“Of all the forms of inequality” Dr. Martin Luther King Jr. once said in a 1966 press conference, “injustice in health is the most shocking and the most inhumane.”
In honor of King’s impact on public health, Duke’s dean of Trinity College Dr. Gary G. Bennett delivered a powerful address Jan. 12 at the Trent Semans Center. Entitled ‘You have to Keep Moving Forward: Obesity in High-Risk Populations,’ Bennett discussed America’s Obesity Epidemic, and its disproportionate effects on Black women.
“More than 40% of the American population has obesity,” Bennett began. Incidence rates among Black women are the highest and have been since the epidemic began in 1955. “These disparities have not closed, and in many cases, they’ve widened over the years,” Bennett said.
Raisi-Estabragh 2023
Type two diabetes, hypertension, and cardiovascular disease are just some of the health risks associated with obesity. Compared to other racial groups, Black women are more likely to suffer from these conditions, as well as die from their effects. Furthermore, it appears that the efficacy of treatment options is significantly lower for patients of African descent.
But why do such disparities exist in the first place? According to Bennett, they can be attributed to a range of internal and external factors. “There certainly are physiological variations that are worth noting here, which is perhaps a challenge in all of obesity research.”
Research published in the journal Nature in 2022 found that, while there are different forms of obesity, that have shared ‘genetic and biological underpinnings.’ Environmental factors are also driving disparities. Black women are “exposed to more obesogenic environments, food desserts,” Bennett explained. With limited access to affordable and nutritious food, options for healthy eating are slim.
But perhaps most interestingly, Black women also have a range of sociocultural factors at play. “There are fewer within-group social pressures to lose weight,” Bennett maintained. Other sociocultural factors include higher body image satisfaction and higher weight misperception. “This is problematic in some ways,” he continued. While it protects against certain eating disorders and low self-esteem, “It does challenge your ability to achieve weight loss.”
For Black women, obesity is a complex public health issue that needs to be addressed.
But how? Frommedication to surgery, there are myriad potential treatment options. According to Bennett, however, the real key is lifestyle intervention. “It really is the foundation.” Comprised of three parts: reduced calorie diet, physical activity, and self-monitoring, lifestyle intervention is able to reach the widest range of participants.
Like other treatment options, the lifestyle intervention route shows racial disparities in its outcomes. Because of this, Dr. Bennett’s work focuses on developing methods that are designed with Black patients in mind.
At the forefront of his research is a new online intervention called iOTA, which stands for Interactive Obesity Treatment Approach. “This is a digital obesity approach that we designed specifically for high-risk populations.” The platform personalizes weight loss goals and feedback, which assist in program retention.
In addition, participants are equipped with coaching support from trained medical professionals. “This IOTA approach does a bunch of things,” Bennett said. “It promotes weight loss and prevents weight gain, improves cardiometabolics,” along with a host of other physical benefits. Results also show a reduction in depressive symptoms and increased patient engagement. Truly incredible.
Scholars like Bennett have continued the fight for public health equity- a fight advocated for by Dr. King many years ago. For more information on Bennett and his work, you can visit his website here.
The finding of natural quasicrystals is a tale of “crazy stubborn people or stubbornly crazy people,” said physicist and Princeton professor, Paul J. Steinhardt, who spoke at Duke University on October 10 regarding his role in their discovery.
Quasicrystals were once thought to be impossible, as crystals were the only stable form of matter. Crystals allow for periodic patterns of atoms while quasicrystals allow for an ordered, yet non-periodic pattern that results in rotational symmetry. Crystals only allow for two-, three-, four-, and six-fold symmetry and create the geographical shapes of squares/rectangles, triangles, hexagons, and rhombuses (Figure 1). However, quasicrystals allow for ten-fold symmetry with unlimited layers of quasicrystal patterns and various shapes. The penrose tiles (Figure 2) is an example of one-dimensional quasicrystal pattern, while the kitchen tiles of your home is an example of a traditional crystal pattern.
After the discovery of man-made quasicrystals from a fellow scientist, Steinhardt wanted to find quasicrystals in nature as opposed to laboratories. He began this by contacting museums with global mineral samples in case they contained undiscovered quasicrystals. This did not yield any results.
Luca Bindi, who then worked for the Museum of Natural History at the University of Florence in Italy, discovered that Steinhardt was searching for natural quasicrystal and wanted to join his endeavors. Bindi found the first interesting sample at the museum he worked in through the rare mineral, khatyrkite, from the Koryak Mountains of Chukotka, Russia. They analyzed the tip of this sample, the width was that of a strand of hair, and discovered the most perfect ten-fold, rotationally symmetric pattern of a quasicrystal from minerals in nature. Even more interesting was that the chemical compound of this quasicrystal, Al63Cu24Fe13, was the exact composition of quasicrystals created in a Japanese laboratory, now found in a rock.
Steinhardt then took these findings to Lincoln Hollister, a renowned geologist, for his expert opinion. Hollister proceeded to tell Steinhardt that this discovery is impossible as its chemical composition of metallic aluminum cannot be created in nature. Steinhardt wondered if this sample came from a meteorite, which was an “ignorant, stupid suggestion, but Lincoln didn’t know that,” Steinhardt said. Lincoln refers Steinhardt to Glenn Macpherson, an expert meteorologist, who further elaborated that metallic aluminum from meteorites is, once again, impossible.
