Marshall University Music Department Presents a Senior Recital, Molly Page, violin

https://mds.marshall.edu/music_perf/1750/thumbnail.jp

Situating Food Insecurity in a Historic Albuquerque Community: The Whorled Relationship between Food Insecurity and Place

This article examines conceptualizations of the relationship between food insecurity and place. We use an ethnographically inspired and community-engaged approach to situate our analysis of fluid dynamics at work in a community with high levels of food insecurity. We propose that the relationship between place and people’s experience of food insecurity is recursive, dialectical, and “whorled.” This relationship reflects complex, interconnected, and multidimensional processes with consequences for the health of residents. Our research demonstrates the key nature of the health-place nexus by exploring how food insecurity articulates with place in unexpected ways that go beyond discussions of food, food environments, food access, food practices or food systems that have become common in the literature

From community data to research archive: Partnering to increase and sustain capacity within a native organization

Community engagement and participation in academic research is growing in popularity and acceptance. Communities are now routinely engaged and participate in academic research design, implementation and interpretation, but the capacity of communities to conduct their own research is not always a product of these engagement initiatives. This article describes a collaboration between an organisation that supports Native American participation in the fields of science, technology, engineering and mathematics (STEM) and university researchers to expand the organisation’s capacity to conduct research by creating a searchable database from their organisational records. We discuss how strategic design of a research collaboration can result in infrastructure development that contributes to community capacity

A Subset of Secreted Proteins in Ascites Can Predict Platinum-Free Interval in Ovarian Cancer

The time between the last cycle of chemotherapy and recurrence, the platinum-free interval (PFI), predicts overall survival in high-grade serous ovarian cancer (HGSOC). To identify secreted proteins associated with a shorter PFI, we utilized machine learning to predict the PFI from ascites composition. Ascites from stage III/IV HGSOC patients treated with neoadjuvant chemotherapy (NACT) or primary debulking surgery (PDS) were screened for secreted proteins and Lasso regression models were built to predict the PFI. Through regularization techniques, the number of analytes used in each model was reduced; to minimize overfitting, we utilized an analysis of model robustness. This resulted in models with 26 analytes and a root-mean-square error (RMSE) of 19 days for the NACT cohort and 16 analytes and an RMSE of 7 days for the PDS cohort. High concentrations of MMP-2 and EMMPRIN correlated with a shorter PFI in the NACT patients, whereas high concentrations of uPA Urokinase and MMP-3 correlated with a shorter PFI in PDS patients. Our results suggest that the analysis of ascites may be useful for outcome prediction and identified factors in the tumor microenvironment that may lead to worse outcomes. Our approach to tuning for model stability, rather than only model accuracy, may be applicable to other biomarker discovery tasks

Training Patient Stakeholders Builds Community Capacity, Enhances Patient Engagement in Research

Our philosophical framework for research with low-income Latino patients with diabetes prioritizes hiring research staff who share the culture and language of the population of study. Inclusive research design requires an active role by patient stakeholders with training opportunities in a collaborative learning environment to allow patient stakeholder data collectors (PSDCs) to build on existing strengths and expertise. To develop this manuscript, our team reflected on our collective experiences in implementing research-specific trainings for PSDCs. Although our population of study is known to be difficult to recruit and retain, our PSDCs have successfully enrolled participants on schedule, and attrition is low. Although language, institutional requirements, and funding restrictions presented training challenges, we overcame these by using a flexible approach and by incorporating the data collectors’ expertise in refining our protocols. We propose that our success in recruiting and retaining participants is a reflection of our engaged research strategy and framework and demonstrates that engagement promotes better science. However, our experience also demonstrates research institutions need to make policy and infrastructural improvements to reduce barriers and make engaged approaches more feasible

A structural and physical study of sol–gel methacrylate–silica hybrids: intermolecular spacing dictates the mechanical properties

