To the non-scientist, sustainability is viewed as plastics recycling, water conservation, and environmental care. How can we use this fundamental view to influence our approach to sustainable science? We can expand our approach to sustainability by implementing new tools and exploring ways to improve current manufacturing practices. Additionally, we can expand the areas that we focus on with relation to sustainability. Environmental Sustainability, Financial Sustainability, and Educational Sustainability are all important pieces that may not always take the spotlight. Advances in sustainable manufacturing and ideas around these three fundamental principles will be discussed.

Affiliated Publications: Org. Process Res. Dev, 2023, 27, 9, 1667-1676.

In this talk, I will discuss our recent efforts to utilize phenyl and vinyl carbocations in C–H functionalization reactions. We will describe how these high-energy dicoordinated carbocations can be generated under mild conditions and utilized in the selective C–C bond forming reactions of simple hydrocarbons. Moreover, we will discuss our efforts to understand the mechanism of these reactions through computational chemistry, kinetics, electron microscopy, and isotopic labeling studies. We will also discuss our efforts to apply electron microscopy to problems in organic chemistry through the use of MicroED and other CryoEM modalities.

My postdoctoral work focused on understanding the physiological consequences of exposure to dusts from concentrated animal feeding operations. In the United States and worldwide, agriculture is a major contributor to air pollution and is linked to the development of respiratory complications in farmers and farm workers. Interestingly, chronic respiratory disorders are frequently associated with gastrointestinal diseases (e.g., inflammatory bowel disease), thereby highlighting the crosstalk between the intestinal microbiota and the lungs (“gut-lung axis”). Yet, the mechanisms responsible for communication between these mucosal sites during chronic exposure to agricultural dust are poorly understood. We have shown that intranasal exposure of 8-week-old male or female C57BL/6J mice (n=12) to 12.5% HDE (containing 22.1-91.1 EU/mL) (n=6) for 3 weeks elevated bronchoalveolar lavage total cell and neutrophil levels (indicative of chronic airway inflammation), and increased intestinal permeability, in comparison to saline controls (n=6). We also report that HDE-treated mice have elevated serum LPS levels (unpaired t-test,p<0.0001; n=6/group) suggesting endotoxemia. To further identify intestinal epithelial responses initiated by HDE, inflammatory genes were examined in intestinal whole tissue lysates by qPCR. Tnfa expression was increased in the proximal colon (unpaired t-test, p=0.0173; n=5-6/group) of HDE-treated mice. Additionally, mRNA expression of the goblet cell marker, Muc2, was not significantly altered along the intestinal tract (unpaired t-test, p<0.05, n=5-6/group). Finally, the Paneth cell-associated marker, Lyz1 (lysozyme), was unchanged in ileum but was increased in proximal colon epithelial cells (unpaired t-test, p=0.0034, n=4/group) of HDE-treated mice. These data may show a protective response to increased permeability, systemic inflammation, and alterations in gut microbiota due to HDE exposure.

Resisting apoptosis is a hallmark of cancer. Therefore, it may be possible to control cancer development by specifically activating apoptotic signaling pathways to cause death in tumor cells.  However, apoptosis signaling is challenging to understand due to dynamic and complex behaviors of ligands, receptors, and intracellular signaling components in response to cancer therapy.  In this work, we predict the apoptotic response based on the combined impact of these features. We expanded a previously established mathematical model of caspase-mediated apoptosis to include extracellular activation and receptor dynamics. In addition, three potential threshold values of caspase-3 necessary for the activation of apoptosis were selected to predict which cells become apoptotic over time. We first vary ligand and receptor levels with the number of intracellular signaling proteins remaining consistent. Then, we vary the intracellular protein molecules in each simulated tumor cell to predict the response of a heterogeneous population. By leveraging the benefits of computational modeling, we investigate the combined effect of several factors on the onset of apoptosis. This work provides quantitative insights for how the apoptotic signaling response can be predicted, and precisely triggered, amongst heterogeneous cells via extracellular activation. 

Traumatic Brain Injuries (TBIs) are a leading cause of disability and death in adults around the world. The brain injury initiates an increase in cytokine production for up to 24 hours after the initial trauma, however several patients have continued symptoms through inflammatory biomarkers such as IL-6, NF-ΚB, and TNFα with post concussion syndrome. Our lab began looking at traditional plant-derived compounds from African-American and Gullah culture in SH-SY5Y cells. Due to the traditional verbal history keeping, some of these treatment remedies have not been as well recorded in science. This is a novel direction for complementary medicine treatments and can expand scientific viewpoints. Preliminary results show that Pinazoline potentially enhanced cellular recovery after exposure to TBI-related neurotoxicants. By observing the 2D morphological effects of treatment with Pinazoline by examining arborization as shown by Sholl analysis and neurite length measurements utilizing FIJI software, Pinazoline increased neurite length and affected arborization. Additionally, levels of TBI-related neurotoxicants in differentiated SH-SY5Y neuronal cells have shown that after treatment, levels repeatedly become reduced back to being similar to control group expression levels indicating anti-inflammatory properties by cytokine expression assays. Another pathological process in TBI is excitotoxicity. Prolonged glutamate exposure is hypothesized to be a fundamental contributor of impairment of cognitive function. With promising preliminary data, we hope to see the long-term effects of this plant-derived compound in a concussion model system (examined by 3D cell culture in hydrogel incorporation with neuronal cells after a sustained force impact) reduce excitotoxicity.

