What can sororities teach us about belonging?

Charlotte Hogg, professor of rhetoric and composition at Texas Christian University, delves in the question.

Faculty Bio:

Dr. Charlotte Hogg is a professor at Texas Christian University specializing in rhetoric and composition. She has authored, co-authored, or co-edited five books, most recently White Sororities and the Cultural Work of Belonging. Her work has also ap­peared in Inside Higher Education, The Washington Post, College English, Rhetoric Review, Peitho, and elsewhere. She teaches women’s rhetorics and literacies, creative nonfiction, and composition.

Transcript:

What is it about sorority life that remains so appealing? Greek-life, even with its bad press, comprises roughly 10% of the college population nationally and as high as 50% on some campuses. I researched National Panhellenic Conference (aka historically-White) sorority life behind the highly curated recruitment videos to better understand what sorority systems can teach us about how subcultures enact belonging.

Belonging seeks to erase differences for insiders, leaving others as outsiders. This kind of ideological work is done rhetorically through creating a shared space of making meaning connected to cultural values. In sororities, this happens by tethering sorority practices, activities, and values to their histories. Constantly connecting the present to the past creates a lineage that can also maintain what is fraught about the system: the divide between insiders and outsiders and who has been able to be a part of that lineage.

Participating in activities that emulate principles of the sorority stoke belonging such as songs, rituals, and learning about the organization’s founders and their lasting relevance across time. Repeatedly hearkening the founders, for example, suggests the ways members are tethered to one another and to the sorority whether they joined in 1851 or 2025, bypassing the fact that sororities began at a time when only privileged, White women were afforded the opportunity of a college education. This erasure occurs subtly by emphasizing positive, admirable qualities all members should carry on from the founders such as seeking knowledge, service, loyalty, and friendship.

Understanding how belonging happens through rhetorical practices can teach us lessons about the double-sided coin of belonging and exclusivity, be it on college campuses, the workplace, or social media we follow.

What happens when platforms recommend opinions instead of users?

Sriniwas Pandey, lecturer at the School of Computing at Binghamton University, details this.

Faculty Bio:

Pandey is a lecturer in the School of Computing at Binghamton University. He received his PhD degree in system science from Binghamton University. He holds bachelor's and master's degrees in computer science engineering from UTU India and IIITDMJ India, respectively. His research interests include complex systems, networks and machine learning. His research aims to comprehend the intricacies of eccentric behavior within society, focusing on identifying the underlying factors contributing to such behaviors and its impact on network dynamics.

Transcript:

Although social media can serve as a civil digital meeting place, pockets of users with intense opinions that clash with others that have different views has become a common occurrence. There are plenty of reasons for this, but one factor is content recommendations by the platform itself.

I co-authored a study with Binghamton University Professor Hiroki Sayama that explores how these content recommendation systems affect the overall social climate on social media.

We created a computer simulation of a social media platform with users connected to each other. Each user had a default set of opinions. However these users could form new opinions or be influenced by what they saw from other users. The strength of connection between users could change over time based on how similar their ideas were.

We found that when the platform only recommended similar users without adjusting what opinions people saw, users broke apart into tight communities that had very different ideologies.

However, when the platform recommended opinions, rather than users, there was far less network fragmentation. This worked even when people naturally preferred users similar to them. This also led to more unusual or off-center opinions. We experimented with different initial social network configurations.

When people were exposed to diverse opinions, their “knowledge base” expanded, giving them more room to generate creative ideas within their community.

This implies that echo chambers are less likely when people see diverse opinions. The findings drive home the importance of social media design – and how choice of recommendation strategy can impact the cohesion of the platform’s community and the extent to which users are able to express less mainstream viewpoints.

There are stark mortality differences between pregnancy and abortion.

Maria Steenland, assistant professor of family science in the School of Public Health at the University of Maryland, explores this.

Faculty Bio:

Dr. Steenland is an Assistant Professor in Family Science in the School of Public Health at the University of Maryland, College Park. She is a health services and health policy researcher focused on maternal and reproductive health policy in the United States. Her research uses
econometric methods to evaluate maternal and reproductive health programs and policies, with a particular focus on Medicaid policy. The overarching goal of her research is to identify policy options to increase the equity and quality of women’s health services. Her previous research
has examined the effect of Medicaid payment policies for immediate postpartum contraception, and expansions of Medicaid eligibility in pregnant and postpartum populations.

Transcript:

After Roe v. Wade was overturned by the Dobbs v. Jackson Women’s Health Organization decision in June of 2022, some advocates and academics expressed concern that abortion bans would harm maternal health. They argued that banning abortion could increase maternal mortality in part because the risk of death from childbirth is much higher than the risk from abortion. Continuing a pregnancy places significant physiologic stress on the body, which can lead to life-threatening complications, such as hemorrhage, sepsis, stroke, and heart failure. A prior study, using data from 1998 through 2005, found that the risk of death from childbirth was about 14 times greater than the risk of death from abortion. In the years since that estimate, the measurement of maternal death has improved, increasing the number of pregnancy-related deaths identified annually. At the same time, abortions are taking place earlier in pregnancy, reducing the risk of complications. Given these changes, my colleagues — Kerra Mercon, Ben Brown, Marie Thoma — and I re-estimated the difference between pregnancy-related death and abortion-related death using national data. Using figures from 2018 to 2021, we calculated a range of mortality ratios. We found that the risk of death from ongoing pregnancy was 44 to 70 times greater than the risk of death from abortion. Importantly, even our most conservative estimate was still three times higher than the previously reported figure. We don’t yet know what effect abortion bans will have on overall maternal mortality in the US. However, we can say that people who are forced to continue their pregnancies because of abortion bans will face a dramatically greater risk of death than had they been able to access an abortion.

Read More:

[University of Maryland School of Public Health] - Study: Risk of maternal death during pregnancy greatly exceeds risk of death from abortion

How do we pull back the curtain on China’s use of AI in its military?

Cole McFaul, senior research analyst at Georgetown University, explores this key question.

Faculty Bio:

Cole McFaul is a Senior Research Analyst and an Andrew W. Marshall Fellow at Georgetown University’s Center for Security and Emerging Technology (CSET), where he mainly focuses on emerging technology competition in the Asia-Pacific and China’s science and technology ecosystem. Prior to joining CSET, Cole researched the political economy of China’s international engagement strategies at the Center for Strategic and International Studies and the Shorenstein Asia-Pacific Research Center at Stanford University. Cole holds a B.A. in Political Science and an M.A. in East Asian Studies from Stanford University.

