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CTSI-CN Announces GY05 Team Science Awards




CTSI-CN is pleased to announce the GY05 awardees for Population Health Team Science and Tranlational Team Science. Congratulations to all!


Population Health Team Science Awards (PHTSAs) aim to form partnerships between two or more faculty from different disciplines and at least one community partner to embark on projects that utilize community based participatory research methods to focus on health disparities in a marginalized population. The research question should be such that no individual within the team could complete the project without the additional expertise of all the other members of the team. 


4 Engaging Autistic Voices in Education and Research (4EAVER): Creating a Partnership with a Community of Autistic Adults

The overarching goal of this project is to a give a voice to autistic adults to guide the development of person-centered interventions that enhance the long-term well-being of autistic adults.

Pictured from the top: Sean Cleary, PhD, MPH; Gregory Wallace,  PhD; Paula Manion, MSN/PNP




Studying Feasibility for a Midwifery-Led Collaborative Perinatal Hybrid Telehealth Model to Reduce Structural Barriers to Care in Medicaid Eligible Populations in the District of Columbia

This study will examine the feasibility of a perinatal care model that employs community-based CPM to deliver perinatal care to Medicaid eligible expectant mothers. The care provided will be through the use of hybrid in-person and telehealth visits, and integrated through telehealth physician collaboration and consultation.

Pictured from the top: Amr M. Madkour, MD; Manya Magnus PhD; Aza Nedhari, MS, LM, CPM; Jonathan Webb, MBA, MPH;





Translational Team Science Awards (TTSAs) aim to promote creative, multidisciplinary team-based research focused on complex or challenging biomedical research questions. TTSA research teams must be comprised of 3 or more independent disciplines or types of expertise. Teams may be formed from any combination of academic labs, clinical partners, industry or foundations. Innovative, high-impact studies of all types (T1-T4) are eligible and faculty were encouraged to apply.


StrepApp: Machine Learning to Improve Diagnostic Accuracy of Streptococcal Pharyngitis

The overall approach is to create a robust database of pharyngeal images annotated with GAS test results to use for developing ML algorithms to distinguish Streptococcal from non-Streptococcal pharyngitis.

Pictured from the top: Rana Hamdy,MD, MPH, MSCE;  Raj Shekhar, PhD;  Jeffrey Dome, MD, PhD






Utilization of optical genome mapping for discovery of novel large genomic rearrangements in pediatric high grade gliomas  

The overall goal of this project is to detect novel actionable aberrations in pediatric High Grade Gliomas (HGGs). To date, little is known about the incidence and clinical significance of large SVs in HGGs, as the full spectrum of these aberrations has yet to be discovered.

Pictured from the top: Miriam Bornhorst, MD; Surajit Bhattacharya, PhD; Hayk Barseghyan, PhD; Eric Villain, MD, PhD