There are always new viruses emerging, and, like SARS-CoV-2, which causes COVID-19, they are constantly evolving into different variants or strains. Researchers are racing to find vaccines and therapies that can improve outcomes for patients worldwide, using methods ranging from traditional lab work to computational biology (bioinformatics), and even artificial intelligence (AI). To understand vaccine development, we first need to understand how our immune system fights germs.
“The scientific world is constantly on the lookout for potential new pandemics so when there is a new virus, we would be able to quickly predict and measure the immune response,” said Dr. Alessandro Sette, a professor at the La Jolla Institute for Immunology in San Diego, California, and Director of the Center for Cancer Immunotherapy and Center for Vaccine Innovation. Being able to predict and measure how the body’s immune system will respond to viruses is essential to developing effective vaccines. The immune system recognizes, remembers, and destroys disease-causing organisms, called pathogens, and can provide long-lasting protection from future attacks. Pathogens are made up of antigens, which activate the immune response.
The body’s immune response is mediated by B cells and T cells. They do not recognize pathogens as a whole but instead recognize epitopes, which are unique markers on the antigens. If you’ve ever seen pictures of the SARS-CoV-2 virus, the spikes on the virus’s surface are the antigens that allow researchers to develop COVID-19 vaccines. These are critical for the immune system’s ability to identify and respond to foreign invaders such as viruses and bacteria.
Predicting B-cell vs. T-cell epitopes
The difference between B cells and T cells makes it necessary to have multiple methods for predicting their epitopes. B cells produce antibodies that usually bind to cell-surface epitopes that are folded in a three-dimensional structure. This method used for B-cell epitope prediction is called discontinuous 3D structure-based epitope prediction.
“Antibodies recognize things on the outside and often recognize three-dimensional structures that are made out of discontinuous epitopes,” said Dr. Sette. “These are epitopes that are made from parts of a protein that are not necessarily like ducks in a row.”
(Teresa Fang)
T cells are entirely different: They recognize chopped-up fragments of proteins bound to human leukocyte antigen (HLA) molecules. Also known as major histocompatibility complex (MHC), these are specialized molecules on a cell’s surface for detection, holding important epitopes, for T cells. T-cell epitope prediction, therefore, is not limited to far-apart 3D structures like B cells are. Instead of discontinuous epitopes, T cells recognize linear epitopes. This method is called linear sequence-based epitope prediction.
“If you could see the structure of an HLA molecule with a peptide bound to it, it looks like a hot dog bun with a sausage in the middle,” Dr. Sette explained. “That is the fragment where the peptide is stretched out.”
Currently, most vaccines and therapeutics target B cells because antibodies are easier to measure than epitope fragments in T cells, although both are important for vaccine design.
Bioinformatics in advancing epitope prediction
In the past, vaccines were developed by using whole inactivated pathogens (such as in polio), an approach that was not always successful, or by predicting epitopes using traditional lab techniques, which are laborious and time-consuming. Recent advances in computational biology and bioinformatics have significantly improved the ability to predict epitopes for B-cell and T-cell activation in a time-sensitive manner.
Dr. Sette is part of a team that develops and oversees the national Immune Epitope Database (IEDB), a free, widely-used bioinformatics resource database for storing epitope structures. It has two purposes: to function as a catalog for epitopes and as a collection of epitope prediction tools for immunology research around the world. The IEDB uses many methods to predict epitopes and is always being updated. Generally, it analyzes patterns in already-known epitope structures to predict the epitope for an unknown one for B-cell or T-cell activation. One key area in these advances lies in AI. Machine learning (ML) algorithms, trained on large datasets of known epitopes and their interactions, can improve the accuracy of predictions. Dr. Sette plans to use ML approaches to improve data curation and algorithm prediction.
“We will be relying on predictions more than data that is already available because if it is a new virus, we’ll have to rely on more innovative approaches,” Dr Sette said. He believes that if another pandemic arrives, epitope prediction will give researchers an upper hand in fighting against its spread.
AVA CUMMINGS ‘25 AND SAACHI ARUN ‘25 OF RBIO WITH THEIR RESEARCH POSTERS AT NCSEF REGION 3B ON FEBRUARY 17. (ANNELIESE HEYDER)
By Anneliese Heyder, Stentorian Editor-in-Chief
The “Science Season” is upon us: when the summer months start getting closer and science fairs, conferences, and competitions begin popping up like flowers. Throughout the spring semester, students at NCSSM will be presenting their research at school and around the state and country.
