather-related disasters such as tornadoes and hurricanes due to poverty, substandard housing, limited access to emergency communication tools, and systemic barriers to preparedness education. This dissertation evaluates the effectiveness of the HEADS-UP (Helping Every Alabamian Develop Storm Understanding and Preparation Plans) led by the Alabama Cooperative Extension System (ACES), which seeks to address these challenges through targeted, community-based interventions.
Guided by the Extension Disaster Education Model (Black, 2012) and the Theory of Planned Behavior (Ajzen, 1991), this research addresses three related topics: (1) assessing disaster preparedness and risk perception among rural residents, (2) evaluating the impact of a structured 3-hour disaster preparedness workshop on participants' knowledge and preparedness behaviors, and (3) analyzing communication preferences and barriers in disseminating severe weather warnings to vulnerable populations.
Utilizing quantitative and mixed-method research methods, data was collected from residents in Alabama's most disaster-prone counties, primarily older adults and women. Key findings indicate significant gaps in risk awareness, shelter access, and understanding of weather alert terminology. Results also demonstrate that targeted educational interventions and tailored communication campaigns substantially enhance preparedness and resilience, particularly among seniors and residents of mobile homes. These findings underscore the effectiveness of community-specific, extension-led disaster education programs and advocate for their continued expansion. Future research should explore broader implementation and assess long-term impacts
Middle Aged Farmer Perspectives on Farm Stress
No full textThis qualitative study explores how middle-aged farmers (ages 35 to 50) perceive and respond to farm stress, economic risk, and transition planning across four U.S. States: Alabama, Kansas, Montana, and North Carolina. By using semi-structured interviews with 57 farmers, the research investigates how producers define farming as a lifestyle, business, or both, and how these definitions of farming affect decision making. The findings reveal that weather, financial stress, work-life balance, human and social risks are deeply interwoven stressors. Coping strategies ranged from self-reliance and faith to informal and peer support networks. Transition planning emerged as a significant challenge, often caused by communication barriers, expectations, and generational tensions. Despite recognizing the importance of transition planning, many farmers did not have a formalized plan. By focusing on the perceptions and experiences of medium to large-scale producers, this study contributes insight into the factors that influence middle-aged ag producers as they make farm management decisions and may inform future policy and initiatives aimed at sustaining this vital sector of agriculture