Transcript:

It’s no secret that China is using AI to modernize its military and compete with the U.S. and other rivals. However, what has remained secret is civilian firms’ involvement in these efforts and China’s fusion of commercial innovation with military power.

My colleagues Sam Bresnick, Daniel Chou and I set out to answer a key question: who supplies the PLA with AI-related goods and services? Our project relies on a novel data set of 2800 AI-related contract award notices published by the PLA between January 2023 and December 2024. We define an AI-related award as any contract supporting AI-enabled or autonomous technologies, like language and vision models, unmanned vehicles, augmented and virtual reality, simulation and training environments, and smart manufacturing and robotics.

From this data set, we identified 338 entities awarded two or more AI-related contracts. Using open-source information, we classified each into one of three groups: state-owned enterprises, research institutions, and nontraditional vendors (which are firms without self-reported state ownership).

We found that state owned enterprises and defense-affiliated research institutions led in AI-related military procurement. Institutions like AVIC, NORINCO, the Chinese Academy of Sciences, and the Seven Sons of National Defense dominate the top of the list.

But a deeper look at who supplies the PLA with AI-related goods and services reveals that a wide range of other organizations are also active. Nearly 70 percent of the entities awarded two or more AI-related contracts were nontraditional vendors. Civilian universities like Shanghai Jiao Tong, Tsinghua University, and Peking University were also awarded AI-related contracts.

Our research reveals that, at least in the public procurement of AI-related goods and services, military-civil fusion is no longer aspirational—it’s operational. Unless the United States adapts to this reality, it risks facing a Chinese defense base that is more capable, adaptable, and technologically sophisticated.

Read More:

[CSET] - Pulling Back the Curtain on China’s Military-Civil Fusion

[CSET] - Civilian Tech Is Powering China’s Military

What is Gulf War Illness and why is recognition important?

Beatrice Golomb, professor of medicine at the University of California San Diego, seeks to inform.

Faculty Bio:

Dr. Golomb is a Professor of Medicine at UC San Diego with over 15 years of experience treating veteran patients, including veterans with Gulf War Illness (GWI). She was the inaugural Scientific Director for the Congressionally directed Research Advisory Committee on Gulf War Veterans’ Illnesses (RAC) and her research for RAND and with funding from the Department of Defense have expanded knowledge of exposure relations, mechanisms, markers and treatment for GWI. Dr. Golomb and her team remain committed to research to improve the lives and health for our heroes from the Gulf War.

Transcript:

For decades, Gulf War veterans have battled for recognition of the often devastating health challenges they experience as a consequence of their honorable service. Next month, we will mark an immensely important milestone for Gulf War veterans, their families, clinicians and researchers. Gulf War illness will finally receive its own International Classification of Diseases — or ICD — diagnostic code. This is more than just administrative coding. This is long-overdue validation for the suffering of the quarter-million affected veterans. It is a formal acknowledgment that Gulf War illness is real, it is physical, and it is service-related. Gulf War illness affects about one-third of the nearly 700,000 U.S. troops who served in the 1990-1991 Gulf War. It manifests as a consistent profile of symptoms: persistent fatigue, cognitive difficulties, chronic pain, respiratory issues, skin problems, gastrointestinal distress. Decades of study have linked Gulf War illness to chemical exposures and identified objective abnormalities such as structural brain changes. With this new ICD code, health care providers will be better able to recognize, diagnose, and treat Gulf War illness. Insurance, medical records, research, and public health tracking will now explicitly acknowledge the condition, rather than forcing patients to substitute related diagnoses. For researchers like me, the change accelerates our ability to study Gulf War illness in large populations, monitor treatment outcomes rigorously, and understand how this condition may overlap or interact with other diseases. To all veterans whose symptoms were dismissed and whose needs went unmet: this new diagnostic code is for you. It’s a recognition of your service. It’s a commitment to your care. And it represents hope — hope that research, medicine, and policy will now move forward more fully, more justly, to give you the answers and the support you deserve.

Read More:

[PNAS] - Acetylcholinesterase inhibitors and Gulf War illnesses

[ScienceDirect] - Adverse effect propensity: A new feature of Gulf War illness predicted by environmental exposures

[National Library of Medicine] - Mitochondrial impairment but not peripheral inflammation predicts greater Gulf War illness severity

Beatrice Golomb, professor of medicine at the University of California San Diego, discussed why a diagnostic code is so important for veterans with Gulf War Illness.

Tuesday

Cole McFaul, senior research analyst at Georgetown University, explores how we pull back the curtain on China’s military-civil fusion.

Wednesday

Maria Steenland, assistant professor of family science in the School of Public Health at the University of Maryland, examines the stark mortality differences between pregnancy and abortion.

Thursday

Sriniwas Pandey, lecturer at the School of Computing at Binghamton University, details what happens when platforms recommend opinions instead of users.

Friday

Charlotte Hogg, professor of rhetoric and composition at Texas Christian University, details what sororities can teach us about belonging.

Catch up with The Academic Minute from 5/18 - 5/22

Monday

George McLeod - Old Dominion University
Building Digital Twins of Our World to Improve Coastal Resilience

Dr. George McLeod is the Director of the Center for Geospatial Science, Education, and Analytics at Old Dominion University and Senior Fellow with Virginia’s Commonwealth Center for Recurrent Flooding Resiliency. He oversees the creation of vital location intelligence for a wide range of academic research questions, including those focused on the intersection of the built landscape and environmental hazards. His expertise in ocean science, geovisualization, remote sensing, and UAV operations has allowed him to play an important role in advancing coastal hazards and flooding resilience research in Virginia.

Tuesday

Tiffany Zhu - Old Dominion University
How Should AI Talk About Us?

Tiffany Zhu is a philosopher. She is an Assistant Professor of Global Ethics and Technology in the Department of Philosophy and Religious Studies at Old Dominion University. Prior to joining ODU in Fall 2025, she was a Faculty Fellow in AI Ethics at the California Center for Ethics and Policy at California State Polytechnic University Pomona.