Two renowned experts in their fields describing the impossibility of Steinhardt and Bindi’s hypotheses was not enough for them to quit. Their next step was to trace Bindi’s khatyrkite to obtain more samples. Firstly, they attempted to find Nico Koekkoek, a Dutch mineral collector who had sold innumerable mineral samples to various museums. Dead end. Then they wrote to museums globally regarding their khatyrkite samples and discovered four potential samples. All fakes. Yet another dead end. Next was to analyze the legitimate sample in St. Petersburg because any sample of a newly discovered mineral must be given to a museum. The uncooperative discoverer, Leonid Razin, had immigrated to Israel and refused to let anyone touch the sample. They had hit a dead end again.
Bindi relayed this story to his sister and her friend over dinner. The friend’s neighbor shared the same common last name as the Dutch mineral collector, so the friend decided to ask his neighbor if it was an unlikely connection. Miraculously, the neighbor was the widow of the Dutch mineral collector and, after much persuading, handed over her late-husband’s secret diary. The diary reveals a mineral smuggler named Tim from Romania whom he received the khatyrkite. They were unable to locate Tim until Koekkoek’s widow relented yet another secret diary, which revealed that Tim had received these minerals from ‘L. Razin.’ The same Leonid Razin who refused them to view the sample! Eventually, Steinhardt discovered that Leonid Razid had sent a man named Valery Kryachko on an expedition for platinum. While he did not find platinum, he gave his samples to Leonid Razin, which astoundingly contained the natural quasicrystals that Steinhardt had searched for decades. Kryachko was completely unaware of its journey and even provided the remaining sample, which Steinhardt and his team used for testing.
Steinhardt’s original “ignorant, stupid suggestion” proved remarkably accurate, as they discovered that a meteorite hit Chukotka and resulted in natural metallic aluminum.
Steinhardt and his dream team needed more samples of khatyrkite to conduct further research. Therefore, seven Russians, five Americans, one Italian, and a cat named Buck set forth the scientific Mission Impossible for natural quasicrystals. They came back with several million grains and after a few weeks, found a sample of clay layer that had not been touched in 10,000 years. This was the first quasicrystal to be declared a natural mineral. They ultimately discovered a total of nine quasicrystal samples, each from a different part of the meteorite.
Steinhardt and his team’s analysis of quasicrystals is still not over and his book, “The Second Kind of Impossible,” delves further into the outlandish details of the over 30 years of research. This extraordinary journey of passion and ambition allows for the thrilling hope for the future of scientific discovery.
If you weren’t outside enjoying the sun on Wednesday, April 19, you were probably milling around Penn Pavilion, a can of LaCroix in hand, taking in the buzz and excited chatter of students presenting at the 2023 Fortin Foundation Bass Connections Showcase.
Open floor presentations at the 2023 Bass Connections Showcase
This annual celebration of Bass Connections research projects featured more than 40 interdisciplinary teams made up of Duke faculty, graduate students, undergraduate students, and even partners from other research institutions.
Research teams presented posters and lightning talks on their findings. You might have heard from students aiming to increase representation of women in philosophy; or perhaps you chatted with teams researching physiotherapy in Uganda or building earthquake warning systems in Nepal. Below, meet three such teams representing a wide variety of academic disciplines at Duke.
Building sustainable university-community partnerships
As Bass Connections team member Joey Rauch described, “this is a poster about all of these other posters.” Rauch, who was presenting on behalf of his team, Equitable University-Community Research Partnerships, is a senior double-majoring in Public Policy and Dance. His interest in non-profit work led him to get involved in the team’s research, which aims to offer a framework for ethical and effective university-community research collaboration – exactly what teams do in Bass Connections. The group looked at complicated factors that can make equitable relationships difficult, such as university incentive structures, power dynamics along racial, socioeconomic, and ethnic lines, and rigid research processes.
Senior Joey Rauch with his team’s 2nd-place poster!
Along the lines of rigid research, when asked about what his favorite part of Bass Connections has been, Rauch remarked that “research is oddly formal, so having a guiding hand through it” was helpful. Bass Connections offers an instructive, inclusive way for people to get involved in research, whether for the first or fourth time. He also said that working with so many people from a variety of departments of Duke gave him “such a wealth of experience” as he looks to his future beyond Duke.
For more information about the team, including a full list of all team members, click here.
Ensuring post-radiation wellness for women
From left to right: seniors Danica Schwartz, Shernice Martin, Kayle Park, and Michelle Huang
The project has been around for three years and this year’s study, which looked at improving female sexual wellness after pelvic radiation procedures, was in fact a sister study to a study done two years prior on reducing anxiety surrounding pelvic exams.
As Huang described, graduate students and faculty conducted in-depth interviews with patients to better understand their lived experiences. This will help the team develop interventions to help women after life events that affect their pelvic and sexual health, such as childbirth or cancer treatment. These interventions are grounded in the biopsychosocial model of pain, which highlights the links between emotional distress, cognition, and pain processing.
For more information about the team, including a full list of all team members, click here.
From dolphins to humans
Sophomores Noelle Fuchs and Jack Nowacek were manning an interactive research display for their team, Learning from Whales: Oxygen, Ecosystems and Human Health. At the center of their research question is the condition of hypoxia, which occurs when tissues are deprived of an adequate oxygen supply.
Sophomores Noelle Fuchs and Jack Nowacek
Hypoxia is implicated in a host of human diseases, such as heart attack, stroke, COVID-19, and cancer. But it is also one of the default settings for deep-diving whales, who have developed a tolerance for hypoxia as they dive into the ocean for hours while foraging.
