Bioethics is an important aspect of the core competency of biology of understanding the relationship between science and society, but because of the controversial nature of the topics covered in bioethics courses, different groups of students may experience identity conflicts or discomfort when learning about them. However, no previous studies have investigated the impact of undergraduate bioethics students’ experiences in bioethics courses on their opinions and comfort. To fill this gap in knowledge, we investigated undergraduate bioethics students’ attitudes about and comfort when learning abortion, gene editing, and physician assisted suicide, as well as how their gender, religious, and political identity influence their attitudes and changes in their attitudes after instruction. We found that religious students were less supportive of gene editing, abortion, and physician assisted suicide than nonreligious students, non-liberal students were less supportive of abortion and physician assisted suicide than liberal students, and women were less supportive of abortion than men. Additionally, we found that religious students were less comfortable than nonreligious students when learning about gene editing, abortion, and physician assisted suicide, and non-liberal students were less comfortable than liberal students when learning about abortion. When asked how their comfort could have been improved, those who felt that their peers or instructors could have done something to increase their comfort most commonly cited that including additional unbiased materials or incorporating materials and discussions that cover both sides of every controversial issue would have helped them to feel more comfortable when learning about gene editing, abortion, and physician assisted suicide. Finally, we found that students who were less comfortable learning about abortion and physician assisted suicide were less likely to participate in discussions regarding those topics. Our findings show that students in different groups not only tend to have different support for controversial topics like gene editing, abortion, and physician assisted suicide, but they also feel differentially comfortable when learning about them, which in turn impacts their participation. We hope that this work helps instructors to recognize the importance of their students’ comfort to their learning in bioethics courses, and from this study, they can take away the knowledge that students feel their comfort could be most improved by the incorporation of additional inclusive materials and course discussions regarding the controversial topics covered in the course.

Methicillin resistant Staphylococcus aureus (MRSA) is currently a major cause of skin and soft tissue infections (SSTI) in the United States. Seasonal variation of MRSA infections in hospital settings has been widely observed. However, systematic time-series analysis of incidence data is desirable to understand the seasonality of community acquired (CA)-MRSA infections at the population level. In this paper, using data on monthly SSTI incidence in children aged 0–19 years and enrolled in Medicaid in Maricopa County, Arizona, from January 2005 to December 2008, we carried out time-series and nonlinear regression analysis to determine the periodicity, trend, and peak timing in SSTI incidence in children at different age: 0-4 years, 5-9 years, 10-14 years, and 15-19 years. We also assessed the temporal correlation between SSTI incidence and meteorological variables including average temperature and humidity. Our analysis revealed a strong annual seasonal pattern of SSTI incidence with peak occurring in early September. This pattern was consistent across age groups. Moreover, SSTIs followed a significantly increasing trend over the 4-year study period with annual incidence increasing from 3.36% to 5.55% in our pediatric population of approximately 290,000. We also found a significant correlation between the temporal variation in SSTI incidence and mean temperature and specific humidity. Our findings could have potential implications on prevention and control efforts against CA-MRSA.

The large-scale use of antivirals during influenza pandemics poses a significant selection pressure for drug-resistant pathogens to emerge and spread in a population. This requires treatment strategies to minimize total infections as well as the emergence of resistance. Here we propose a mathematical model in which individuals infected with wild-type influenza, if treated, can develop de novo resistance and further spread the resistant pathogen. Our main purpose is to explore the impact of two important factors influencing treatment effectiveness: i) the relative transmissibility of the drug-resistant strain to wild-type, and ii) the frequency of de novo resistance. For the endemic scenario, we find a condition between these two parameters that indicates whether treatment regimes will be most beneficial at intermediate or more extreme values (e.g., the fraction of infected that are treated). Moreover, we present analytical expressions for effective treatment regimes and provide evidence of its applicability across a range of modeling scenarios: endemic behavior with deterministic homogeneous mixing, and single-epidemic behavior with deterministic homogeneous mixing and stochastic heterogeneous mixing. Therefore, our results provide insights for the control of drug-resistance in influenza across time scales.