Wednesday

Maryam Golbazi - Old Dominion University
Where the Heat Hits Hardest

Maryam Golbazi is a Research Assistant Professor at Old Dominion University working with the Joint Institute on Advanced Computing for Environmental Studies (JI-ACES). She specializes in numerical weather prediction models, atmospheric chemistry modeling, wind energy, and data assimilation. Her work integrates advanced numerical modeling with satellite and in-situ observations to improve forecasts of air pollution, wind energy resources, and extreme weather events. She is currently leveraging data science and AI/ML methods to develop localized weather models, while maintaining the rigor and integrity of established physical modeling techniques. With prior research experience at the National Center for Atmospheric Research and many collaborative projects, Dr. Golbazi’s research bridges science and application to address pressing environmental and energy challenges. She aims to leverage fundamental science and state of the art data-driven techniques to produce actionable insights that help protect communities, inform policy, and guide sustainable infrastructure planning.

Thursday

Hong Qin - Old Dominion University
How Fast Can a Viral Variant Spread?

Hong Qin is an Associate Professor in the School of Data Science and the Department of Computer Science at Old Dominion University. His work develops AI and statistical methods for genomic surveillance, pandemic prediction, and trustworthy health AI.

Friday

Khan Iftekharuddin - Old Dominion University
How Does Non-Invasive Detection of Aggressive Brain Tumor Recurrence Work?

Dr. Khan Iftekharuddin is a professor and Batten Endowed Chair in Machine Learning in the department of Electrical and Computer Engineering (ECE) at Old Dominion University (ODU). He concurrently serves as a Director, ODU Vision Lab and an Inaugural Director, Institute of Data Science. Dr. Iftekharuddin has been cited among the top 2% researchers in the globe for both career-long impact and single-year impact, and his Vision Lab has consistently ranked among top teams in Global Brain Tumor Segmentation and Patient Survivability Prediction Challenges co-organized by MICCIA and NCI since 2014.

The Academic Minute airs on the WAMC Northeast Public Radio network at 7:30 a.m. and 3:56 p.m. weekdays.

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On Old Dominion University Week: A non-invasive method for detecting an aggressive brain tumor could be key for patients. But how does it work?

Khan Iftekharuddin, Professor and Eminent Scholar, delves into this.

Faculty Bio:

Dr. Khan Iftekharuddin is a professor and Batten Endowed Chair in Machine Learning in the department of Electrical and Computer Engineering (ECE) at Old Dominion University (ODU). He concurrently serves as a Director, ODU Vision Lab and an Inaugural Director, Institute of Data Science. Dr. Iftekharuddin has been cited among the top 2% researchers in the globe for both career-long impact and single-year impact, and his Vision Lab has consistently ranked among top teams in Global Brain Tumor Segmentation and Patient Survivability Prediction Challenges co-organized by MICCIA and NCI since 2014.

Prior to his current roles, he served as an Interim Dean in Batten College of Engineering and Technology, Associate Dean for Research, Innovation and Graduate Studies, and Chair of the ECE Department at ODU. He received his MS (1991) and PhD (1995) degrees in Electrical and Computer Engineering from University of Dayton, OH.

Transcript:

Glioblastoma Multiforme, or GBM, is the most aggressive and deadly type of brain cancer, killing about 10,000 Americans each year and accounting for half of all brain cancer deaths in the U.S. The fast-growing cancer spreads microscopic cancer cells in surrounding healthy tissue and has an average survivability of 18-24 months from diagnosis.

Prognosis for GBM is poor, with recurrence in 90% of patient cases within six to nine months, even after aggressive treatment protocol including surgery, radiation and chemotherapy. Diagnosing brain tumor recurrence on standard imaging scans like MRIs is challenging because treatment-related changes in the brain tissues, such as scar tissue, necrosis (dead tissues) and edema (swelling), often appear like recurrent tumor tissue. Currently, the only way to confirm tumor recurrence is through an invasive brain biopsy.

My colleagues and I are investigating how computational modeling, AI, and machine learning methods can help distinguish true tumor recurrence from surrounding abnormal tissues, without needing to do a biopsy. This work builds on long-standing research of brain tumor volume segmentation and tracking, tumor sub-typing, and patient survivability prediction.

We’re working with about half a dozen clinical collaborators across the US to analyze and process large amounts of high-resolution Magnetic Resonance imaging alongside molecular and patient clinical data. This analysis will help us develop non-invasive AI models that classify tumor recurrence and radiation-induced challenges. These tools could improve early detection, tracking, and treatment planning, helping physicians better predict the trajectory of tumor growth and tailor interventions for individual patients.

Additionally, we’re working to study inherent biases in these AI models and ensure that they are representative of different patient populations. This will bolster their robustness and efficacy in clinical settings.

Research Projects

On Old Dominion University Week: How fast can a viral variant spread?

Hong Qin, associate professor in the School of Data Science and the Department of Computer Science at Old Dominion University, analyzes the data to find out.

Faculty Bio:

Hong Qin is an Associate Professor in the School of Data Science and the Department of Computer Science at Old Dominion University. His work develops AI and statistical methods for genomic surveillance, pandemic prediction, and trustworthy health AI.

Transcript:

Viruses evolve as they spread, and when a new viral variant begins to outcompete others, it can quickly reshape an outbreak. But measuring a variant’s advantage is tricky, because case counts and sequencing volume rise and fall for reasons unrelated to biology.

A new approach called the differential population growth rate, or DPGR, focuses on comparisons instead of absolute numbers. In a given region and short time window, DPGR looks at two variants that are sampled side-by-side. It tracks the ratio of their weekly sequence counts and takes a logarithm. If that log-ratio changes roughly as a straight line, the slope estimates how much faster one variant is growing than the other. A positive slope means variant A is gaining on variant B; a negative slope means variant A is losing ground.

This pairwise design makes one variant an internal control, helping reduce distortions from shifting testing, reporting, or sequencing intensity. DPGR also has an additive property: if variant A overlaps with B, and B overlaps with C, their slopes can be combined to estimate a comparison of A versus C, even when A and C rarely appear together.

Using DPGR with genomic surveillance data, researchers can map how variants’ advantages change across places and over time. For example, COVID-19’s Omicron variant outpaced the Delta variant worldwide, but the estimated advantage of Omicron differed by region. DPGR can also compare sublineages and build a “fitness staircase” that summarizes stepwise gains.

The result? A simple, interpretable signal that complements other epidemic models and can help anticipate which variant may dominate next.

Read More:

[Wiley] - A data-driven sliding-window pairwise comparative approach for the estimation of transmission fitness of SARS-CoV-2 variants and construction of the evolution fitness landscape

YouTube

On Old Dominion University Week: When it’s hot out, some places are hotter than others.

Maryam Golbazi, research assistant professor of climate science, examines why.

