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The goal of this study was to evaluate the impact of a two-quarter freshman course series entitled “Food: A Lens for Environment and Sustainability” (Food cluster) on the carbon footprint of food choices by college freshmen attending a large public university in California. Students enrolled in the course completed a baseline questionnaire about their diets in early fall quarter and then again at follow-up, about 6 months later at the end of the winter quarter. The control group consisted of freshmen enrolled in a different course series entitled “Evolution of the Cosmos and Life” (Cosmos cluster). The instruction in the Food cluster included lecture material on general environmental science and life cycle analyses of food, an analysis of a reading comparing the environmental footprint of various types of meats, and classroom exercises to calculate the environmental footprint of typical foods. The Cosmos cluster instruction included climate change, but no information about food. While the two groups were statistically indistinguishable at baseline, throughout the period of the study, Food cluster students decreased (a) their overall dietary carbon footprint for a 2000-kcal normalized diet by 7% (p = 0.062), (b) the beef component of their dietary carbon footprint by 19% (p = 0.024), and (c) their reported ruminant consumption by 28% (p < 0.001). At follow-up, the overall dietary footprints for Food cluster students were 4153 and 5726 g CO2-eq/day for female and male students, respectively, compared to 4943 and 6958 g CO2-eq/day for female and male Cosmos students. In the Food cluster, both genders decreased their reported ruminant meat consumption by about a serving per week, while reported ruminant meat consumption increased for males in the control group. Modest, voluntary dietary changes such as those observed in this study could play an important role in mitigating climate change. Extrapolated across the entire US population, the difference in dietary carbon footprint observed between the Food cluster and control group would amount to 33% of the reduction required for the 2013 President’s Climate Action Plan (2013).

In vivo genome editing with clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 generates powerful tools to study gene regulation and function. We revised the homology-assisted CRISPR knock-in method to convert Drosophila GAL4 lines to LexA lines using a new universal knock-in donor strain. A balancer chromosome–linked donor strain with both body color (yellow) and eye red fluorescent protein (RFP) expression markers simplified the identification of LexA knock-in using light or fluorescence microscopy. A second balancer chromosome–linked donor strain readily converted the second chromosome–linked GAL4 lines regardless of target location in the cis-chromosome but showed limited success for the third chromosome–linked GAL4 lines. We observed a consistent and robust expression of the yellow transgene in progeny harboring a LexA knock-in at diverse genomic locations. Unexpectedly, the expression of the 3xP3-RFP transgene in the “dual transgene” cassette was significantly increased compared with that of the original single 3xP3-RFP transgene cassette in all tested genomic locations. Using this improved screening approach, we generated 16 novel LexA lines; tissue expression by the derived LexA and originating GAL4 lines was similar or indistinguishable. In collaboration with 2 secondary school classes, we also established a systematic workflow to generate a collection of LexA lines from frequently used GAL4 lines.

This work introduces the particle-intensity channel (PIC) as a model for molecular communication systems and characterizes the capacity limits as well as properties of the optimal (capacity-achieving) input distributions for such channels. In the PIC, the transmitter encodes information, in symbols of a given duration, based on the probability of particle release, and the receiver detects and decodes the message based on the number of particles detected during the symbol interval. In this channel, the transmitter may be unable to control precisely the probability of particle release, and the receiver may not detect all the particles that arrive. We model this channel using a generalization of the binomial channel and show that the capacity-achieving input distribution for this channel always has mass points at probabilities of particle release of zero and one. To find the capacity-achieving input distributions, we develop an efficient algorithm we call dynamic assignment Blahut-Arimoto (DAB). For diffusive particle transport, we also derive the conditions under which the input with two mass points is capacity-achieving.

Genome editing in vivo with CRISPR/Cas9 generates powerful tools to study gene regulation and function. We developed CRISPR-based methods that permitted secondary school student scientists to convert Drosophila GAL4 lines to LexA lines. Our novel curricula implement a new donor strain optimizing Homology-assisted CRISPR knock-in (HACK) that simplifies screening using light microscopy. Successful curricula adoption by a consortium of schools led to the generation and characterization of 16 novel LexA lines. This includes extensive comparative tissue expression analysis between the parental Gal4 and derived LexA lines. From this collaboration, we established a workflow to systematically generate LexA lines from frequently-used GAL4 lines. Modular courses developed from this effort can be tailored to specific secondary school scheduling needs, and serve as a template for science educators to innovate courses and instructional goals. Our unique collaborations highlight that resources and expertise harnessed by university-based research laboratories can transform experiential science instruction in secondary schools while addressing research needs for the community of science.

Abstract Advances in whole genome sequencing promise to enable the accurate and comprehensive structural variant (SV) discovery. Dissecting SVs from whole genome sequencing (WGS) data presents a substantial number of challenges and a plethora of SV-detection methods have been developed. Currently, there is a paucity of evidence which investigators can use to select appropriate SV-detection tools. In this paper, we evaluated the performance of SV-detection tools using a comprehensive PCR-confirmed gold standard set of SVs. In contrast to the previous benchmarking studies, our gold standard dataset included a complete set of SVs allowing us to report both precision and sensitivity rates of SV-detection methods. Our study investigates the ability of the methods to detect deletions, thus providing an optimistic estimate of SV detection performance, as the SV-detection methods that fail to detect deletions are likely to miss more complex SVs. We found that SV-detection tools varied widely in their performance, with several methods providing a good balance between sensitivity and precision. Additionally, we have determined the SV callers best suited for low and ultra-low pass sequencing data. Competing Interest Statement The authors have declared no competing interest. Footnotes * Modified author affiliation * https://github.com/Mangul-Lab-USC/benchmarking-sv-callers-paper/