The North Carolina Science and Engineering Fair, or NCSEF, kicked off on February 17th at NCSSM as Region 3b, with both juniors and seniors competing by sharing their research with judges, teachers, and students. Some students completed research independently or with a team, while others were part of the RSci or Mentorship programs.
Luke Malta ‘25 was an RChem student who presented at NCSEF. “I spent a lot of time perfecting my poster, sitting down and making sure I have as much information as possible,” he described his preparation. “I also planned on practicing presenting in front of the current RChem students to get some feedback from them and Dr. Bruno.”
Sawyer Kribbs ‘25 from RBio did the same.“I began to prepare by practicing my speech a couple of nights before presenting it to the judges. I was pretty nervous, but I felt ready,” he said, adding that he enjoyed talking with other students about his research and was impressed with the other projects at the fair.
Some of the students who presented did their research at another university with a mentor and a team of undergraduate or graduate students. “I would say NCSEF was a great experience! It prepared me for future symposiums I plan to attend since there will be judges who are experts in the topic I’m researching, and how to interact with them,” said Hima Manne ‘25, who was part of the Mentorship program.
Manne also explained how she prepared for NCSEF, stating “Planning included updating my research findings on the poster I previously had and prepping for specific questions about methods and future directions.”
DANTE TRINGALE ‘25 WITH THEIR RESEARCH POSTER. (Anneliese Heyder)
Most of the eight categories advance the three top winners to the state-level North Carolina Science and Engineering Fair. The categories include Biological Science A, Biological Science B, Chemistry, Environmental/Earth Science, Engineering, Mathematics, Technology, and Physics. There are other special prizes as well, such as the Regeneron Biomedical Science Award, the Stockholm Junior Water Prize, and the NC One Water Award. However, the grand prize is an all-expense paid trip to the International Science and Engineering Fair in May.
Not only must they practice their speaking and speaking skills, but students must also make sure they have all the required documents signed and their posters ready to be presented. Mentors play a significant role in helping their students prepare–printing posters, checking over materials, and organizing the event.
Both teachers and students dedicate their time to making sure the fair goes smoothly for everyone. NCSEF provides an opportunity for peers to show one another their passions and skills and learn about various research topics. It is also a great way to make connections and meet professionals in the field–for some students, their research is just the first step in their future careers.
In this fantasy, it’s the last day before winter break, and she’s placing her foot in the optimal position to spring up from her seat and be the first one out the door. Her eyes — always big and round and beautiful — reflect the words coming out of her mouth. It echoes what the crowd is saying, let’s go to the beach!
In this fantasy, I can’t get through an afternoon drive without remembering all the things I’ve read on the billboards and graffiti on the road signs. Photographic memory. I look forward to getting home, full of the strangers who say “God bless you” on their cardboard signs at traffic signals and disappear into thin air on hot days because they’ve all appeared in our house. She’s watching on TV the latest updates of the barrier wall around New York City, and we giggle because it looks like a scene from that anime with the titans.
In this one, the ground trembles and that’s the signal that another glacier has been dethroned, and she looks at me with fear and confusion; I meet her with the same. We must check on our sand castles before the sea swallows them forever.
In this one, we catch picnics at the park in the windows between droughts and tornadoes so that we don’t mess up counting the millions of freckles on our faces. She takes out the vegetarian sandwiches for us to eat, and I wrinkle my nose to protest as if my bloodline has never eaten vegetables before. They’re wrapped in yellow paper, but under this sun it looks black.
In this fantasy, water tastes like smoke. We live up in mountains and underground like moles, and racism doesn’t exist because we’re all red from the freezing cold or the bitter heat. I tell her I’m dying.
—–
We live in extraordinary times for the understanding of science. Before January 2024, I thought I was strictly a humanities student—I was content writing about how humans interact with the environment rather than conducting climate research myself. But as I dug deeper, I realized thatlearning about a problem was just as important as being part of the solution. And, if it’s possible to be the solution, I’d rather be the solution. So, in January 2024, I also became a STEM student, creating a climate model to predict sea level rise to help coastal communities.