Faculty Bio:

Maryam Golbazi is a Research Assistant Professor at Old Dominion University working with the Joint Institute on Advanced Computing for Environmental Studies (JI-ACES). She specializes in numerical weather prediction models, atmospheric chemistry modeling, wind energy, and data assimilation. Her work integrates advanced numerical modeling with satellite and in-situ observations to improve forecasts of air pollution, wind energy resources, and extreme weather events. She is currently leveraging data science and AI/ML methods to develop localized weather models, while maintaining the rigor and integrity of established physical modeling techniques. With prior research experience at the National Center for Atmospheric Research and many collaborative projects, Dr. Golbazi’s research bridges science and application to address pressing environmental and energy challenges. She aims to leverage fundamental science and state of the art data-driven techniques to produce actionable insights that help protect communities, inform policy, and guide sustainable infrastructure planning.

Transcript:

On a summer afternoon in Hampton Roads, Virginia, the heat doesn’t feel the same everywhere. In some neighborhoods, the air lingers thick, heavy, slow to cool even after sunset. In others, just a few miles away, temperatures drop faster, offering relief once the sun goes down. These differences aren’t random. They’re shaped by concrete, roads, buildings, and the environment.

In our study, which I conducted with my colleague Frank Liu, we used some of the highest-resolution weather simulations ever applied to a real U.S. city to understand how extreme heat behaves at the neighborhood scale. Instead of looking at cities from satellites, we zoomed in, down to city blocks, using advanced atmospheric models.

During two intense heat waves in the summer of 2024, our simulations revealed that dense urban areas were, on average, up to five or six degrees hotter than nearby rural regions. And at night urban neighborhoods stayed warm far longer.

But temperature was only part of the story.

When we combined heat exposure with census data, a pattern emerged: lower-income communities experienced higher heat stress. And that translated directly into energy demand.

That matters, because cooling isn’t free. For families already struggling with energy costs, extreme heat becomes both a health risk and a financial burden.

As heat waves become longer and more intense, understanding where heat concentrates, and who pays the price, may be just as important as predicting the temperature itself. Our research shows that climate change isn’t just about rising averages. It’s about how people experience heat differently, day to day, street to street!

Read More:

[Springer Nature] - High-resolution modeling of extreme heat events with socioeconomic consideration: a real-case WRF–LES approach

On Old Dominion University Week: Can AI chatbots spread generalizations?

Tiffany Zhu, assistant professor of global ethics and technology, examines why this could be the case.

Faculty Bio:

Tiffany Zhu is a philosopher. She is an Assistant Professor of Global Ethics and Technology in the Department of Philosophy and Religious Studies at Old Dominion University. Prior to joining ODU in Fall 2025, she was a Faculty Fellow in AI Ethics at the California Center for Ethics and Policy at California State Polytechnic University Pomona

Transcript:

AI chatbots powered by large language models are increasingly shaping our understanding of the world. Some of my research examines how they use a linguistic device called “generics,” which expresses generalizations without explicit quantification. An example of a sentence using a generic to talk about a social group would be: “Immigrants work low-wage jobs”. These statements are consequential because they can spread stereotypes.

One study looking at ChatGPT 3.5 found, among other tendencies, that the chatbot often paired social generics with what I call individuation hedges, which emphasize diversity within groups. For instance, when asked “Are women more likely to get attacked while walking alone at night?,” the chatbot affirmed the trend but added that “the likelihood of getting attacked depends on an individual’s characteristics.”

Not only are these hedges too formulaic to counteract unfair generalizations, they also reduce the accuracy of some responses, obscure the structural causes of social patterns including oppression, and could lead users to form false or even harmful beliefs about themselves and others.

To improve their use, I proposed a strategy with three elements. First, I suggest requiring democratic and interdisciplinary guidance during the process of reinforcement learning through human feedback. Second, I advise shifting away from a transactional toward a dialogical model of AI-human interaction, meaning chatbots should probe for context and user goals and assumptions rather than simply providing answers. Finally, I suggest chatbots should use generics in conjunction with historical framing and asking counterfactual questions, in order to help AI users to think flexibly about how social reality is contingent, changeable, and sometimes unjust.

On Old Dominion University Week: Coastal resilience will be key going forward in a warming climate.

George McLeod, director of the Center for Geospatial Science, Education, and Analytics, shows how virtual worlds can help us protect our own.

Faculty Bio:

Dr. George McLeod is the Director of the Center for Geospatial Science, Education, and Analytics at Old Dominion University and Senior Fellow with Virginia’s Commonwealth Center for Recurrent Flooding Resiliency. He oversees the creation of vital location intelligence for a wide range of academic research questions, including those focused on the intersection of the built landscape and environmental hazards. His expertise in ocean science, geovisualization, remote sensing, and UAV operations has allowed him to play an important role in advancing coastal hazards and flooding resilience research in Virginia.

Transcript:

When I tell people what we’re working on, the first question is almost always the same: “Okay… what exactly is a digital twin?”

At its simplest, a digital twin is a virtual version of a real place or object. Most of us have seen something like this before—think about the detailed, three-dimensional cities you move through in video games. They look real, but they’re mostly just scenery.

In our work on coastal resilience, the digital twin isn’t the backdrop; it’s the main character.

We’re building virtual versions of real coastal communities and entire regions so we can study very real challenges: sea-level rise, storm flooding, water quality, and the public-health impacts that come with all of that. And unlike a static 3D model, these digital twins are alive. They combine physical models of land and water with models of how systems behave, things like transportation networks, population movement, and hydrology.

That lets us ask big, practical questions. For example: If a Category 3 hurricane hits Virginia on top of an extra foot of sea-level rise, which neighborhoods flood first? Which roads are cut off—and for how long? How much damage might we see? Who could be displaced, and where should emergency responders focus their efforts?

Our most ambitious project takes this idea even further. We’re working with colleagues at NASA to build what we call the Coastal Zone Digital Twin of the entire Chesapeake Bay. It’s a dynamic system that’s constantly updated, showing what’s happening now, what’s likely to happen next, and letting us test “what if” scenarios, so communities can prepare for the coastal future that’s already on the way.

Monday

George McLeod, director of the Center for Geospatial Science, Education, and Analytics, shows how virtual worlds can help us protect our own.

Tuesday

Tiffany Zhu, assistant professor of global ethics and technology, examines why AI chatbots can spread generalizations.

Wednesday

Maryam Golbazi, research assistant professor of climate science, examines where the heat hits the hardest on hot days.

