United States

The disproportionate increase in cases of SARS-CoV-2 virus causing COVID-19 in communities of color across the U.S has sparked conversations on the effect that the deadly virus has on communities of color and the lingering question of why. COVID-19 was first reported in Wuhan, China in December 2019 and has subsequently spread worldwide thus, called a pandemic by the World Health Organization. Current data shows that communities of color have been impacted at a much higher rate than other ethnicities. This cohort study discusses why higher rates of diabetes among communities of color cause disproportionately higher rates of transmission and mortality as a result of COVID-19 and examines the mechanisms of diabetes that cause disproportionately higher rates of transmission and mortality as a result of COVID-19. By evaluating scientific evidence and physical data, our research findings show that the transmission and mortality as a result of COVID-19 among communities of color occur at a higher rate compared to other demographic groups due to underlying health conditions. In 2018, it was reported by the CDC that 11.7 percent of African Americans and 12.5 percent of Latinx people were diagnosed with diabetes. This research also indicates that people of color, specifically Latinx and African Americans, are disproportionately affected at higher rates by COVID-19 due to higher rates of diabetes compounded by medication that is commonly taken by diabetes patients, such as ACE inhibitors and ARBs. Both of these types of medications can potentially upregulate the ACE-2 receptor, which is the entryway for SARS-CoV-2 into the body. As a result, patients with diabetes have a higher susceptibility to severe SARS-CoV-2 infection, resulting in worse outcomes in communities of color. This is, however, contradicting speculation that these types of medications can be a potential treatment for COVID-19. Further, this research verifies the impact that socioeconomic factors have on minoritized people and how this may predispose them to diabetes and other underlying health conditions. In Dekalb County, Georgia, African Americans’ median household income was $50,901 in 2018; while their white peers&#39; income was $95,450. The research study reflects the importance of good overall health and wellness management amongst communities of color, while also highlighting the importance of knowledge of and understanding about medical prescriptions, medications, and the effects that it has on the body.

Molsamp 2021

The Effects of COVID-19 on Communities of Color Due to Diabetes Mellitus and Other Underlying Health Issues

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The disproportionate increase in cases of SARS-CoV-2 virus causing COVID-19 in communities of color across the U.S has sparked conversations on the effect that the deadly virus has on communities of color and the lingering question of why. COVID-19 was first reported in Wuhan, China in December 2019 and has subsequently spread worldwide thus, called a pandemic by the World Health Organization. Current data shows that communities of color have been impacted at a much higher rate than other ethnicities. This cohort study discusses why higher rates of diabetes among communities of color cause disproportionately higher rates of transmission and mortality as a result of COVID-19 and examines the mechanisms of diabetes that cause disproportionately higher rates of transmission and mortality as a result of COVID-19. By evaluating scientific evidence and physical data, our research findings show that the transmission and mortality as a result of COVID-19 among communities of color occur at a higher rate compared to other demographic groups due to underlying health conditions. In 2018, it was reported by the CDC that 11.7 percent of African Americans and 12.5 percent of Latinx people were diagnosed with diabetes. This research also indicates that people of color, specifically Latinx and African Americans, are disproportionately affected at higher rates by COVID-19 due to higher rates of diabetes compounded by medication that is commonly taken by diabetes patients, such as ACE inhibitors and ARBs. Both of these types of medications can potentially upregulate the ACE-2 receptor, which is the entryway for SARS-CoV-2 into the body. As a result, patients with diabetes have a higher susceptibility to severe SARS-CoV-2 infection, resulting in worse outcomes in communities of color. This is, however, contradicting speculation that these types of medications can be a potential treatment for COVID-19. Further, this research verifies the impact that socioeconomic factors have on minoritized people and how this may predispose them to diabetes and other underlying health conditions. In Dekalb County, Georgia, African Americans’ median household income was $50,901 in 2018; while their white peers' income was $95,450. The research study reflects the importance of good overall health and wellness management amongst communities of color, while also highlighting the importance of knowledge of and understanding about medical prescriptions, medications, and the effects that it has on the body.

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Neurotransmitters are vital for understanding the relationship between biological interactions in the brain and their subsequent effects on cognition and behavior. Neuromodulators are neurotransmitters with the ability to regulate other cells, most commonly functioning by activating G-protein-coupled receptors (GPCRs). Protein kinase A (PKA) integrates input from GPCRs and triggers different cellular responses dependent on the timing of neuromodulatory inputs and the location of the subcellular compartment in which it is activated. PKA has previously been found to modulate several important functions in the brain, including synaptic transmission, plasticity, learning and memory. We have targeted a PKA activity reporter to different subcellular compartments. The goal of this project is to evaluate how accurately the subcellular reporting targeting is. I created short programs (macros) to automate the colocalization analysis of confocal images to find co-occurring or “colocalized” regions of interest between compartmentally targeted PKA reporters with synaptic terminal markers. These macros will help streamline colocalization analysis into a more objective and efficient process, as performing the analysis manually is a subjective and time-consuming procedure. I found that the macros successfully identified colocalized regions of interest between confocal images of PKA reporters and synaptic terminal markers in an automated manner, with some manual intervention required. Conducting colocalization analysis in an automated manner allows us to evaluate how efficiently we have targeted the PKA reporters to different subcellular compartments. Learning more about how and where GPCRs activate PKA, as well as the resultant behaviors, will help us to better understand the dynamics of neuromodulator action, and the various neurodegenerative and psychiatric disorders in which PKA plays a considerable role.