Global climate models (GCMs) are continually created or updated in the scientific world. These models are tuned and validated using the Intergovernmental Panel on Climate Change’s (IPCC) Representative Concentration Pathways (RCPs). These scenarios predict climate behavior based on projections of greenhouse gas (GHG) emissions, atmospheric concentrations, air pollutant emissions, and land use. The IPCC has ruled these scenarios for all countries from the most to the least predicted GHG emissions: RCP8.5, RCP6.0, RCP4.5, and RCP2.6.
Where are we now? In 2022, the IPCC released a report based on 14,000 scientific papers from over 300 authors, stating that Earth’s temperature will reach the critical threshold of 1.5 degrees Celsius within 20 years. This report is described by U.N. Secretary-General António Guterres as an “atlas of human suffering and a damning indictment of failed climate leadership.” As of 2024, we are following the highest prediction pathway: RCP8.5. This predicts that by 2081-2100, temperatures will increase by 3.7 degrees Celsius, global sea levels will rise by 0.63 meters, and extreme weather will greatly increase.
I won’t overwhelm you with more numbers; you can read about them in news articles and reports. You’ve likely already heard about rising sea levels, climate protests, and species extinction due to global warming and deforestation.
Perhaps you believe every update, every statistic, and every quote you read., And, when you open the weather app on your phone and see a week of rain or above 90° temperatures, you may even shed one or two tears for our poor planet.
Or you may have attitude. It’s just the same thing every day! I get it!
Or maybe you’ll join the climate protesters for a bit. Stop cutting down our trees! Or you’ll join the counter-protest. Extremely Mad Scientist! It’s So Severe, The Nerds Are Here!
Then we’ll go back to living our lives.
Historically, climate research has been met with skepticism and denialism. When the journal Science published a letter signed by 255 members of the US National Academy of Sciences in May 2010, it began with, “We are deeply disturbed by the recent escalation of political assaults on scientists in general and on climate scientists in particular. All citizens should understand some basic scientific facts. There is always some uncertainty associated with scientific conclusions; science never absolutely proves anything.”
But political exposure twists the interpretation:
2011. Presidential candidate, Mitt Romney. “We don’t know what’s causing climate change, and the idea of spending trillions and trillions of dollars to try and reduce CO2 emissions is not the right course for us.”
2015. US Senator Ted Cruz. “Any good scientist questions all science. If you show me a scientist who stops questioning science, I’ll show you someone who isn’t a scientist.”
2016. Donald Trump wanted to eliminate all climate research done by NASA. “Mr. Trump’s decisions will be based upon solid science, not politicized science,” said his top NASA adviser Bob Walker.
2024 is still the same. “Can you imagine, this guy says global warming is the greatest threat to our country?” Trump referred to President Joe Biden at a rally in June, which had the hottest June in recorded history across the globe. “Global warming is fine. In fact, I heard it was going to be very warm today. It’s fine.”
Now, the problem isn’t simply misinformation and believability about climate science. Yes, science produces findings that reveal something true (or close to true) about nature based on evidence. But what we need the general public to know is not a better understanding of those findings, but a better understanding of what makes those findings distinctive.
Some believe the philosophy of science is based on the idea that the “scientific method,” if rigorously applied, always produces good science. Twentieth-century philosopher Karl Popper warned against this, citing the problem of demarcation: a theory can’t be correct unless it can be proven wrong. In other words, it might be that people don’t believe in climate change because they don’t recognize its effects in their daily lives.
Conducting research is not something that anybody can jump into and do, but it was through experiencing research firsthand that I knew the severity of climate change. My classmates, who are also conducting climate research, now know that. We are lucky to have the resources and opportunity to do that.
We can’t pretend that our efforts won’t be heard because we’re just one person. I can’t “solve” climate change,” and neither can a whole country. But I can recognize the differences in my life that climate change is making, and I am not comfortably numb enough to sit still and live with what I don’t like. At its core, what makes science distinctive is its purpose to make people care about things bigger than themselves. It’s not the subject or method of inquiry but the values and behavior of those engaged in it that make science matter.
RChem students Nihar Kummetha ‘25, Matt Czar ‘25, and June Brewer ‘25. Luke Malta.
By Noah Fine, Stentorian Staff Writer
Research in Science (“RSci”) applications are on the horizon for juniors at NCSSM. What exactly are the RSci programs? Which one is right for you? What will you get out of the student research programs at NCSSM? What other research opportunities are there?
