Dynamic and flexible nucleic acid models can provide current and future scientists with physical intuition for the structure of DNA and the ways that DNA and its synthetic mimics can be used to build self-assembling structures and advanced nanomachines. As more research labs and classrooms dive into the field of structural nucleic acid nanotechnology, students and researchers need access to interactive, dynamic, handheld models. Here, we present a 3D-printable kit for the construction of DNA and peptide nucleic acid (PNA). We have engineered a previous modular DNA kit to reduce costs while improving ease of assembly, flexibility, and robustness. We have also expanded the scope of available snap-together models by creating the first 3D-printable models of γPNA, an emerging material for nuclease- and protease-resistance nanotechnology. Building on previous research, representative nucleic acid duplexes were split into logical monomer segments, and atomic coordinates were used to create solid models for 3D printing. We used a human factors approach to customize 3 types of articulated snap-together connectors that allow for physically relevant motion characteristic of each interface in the model. Modules are easy to connect and separate manually but stay together when the model is manipulated. To greatly reduce cost, we bundled these segments for printing, and we created a miniaturized version that uses less than half the printing material to build. Our novel 3D-printed articulated snap-together models capture the flexibility and robustness of DNA and γPNA nanostructures. Resulting handheld helical models replicate the geometries in published structures and can now flex to form crossovers and allow biologically relevant zipping and unzipping to allow complex demonstrations of nanomachines undergoing strand displacement reactions. Finally, the same tools used to create these models can be readily applied to other types of backbones and nucleobases for endless research and education possibilities.ABSTRACT
Specifications grading is a student-centered assessment method that enables flexibility and opportunities for revision. Here, we describe the first known full implementation of specifications grading in an upper-division chemical biology course. Due to the rapid development of relevant knowledge in this discipline, the overarching goal of this class is to prepare students to interpret and communicate about current research. In the past, a conventional points-based assessment method made it challenging to ensure that satisfactory standards for student work were consistently met, particularly for comprehensive written assignments. Specifications grading was chosen because the core tenet requires students to demonstrate minimum learning objectives to achieve a passing grade and complete more content of increased cognitive complexity to achieve higher grades. This strict adherence to determining grades based on demonstrated skills is balanced by opportunities for revision or flexibility in assignment deadlines. These options are made manageable for the instructors through the use of a token economy with a limited number of tokens that students can choose to use when needed. Over the duration of the course, a validated survey on self-efficacy showed slight positive trends, student comprehension and demonstrated skills qualitatively improved, and final grade distributions were not negatively affected. Instructors noticed that discussions with students were more focused on course concepts and feedback, rather than grades, while overall grading time was reduced. Responses to university-administered student feedback surveys revealed some self-reported reduction in anxiety, as well as increased confidence in managing time and course material. Recommendations are provided on how to continue to improve the overall teaching and learning experience for both instructors and students.ABSTRACT
There are many instances of collective behaviors in the natural world. For example, eukaryotic cells coordinate their motion to heal wounds; bacteria swarm during colony expansion; defects in alignment in growing bacterial populations lead to biofilm growth; and birds move within dynamic flocks. Although the details of how these groups behave vary across animals and species, they share the same qualitative feature: they exhibit collective behaviors that are not simple extensions of details associated with the motion of an individual. To learn more about these biological systems, we propose studying these systems through the lens of the foundational Vicsek model. Here, we present the process of building this computational model from scratch in a tutorial format that focuses on building the appropriate skills of an undergraduate student. In doing so, an undergraduate student should be able to work alongside this article, the corresponding tutorial, and the original manuscript of the Vicsek model to build their own model. We conclude by summarizing some of the current work involving computational modeling of flocking with Vicsek-type models.ABSTRACT
As biophysicists, many of us are keen on conveying the beauty and importance of our field to diverse audiences, including those who are not, and do not intend to be, scientists. In this report, I describe experiences communicating biophysics to nonscientists: nonscience major undergraduate students at a large, public US university, high school students, and general readers. I highlight approaches that help capture the attention of wider audiences, especially drawing on examples that illuminate health and disease. Readers of this report presumably appreciate the value of biophysics. The fusion of biology and physics illuminates the workings of the livingIntroduction