The project, which has been around for four years, has two sub-teams. Fuchs, an Environmental Science and Policy major, was on the side of the team genetically mapping deep-diving pilot whales, beaked whales, and offshore bottlenose dolphins off the coast of Cape Hatteras to identify causal genetic variants for hypoxia tolerance within specific genes. Nowacek, a Biology and Statistics double-major, was on the other side of the research, analyzing tissue biopsies of these three cetaceans to conduct experiences on hypoxia pathways.
The team has compiled a closer, more interactive look into their research on their website.
And when asked about her experience being on this team and doing this research, Fuchs remarked that Bass Connections has been a “great way to dip my toe into research and figure out what I do and don’t want to do,” moving forward at Duke and beyond.
For more information about the team, including a full list of all team members, click here.
Statistics and computer science double major Jenny Huang (T’23) started Duke as many of us do – vaguely pre-med, undecided on a major – but she knew she had an interest in scientific research. Four years later, with a Quad Fellowship and an acceptance to MIT for her doctoral studies, she reflects on how research shaped her time at Duke, and how she hopes to impact research.
Jenny Huang (T’23)
What is it about statistics? And what is it about research?
With experience in biology research during high school and during her first year at Duke, Huang toyed with the idea of an MD/PhD, but ultimately realized that she might be better off dropping the MD. “I enjoy figuring out how the world works” Huang says, and statistics provided a language to examine the probabilistic and often unintuitive nature of the world around us.
In another life, Huang remarked, she might have been a physics and philosophy double major, because physics offers the most fundamental understanding of how the world works, and philosophy is similar to scientific research: in both, “you pursue the truth through cyclic questioning and logic.” She’s also drawn to engineering, because it’s the process of dissecting things until you can “build them back up from first principles.”
At the International Society for Bayesian Analysis summer conference in Montreal
Huang’s research and the impact of COVID-19
For Huang, research started her first year at Duke, on a Data+ team, led by Professor Charles Nunn, studying the variation of parasite richness across primate species. To map out what types of parasites interacted with what type of monkeys, the team relied on predictors such as body mass, diet, and social activity, but in the process, they came up against an interesting phenomenon.
It appeared that the more studied a primate was, the more interactions it would have with parasites, simply because of the amount of information available on the primate. Due to geographic and experimental constraints, however, a large portion of the primate-parasite network remained understudied. This example of a concept in statistics known as sampling bias was muddling their results. One day, while making an offhand remark about the problem to one of her professors (Professor David Dunson), Huang ended up arranging a serendipitous research match. It turned out that Dunson had a statistical model that could be applied to the problem Nunn and the Data+ team were facing.
The applicability of statistics to a variety of different fields enamored Huang. When COVID-19 hit, it impacted all of us to some degree, but for Huang, it provided the perfect opportunity to apply mathematical models to a rapidly-changing pandemic. For the past two summers, through work with Dunson on a DOMath project, as well as Professor Jason Xu and Professor Rick Durrett, Huang has used mathematical modeling to assess changes in the spread of COVID-19.
On inclusivity in research
As of 2018, just 28% of graduates in mathematics and statistics at the doctoral level identified as women. Huang will eventually be included in this percentage, seeing as she begins her Ph.D. at MIT’s Department of Electrical Engineering and Computer Science in the fall, working with Professor Tamara Broderick.
“When I was younger, I always thought that successful and smart people in academia were white men,” Huang laughed. But that’s not true, she emphasizes: “it’s just that we don’t have other people in the story.” As one of the few female-presenting people in her research meetings, Huang has often felt pressure to underplay her more, “girly” traits to fit in. But interacting with intelligent, accomplished female-identifying academics in the field (including collaborations with Professor Cynthia Rudin) reaffirms to her that it’s important to be yourself: “there’s a place for everyone in research.”
At the Joint Statistical Meetings Conference in D.C with fellow researcher Gaurav Parikh
Advice for first-years and what the future holds
While she can’t predict where exactly she’ll end up, Huang is interested in taking a proactive role in shaping the impacts of artificial intelligence and machine learning on society. And as the divide between academia and industry is becoming more and more gray, years from now, she sees herself existing somewhere in that space.
Her advice for incoming Duke students and aspiring researchers is threefold. First, Huang emphasizes the importance of mentorship. Having kind and validating mentors throughout her time at Duke made difficult problems in statistics so much more approachable for her, and in research, “we need more of that type of person!”
Second, she says that “when I first approached studying math, my impatience often got in the way of learning.” Slowing down with the material and allowing herself the time to learn things thoroughly helped her improve her academic abilities.
Being around people who have this shared love and a deep commitment for their work is just the human endeavor at its best.
Jenny huang
Lastly, she stresses the importance of collaboration. Sometimes, Huang remarked,“research can feel isolating, when really it is very community-driven.” When faced with a tough problem, there is nothing more rewarding than figuring it out together with the help of peers and professors. And she is routinely inspired by the people she does research with: “being around people who have this shared love and a deep commitment for their work is just the human endeavor at its best.”
Post by Meghna Datta, Class of 2023
(Editor’s note: This is Jenny’s second appearance on the blog. As a senior at NC School of Science and Math, she wrote a post about biochemist Meta Kuehn.)
If you’re a doe-eyed first-year at Duke who wants to eventually become a doctor, chances are you are currently, or will soon, take part in a pre-med rite of passage: finding a lab to research in.