When people talk about RSci, they’re talking about four year-long courses: Research in Chemistry (“RChem”), Research in Biology (“RBio”), Research in Physics (“RPhys”), and Research in Computational Science (“RComp” or “RCompSci”). In addition, NCSSM also hosts Research in Mathematics (“RMath”). What sets these courses apart from other research opportunities?
Research starts during RSci students’ J-Term and continues through the spring semester into the Summer Research and Innovation Program (SRIP), and concludes in the fall semester of senior year. In addition, RChem, RBio, and RPhys (but not RComp) are double-blocked, which means that student researchers will be working on independent research during both F and G blocks. Double-blocking allows students the opportunity to dive into their research questions for twice as much time as in a normal class, in addition to SRIP, which is equivalent to a few months of normal class time. However, this also means that choosing to take an RSci is a large time commitment.
“Why would you want to spend hours and hours on an investigation if you aren’t enjoying it?” asked RPhys instructor Dr. Jonathan Bennett, who will be passing on the RPhys teaching position to Dr. Michael Falvo at the end of 2024.
However, RSci also gives students the opportunity to learn how to adapt when things don’t go their way the first time. “Usually there’s a point where students have had to deal with disappointment,” reflected RChem instructor Dr. Tim Anglin. “But they push through, and there’s always that time they bring me something and they’re like, ‘it worked!’”
Research in Biology (“RBio”)
In RBio, students will learn the ins and outs of research with model organisms. During J-Term RBio students spend between two and four weeks conducting a mini research project, setting a strong foundation for the skills they’ll need during the rest of the year: group work, wet bench techniques, and presenting their work, according to Dr. Kim Monahan, who teaches RBio alongside Dr. Heather Mallory.
After J-Term, RBio students begin to research questions that can be answered by studying a model organism. For example, a previous student researched multiple sclerosis by studying earthworms.
Organism choice is restricted by cost and regulations: E. coli could be a great choice, but A. mississippiensis, the American alligator, would not. Other popular organisms include C. elegans, plants, and embryonic zebrafish. Learning how to work with a student’s selected model organism—and how to adapt when their model organism produces unexpected results—is one of the core focuses of the RBio experience. Popular areas of study include neurodegenerative disease, genetic engineering, and more.
To an outside observer, RBio may feel like one big family of researchers. Dr. Monahan acknowledges that team building is “something me and [Dr.] Mallory work very hard on.” She says that learning how to communicate with peers, teachers, and those from other RSci programs is one of the most valuable experiences for an RBio student. Those science communication skills will come in handy during the spring when RBio students prepare an oral project defense, and in the late fall, when students are encouraged to submit their work to research symposiums and competitions.
Research in Chemistry (“RChem”)
RChem students solve problems using the language of atoms, molecules, and proteins. No prior chemistry lab experience is required, so RChem students spend the first two weeks of J-Term building a foundation of basic laboratory techniques, such as pipetting, as they work on a shared short-term research project. During the spring, students explore possible research questions and plan out experiments in preparation for project defenses in early April. For the remainder of the year, students work to synthesize and test chemical products.
In the past, students have enjoyed exploring environmental chemistry, polymer chemistry, and drug design. However, projects that involve research with primate cell lines or potentially dangerous chemicals may not be feasible. Finding creative ways to address problems while working around these limitations is at the heart of RChem problem-solving. The two RChem classes, taught by Anglin and Dr. Michael Bruno, work separately most days. However, there are always opportunities for collaboration between students, even those outside of RChem. In fact, Anglin says that he particularly enjoys projects that sit at the periphery of chemistry, as they allow him to collaborate with the other RSci programs.
Research in Physics (“RPhys”)
According to Dr. Bennett, each RPhys project is completely unique in terms of both research questions and techniques. Previous research topics include computationally modeling turbulent flow, building miniature ion thrusters, and a variety of quantum computing projects. Since it would be impractical to teach such a wide variety of research techniques, he explained that instruction throughout the year focuses on building the skills necessary to become a competent researcher.
Students focus on dissecting and evaluating scientific papers during J-Term, preparing them to develop a research question and write a proposal during spring semester. RPhys students then run experiments during SRIP and share their research through a poster and research paper in the fall. Students then have the opportunity to present at a professional physics conference and submit their research to symposiums and competitions. Dr. Bennett emphasizes building these skills in the hope that they will empower RPhys students even after leaving NCSSM.