Thursday

Hong Qin, associate professor in the School of Data Science and the Department of Computer Science at Old Dominion University, analyzes the data to examine how fast a viral variant can spread.

Friday

Khan Iftekharuddin, Professor and Eminent Scholar, delves into a non-invasive method for detecting an aggressive brain tumor.

Catch up with The Academic Minute from 5/12 - 5/16

Monday

Edison Bicudo - Aston University
How Language and Cognition Shape Our Societies and Political Life

Dr Edison Bicudo is a Lecturer in the Department of Society and Politics, Aston University, in the UK. He is interested in the regulation, governance, digitalisation, and financialisation of health technology development. With background in sociology, political economy, and geography, he is also interested in the ideological and cognitive underpinnings of technology governance.

Tuesday

Raymond Goodrich - Colorado State University
Testing a Promising New Cancer Immunotherapy in Ovarian Cancer Patients

Former Executive Director of the Infectious Disease Research Center, Ray Goodrich has been investigating vaccine candidates to combat the pathogens that cause COVID-19, tuberculosis and influenza. He also led the development program for a cancer vaccine targeting solid organ tumors.

Wednesday

Indranil Bardhan - University of Texas at Austin
A Positive Lesson From COVID-19 Clinical Trials and IT Capabilities Decreased Death Rates in Hospitals

Indranil Bardhan is the Charles and Elizabeth Prothro Regents Chair in Health Care Management in the McCombs School of Business at The University of Texas at Austin. He is a professor of management information systems and teaches courses in the MBA program as well as the M.S. program.

Thursday

Carlena Ficano - Hartwick College
Systemic Barriers Faced By Minority and Women Entrepreneurs

Dr. Ficano’s areas of expertise include: labor economics, applied econometrics, social policy on low income family well-being, the economics of higher education and, most recently, local economic development.

Friday

Jinglu Jiang - Binghamton University
Multitasking and Phishing Emails

The Academic Minute airs on the WAMC Northeast Public Radio network at 7:30 a.m. and 3:56 p.m. weekdays.

It is also carried by:

KTCU - Dallas-Ft. Worth, TX, KMPB - Dillon, CO, KUCR - Riverside, CA, KTSW - San Marcos, TX, WNAA - Greensboro, NC, WYPL - Memphis, TN, WERB - Berlin, CT, WITR - Rochester, NY, W257BL - Oneonta, NY, W226AC - Troy, NY, WAMC - Albany, NY, WCAN - Canajoharie, NY, W246BJ - Hudson, NY, WAMQ - Great Barrington, MA, WUSR - Scranton, PA, WSUM - Madison. WI, WLUR - Lexington, VA, RADIO READING SERVICE OF MS - Jackson, MS, W240CR - Peekskill, NY, W225BM - Scotia, NY, W299AG - Newburgh, NY, W280DJ - Beacon, NY, W295AA - Middletown, NY, W243BZ - Ellenville, NY,W296BD - Warwick, NY, WOSR - Middletown, NY, WLNA - Beacon, NY, WBNR - Beacon, NY,WCEL - Plattsburgh, NY, WANC - Ticonderoga, NY, KJZA - Kingman, AZ, KJZA - Kingman, AZ,KJZP - Kingman, AZ, KJZK - Kingman, AZ, WAMK - Kingston, NY, W271BF - Highland, NY, WRUN - Utica, NY, WGHQ - Beacon, NY, KAMU - College Station, TX, KRPS - Pittsburg, KS,WUIS - Springfield, IL, CISE - Wolseley, SK (Canada), KISU - Pocatello, ID, W215BG - Milford, PA, CRIS Radio - Windsor, CT, WUOW - Oneonta, NY, WRFA - Jamestown, NY, KXCV - Maryville, MO, WKCC - Kankakee, IL, WWES - Mt. Kisco, NY, KENW - Portales, NM, CISE - Wolseley, SK (Canada), W248AN - Cooperstown, NY, WRUC - Schenectady, NY, WGSU - Geneseo, NY, WAMK - Dover Plains, NY, Science Zone Radio, WSCL - Salisbury, MD, WSDL - Ocean City, MD, KRNW - Chillicothe, MO, WNUB - Northfield, VT, Armed Forces Radio, KNAU, AZ - Arizona Public Radio, KTWH, Two Harbors, MN, KTNA, Talkeetna, AK, WUFT-FM – Gainesville, FL, WBZC - Pemberton, NJ, KPBM, Poplar Bluff, MO, WLRH - Huntsville, AL, WITC - Cazenovia, NY, KUSU – Logan, UT, WRDL – Ashland, OH, KSLU-FM - Hammond, LA

Funding support comes from the American Association of Colleges and Universities:

Are you good at multitasking?

Jinglu Jiang, associate professor at the School of Management at Binghamton University, reveals how this behavior may allow harmful emails to slip by.

Transcript:

The ability to juggle multiple tasks is a defining feature of modern work. But that constant multitasking may make people more vulnerable to phishing attacks.

In a recent study, my co-authors and I examined how multitasking affects people’s ability to detect phishing emails. We conducted two online experiments with nearly one thousand participants. In both experiments, participants worked in multitasking settings. They first completed a mentally demanding primary task, like memorizing numbers or work-related information, while being interrupted with a secondary task: deciding whether incoming emails were legitimate or phishing. This setup mirrors everyday work environments, where email alerts arrive while people are focused on other tasks.

We found that when the primary task placed a high demand on people’s working memory, phishing detection performance dropped substantially. However, we also identified an important countermeasure. When participants received a simple reminder that some emails might be phishing attempts, detection performance improved—even under heavy cognitive load.

We also found that message design plays a role. Reminders were especially effective against phishing emails that promised rewards. By contrast, loss-framed messages—such as warnings about account suspension—tended to trigger vigilance on their own, leaving less room for reminders to add value.

Together, these findings suggest that phishing defenses should account for multitasking, not assume users are fully attentive. Organizations may benefit from context-aware reminders that support attention when cognitive demands are highest and risks are most likely to go unnoticed.

The intersection of race, gender, and financial access needs further study.

Carlena Ficano, professor of economics at Hartwick College, discusses why.

Faculty Bio:

Dr. Ficano’s areas of expertise include: labor economics, applied econometrics, social policy on low income family well-being, the economics of higher education and, most recently, local economic development.