Most pre-meds find themselves researching in the fields of biology, chemistry, or neuroscience, with many hoping to make research a part of their future careers as clinicians. Undergraduate student and San Diego native Eden Deng (T’23) also found herself plodding a similar path in a neuroimaging lab her freshman year.
Eden Deng T’23
At the time, she was a prospective neuroscience major on the pre-med track. But as she soon realized, neuroimaging is done through fMRI. And to analyze fMRI data, you need to be able to conduct data analysis.
This initial research experience at Duke in the Martucci Lab, which looks at chronic pain and the role of the central nervous system, sparked a realization for Deng. “Ninety percent of my time was spent thinking about computational and statistical problems,” she explained to me. Analysis was new to her, and as she found herself struggling with it, she thought to herself, “why don’t I spend more time getting better at that academically?”
Deng at the Martucci Lab
This desire to get better at research led Deng to pursue a major in Statistics with a secondary in Computer Science, while still on the pre-med track. Many people might instantly think about how hard it must be to fit in so much challenging coursework that has virtually no overlap. And as Deng confirmed, her academic path not been without challenges.
For one, she’s never really liked math, so she was wary of getting into computation. Additionally, considering that most Statistics and Computer Science students want to pursue jobs in the technology industry, it’s been hard for her to connect with like-minded people who are equally familiar with computers and the human body.
“I never felt like I excelled in my classes,” Deng said. “And that was never my intention.” Deng had to quickly get used to facing what she didn’t know head-on. But as she kept her head down, put in the work, and trusted that eventually she would figure things out, the merits of her unconventional academic path started to become more apparent.
Research at the intersection of data and health
Last summer, Deng landed a summer research experience at Mount Sinai, where she looked at patient-level cancer data. Utilizing her knowledge in both biology and data analytics, she worked on a computational screener that scientists and biologists could use to measure gene expression in diseased versus normal cells. This will ultimately aid efforts in narrowing down the best genes to target in drug development. Deng will be back at Mount Sinai full-time after graduation, to continue her research before applying to medical school.
Deng presenting on her research at Mount Sinai
But in her own words, Deng’s most favorite research experience has been her senior thesis through Duke’s Department of Biostatistics and Bioinformatics. Last year, she reached out to Dr. Xiaofei Wang, who is part of a team conducting a randomized controlled trial to compare the merits of two different lung tumor treatments.
Generally, when faced with lung disease, the conservative approach is to remove the whole lobe. But that can pose challenges to the quality of life of people who are older, with more comorbidities. Recently, there has been a push to focus on removing smaller sections of lung tissue instead. Deng’s thesis looks at patient surgical data over the past 15 years, showing that patient survival rates have improved as more of these segmentectomies – or smaller sections of tissue removal – have become more frequent in select groups of patients.
“I really enjoy working on it every week,” Deng says about her thesis, “which is not something I can usually say about most of the work I do!” According to Deng, a lot of research – hers included – is derived from researchers mulling over what they think would be interesting to look at in a silo, without considering what problems might be most useful for society at large. What’s valuable for Deng about her thesis work is that she’s gotten to work closely with not just statisticians but thoracic surgeons. “Originally my thesis was going to go in a different direction,” she said, but upon consulting with surgeons who directly impacted the data she was using – and would be directly impacted by her results – she changed her research question.
The merits of an interdisciplinary academic path
Deng’s unique path makes her the perfect person to ask: is pursuing seemingly disparate interests, like being a Statistics and Computer Science double-major on the pre-med, track worth it? And judging by Deng’s insights, the answer is a resounding yes.
At Duke, she says, “I’ve been challenged by many things that I wouldn’t have expected to be able to do myself” – like dealing with the catch-up work of switching majors and pursuing independent research. But over time she’s learned that even if something seems daunting in the moment, if you apply yourself, most, if not all things, can be accomplished. And she’s grateful for the confidence that she’s acquired through pursuing her unique path.
Moreover, as Deng reflects on where she sees herself – and the field of healthcare – a few years from now, she muses that for the first time in the history of healthcare, a third-party player is joining the mix – technology.
While her initial motivation to pursue statistics and computer science was to aid her in research, “I’ve now seen how its beneficial for my long-term goals of going to med school and becoming a physician.” As healthcare evolves and the introduction of algorithms, AI and other technological advancements widens the gap between traditional and contemporary medicine, Deng hopes to deconstruct it all and make healthcare technology more accessible to patients and providers.
“At the end of the day, it’s data that doctors are communicating to patients,” Deng says. So she’s grateful to have gained experience interpreting and modeling data at Duke through her academic coursework.
And as the Statistics major particularly has taught her, complexity is not always a good thing – sometimes, the simpler you can make something, the better. “Some research doesn’t always do this,” she says – she’s encountered her fair share of research that feels performative, prioritizing complexity to appear more intellectual. But by continually asking herself whether her research is explainable and applicable, she hopes to let those two questions be the North Stars that guide her future research endeavors.
At the end of the day, it’s data that doctors are communicating to patients.
Eden Deng
When asked what advice she has for first-years, Deng said that it’s important “to not let your inexperience or perceived lack of knowledge prevent you from diving into what interests you.” Even as a first-year undergrad, know that you can contribute to academia and the world of research.
And for those who might be interested in pursuing an academic path like Deng, there’s some good news. After Deng talked to the Statistics department about the lack of pre-health representation that existed, the Statistics department now has a pre-health listserv that you can join for updates and opportunities pertaining specifically to pre-med Stats majors. And Deng emphasizes that the Stats-CS-pre-med group at Duke is growing. She’s noticed quite a few underclassmen in the Statistics and Computer Science departments who vocalize an interest in medical school.