Dr. Bennett highly encouraged applicants for the class of ‘26 to attend the upcoming interest meeting. “Go to that meeting, get the information, ask your question, and listen carefully to the instructors,” he said, and advised applicants to “be you, but do your homework, so you’ll be more informed [about what RPhys has to offer].”
Research In Computational Science (“RComp” or “RCompSci”)
RComp allows students the most freedom of the four RSci programs because any question that can be answered with computational methods is fair game. Past RComp projects have included facial recognition software for horses, automated dating of Egyptian hieroglyphic text, and analysis of fourth-down plays in football games.
RComp is currently taught by Mr. Bob Gotwals, who will be passing on the position to a new faculty member at the end of 2024. Dr. Daniel Egger, a professor from Duke University, is currently undergoing training to teach RComp starting in 2025.
Mr. Gotwals, who has led NCSSM’s Computational Science Department since 2006, warns that Research in Computational Science is not Research in Computer Science. For example, Mr. Gotwals advises students not to come in with the goal of learning Python code, but rather to think of Python code as a tool used to model whatever interests them.
In contrast to the other RSci programs, RComp has no traditional benchwork component. All experiments are run computationally, which means that students conduct research using either their personal computers or the Pittsburgh Supercomputing Center’s supercomputer. Also unique among the RSci programs, RComp students have the opportunity to find a mentor in the field they’re researching, who can help them understand their problem from the perspective of a researcher in the field.
Research in Mathematics (“RMath”)
RMath is a single-semester, spring course. An application to RMath during the school year does not come bundled with an application to RMath during SRIP—they are separate classes, taught by different teachers. This means that spring RMath applications are open to both juniors and seniors.
In contrast to RSci programs, where students start by developing their own research questions, RMath students begin their research by choosing a problem from The American Mathematical Monthly (AMM), a prestigious peer-reviewed math journal. Problems from AMM have only been solved once before, by the researchers who originally proposed them. Next, RMath students work in small groups to find a solution and publish their results. Particularly inventive or elegant solutions may even earn publication in a later issue of AMM.
RMath students learn how to format and typeset papers in LaTeX (a software for typesetting documents), present their findings to others, and conduct research in pure mathematics. Popular areas of research include combinatorics, game theory, and advanced calculus, but projects modeling real-life scenarios are not the focus.
“This is RMath, not RAppliedMath,” says Dr. Michael Lavigne, who will teach RMath during SRIP 2025.
RBio student Henry Hanson ‘25 observes plates through a microscope. Vincent Shen.
Advice & Next Steps For Applying
Now you’re interested in STEM research at NCSSM-Durham. What are the next steps? Attend the Research and Innovation fair and interest meetings, and then reach out to the teachers of the classes you’re interested in! Dr. Monahan says that RSci teachers are “always open if you have a question,” and Dr. Lavigne has free copies of past RMath papers on his door for interested students.
Most applications will ask you to submit some sort of project idea. Don’t take this as something that’s set in stone, instead try your best to think of something that’s realistic and you would enjoy spending a whole year learning about. Seniors who are currently in RSci are a great resource for this. Don’t be scared of applying, especially if you think that your project ideas aren’t good enough for the programs that you’re interested in.
On the other hand, don’t try to change your interests just for an application or to cater to what you think the RSci teachers want. “Students shouldn’t be thinking about how they can serve the class, it’s the other way around,” says Dr. Anglin. Think of ideas that excite you, and RSci will meet you halfway.
Finally, Mr. Gotwals emphasizes that RSci and RMath are amazing opportunities for student research, but that it’s important to remember they’re not the only opportunities. Mentorship, Research/Research Experience in Humanities (“RHum” and “RexHum” respectively), J-Term Courses Research Experience in Chemistry and Research Experience in Biology, and the multitude of SRIP programs offered each year provide opportunities to conduct research in an entirely different way, with the option of freeing up space in your schedule to take more classes that interest you.
Research-intensive classes, labeled with “*R*” in the course catalog, are also an opportunity to learn valuable techniques used by scientists in the field through a significant research project.
If you are willing to accept the challenge, NCSSM has a research opportunity for you.