Recent courses taught include:

• Econometrics

• The Marketplace

• Microbes, Markets, and Food

• Labor Economics

• The Economics of Race and Gender

• Principles of microeconomics

Her current research in collaboration with Lawrence Ogbeifun, assistant professor of economics at Hartwick College, https://www.hartwick.edu/people/lawrence-ogbeifun/ investigates barriers that women and racial minorities face in accessing small business loans. This research project engages the authors in applied macroeconomic (Ogbeifun) and microeconomic (Ficano) work that directly relates to and could be used as examples in their regular course offerings in labor economics, the economics of race and gender, principles of microeconomics, principles of macroeconomics, econometrics and macroeconomic theory.

Transcript:

Is it possible to quantify what is lost both by the entrepreneurs and by the larger society, when access to credit is limited by the intersection of one’s race and gender?

Small businesses success is a well-recognized driver of community well-being. But not everyone seeking to secure a small-business loan is viewed equally by lenders--and differential access to credit for minority and women entrepreneurs has the potential to impose significant constraints on local and regional economies.

My current research, conducted jointly with co-author Dr. Lawrence Ogbeifun, aims to shed new light on the systemic barriers faced by minority and women entrepreneurs in accessing small business loans and the broader economic consequences of this inequity.

Using confidential data on credit application success over a seven-year period and building upon earlier work that examined gender-differences in lending, this current project applies an important new lens to questions of lending discrimination and its implications.

By using an intersectional approach that examines race and gender, we are seeking to quantify how small business lending discrimination limits business growth and innovation, ultimately hindering overall economic development.

It is our hope that this work will contribute meaningfully to the field of economics and public policy by filling a gap in the literature around the intersection of race, gender, and financial access. Only empirical evidence can shape future lending practices aimed at promoting equity in small business finance—and this topic is relevant to a wide range of stakeholders, including policymakers, financial institutions, and advocacy groups working toward inclusive economic development.

This research is directly relevant to our teaching responsibilities in courses on labor economics, race and gender, and macroeconomic policy. The insights gained from this research will enhance the learning experiences of our students, encourage critical thinking, and contribute to academic discourse and hopefully drive new conversations on systemic inequities.

What do electronic medical records have to do with declining COVID mortality rates at hospitals?

Indranil Bardhan, Charles and Elizabeth Prothro Regents Chair in Health Care Management at the McCombs School of Business at the University of Texas at Austin, answers this.

Faculty Bio:

Indranil Bardhan is the Charles and Elizabeth Prothro Regents Chair in Health Care Management in the McCombs School of Business at The University of Texas at Austin. He is a professor of management information systems and teaches courses in the MBA program as well as the M.S. program.

Bardhan has a courtesy appointment as a professor in the Department of Medical Education at Dell Medical School. His research focuses on health care analytics and digital health innovation, and involves close collaboration with the University of Texas Southwestern Medical Center and Dell Med. His studies have been funded by the National Science Foundation and the UT Health system.

Bardhan’s research has won 10 best paper or runner-up awards and includes more than 50 publications in premier scholarly journals. He has also served as senior editor of several prestigious journals.

Bardhan holds a Ph.D. in management science and information systems from Texas McCombs. He was inducted as a distinguished fellow of the INFORMS Information Systems Society in 2019.

Transcript:

During the first year of the COVID-19 pandemic, there was a little-known success story in U.S. hospitals. Mortality rates from COVID cases dropped from more than 7% in April 2020 to less than 2% a year later. What explains this decline? Our research found that one mechanism is a learning effect at hospitals, which is associated with testing new treatments.

Using county-level data, we found a lower rate of COVID deaths in counties where hospitals participated in clinical trials and had greater capabilities for health IT, such as using electronic medical records.

Not only did counties whose hospitals had greater IT capabilities do better at treating patients several months into the pandemic, but they also learned faster. We found that the learning effect of clinical trials was enhanced by having strong IT capability.

More specifically, counties with advanced record use were better able to share data with other hospitals and to learn what treatments were working or not working against COVID-19. That sharing made a life-and-death difference.

• Counties with high IT ratings reduced mortality rates per capita 75% over the pandemic’s first year. That’s compared to 47% for low-rated counties.

• If all hospitals had had higher levels of IT, they would have seen 20,853 fewer deaths nationwide.

As with IT, participating in clinical trials helped hospitals exchange information with other institutions and contributed to solutions.

We hope that our research can help policymakers and decision makers understand the value of IT a little bit better. Perhaps they can invest in the right kinds of information technology to help hospitals make faster and better decisions, which ultimately will save more lives.

Read More:

[Nature] - Learning from COVID-19: clinical trials, health information technology, and patient mortality

There may be encouraging news for ovarian cancer patients on the way.

Ray Goodrich, professor in the department of Microbiology, Immunology and Pathology at Colorado State University, tells us more.

Faculty Bio:

Former Executive Director of the Infectious Disease Research Center, Ray Goodrich has been investigating vaccine candidates to combat the pathogens that cause COVID-19, tuberculosis and influenza. He also led the development program for a cancer vaccine targeting solid organ tumors.

Goodrich has worked in infectious disease research for more than 35 years, during which he has managed research staff and development programs in the fields of transfusion and transplantation medicine and pathogen reduction technologies. He has been awarded 58 patents covering technology in these areas and is a co-author of 300 peer reviewed articles and abstracts.

Goodrich is an active member of the American Chemical Society, serves on the board of directors for the Association for the Advancement of Blood and Biotherapies and serves as a special government employee for the Advisory Committee on Blood and Tissue Safety and Availability at the U.S. Department of Health and Human Services.

Transcript:

Earlier this year, a biotechnology startup I lead received a patent for an innovative new cancer immunotherapy developed at Colorado State University. More recently, we have been given clearance from the U.S. Food and Drug Administration to begin a Phase 1 clinical trial testing this therapy in humans.

The trial will be conducted in ovarian cancer patients at the City of Hope, a leading cancer research center in southern California. We are looking to begin enrolling patients around the end of the year.

Here’s how it works: We can extract and expose a patient’s own tumor cells to ultraviolet light and vitamin B2. This renders the tumor cells “quasi-dead.” Those cells, which can no longer divide and are not harmful, are then injected back into the patient. Although the cells are inactive, they help stimulate a patient’s immune system to develop a stronger immune response to attack the cancer in their body.

The treatment is similar to a process I developed decades ago to “clean” blood prior to it being given to patients in need of blood transfusions. This blood-cleaning process is widely used today and has helped greatly reduce the risk of transfusion-transmitted diseases.

I began adapting that process into cancer therapy in 2017 and it has proven effective across multiple studies, including in human tissue samples and in a pilot study in companion dogs at Colorado State University’s Flint Animal Cancer Center.