So if you also want to hone your ability to communicate research that you care about – whether you’re pre-med or not – feel free to jump right into the world of data analysis. As Deng concludes, “everyone has something to say that’s important.”
What are the trials and tribulations one can expect? And conversely, what are the highlights? To answer these questions, Duke Research & Innovation Week kicked off with a panel discussion on Monday, January 23.
The panel
Moderated by George A. Truskey, Ph.D, the Associate Vice President for Research & Innovation and a professor in the Department of Biomedical Engineering, the panelists included…
Claudia K. Gunsch, Ph.D., a professor in the Departments of Civil & Environmental Engineering, Biomedical Engineering, and Environmental Science & Policy. Dr. Gunsch is the director of the NSF Engineering Research Center for Microbiome Engineering (PreMiEr) and is also the Associate Dean for Duke Engineering Research & Infrastructure.
Dr. Claudia Gunsch
Yiran Chen, Ph.D., a professor in the Department of Electrical & Computer Engineering. Dr. Chen is the director of the NSF AI Institute for Edge Computing (Athena).
Dr. Yiran Chen
Stephen Craig, Ph.D., a professor in the Department of Chemistry. Dr. Craig is the director of the Center for the Chemistry of Molecularly Optimized Networks (MONET).
Dr. Stephen Craig
The centers
As the panelists joked, a catchy acronym for a research center is almost an unspoken requirement. Case in point: PreMiEr, Athena, and MONET were the centers discussed on Monday. As evidenced by the diversity of research explored by the three centers, large externally-funded centers run the gamut of academic fields.
PreMiEr, which is led by Gunsch, is looking to answer the question of microbiome acquisition. Globally, inflammatory diseases are connected to the microbiome, and studies suggest that our built environment is the problem, given that Americans spend on average less than 8% of time outdoors. It’s atypical for an Engineering Research Center (ERC) to be concentrated in one state but uniquely, PreMieR is. The center is a joint venture between Duke University, North Carolina A&T State University, North Carolina State University, the University of North Carolina – Chapel Hill and the University of North Carolina – Charlotte.
PreMiEr – not to be confused with the English Premier League
Dr. Chen’s Athena is the first funded AI institute for edge computing. Edge computing is all about improving a computer’s ability to process data faster and at greater volumes by processing data closer to where it’s being generated. AI is a relatively new branch of research, but it is growing in prevalence and in funding. In 2020, 7 institutes looking at AI were funded by the National Science Foundation (NSF), with total funding equaling 140 million. By 2021, 11 institutes were funded at 220 million – including Athena. All of these institutes span over 48 U.S states.
Athena, or the Greek goddess of wisdom, is a fitting name for a research center
MONET is innovating in polymer chemistry with Stephen Craig leading. Conceptualizing polymers as operating in a network, the center aims to connect the behaviors of a single chemical molecule in that network to the behavior of the network as a whole. The goal of the center is to transform polymer and materials chemistry by “developing the knowledge and methods to enable molecular-level, chemical control of polymer network properties for the betterment of humankind.” The center has nine partner institutions in the U.S and one internationally.
MONET, like French painter Claude Monet
Key takeaways
Research that matters
Dr. Gunsch talked at length about how PreMiEr aspires to pursue convergent research. She describes this as identifying a large, societal challenge, then determining what individual fields can “converge” to solve the problem.
Because these centers aspire to solve large, societal problems, market research and industry involvement is common and often required in the form of an industry advisory group. At PreMiEr, the advisory group performs market analyses to assess the relevance and importance of their research. Dr. Chen also remarked that there is an advisory group at Athena, and in addition to academic institutions the center also boasts collaborators in the form of companies like Microsoft, Motorola, and AT&T.
Dr. Chen presenting on Athena’s partner institutions at Monday’s talk.
Commonalities in structure
Most research centers, like PreMiEr, Athena, and MONET, organize their work around pillars or “thrusts.” This can help to make research goals understandable to a lay audience but also clarifies the purpose of these centers to the NSF, other funding bodies, host and collaborating institutions, and the researchers themselves.
How exactly these goals are organized and presented is up to the center in question. For example, MONET conceptualizes its vision into three fronts – “fundamental chemical advances,” “conceptual advances,” and “technological advances.”
At Athena, the research is organized into four “thrusts” – “AI for Edge Computing,” “AI-Powered Computer Systems,” “AI-Powered Networking Systems,” and “AI-Enabled Services and Applications.”
Meanwhile, at PreMiEr, the three “thrusts” have a more procedural slant. The first “thrust” is “Measure,” involving the development of tracking tools and the exploration of microbial “dark matter.” Then there’s “Modify,” or the modification of target delivery methods based on measurements. Finally, “Modeling” involves predictive microbiome monitoring to generate models that can help analyze built environment microbiomes.
A center is about the people
“Collaborators who change what you can do are a gift. Collaborators who change how you think are a blessing.”
Dr. stephen craig
All three panelists emphasized that their centers would be nowhere without the people that make the work possible. But of course, humans complicate every equation, and when working with a team, it is important to anticipate and address tensions that may arise.
Dr. Craig spoke to the fact that successful people are also busy people, so what may be one person’s highest priority may not necessarily be another person’s priority. This makes it important to assemble a team of researchers that are united in a common vision. But, if you choose wisely, it’s worth it. As Dr. Craig quipped on one of his slides, “Collaborators who change what you can do are a gift. Collaborators who change how you think are a blessing.”
