Musical tastes reflect our unique values and experiences, our relationships with others, and the places where we live. But as each of these things changes, do our tastes also change to reflect the present, or remain fixed, reflecting our past? Here, we investigate how where a person lives shapes their musical preferences, using geographic relocation to construct quasi-natural experiments that measure short- and long-term effects. Analyzing comprehensive data on over 16 million users on Spotify, we show that relocation within the United States has only a small impact on individuals’ tastes, which remain more similar to those of their past environments. We then show that the age gap between a person and the music they consume indicates that adolescence, and likely their environment during these years, shapes their lifelong musical tastes. Our results demonstrate the robustness of individuals’ musical identity, and shed new light on the development of preferences.

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For over 25 years, imaging of DNA by atomic force microscopy has been intensely pursued. Ideally, such images are then used to probe the physical properties of DNA and characterize protein–DNA interactions. The atomic flatness of mica makes it the preferred substrate for high signal-to-noise ratio (SNR) imaging, but the negative charge of mica and DNA hinders deposition. Traditional methods for imaging DNA and protein–DNA complexes in liquid have drawbacks: DNA conformations with an anomalous persistence length (p), low SNR, and/or ionic deposition conditions detrimental to preserving protein–DNA interactions. Here, we developed a process to bind DNA to mica in a buffer containing both MgCl₂ and KCl that resulted in high SNR images of equilibrated DNA in liquid. Achieving an equilibrated 2D configuration (i.e., p = 50 nm) not only implied a minimally perturbative binding process but also improved data quality and quantity because the DNA’s configuration was more extended. In comparison to a purely NiCl₂-based protocol, we showed that an 8-fold larger fraction (90%) of 680-nm-long DNA molecules could be quantified. High-resolution images of select equilibrated molecules revealed the right-handed structure of DNA with a helical pitch of 3.5 nm. Deposition and imaging of DNA was achieved over a wide range of monovalent and divalent ionic conditions, including a buffer containing 50 mM KCl and 3 mM MgCl₂. Finally, we imaged two protein–DNA complexes using this protocol: a restriction enzyme bound to DNA and a small three-nucleosome array. We expect such deposition of protein–DNA complexes at biochemically relevant ionic conditions will facilitate biophysical insights derived from imaging diverse protein–DNA complexes.

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“With respect to components of academia, I firmly believe that these are difficult to separate,” she says. “The best way to deeply understand scientific concepts is to get your hands dirty— actually perform an experiment, write a program, or solve a math problem — or to teach the concepts to someone else. In the best-case scenarios, you do both.”

Her ability to apply this philosophy recently earned Dowell the National Science Foundation’s most prestigious award for junior faculty, the Faculty Early Career Development (CAREER) grant. Providing five years of support totaling more than $650,000, the grant recognizes emerging investigators who excel at combining teaching and research in ways that directly impact their institutions and the broader community. Dowell is one of only ten scientists nationwide in the field of molecular and cellular bioscience who have received the award so far this year.

The CAREER program requires scientists to complete specific aims in both teaching and research.  Successful candidates have designed projects in which their research feeds into their teaching goals and vice versa, creating a long-term cycle that advances both aims. Projects are also expected to meet institutional needs, such as providing students with mentored external development opportunities or promoting interdisciplinary research.

Dowell prefers the term “” in her lab’s approach, a term coined by her graduate mentor, Dr. Sean Eddy. Given her and her students’ concentrations in computer science, statistics, molecular biology and genetics, she defines the concept as “following problem wherever it leads you.”

“I have a hard time when people ask me how I integrate such diverse fields,” she says. “It isn't about integrating fields, areas or components, but rather ignoring those kinds of boundaries.”

The CAREER project embraces this philosophy by providing two unique educational activities for students while furthering the Dowell lab’s continuing research on the molecular impact of aneuploidy. Down syndrome is a well-known example of aneuploidy, which occurs when a person has more copies of a chromosome than normal.

Using computational models of biological processes and experiments on yeast cells, the Dowell lab will explore how regulators—genes that affect the function and form of other genes— affect the early processes of genetic expression, called transcription.

Dowell describes her research in musical terms. If the human genome is the score for a symphony, transcription is like the music heard from that score. In genetics, a regulator gene performs the work of the musical conductor, controlling qualities such as tempo and volume.  