Automating colocalization analysis of confocal microscopy images

Interactions of aqueous solutions of K2PtCl4 with solutions of three nitroso-naphtolates at room temperature results in formation of precipitates of PtL2·Solv composition (Solv = acetonitrile CH3CN, or dimethylformamide DMF). Compounds will be isolated via filtration, washed with water, and then dried under vacuum in a desiccator charged with H2SO4(c). Characterization of these new compounds will be carried out using conventional physical-chemical techniques such as melting points determination, elemental analysis on C,H,N content, as well as using spectroscopic methods. These will be the IR-, UV-visible spectroscopy and fluorescence measurements (both in solid state and in solution). Particularly interesting will be investigations of the NIR region for the emission. Crystal growth for the X-ray analysis will be done by using the vapor diffusion method in two-vials closed system and selected single crystals will undergo structural characterization. All synthesized compounds are planned for biological in vitro cell culture studies against human cancers.

Synthesis and Characterization of Oximates of Pt-group Metals

The Springfield Plateau groundwater province is an aquifer that runs through southwestern Missouri and parts of Oklahoma and Arkansas. It overlies the Ozark confining unit and is mainly recharged by precipitation. This karst aquifer is unconfined, which makes it vulnerable to waste contaminants from animals or other surface activities, that can percolate through the soil and fractured limestone. Little research has been reported on this aquifer since it is not used for drinking supply or irrigation. There are karst features that have form, such as springs that feed into streams that sustain the nearby biota The objective of this study is to evaluate the ground water quality through analysis of the nitrates and selected major ions in samples collected from springs and streams in Polk county Missouri. I will be collecting about 40 samples and will analyze for pH, alkalinity, turbidity, sulfate, chloride, and nitrate. The results will show the extent of contamination of groundwater (springs) and their impact to receiving streams. Also, since I will be collecting samples at intervals of 1-2 months, I will determine seasonal changes in water quality.​ ​

Water Quality Analysis of the Springfield Plateau Aquifer

My research will primarily deal with synthesizing and characterizing various mesoporous nanomaterials and their composites. When synthesizing these materials, we aim to make them tunable in terms of their uniformity, size, and mesporosity to improve the nanomaterial’s nucleic acid binding capabilities for gene therapy, RNA stabilization, vaccine adjuvants, and other biological applications. I will be conducting wetlab research and synthesizing ZnO nanoparticles and their composite colloid via a template method. The precursor will be dissolved, heated in an autoclave, and the resultant powder will be centrifuged and washed. Eventually, the nanoparticles and colloid mixture will be ground and sintered, followed by calcination at 300-450 C. For this semester, my focus will be on synthesizing enough tunable mesoporous nanomaterials for extensive characterization and biological testing.

Synthesis of Tunable Mesoporous Zinc Oxide Nanoparticles for Biological Applications

Our planet’s energy crisis and environmental pollutions, caused partly by our continuous use of nonrenewable energy sources, have led us to explore new technologies that can harvest energy from the environment. Vibrational energy harvesters, that rely on mechanical energy, have proven themselves to be a useful way of converting ambient energy into electricity. Piezoelectric materials are used as transducers for electromechanical energy harvesting systems. This research will investigate optimal piezoelectric energy harvesting designs.

Analytical Investigation of Optimal Piezoelectric Energy Harvester Designs

Our project focuses on constructing an elementary NV center experiment at a low-cost and at home. Through the Zeeman Effect, the ms= +/- 1 degeneracy is lifted by a magnetic field. Green light induces unpaired electrons in the N-V- center from their spin-1 ground state to their spin-1 excited state. At this point, the electrons either emit red fluorescence when they transition back to ground state or they change their spin-state (if they are ms= +/- 1) and transition to a singlet state before the ground state (ms = 0). The ms= +/- 1 transition to the singlet state reduces its fluorescence intensity. As a result, the more electrons present in the ms = 0 ground state, the greater it fluoresces. Consequently, when a resonant microwave frequency corresponding to the Zeeman shift is applied, the transitions from I 0 > -> I +/- 1 > state results in a decrease in luminescence. External perturbations such as temperature, strain, and magnetic field affect the Zeeman shift and measurement of the adjusted luminescence allows for the detection of these quantities provided the others are known.