In academia, there is a loud push for diversity, and research centers are no exception. Dr. Chen spoke about Athena’s goals to continue to increase their proportions of female and underrepresented minority (URM) researchers. At PreMiEr, comprised of 42 scholars, the ratio of non-URM to URM researchers is 83-17, and the ratio of male to female researchers is approximately 50-50.
In conclusion, cutting-edge research is often equal parts thrilling and mundane, as the realities of applying for funding, organizing manpower, pushing through failures, and working out tensions with others sets in. But the opportunity to receive funding in order to start and run an externally-funded center is the chance to put together some of the brightest minds to solve some of the most pressing problems the world faces. And this imperative is summarized well by the words of Dr. Craig: “Remember: if you get it, you have to do it!”
The healthcare industry and academic medicine are excited about the potential for artificial intelligence — really clever computers — to make our care better and more efficient.
The students from Duke’s Health Data Science (HDS) and AI Health Data Science Fellowship who presented their work at the 2022 Duke AI Health Poster Showcase on Dec. 6 did an excellent job explaining their research findings to someone like me, who knows very little about artificial intelligence and how it works. Here’s what I learned:
Artificial intelligence is a way of training computer systems to complete complex tasks that ordinarily require human thinking, like visual categorization, language translation, and decision-making. Several different forms of artificial intelligence were presented that do healthcare-related things like sorting images of kidney cells, measuring the angles of a joint, or classifying brain injury in CT scans.
Talking to the researchers made it clear that this technology is mainly intended to be supplemental to experts by saving them time or providing clinical decision support.
Meet Researcher Akhil Ambekar
Akhil standing next to his poster “Glomerular Segmentation and Classification Pipeline Using NEPTUNE Whole Slide Images”
Akhil Ambekar and team developed a pipeline to automate the classification of glomerulosclerosis, or scarring of the filtering part of the kidneys, using microscopic biopsy images. Conventionally, this kind of classification is done by a pathologist. It is time-consuming and limited in terms of accuracy and reproducibility of observations. This AI model was trained by providing it with many questions and corresponding answers so that it could learn how to correctly answer questions. A real pathologist oversaw this work, ensuring that the computer’s training was accurate.
Akil’s findings suggest that this is a feasible approach for machine classification of glomerulosclerosis. I asked him how this research might be used in medicine and learned that a program like this could save expert pathologists a lot of time.
What was Akhil’s favorite part of this project? Engaging in research, experimenting with Python and running different models, trying to find what works best.
Meet Researcher Irene Tanner
Irene Tanner and her poster, “Developing a Deep Learning Pipeline to Measure the Hip-Knee-Ankle Angle in Full Leg Radiographs”
The research Irene Tanner and her team have done aims to develop a deep learning-based pipeline to calculate hip-knee-ankle angles from full leg x-rays. This work is currently in progress, but preliminary results suggest the model can precisely identify points needed to calculate the angles of hip to knee to ankle. In the future, this algorithm could be applied to predict outcomes like pain and physical function after a patient has a joint replacement surgery.
What was Irene’s favorite part of this project? Developing a relationship with mentor, Dr. Maggie Horn, who she said provided endless support whenever help was needed.
Meet Researcher Brian Lerner
Brian Lerner and his poster, “Using Deep Learning to Classify Traumatic Brain Injury in CT Scans”
Brian Lerner and his team investigated the application of deep learning to standardize and sharpen diagnoses of traumatic brain injury (TBI) from Computerized Tomography (CT) scans of the brain. Preliminary findings suggest that the model used (simple slice) is likely not sufficient to capture the patterns in the data. However, future directions for this work might examine how the model could be improved. Through this project, Brian had the opportunity to shadow a neurologist in the ER and speculated upon many possibilities for the use of this research in the field.
What was Brian’s favorite part of this project? Shadowing neurosurgeon Dr. Syed Adil at Duke Hospital and learning what the real-world needs for this science are.
Many congratulations to all who presented at this year’s AI Health Poster Showcase, including the many not featured in this article. A big thanks for helping me to learn about how AI Health research might be transformative in answering difficult problems in medicine and population health.
With mask mandates being overturned and numerous places going back to “normal,” COVID is becoming more of a subconscious thought. Now, this is not a true statement for the entire population, since there are people who are looking at the effects of the pandemic and the virus itself.
I attended a poster presentation for the “The Pandemic Divide” event hosted here at Duke by the Samuel Dubois Cook Center on Social Equity. To me, all the poster boards conveyed the theme of how COVID-19 had affected our lives in more ways than just our health. One connection that particularly caught my eye would be the one between American Education and COVID.
The poster for the conference
As a student who lived through COVID while attending high school, I can safely say that the pandemic has affected education. However, based on the posters I saw, it is important to know that education, too, has a strong and impactful impact on COVID-19.
Dr. Donald J. Alcendor after a great presentation
The first evidence I saw was from Donald J. Alcendor, an associate professor of microbiology and immunology at Meharry Medical College in Nashville. His poster was about the hesitancy surrounding COVID-19 vaccines. One way he and his team figured out to lessen the hesitance from the public was to improve the public’s trust. To achieve this, Alcendor and his team sent trusted messengers into the community. One of the types of messengers they provided was scientists who studied COVID-19. These scientists were able to bring factual information about the disease, how it spreads, and the best course of action to act against it. Alcendor and his research team also brought in “vaccine ambassadors” to the community and a mobile unit to help give the community vaccines. He noted that this was accomplished with support from the Bloomberg Foundation’s Greenwood Initiative, which addresses Black health issues.