Sol–gel hybrids are inorganic/organic co-networks with nanoscale interactions between the components leading to unique synergistic mechanical properties, which can be tailored, via a selection of the organic moiety. Methacrylate based polymers present several benefits for class II hybrids (which exhibit formal covalent bonding between the networks) as they introduce great versatility and can be designed with a variety of chemical side-groups, structures and morphologies. In this study, the effect of high cross-linking density polymers on the structure–property relationships of hybrids generated using poly(3-trimethoxysilylpropyl methacrylate) (pTMSPMA) and tetraethyl orthosilicate (TEOS) was investigated. The complexity and fine scale of the co-network interactions requires the development of new analytical methods to understand how network evolution dictates the wide-ranging mechanical properties. Within this work we developed data manipulation techniques of acoustic-AFM and solid state NMR output that provide new approaches to understand the influence of the network structure on the macroscopic elasticity. The concentration of pTMSPMA in the silica sol affected the gelation time, ranging from 2 h for a hybrid made with 75 wt% inorganic with pTMSPMA at 2.5 kDa, to 1 minute for pTMSPMA with molecular weight of 30 kDa without any TEOS. A new mechanism of gelation was proposed based on the different morphologies derived by AC-AFM observations. We established that the volumetric density of bridging oxygen bonds is an important parameter in structure/property relationships in SiO2 hybrids and developed a method for determining it from solid state NMR data. The variation in the elasticity of pTMSPMA/SiO2 hybrids originated from pTMSPMA acting as a molecular spacer, thus decreasing the volumetric density of bridging oxygen bonds as the inorganic to organic ratio decreased

A Subset of Secreted Proteins in Ascites Can Predict Platinum-Free Interval in Ovarian Cancer

Simple SummaryIdentifying proteins that correlate with better or worse outcomes may help to identify new treatment approaches for advanced high-grade serous ovarian cancer. Here, we utilize a machine learning technique to correlate the levels of 58 secreted proteins in tumor ascites with the time to disease recurrence after chemotherapy, which is known clinically as the platinum-free interval. We identify several candidate proteins correlated to shorter or longer platinum-free intervals and describe model analysis methods that may be useful for other studies aiming to identify factors impacting patient outcomes. Future validation of these factors in a prospective cohort would confirm their clinical utility, whereas a study of the mechanisms that they impact may identify new therapies. The time between the last cycle of chemotherapy and recurrence, the platinum-free interval (PFI), predicts overall survival in high-grade serous ovarian cancer (HGSOC). To identify secreted proteins associated with a shorter PFI, we utilized machine learning to predict the PFI from ascites composition. Ascites from stage III/IV HGSOC patients treated with neoadjuvant chemotherapy (NACT) or primary debulking surgery (PDS) were screened for secreted proteins and Lasso regression models were built to predict the PFI. Through regularization techniques, the number of analytes used in each model was reduced; to minimize overfitting, we utilized an analysis of model robustness. This resulted in models with 26 analytes and a root-mean-square error (RMSE) of 19 days for the NACT cohort and 16 analytes and an RMSE of 7 days for the PDS cohort. High concentrations of MMP-2 and EMMPRIN correlated with a shorter PFI in the NACT patients, whereas high concentrations of uPA Urokinase and MMP-3 correlated with a shorter PFI in PDS patients. Our results suggest that the analysis of ascites may be useful for outcome prediction and identified factors in the tumor microenvironment that may lead to worse outcomes. Our approach to tuning for model stability, rather than only model accuracy, may be applicable to other biomarker discovery tasks.</p

Development of a Protocol for Obtaining Biological Samples for Genetic Testing from Remote Individuals

Pharmacogenomic sequencing allows individuals to learn more about how they will respond to certain medications but requires shipping of a biological sample. One complication of sending biological samples to remote laboratories is stability. Blood generally yields sufficient quantities of high-quality DNA but requires a clinic visit. Saliva and buccal swabs are routinely used for DNA extractions, but the DNA quality is notoriously low due to the presence of bacteria in the mouth. Additionally, elderly individuals have difficulty producing enough saliva for testing, and the tubes contain several milliliters of liquid and shipping requires special considerations. Dried blood spot cards, which serve as an alternative to saliva and buccal swabs, yield high-quality DNA and ship easily, but may produce a lower yield. This project aims to determine which biological sample methods can reasonably be obtained from remote individuals

Loss of Olfactory Receptor Genes Coincides with the Acquisition of Full Trichromatic Vision in Primates

Olfactory receptor (OR) genes constitute the molecular basis for the sense of smell and are encoded by the largest gene family in mammalian genomes. Previous studies suggested that the proportion of pseudogenes in the OR gene family is significantly larger in humans than in other apes and significantly larger in apes than in the mouse. To investigate the process of degeneration of the olfactory repertoire in primates, we estimated the proportion of OR pseudogenes in 19 primate species by surveying randomly chosen subsets of 100 OR genes from each species. We find that apes, Old World monkeys and one New World monkey, the howler monkey, have a significantly higher proportion of OR pseudogenes than do other New World monkeys or the lemur (a prosimian). Strikingly, the howler monkey is also the only New World monkey to possess full trichromatic vision, along with Old World monkeys and apes. Our findings suggest that the deterioration of the olfactory repertoire occurred concomitant with the acquisition of full trichromatic color vision in primates