Stanford University
Showing 23,831-23,840 of 35,699 Results
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Anca M. Pasca, MD
Assistant Professor of Pediatrics
Current Research and Scholarly InterestsI am a physician-scientist, neonatologist, and stem cell biologist whose research focuses on understanding mechanisms of human brain development, neuroinflammation, and neurological injury using patient-derived stem cell models.
I was among the early pioneers of three-dimensional human cortical organoid technologies and contributed to development of foundational protocols for generating region-specific human brain organoids from pluripotent stem cells. My work helped establish the feasibility of modeling human brain development and disease using stem cell-derived tissues and has contributed to the widespread adoption of organoid technologies across neuroscience, regenerative medicine, and translational research.
A major focus of my laboratory is the development of increasingly sophisticated multicellular organoid and assembloid systems that incorporate diverse neuronal and glial populations to model complex human brain circuitry and disease processes. We integrate stem cell biology, organoid engineering, CRISPR-based genome editing, single-cell transcriptomics, epigenomics, high-content imaging, and computational approaches to identify disease mechanisms and therapeutic targets. These technologies have been applied to studies of hypoxic brain injury, 22q11.2 deletion syndrome, Trisomy 21 (Down Syndrome), Trisomy 18, narcolepsy, Alzheimer's and Parkinson's Disease. -
Sergiu P. Pasca
Kenneth T. Norris, Jr. Professor of Psychiatry and Behavioral Sciences and Bonnie Uytengsu and Family Director of the Stanford Brain Organogenesis Program and Senior Fellow, by courtesy, at the Hoover Institution
Current Research and Scholarly InterestsA critical challenge in understanding the intricate programs underlying development, assembly and dysfunction of the human brain is the lack of direct access to intact, functioning human brain tissue for detailed investigation by imaging, recording, and stimulation.
To address this, we are developing bottom-up approaches to generate and assemble, from multi-cellular components, human neural circuits in vitro and in vivo.
We introduced the use of instructive signals for deriving from human pluripotent stem cells self-organizing 3D cellular structures named brain region-specific spheroids/organoids. We demonstrated that these cultures, such as the ones resembling the cerebral cortex, can be reliably derived across many lines and experiments, contain synaptically connected neurons and non-reactive astrocytes, and can be used to gain mechanistic insights into genetic and environmental brain disorders. Moreover, when maintained as long-term cultures, they recapitulate an intrinsic program of maturation that progresses towards postnatal stages.
We also pioneered a modular system to integrate 3D brain region-specific organoids and study human neuronal migration and neural circuit formation in functional preparations that we named assembloids. We have actively applied these models in combination with studies in long-term ex vivo brain preparations to acquire a deeper understanding of human physiology, evolution and disease mechanisms.
We have carved a unique research program that combines rigorous in vivo and in vitro neuroscience, stem cell and molecular biology approaches to construct and deconstruct previously inaccessible stages of human brain development and function in health and disease.
We believe science is a community effort, and accordingly, we have been advancing the field by broadly and openly sharing our technologies with numerous laboratories around the world and organizing the primary research conference and the training courses in the area of cellular models of the human brain. -
Magdalini Paschali
Postdoctoral Scholar, Radiology
Current Research and Scholarly InterestsMy research focuses on utilizing machine learning models to enhance the understanding, diagnosis, and treatment of clinical disorders. I am interested in multi-modal learning, combining imaging data like MRI and CT scans with non-imaging data such as electronic health records, creating more holistic and accurate diagnostic models. I am also interested in the robustness of deep neural networks under domain shifts, investigating how models perform when faced with changes in input data distributions.
Finally, I am interested in early biomarker identification using AI model interpretability, to enable the early detection and targeted treatment of chronic disorders. -
Deepro Pasha
Ph.D. Student in Electrical Engineering, admitted Autumn 2025
Current Research and Scholarly InterestsHigh complexity research in optimizing medical imaging modalities.