With this mobile unit, Alcendor and his team were able to reach people and help those who were otherwise unable to receive help for themselves because of their lack of transportation. They provided people from all backgrounds with help and valuable information.
Alcindor said he and his team planned pop-up events based on where the community they were trying to reach congregates. With the African American community, he planned pop-up events at churches and schools. Then for the Latino community, he planned pop-events where families tend to gather, and he held events in Latin0 neighborhoods. In addition, he made sure that the information was available in Spanish at all levels, from the flyers and the surveys, to the vaccinators themselves.
All of these amenities that he and his group provided were able to educate the community about COVID-19 and improve their trust in the scientists working on the disease. Alcendor and his team were able to impact COVID-19 through education, and by going to the event, it was evident to me that he was not the only one who accomplished this.
Dr. Colin Cannonier and his poster
Colin Cannonier, an associate professor of economics at Belmont University in Nashville, asked and answered the question, “does education have an impact on COVID? Specifically, does it change health and wellbeing?” To answer this question, he researched how education about COVID can affect a person. He discovered that when a person is more educated about COVID, how it is spread, and its symptoms, they are more likely to keep the pandemic in check through their behavior. He came to this conclusion because he realized that when higher educated people know more about COVID, they exhibit behaviors to remain healthy, meaning that they would follow the health protocols given by the health officials.
While this may seem like common sense that the more educated a person is, the more they make smart choices pertaining to COVID, this shows how important education is and how deadly ignorance is. Cannonier’s research gave tangible evidence to show that education is a weapon against diseases. Unfortunately, it is evident that some officials did not believe in educating the public about the virus or the virus itself, and that proved to be extremely deadly.
To fully capture the relationship between COVID and education, one must also talk about how COVID-19 affected education.
Ms. Stacey Akines and her wonderful poster
Stacey Akines, a history graduate student at Carnegie Mellon University, studied how education was changed by the pandemic.
First, she realized that COVID schooling crossed over with homeschooling. Then she uncovered that more Black people started to research and teach their children about Black history. This desire to teach youth more about their history caused an increase in the number of Black homeschoolers. In fact, the number of Black homeschoolers doubled during the fall of 2020. While to some, this change to homeschooling may have a negative impact on one’s life, it actually gives the student more opportunities to learn things.
It is no secret that there are many books being banned here in the U.S., and there are many state curriculums that are changing to erase much of Black history. Homeschooling a child gives the parent an opportunity to ensure that the education they receive is true to and tells their history
Unlike me, where during high school, education felt lackluster and limited because of COVID, some parents saw an opportunity to better their child’s education.
A hall of Posters
I hope that it is clear that the relationship between COVID and education is a complex one. Both can greatly impact each other, whether it’s for the better or for the worse. COVID thrives when we are uneducated, and it very nearly destroyed education too, but for the efforts of some dedicated educators.
“After COVID-19,” senior Cynthia Dong (T’23) remarks, “so much of what was wrong with the medical system became visible.”
Duke undergraduate Cynthia Dong, Class of 2023
This realization sparked an interest in how health policy could be used to shape health outcomes. Dong, who is pursuing a self-designed Program II major in Health Disparities: Causes and Policy Solutions, is a Margolis Scholar in Health Policy and Management. Her main research focus is telehealth and inequitable access to healthcare. Her team looks at patient experiences with telehealth, and where user experience can be improved. In fact, she’s now doing her thesis as an offshoot of this work, researching how telehealth can be used to increase access to healthcare for postpartum depression.
Presenting research on telehealth
In addition to her health policy work, however, Dong also works as a research assistant in the neurobiology lab of Dr. Anne West, and her particular focus is on the transcription mechanism of the protein BDNF, or brain-derived neurotrophic factor.
While lab research can be clearly visualized by most people (think pipettes, rows of benches littered with bottles and plastic tubes, blue rubber gloves everywhere), health policy research is perhaps a little more abstract. When asked what the process of research through Margolis is like, Dong says that “it’s not team-based or individual – it’s a lot of both.” This looks like individual research on specific topics, talking to different stakeholder groups and people with certain expertise, and then convening for weekly team meetings.
With other Margolis Scholars
For Dong, research has been invaluable in teaching her to apply knowledge to something tangible. Doing that, you’re often “forced to understand that not everything is in my control.” But on the flip side, research can also be frustrating for her because so much of it is uncertain. “Will your paper get published? Is what you’re doing relevant to the research community? Will people invest in you?”
In that vein, research has humbled her a lot. “What it means to try to solve a societal problem is that it’s not always easy, you have to break it down into chunks, and even those chunks can be hard to solve.”
After graduation, Dong plans on taking a couple of gap years to be with family and scribe before ultimately pursuing an MD-MPH. Because research can be such a long, arduous process, she says that “It took me a long time to realize that the work we do matters.” In the future, though, she anticipates that her research through Margolis will directly inform her MPH studies, and that “with the skills I’ve learned, I can help create good policy that can address the issues at hand.”
What brings seniors Deney Li and Amber Fu together? Aside from a penchant for photoshoots (keep scrolling) and neurobiology, both of them are student research assistants at the lab of Dr. Andrew West, which is researching the mechanisms underlying Parkinson’s in order to develop therapeutics to block disease progression. Ahead lie insights on their lab work, their lab camaraderie, and even some wisdom on life.