High Sensitivity Magnetometry with Nitrogen Vacany Centers

Leaf shape is genetically determined, characteristic to each plant species (heterochrony), and changes developmentally (heteroblasty) and seasonally (environmental plasticity). Aside from being a fascinating biological phenomenon, leaf shape is also important from the perspective of agricultural and environmental sustainability, as it influences the efficiency of light harvesting, evapotranspiration and thermal regulation in plants. This study examines the genetic variation of leaf shape in an F1 hybrid population from a cross between two North American grapevine species Vitis rupestris and Vitis riparia. We collected leaf shape data from three different positions in the shoot. The analysis of the data will allow us to assess the phenotypic variation due to heterochrony, heteroblasty and environmental plasticity. The data presented here examine the range of two key phenotypic features, leaf size and leaf blade width) in F1 progeny. The range of variation in these two phenotypes from the parent phenotypes demonstrate transgressional segregation. These traits may be exploited by agricultural sustainability to breed specific plants with agronomically optimal morphology.

Transgressive Segregation of Leaf Shape in Grapevine

Animal diet breadth varies along a continuum, from extreme specialization (foraging on a few or one food type) to extreme generalization (foraging on many different food types). Greater diet breadth is frequently associated with reduced extinction risk. Pollinators such as bees are essential in natural and agricultural landscapes and many species are declining rapidly. Most bee species are thought to be highly specialized to feeding on the pollen of specific plant species, which could increase their extinction risk. Currently, we are experiencing a pollination crisis, with perhaps the majority of pollinator species declining at a rapid rate. However, we currently lack a consolidated accounting of how pollen diet breadth varies across the approximately 20,000 bee species. In this study, we are conducting a literature search to determine the pollen diet breadth of as many bee species as possible. Over 1700 bee species and their pollen hosts have been recorded in our database so far. Our records indicate that of these bee species, around 5% are extreme specialists (monolectic) and a further 73% are strongly specialized (oligolectic); only around 22% of the bee species are extreme generalists (polylectic). On average, bees used 1.4 plant families, 2.6 genera, and 2.6 species as pollen hosts. Diet breadth across all bee species ranged from 1-49 plant families, 1-96 genera, and 1-61 species. Characterizing diet breadth across the bees not only aids in conserving bees, but helps guide conservation of the plants on which bees forage.

Plant Host Specialization By Bees and Implications For Conservation

The goal of this project is to investigate the correlation between discharge and drainage basin area with the hope of being able to create a simple equation relating the average discharge from a spring, to the drainage area feeding that spring. Having such a relationship would allow us to measure discharge from any given spring and estimate the drainage area flowing to that spring. This is helpful in the event of a pollution event occurring within a spring and land managers wondering where the pollution may have come from and can travel to. Study locations include springs on Ward Branch Creek, Doling Park, Silver Springs, Smallin Cave, and Jones Spring. Doling Cave and Jones Spring are home to caves, and water flows exit their respective caves. Smallin Cave, Jones Spring and Doling Park (Giboney Cave) have dataloggers recording water temperature about every 15 minutes. Ward Branch Creek, and Silver Spring do not have temperature loggers. Having temperature-loggers can give insight on whether those sites are being fed by deeper groundwater flow, shallow groundwater, or both. Flow volume is calculated on every site except Smallin Cave. Initial data shown opposite trends in temperature between Doling Park’s cave, and Jones Spring Cave with the introduction of moderate precipitation. The spring’s temperature typically indicates whether the spring is fed by a shallow drainage system (caves or similar) or by a deeper (and larger) groundwater aquifer. Using this information, the discharge volumes will help us sort out smaller drainage basins from larger groundwater systems. We will be using the equation Q=KA^C, to estimate discharge, (“Q”) in ft³/sec. We will be graphing upstream drainage areas (“A”), against baseflow (“Q”), and plotting each spring on the graph. We hope to find a good line of correlation. If there is a good line of best-fit, the slope of that line will equal our (“K”) factor within the full equation. This equation has been used in various other hydrologic studies and practices to estimate discharge amounts in various locations (Galster & Pazzaglia & etc., 2006). Initial data shows that baseline flow for Doling Park and Jones Spring Cave are 4ft^3/sec for Doling Park, and 7.2ft^3/sec for Jones Spring. We have found that Jones Spring consistently drops in temperature with the introduction of precipitation (substantial rain). However, Doling Park has shown it is much more radical, and has little to no relation in temperature trends to Jones Spring. This data so far gives us some insight on the similarities and differences between 2 of our locations. In conclusion, this new data can prove beneficial to the cities and communities on The Springfield Plateau in regard to the movement of water, and the study of groundwater in Springfield Missouri.  

Temperature and Discharge Monitoring of Springs and Streams to Approximate Water Drainage Basins in The Springfield Plateau, Missouri

Current screening procedures for lung cancer involve the use of low-dose computed tomography (LDCT). However, this approach has correlated with high false-positive rates, invasive and costly workups. In addition, 80% of diagnosed patients are unresponsive to treatment. There is a need for biomarkers with improved diagnostic accuracy and a capability of predicting response in order to improve treatment. In this study, a set of three miRNAs have been identified that can faithfully differentiate between disease free and lung cancer patients. These miRNAs have also shown to converge on pathways responsible for promoting onceogenesis pf lung cancer and mediating resistance, suggesting potential to serve as a predticitve diagnostic tools.

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