Undergraduate scholars shine at spring symposium
Eleven students from six North Carolina universities participated in the NIEHS Scholars Connect Program (NSCP) Annual Symposium, April 18. The event marked the conclusion of an academic year-long internship, which pairs local students with NIEHS scientists to develop projects, conduct research, and analyze and present results. The program has matched and placed 113 students since 2012.
The skill-building initiative challenges scholars to explain their research projects in a variety of formats — from poster presentations in the summer to three-minute elevator pitches for non-specialist audiences in the fall. The Annual Symposium in the spring provides a forum for scholars to formally present their work.
“We model a scientific conference for scholars to explain the core of their research, effectively communicate their findings, and engage with the audience,” said Suchandra Bhattacharjee, Ph.D., NIEHS undergraduate research training program manager.
Several students were recognized for their symposium presentations and for overall performance in the program.
Spring Best Presenter and NSCP 2024-25 Outstanding Scholar Award:
Emma Morgan, mentored by Lisa Padilla, Asmita Singh, Ph.D., and Carlos Guardia, Ph.D., Reproductive and Developmental Biology Laboratory.
Spring Honorable Mention Presenters:
Faith Dee, mentored by Niketa Bhawsinghka, Ph.D., and Roel Schaaper, Ph.D., Genomic Integrity and Structural Biology Laboratory, and Kiara Smith, mentored by Yitang Yan, Ph.D., and Darlene Dixon, D.V.M., Ph.D., Mechanistic Toxicology Branch.
Honorable Mention Outstanding Scholars:
Ricardo Scheufen-Tieghi, mentored by José Teófilo Moreira Filho, Ph.D., and Nicole Kleinstreuer, Ph.D., Predictive Toxicology Branch.
Olivia Hsu, mentored by Kanda Borgognoni, Ph.D., and Robin Stanley, Ph.D., Molecular and Cellular Biology Laboratory.
For more information about the program, visit this webpage. (DM)
From left to right, standing, Emma Morgan, Olivia Hsu, Ricardo Scheufen-Tieghi, Dhruv Ranganath, Faith Dee, Isabella Russ, Taymar Smith, Kiara Smith, Justin Stegeman; seated, Coren O’Brien, Program Coordinator Suchandra Bhattacharjee, Ph.D., Office of Science Education & Outreach Director Ericka Reid, Ph.D., and Arnav Thakar.
Panel reveals how AI is driving advances in autism screening
Leading scientists from the Duke University Autism Center of Excellence gathered at NIEHS, April 14, for presentations and a panel discussion of how artificial intelligence (AI) is transforming early detection and biomarker discovery in autism. Hosted by Cindy Lawler, Ph.D., of the NIEHS Division of Extramural Research and Training, the panel highlighted new approaches to enhance autism research and diagnosis.
- Geraldine Dawson, Ph.D., described an AI-based screening tool that uses computer vision, which is capable of extracting information from images, to analyze children’s behavior, providing a more accessible and scalable way to detect autism early.
- Ben Goldstein, Ph.D., shared how machine learning models applied to electronic health records are helping to detect autism and related neurodevelopmental conditions in the general population.
- David Carlson, Ph.D., presented findings on using AI to detect unique patterns of brain network activity in children with autism and attention-deficit/hyperactivity disorder (ADHD), revealing potential biomarkers for diagnosis and treatment.
“We are trying to understand some of the biological differences that happen in autism, to measure exactly what is being changed,” said Carlson. “If we can measure it, we can potentially use that information to develop future interventions or treatments.”
The session emphasized the promise of AI in personalizing care, improving diagnostic timelines, and uncovering the neurological underpinnings of autism. These advances may offer new hope to families and clinicians navigating this complex condition. (MB)
Citations:
Carson WE 4th, Major S, Akkineni H, Fung H, Peters E, Carpenter KLH, Dawson G, Carlson DE. 2024. Model selection to achieve reproducible associations between resting state EEG features and autism. Sci Rep 14(1):25301.
Huang WA, Engelhard M, Coffman M, Hill ED, Weng Q, Scheer A, Maslow G, et al. 2024. A conditional multi-label model to improve prediction of a rare outcome: An illustration predicting autism diagnosis. J Biomed Inform 157:104711.
Perochon S, Di Martino JM, Carpenter KLH, Compton S, Davis N, Eichner B, Espinosa S, et al. 2023. Early detection of autism using digital behavioral phenotyping. Nat Med 29(10):2489-2497.
Air pollution fact sheet updated
NIEHS recently released an updated fact sheet about air pollution and how it may affect the health of children and adults. Air pollution is a mix of hazardous substances, such as fine particulate matter (PM2.5) and nitrogen dioxide, from sources like vehicle exhaust and wildfire smoke. The fact sheet highlights NIEHS-supported research examining how these substances can affect public health. For example, recent studies show a relationship between long-term exposure to PM2.5 and the risk of developing breast cancer in women. Learn more about potential links between air pollution and other conditions, such as dementia, asthma, and diabetes, in this free-to-download fact sheet (743KB). (SE)
(Douglas Murphy, Ph.D., is a technical writer-editor and Samantha Ebersold is a communications specialist in the NIEHS Office of Communications and Public Liaison. Marla Broadfoot, Ph.D., is a contract writer for that office.)