(Interview edited for clarity. Author notes in italics.)
What are you guys studying here at Duke? What brought you to the West lab?
DL: I am a biology and psychology double major, with a pharmacology concentration. I started working at a lab spring semester of freshman year that focused on microbial and environmental science, but that made me realize that microbiology wasn’t really for me. I’ve always known I wanted to try something in pharmaceutics and translational medicine, so I transitioned to a new lab in the middle of COVID, which was the West lab. The focus of the West lab is neurobiology and neuropharmacology, and looking back it feels like fate that my interests lined up so well!
Deney Li
AF: I am majoring in neuroscience with minors in philosophy and chemistry, on the pre-med track. I knew I wanted to get into research at Duke because I had done research in high school and liked it. I started at the same time as Deney – we individually cold-emailed at the same time too, in the fall! I was always interested in neuroscience but wasn’t pre-med at the time. A friend in club basketball said her lab was looking for people, and the lab was focused on neurobiology – which ended up being the West lab!
Amber Fu
What projects are you working on in lab?
DL: My work mainly involves immunoassays that test for Parkinson’s biomarkers. My postdoc is Yuan Yuan, and we’re looking at four drugs that are kinase inhibitors (kinases are enzymes that phosphorylate other proteins in the body, which turns them either on or off). We administer these drugs to mice and rats, and look at LRRK2, Rab10 and phosphorylated Rab10 protein levels in serum at different time points after administration.These protein levels are important and indicative because more progressive forms of Parkinson’s are related to higher levels of these proteins.
AF: For the past couple of years, I’ve been working under Zhiyong Liu (a postdoc in the lab). There are multiple factors affecting Parkinson’s, and different labs ones study different factors. The West lab largely studies genetic factors, but what we’re doing is unique for the lab. There’s been a lot of research on how nanoplastics can go past the blood-brain barrier, so we are studying how this relates to mechanisms involved in Parkinson’s disease. Nanoplastics can catalyze alpha-synuclein aggregation, which is a hallmark of the disease. Specifically, my project is trying to make our own polystyrene nanoplastics that are realistic to inject into animal models.
What I’m doing is totally different from Deney – I’m studying the mechanisms surrounding Parkinson’s, Deney is more about drug and treatments – but that’s what’s cool about this lab – there are so many different people, all studying different things but coming together to elucidate Parkinson’s.
Another important project
How much time do you spend in lab?
DL: I’m in lab Mondays, Wednesdays, and Fridays from 9 to 6. All my classes are on Tuesdays and Thursdays!
AF: I’m usually in lab Tuesdays and Thursdays from 12 to 4, Fridays from 9 to 11:45, and then whenever else I need to be.
Describe lab life in three words:
DL: Unexpected growth (can I just do two)?
AF: Rewarding, stimulating, eye-opening.
Lab life also entails goats and pumpkins
What’s one thing you like about lab work and one thing you hate?
DL: What I like about lab work is being able to trouble-shoot because it’s so satisfying. If I’m working on a big project, and a problem comes up, that forces me to be flexible and think on my toes. I have to utilize all the soft skills and thinking capabilities I’ve acquired in my 21 years of life and then apply them to what’s happening to the project. The adrenaline rush is fun! Something I don’t like is that there’s lots of uncertainty when it comes to lab work. It’s frustrating to not be able to solve all problems.
AF: I like how I’ve been able to learn so many technical skills, like cryosectioning. At first you think they’re repetitive, but they’re essential to doing experiments. A process may look easy, but there are technical things like how you hold your hand when you pipette that can make a difference in your results. Something I don’t like is how science can sometimes become people-centric and not focused on the quality of research. A lab is like a business – you have to be making money, getting your grants in – and while that’s life it’s also frustrating.
What do you want to do in the future post-Duke? How has research informed that?
DL: I want to do a Ph.D. in neuropharmacology. I’m really interested in research on neurodegeneration but also have been reading a lot about addiction. So I’ll either apply to graduate school this year or next year. My ultimate goal would be to get into the biotech startup sphere, but that’s more of a 30-years-down-the-road goal! Being in this lab has taught me a lot about the pros and cons of research, which I’m thankful for. Lab contradicts with my personality in some ways– I’m very spontaneous and flexible, but lab requires a schedule and regularity, and I like the fact that I’ve grown because of that.
AF: The future is so uncertain! I am currently pre-med, but want to take gap years, and I’m not quite sure what I want to do with them. Best case scenario is I go to London and study bioethics and the philosophy of medicine, which are two things I’m really interested in. They both influence how I think about science, medicine, and research in general. After medical school, though, I have been thinking a lot about doing palliative care. So if London doesn’t work out, I want to maybe work in hospice, and definitely wouldn’t be opposed to doing more research – but eventually, medical school.
What’s one thing about yourself right now that your younger, first-year self would be surprised to know?
DL: How well I take care of myself. I usually sleep eight hours a day, wake up to meditate in the mornings most days, listen to my podcasts… freshman-year-Deney survived on two hours of sleep and Redbull.
AF: Freshman year I had tons of expectations for myself and met them, and now I’m meeting my expectations less and less. Maybe that’s because I’m pushing myself in my expectations, or maybe because I’ve learned not to push myself that much in achieving them. I don’t necessarily sleep eight hours and meditate, but I am a little nicer to myself than I used to be, although I’m still working on it. Also, I didn’t face big failures before freshman year, but I’ve faced more now, and life is still okay. I’ve learned to believe that things work out.