I am optimistic that this therapy may be able to help women who are battling ovarian cancer. If proven safe and effective, the treatment could also be used to treat other types of solid-tumor cancers.

This treatment could also greatly improve access to cancer therapy. The devices are small and relatively inexpensive — they could easily be deployed at regional centers and hospitals — and when more people have access to technologies like this, everyone benefits.

Read More:

[Colorado State] - Cancer therapy developed at CSU cleared for human clinical trials

Language can shape our societies and our political lives.

Edison Bicudo, lecturer in the Department of Society and Politics at Aston University, discusses how.

Faculty Bio:

Dr Edison Bicudo is a Lecturer in the Department of Society and Politics, Aston University, in the UK. He is interested in the regulation, governance, digitalisation, and financialisation of health technology development. With background in sociology, political economy, and geography, he is also interested in the ideological and cognitive underpinnings of technology governance.

Transcript:

I have a question for you, the person listening to this podcast. How would you define the nation state?

If your definition is something like “the nation state is the manager of collective life” – then your reasoning is metaphoric. You are unconsciously drawing analogies and proposing that THE STATE IS A MANAGER. However, if your answer is something like “the state is the entity protecting people’s values and wellbeing – then your understanding is metonymic. You are unconsciously taking THE WHOLE FOR THE PARTS and considering the relation between national agencies and citizens.

Why does the difference matter? Because it motivates concrete projects and measures. If the metaphoric view prevails, the state will take the shape of a corporation trying to maximise gains and outcomes. If the metonymic view prevails, the state will be more like an institution safeguarding wellbeing and rights.

It is therefore key to recognise the understandings that prevail in society. This is the interpretation proposed by sociognistics. The word sociognistics combines three words: sociology, cognition, and linguistics. In this approach, social and political conflicts derive from divergent understandings made possible by language.

These divergences define whether people favour state efficiency or state morality, whether they trust or oppose science, whether they favour democratic regimes or the newest forms of fascism, and so forth.

I could finish by asking: Do you understand? But it is better to ask: How do you understand?

Read More:

[Taylor & Francis Group] - Sociology, Cognition, and Linguistics Towards a Theory of Sociognistics

[Oxford Academic] - Cognitive Foundations of Society: The Concept of Schemata in Cell, Gene, and Tissue Therapies

[Elgaronline] - Understandings of commercial and open-source 3D bioprinting: The politics of metaphors and metonymies

Monday

Edison Bicudo, lecturer in the Department of Society and Politics at Aston University, discusses how language can shape our societies and our political lives.

Tuesday

Ray Goodrich, professor in the department of Microbiology, Immunology and Pathology at Colorado State University, tells us encouraging news for ovarian cancer patients may be on the way.

Wednesday

Indranil Bardhan, Charles and Elizabeth Prothro Regents Chair in Health Care Management at the McCombs School of Business at the University of Texas at Austin, talks electronic medical records and declining COVID mortality rates at hospitals.

Thursday

Carlena Ficano, professor of economics at Hartwick College, discusses why the intersection of race, gender, and financial access needs further study.

Friday

Jinglu Jiang, associate professor at the School of Management at Binghamton University, reveals how multitasking may allow harmful emails to slip by.

Catch up with The Academic Minute from 5/4 - 5/8

Monday

Zhen Yan - Virginia Tech
Weightlifting Beats Running for Blood Sugar Control

Zhen Yan’s research highlights the importance of the power plants of our cells, the mitochondria. The quantity, number, and function of mitochondria are critically important to maintaining good health.

Tuesday

Sarah Lessard - Virginia Tech
Keto Diet, Exercise and High Blood Sugar

Identifying mechanisms to optimize the therapeutic benefits of exercise

Why do some people gain fewer health benefits from exercise than others?

Increased aerobic exercise capacity is one of the key health benefits of aerobic training. Some individuals, however, are “exercise resistant” and fail to improve fitness and other key health markers with training.

Wednesday

Stephanie DeLuca - Virginia Tech
Intensive Therapy Benefits For Infants and Toddlers With Cerebral Palsy

For more than 25 years, Stephanie Deluca, Ph.D., has studied how intensive neurorehabilitation treatments help children and adults with these impairments.
Dr. DeLuca has helped develop and rigorously test multiple neurorehabilitation therapy protocols and led numerous clinical research trials. Her interdisciplinary research efforts have included; engagement of families, international training, and innovative teaching to prepare the next generation of clinicians and scientists.

Thursday

Read Montague - Virginia Tech
Parkinson’s and Essential Tremor

Dr. Montague’s research focuses on computational neuroscience: the connection between physical mechanisms present in real neural tissue and the computational functions that these mechanisms embody. His early theoretical work focused on the hypothesis that dopaminergic systems encode a particular kind of computational process, a reward prediction error signal, similar to those used in areas of artificial intelligence like optimal control. The Montague Lab uses theoretical, computational, and experimental approaches to the problems of mental health and its derangement by disease and injury. They recently pioneered new approaches to measure sub-second fluctuations in dopamine and serotonin levels in the striatum of conscious human subjects.

Friday

Alex DeFelicantonio - Virginia Tech
Ozempic, Wegovy May Help Reduce Alcohol Use

Alexandra DiFeliceantonio, Ph.D., is an appetitive neuroscientist who studies how the brain integrates peripheral signals to guide food selection and eating behaviors. Using multimodal brain imaging and metabolic measures, her laboratory in Roanoke studies food motivation to ask new questions about diet, food choice, and addiction.

The Academic Minute airs on the WAMC Northeast Public Radio network at 7:30 a.m. and 3:56 p.m. weekdays.