Reliance on Internet connectivity is detrimental where modern networking technology is lacking, power outages are frequent, or network connectivity is expensive, sparse, or non-existent (i.e., underserved urban communities, rural areas, natural disasters). Though there has been much research conducted around 5G and 6G serving as the conduit for connecting any and everything; scalability issues are a major concern and real-world deployments have been limited. Realization of the limitations resulting from reliance on Internet and cellular connectivity are prevalent in mHealth applications where remote patient monitoring has improved the timeliness of clinical decision making, decreased the length of hospital stays, and reduced mortality rates everywhere in the nation except in medically underserved and rural communities in the US like Appalachian Kentucky, where chronic disease is approximately 20% more prevalent than other areas. As an alternative, deploying resilient networking technology can facilitate the flow of information in resource-deprived environments to disseminate non-emergency, but life saving data. In addition, leveraging opportunistic communication can supplement cellular networks to assist with keeping communication channels open during high-use and extreme situations. This talk will discuss the pragmatic applications of designing opportunistic systems for particular entities (patients, citizens, etc.); specifically applied to healthcare and increasing patient adherence, permitting any community to become smart and connected while simultaneously keeping network connectivity costs to a minimum.

The deployment of ever-larger machine learning models reflects a growing consensus that the more expressive the model---and the more data one has access to---the more one can improve performance. As models get deployed in a variety of real-world scenarios, they inevitably face strategic environments. In this work, we consider the natural question of how the interplay of models and strategic interactions affects scaling laws. We find that strategic interactions can break the conventional view of scaling laws---meaning that performance does not necessarily monotonically improve as models get larger or more expressive (even with infinite data). We show the implications of this result in several contexts including strategic regression, strategic classification, and multi-agent reinforcement learning. In particular, we show that each of these settings admits a Braess' paradox-like phenomenon in which choosing less expressive models allows one to achieve strictly better equilibrium outcomes. Motivated by these examples, we then propose a new paradigm for model-selection in games wherein an agent seeks to choose amongst different model classes to use as their action set in a game.

Reinforcement Learning is employed to address the challenge of maintaining safe occupancy in public spaces during epidemics. This is crucial for minimizing disease transmission while allowing essential activities to continue. This involves determining the number of individuals who can safely access public spaces such as offices, learning facilities, and communal areas. My approach is data-driven, and could utilize information such as the physical layout, ventilation, hygiene measures, and local infection rates to create a risk model. I propose dynamic thresholds that adapt to changing circumstances and use reinforcement learning to in figure out trade-offs based on safety and utility considerations in addition to the thresholds. 

Mechanical performance in optical coatings such as ceramic/ceramic nanomultilayers (NMs), where the coating constituents are selected for their index of refraction over a spectral wavelength range, is an area of research that has remained relatively unexplored. Specifically, existing data for mechanical tests of optical NMs is limited and usually performed via indentation. In this study, AlN/Al₂O₃, TiO₂/SiO₂, and AlN/SiO₂ NMs synthesized in aperiodic, optically optimized configurations and non-optimized bilayer configurations were tested using microtensile testing, nanoindentation, and pillar splitting techniques, presenting an unprecedented, global view of mechanical behavior in optical ceramic/ceramic NMs. More specifically, trends across all deformation modes and within each test highlight how periodicity, interface crystallinity, and volume fraction may jointly affect optical and mechanical behavior. Through comparative analysis, both configurations of the crystalline/amorphous AlN/Al₂O₃ NMs exhibit the highest mechanical performance across all three testing techniques with an average optimized transmittance of 93.8% across the UV-Vis-NIR spectra. Overall, this study shows that a range of mechanical behavior can be achieved while maintaining high optical UV-Vis-NIR transmittance of ceramic nanomultilayers, subsequently highlighting a path towards joint opto-mechanical optimization.

When we think of a galaxy, we often imagine a spinning disk of stars and gas surrounding a glowing center. But galaxies are more than meets the eye, and the disks we see are just a small part of the whole. We now know galaxies to be surrounded by huge halos of gas that provide the material from which stars are formed. In this lecture, we will explore the scope of these nearly invisible halos, describe how we can detect them, and look at computer simulations that help reveal their lesser known properties and their influences, such as magnetic fields!

Site response in sedimentary basins is governed by mechanisms associated with three-dimensional features. This includes the generation of propagating surface waves due to trapped and refracted seismic wave, the focusing of seismic energy due to basin shape and size, and the resonance of the entire basin sediment structure. These effects are referred to as basin effects and they lead to a significant increase in the amplification of observed ground motions from earthquake events. Currently, ground motion models (GMMs) incorporate basin effects using the time-averaged shear- wave velocity in the upper 30 m (𝑉S30), and the isosurface depths (depth to a particular shear wave velocity horizon, 𝑧x). The basin component of the model is “centered” in that it describes site response features (amplification) that differ from the mean (described by 𝑉𝑆𝑆30) at intermediate to long periods. This approach captures site response features associated with basin sediment deposits, but it limited in its description of lateral and other three-dimensional (3D) contributing effects. Earthquake simulation platforms incorporate basin related features through velocity models, which describe the features and structure of the subsurface (including basin extents, faults, non-basin areas). However, these velocity models are currently limited in vertical profile resolutions at the margins of sedimentary basins, particularly for areas with spares distribution of stations. Our current investigation is focused on exploring alternative approaches for describing lateral and other 3D features in the development of region-specific models to improve the characterization of site response in sedimentary basins. To accomplish this we have developed basin geometric parameters (multi-dimensional metadata) to be used in improved basin site response analysis and model development. The performance of the models are evaluated by assessing their ability to reduce bias and uncertainty in hazard estimates.