While regulators in the human genome number about 1,800, having too many of these conductors in a particular cell can throw off the music. Aneuploidy is an example in which the dose of regulators has altered expression of genes, causing deleterious affects for people with Down syndrome.

“We understand that transcription is affected by aneuploidy, but we don’t know how it works at the molecular level,” Dowell says.

The educational component of project contains two unique objectives that encourage students to engage in external opportunities that contribute to their education and community. The first objective is to establish a permanent iGEM team at CU. iGEM, or international Genetically Engineered Machine, is the world’s foremost synthetic biology competition for undergraduates. Last year’s CU team won the gold medal at the North American competition for their “DIY Biology” project to create a set of low-cost tools for performing synthetic biology.

The second objective is to better engage scientists in understanding Responsible Conduct of Research (RCR) by creating an interactive game. RCR encompasses professional norms and ethical principles scientists must use in the performance of their work. 

“The game will not only train scientists in an engaging and interactive manner but also will enable studies into how peer pressure influences ethical behavior.” Dowell wrote in her CAREER grant application. “In the end, the long term impact of creating honest, intelligent and creative scientists is incalculable.”

More information on antedisciplinary research, iGEM and aneuploidy can be found on the 

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“I was lucky that I had a graduate advisor who understood that I had 11 Olympic workouts a week,” she says of her graduate experience. “But, being at MIT was a fire hose of fabulous things to think about.”

Bradley acts as an advisor on the Biofrontiers Institute’s graduate program because cross-discipline work is something she is passionate about. Computer science now plays a huge role in managing the massive data sets in the biosciences.

“Computers, by default, are cross-disciplinary. They are used everywhere in scientific discovery. We solve equations with computers because we can’t solve them with pencil and paper,” she says. “And it is because I am open to working across disciplines that I tend to be the home in the department for the student projects nobody else will supervise.”

Rhonda Hoenigman is pursuing a Ph.D., and with Bradley’s encouragement and advice, she has created a computer algorithm that aids in the design of efficient landscapes: those that offer the best growth, with the most shade, using the least amount of water. This “agent-based” algorithm allows the plants to move themselves in a virtual world, and find the places they would grow the best. Hoenigman has a vision for the algorithm to help building planners save water while cooling structures with shade—a necessity for water-starved areas like the American Southwest.

Caleb Phillips, another student who works with Bradley, also created a new algorithm that addresses sustainability: one that can show us how to redistribute food waste.  Phillips’ algorithm takes into account how much food is being thrown away across a given region, like �鶹ӰԺ County, and also calculates the cost of rescuing it and redistributing it to organizations in need across that region.

Most food rescue organizations use a warehouse model, which usually prevents them from handling fresh produce and other perishables. In addition, transportation costs are higher when trucks are needed to deliver food from a central warehouse.

With the help of this algorithm, the organization that Phillips founded, , takes surplus foods from stores and restaurants, and delivers them immediately to organizations that will use them. The kicker: �鶹ӰԺ Food Rescue picks up and delivers food using bikes and trailers, keeping costs at their lowest.

“�鶹ӰԺ 70 or 80 pounds a day is a normal delivery, but we rescued 950 pounds the day after Thanksgiving,” says Phillips, who has to notch his belt a little tighter because of all the bike deliveries he now makes. On days where food donations are too heavy, or the snow is too deep, Phillips’ organization has access to trucks via �鶹ӰԺ’s CarShare program. “There is definitely enough food in �鶹ӰԺ County to feed everyone,” he says.

“It’s not about us faculty, it’s about them, the students,” Bradley says. “That’s what grad school is about.” And it must be that old Olympic discipline she has that allows her to mentor incredible students, while still producing amazing work of her own.

Bradley studies chaos theory and computer performance dynamics. In her work, dropping the last decimal place off of a number that has six places after the decimal may seem insignificant—not even enough to worry about in a huge data set. But those insignificant numbers can have huge impacts across a large collection of data or across a long period of time. This theory is also known as the “Butterfly Effect,” referring to the flapping of an insect’s wing that could cause enough atmospheric change, over time, to create a devastating hurricane. Bradley is using this theory to work toward learning to predict and manage how computers and data interact.

You don’t have to look too hard to see that there is another “Butterfly Effect” going on in Bradley’s world. If chaos theory is predicting how a small change can equal a large effect, you only need to look as far as Bradley’s students to see how her interactions are exactly that: the butterfly’s wing creating a hurricane of change.

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