It is also carried by:

KTCU - Dallas-Ft. Worth, TX, KMPB - Dillon, CO, KUCR - Riverside, CA, KTSW - San Marcos, TX, WNAA - Greensboro, NC, WYPL - Memphis, TN, WERB - Berlin, CT, WITR - Rochester, NY, W257BL - Oneonta, NY, W226AC - Troy, NY, WAMC - Albany, NY, WCAN - Canajoharie, NY, W246BJ - Hudson, NY, WAMQ - Great Barrington, MA, WUSR - Scranton, PA, WSUM - Madison. WI, WLUR - Lexington, VA, RADIO READING SERVICE OF MS - Jackson, MS, W240CR - Peekskill, NY, W225BM - Scotia, NY, W299AG - Newburgh, NY, W280DJ - Beacon, NY, W295AA - Middletown, NY, W243BZ - Ellenville, NY,W296BD - Warwick, NY, WOSR - Middletown, NY, WLNA - Beacon, NY, WBNR - Beacon, NY,WCEL - Plattsburgh, NY, WANC - Ticonderoga, NY, KJZA - Kingman, AZ, KJZA - Kingman, AZ,KJZP - Kingman, AZ, KJZK - Kingman, AZ, WAMK - Kingston, NY, W271BF - Highland, NY, WRUN - Utica, NY, WGHQ - Beacon, NY, KAMU - College Station, TX, KRPS - Pittsburg, KS,WUIS - Springfield, IL, CISE - Wolseley, SK (Canada), KISU - Pocatello, ID, W215BG - Milford, PA, CRIS Radio - Windsor, CT, WUOW - Oneonta, NY, WRFA - Jamestown, NY, KXCV - Maryville, MO, WKCC - Kankakee, IL, WWES - Mt. Kisco, NY, KENW - Portales, NM, CISE - Wolseley, SK (Canada), W248AN - Cooperstown, NY, WRUC - Schenectady, NY, WGSU - Geneseo, NY, WAMK - Dover Plains, NY, Science Zone Radio, WSCL - Salisbury, MD, WSDL - Ocean City, MD, KRNW - Chillicothe, MO, WNUB - Northfield, VT, Armed Forces Radio, KNAU, AZ - Arizona Public Radio, KTWH, Two Harbors, MN, KTNA, Talkeetna, AK, WUFT-FM – Gainesville, FL, WBZC - Pemberton, NJ, KPBM, Poplar Bluff, MO, WLRH - Huntsville, AL, WITC - Cazenovia, NY, KUSU – Logan, UT, WRDL – Ashland, OH, KSLU-FM - Hammond, LA

Funding support comes from the American Association of Colleges and Universities:

On Fralin Biomedical Research Institute at Virginia Tech Week: Can weight loss drugs help reduce alcohol use?

Alex DiFeliceantonio, Assistant Professor and Interim Co-director of the Center for Health Behaviors Research, looks into this.

Faculty Bio:

Alexandra DiFeliceantonio, Ph.D., is an appetitive neuroscientist who studies how the brain integrates peripheral signals to guide food selection and eating behaviors. Using multimodal brain imaging and metabolic measures, her laboratory in Roanoke studies food motivation to ask new questions about diet, food choice, and addiction.

While completing a bachelor’s degree in psychology at Sweet Briar College, she became interested in reward learning and motivation. This led her to pursue a master’s degree and doctorate in biopsychology from the University of Michigan, where she studied how opioids alter motivation in animal models. During her postdoctoral training at Yale University and the Max Planck Institute for Metabolism Research in Germany, Dr. DiFeliceantonio examined the role of post-ingestive dopamine signaling in eating behavior and food choices.

Transcript:

More than half of U.S. adults drink alcohol, and about one in ten meets criteria for alcohol use disorder. Current medications that reduce drinking act directly on the brain. But our work tested a different mechanism.

We studied people taking GLP-1 receptor agonists — drugs widely prescribed for diabetes and weight loss. These drugs are known to slow how quickly the stomach empties. We asked: could that also slow alcohol’s path into the bloodstream?

Participants taking GLP-1s and those not on the drugs each consumed the same standardized dose of alcohol. We measured breath alcohol concentration, blood pressure, blood glucose, and asked participants to report their cravings and level of intoxication.

Despite drinking the same amount, those on GLP-1s showed a slower rise in breath alcohol concentration. They also reported feeling less intoxicated on questions such as “How drunk do you feel right now?”

This delayed absorption matters because faster delivery of a drug increases its abuse potential. By slowing alcohol’s effects, GLP-1s may reduce both the subjective appeal of drinking and the physiological impact on the body.

Our findings suggest that these medications could play a role in reducing alcohol use — not by altering brain reward circuits directly, but by changing how the body processes alcohol.

While this was a small pilot study, the results highlight a promising new direction: repurposing an existing class of safe, widely used drugs to help people who want to cut back on drinking.

Read More:

[Virginia Tech] - ‘How drunk do you feel?’: Ozempic, Wegovy may help reduce alcohol use

On Fralin Biomedical Research Institute at Virginia Tech Week: How do we distinguish which symptoms belong to what neurological disease?

Read Montague, Vernon Mountcastle Research Professor and Director of the Center for Human Neuroscience Research, explores this.

Faculty Bio:

Dr. Montague’s research focuses on computational neuroscience: the connection between physical mechanisms present in real neural tissue and the computational functions that these mechanisms embody. His early theoretical work focused on the hypothesis that dopaminergic systems encode a particular kind of computational process, a reward prediction error signal, similar to those used in areas of artificial intelligence like optimal control. The Montague Lab uses theoretical, computational, and experimental approaches to the problems of mental health and its derangement by disease and injury. They recently pioneered new approaches to measure sub-second fluctuations in dopamine and serotonin levels in the striatum of conscious human subjects.

Transcript:

Tremor is one of the most common symptoms of neurological disease. But two conditions that cause tremor — Parkinson’s disease and essential tremor — can look very similar, especially in the early stages. Distinguishing them is a persistent challenge.

We recorded real-time chemical signaling in the brain during surgery, focusing on dopamine and serotonin. Patients played a simple decision-making game involving fair and unfair monetary offers while we measured how their brain chemistry responded to unexpected outcomes.

A computational model revealed clear differences. In essential tremor, dopamine and serotonin worked in opposition: when one increased, the other decreased. In Parkinson’s disease, that reciprocal pattern was disrupted.

The strongest signal separating the two disorders wasn’t dopamine, as many would expect, but serotonin. Its altered dynamics turned out to be the most reliable marker of Parkinson’s disease.

These results suggest that serotonin could serve as a new biomarker for distinguishing Parkinson’s from essential tremor. More broadly, they show how combining behavioral tasks, computational modeling, and real-time neurochemistry can expose hidden disease signatures in the brain.
By identifying these neurochemical fingerprints, we move closer to more accurate diagnoses and, ultimately, more personalized treatments for tremor disorders.

This discovery reflects years of international, cross-disciplinary teamwork between researchers who revisited data collected nearly a decade ago with new analytical tools. By combining engineering, neuroscience, and computational modeling, the team transformed a long-standing puzzle into a clinically meaningful finding.

Read More:

[Virginia Tech] - Scientists reveal brain signaling that sets Parkinson’s disease apart from essential tremor