12 research outputs found
Asynchronous student engagement in analysis of climate data achieves learning objectives related to climate change understanding, statistical competence, and climate anxiety
Learning in asynchronous online environments has gained importance over the last several decades, and educational environment shifts from the COVID-19 pandemic appear to have increased this need. Science educators and students need information about which approaches work in the asynchronous environment where informal feedback tends to be reduced, compared to other teaching modalities. In this study, we asynchronously implemented a learning module across 5 institutions that guided students (N = 199) from prescriptive data analysis through guided inquiry and eventually to open inquiry. The module focuses on the science behind climate change. Students work with the same authentic data sets used by professional scientists to examine geologic history and causes of climate change. By analyzing contemporary atmospheric carbon dioxide and temperature data and then using the 800,000-year record available from the Vostok ice core proxy record of atmospheric properties, students identify the causes of climate change and discover the unprecedented nature of recent atmospheric changes. Using a pre/post-module assessment, we demonstrate improvement in students’ understanding of climate change processes and statistical methods used to analyze data. However, there was no evidence that the module develops students’ scientific reasoning about the relationship between causation and correlation. Students maintained that correlation is not causation, even when a robust causal mechanism (i.e., the greenhouse effect) explains the link between atmospheric carbon dioxide and temperature. Finally, our analysis indicated that generally, anxiety about climate change was reduced during the module, such that students become less anxious about the climate change the more they learn about it. However, science-denying students experienced much higher anxiety about climate change than students who accepted the scientific consensus about climate change. Climate science-dissenting students were so few in this study that a statistical comparison was not possible, but this intriguing finding warrants further investigation of the role of anxiety in science denial. Mainly, this study demonstrates how asynchronous online learning environments can indeed support the achievement of learning objectives related to conducting authentic science, such as increasing understanding of climate change and statistical concepts, all while not provoking anxiety about climate change
Derivatives of a benzoquinone acyl hydrazone with activity against Toxoplasma gondii
Toxoplasma gondii is an obligate intracellular parasite with global incidence. The acute infection, toxoplasmosis, is treatable but current regimens have poor host tolerance and no cure has been found for latent infections. This work builds upon a previous high throughput screen which identified benzoquinone acyl hydrazone (KG8) as the most promising compound; KG8 displayed potent in vitro activity against T. gondii but only marginal in vivoefficacy in a T. gondii animal model. To define the potential of this new lead compound, we now describe a baseline structure-activity relationship for this chemotype. Several derivatives displayed IC50\u27s comparable to that of the control treatment pyrimethamine with little to no cytotoxicity. The best of these, KGW44 and KGW59, had higher metabolic stability than KG8. In an in vivo T. gondii murine model, KGW59 significantly increased survivorship. This work provides new insights for optimization of this novel chemotype
Diaryl ureas as an antiprotozoal chemotype
We now describe the physicochemical profiling, in vitro ADME, and antiparasitic activity of eight N,N'-diarylureas to assess their potential as a broad-spectrum antiprotozoal chemotype. Chromatographic LogD7.4 values ranged from 2.5 to 4.5; kinetic aq. solubilities were /=10. One N,N'-diarylurea had demonstrable activity in mouse models of malaria and toxoplasmosis
The Relationship Between Environmental Parameters and Microbial Water Quality at Two Costa Rican Beaches from 2002 to 2017
Environmental conditions influence fecal indicator bacteria (FIB) levels, which are routinely used to characterize recreational water quality. This study examined 15 years of environmental and FIB data at Puntarenas and Jacó beach, Costa Rica. FIB relationships with sea level, wave height, precipitation, direct normal irradiance (DNI), wind, and turbidity were analyzed. Pearson\u27s correlations identified lags between 24 and 96 h among environmental parameters and FIB. Multiple linear regression models composed of environmental parameters explained 24% and 27% of fecal coliforms and enterococci variability in Jacó, respectively. Puntarenas’s models explained 17–26% of fecal coliforms and 12–18% enterococci variability. Precipitation, sea level anomalies, and wave height most frequently explained FIB variability. Hypothesis testing often identified significant differences in precipitation, wave height, daily sea level anomalies, and maximum sea level 24 h prior between days with and without FIB threshold exceedance. Unexpected FIB interactions with DNI, sea level, and turbidity highlight the importance of future investigations