Synthetic plastics are ubiquitously used in a broad range of applications, including food and drink packaging. Plastics often contain chemical additives, including bisphenols, phthalates, and terephthalic acid, which can degrade under thermal stress. The environmental presence of these chemicals is cause for public concern, especially in consumer products that utilize plastic packaging, as many have been identified as endocrine disruptors. This study sought to determine exposure to phthalates, bisphenols, and terephthalic acid by quantifying a broad spectrum of these analytes within three bottled water brands at varying temperature exposure levels using the combination of solid phase extraction followed by isotope dilution liquid chromatography-tandem mass spectrometry. Monobenzyl phthalate was detected in two of the three brands after bottles were heated to ~100 °C, ranging from 98 – 107 ng/L, and bisphenol A was detected in one brand at ~100 °C at an average concentration of 748 ± 36 ng/L. Subsequent mass loading calculations demonstrated that bioaccumulation of BPA from Brand C after high levels of temperature exposure well exceeded the tolerable daily intake (TDI). Findings in this study indicate that consumers should not be expected to incur harmful exposures to the target compounds under normal conditions as analytes were not measured in water bottle samples at 25 °C or 60 °C. Further studies should explore a more nuisance approach to heating over long durations, including that of ultraviolet exposure.
There is increasing interest in understanding how active learning affects students’ mental health as science courses transition from traditional lecture to active learning. Prior research has found that active learning can both alleviate and exacerbate undergraduate mental health problems. Existing studies have only examined the relationship between active learning and anxiety. No studies have examined the relationship between active learning and undergraduate depression. To address this gap in the literature, we conducted hour-long exploratory interviews with 29 students with depression who had taken active learning science courses across six U.S. institutions. We probed what aspects of active learning practices exacerbate or alleviate depressive symptoms and how students’ depression affects their experiences in active learning. We found that aspects of active learning practices exacerbate and alleviate students’ depressive symptoms, and depression negatively impacts students’ experiences in active learning. The underlying aspects of active learning practices that impact students’ depression fall into four overarching categories: inherently social, inherently engaging, opportunities to compare selves to others, and opportunities to validate or invalidate intelligence. We hope that by better understanding the experiences of undergraduates with depression in active learning courses we can create more inclusive learning environments for these students.
Diabetes affects millions of people globally and can lead to other severe health complications when undiagnosed or not properly managed. The incidence of diabetes has rapidly increased over the past several years, however, not all individuals have access to affordable or convenient healthcare. We hypothesize that wastewater-based epidemiology (WBE) has the potential to assess community health status by analyzing biomarkers indicative of human health and disease, including diabetes. Used in tandem with current methods, monitoring indicators of diabetes in community wastewater could provide a comprehensive assessment tool for disease prevalence in large and small populations. Specifically, the proposed targeted biomarker evaluated in this study to indicate population-wide diabetes prevalence was 8-hydroxy-2’- deoxyguanosine (8-OHdG). This work combines a rigorous literature review and initial laboratory studies to explore the possibility of diabetes monitoring at the community level using WBE. Here, 24-hour composite wastewater samples were collected from within two wastewater sub-catchments of Greater Tempe, AZ. Overall goals of this study were to: i) Determine the feasibility to detect endogenous markers of diabetes in community wastewater; ii) Assess the potential impact of confounding factors, such as smoking, cancer, and atherosclerosis, through a literature analysis; and iii) Evaluate the socioeconomic status and demographics of the study population. Preliminary results of the experiments suggest this methodology to be feasible, as indicated by the observation of detectable signals of 8-OHdG in community wastewater collected from the sewer infrastructure; however, future work and continued experimentation will be required to address low signal intensity and assay precision and accuracy. Thus, the work presented here provides valuable proof-of-concept data, with detailed information on the method employed and identified opportunities to further determine the relationship between 8-OHdG concentrations in municipal wastewater and diabetes prevalence at the community level.
Diabetes affects millions of people globally and can lead to other severe health complications when undiagnosed or not properly managed. The incidence of diabetes has rapidly increased over the past several years, however, not all individuals have access to affordable or convenient healthcare. We hypothesize that wastewater-based epidemiology (WBE) has the potential to assess community health status by analyzing biomarkers indicative of human health and disease, including diabetes. Used in tandem with current methods, monitoring indicators of diabetes in community wastewater could provide a comprehensive assessment tool for disease prevalence in large and small populations. Specifically, the proposed targeted biomarker evaluated in this study to indicate population-wide diabetes prevalence was 8-hydroxy-2’-deoxyguanosine (8-OHdG). This work combines a rigorous literature review and initial laboratory studies to explore the possibility of diabetes monitoring at the community level using WBE. Here, 24-hour composite wastewater samples were collected from within two wastewater sub-catchments of Greater Tempe, AZ. Overall goals of this study were to: i) Determine the feasibility to detect endogenous markers of diabetes in community wastewater; ii) Assess the potential impact of confounding factors, such as smoking, cancer, and atherosclerosis, through a literature analysis; and iii) Evaluate the socioeconomic status and demographics of the study population. Preliminary results of the experiments suggest this methodology to be feasible, as indicated by the observation of detectable signals of 8-OHdG in community wastewater collected from the sewer infrastructure; however, future work and continued experimentation will be required to address low signal intensity and assay precision and accuracy. Thus, the work presented here provides valuable proof-of-concept data, with detailed information on the method employed and identified opportunities to further determine the relationship between 8-OHdG concentrations in municipal wastewater and diabetes prevalence at the community level.
Currently, there are a number of studies confirming the link between exposure to certain chemicals, notably pesticides (Costello et. al. 2009, Wang et. al 2014), heavy metals such as arsenic (Chen et. al. 2017), ambient air pollution (Chen et. al. 2016), and chemicals specific to certain industrial fields (Nielsen et. al. 2021). However, few papers have attempted to perform a widespread analysis of the factors associated with Parkinson’s disease to identify whether the risk of developing the disease is dependent on different factors regionally. The goal of my thesis project is to complete a meta-analysis of toxins- where exposure may occur in both residential and occupational settings- that are associated with Parkinson’s to determine such regional differences and to identify any gaps in current literature, which may direct the course of future research in the field. As seen in this paper, it appears that occupational exposure to toxins appears to have the greatest impact on the risk of developing Parkinson’s disease, particularly pesticides and industrial toxins. However, there are numerous gaps with regards to data collection, regions studied, and quantification of toxin concentrations. However, this data may be useful in identifying at-risk populations if more extensive incremental and biopsy data regarding these toxins is provided.
