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Shape-dependent cellular uptake of iron oxide nanorods: mechanisms of endocytosis and implications on cell labeling and cellular delivery
This paper examines how the shape and size of iron oxide nanorods affect their cellular uptake mechanisms. The study reveals the implications of different internalization pathways and their potential use in biomedical applications such as drug delivery and cell labeling.
Anbu Mozhi Thamizhchelvan, Hedi Ma, Tianhe Wu, Darlene Nguyen, Jonathan Padelford, Ted J. Whitworth, Yuancheng Li, Lily Yang, Hui Mao
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Shape-dependent cellular uptake of iron oxide nanorods: mechanisms of endocytosis and implications on cell labeling and cellular delivery
Hemodynamic property incorporated brain tumor segmentation by deep learning and density-based analysis of dynamic susceptibility contrast-enhanced magnetic resonance imaging (MRI)
In this paper, we presents a novel hybrid method that improves brain tumor segmentation by integrating hemodynamic properties from dynamic susceptibility contrast (DSC) enhanced MRI with deep learning spatial segmentation techniques. The approach, tested on a cohort of 513 patients, demonstrated enhanced segmentation precision and the ability to uncover hemodynamic heterogeneity within tumors, showing potential for more accurate tumor monitoring and treatment response assessment..
Leonardo Tang, Tianhe (Rory) Wu, Ranliang Hu, Quanquan Gu, Xiaofeng Yang, Hui Mao
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Hemodynamic property incorporated brain tumor segmentation by deep learning and density-based analysis of dynamic susceptibility contrast-enhanced magnetic resonance imaging (MRI)
Application and Regulatory Challenges of Artificial Intelligence/Machine Learning in Clinical Trials from the Perspectives of FDA Discussion, EMA Reflection Paper, and the Stakeholders’ Comments
This article explores the complex landscape of AI/ML applications in clinical trials, shedding light on regulatory challenges through the lens of FDA discussions, EMA reflections, and stakeholder feedback.
Lixin Yao, Tianhe (Rory) Wu
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Label-Free Chemically and Molecularly Selective Magnetic Resonance Imaging
In this paper, we reviewed the recent development of Label-Free Chemically and Molecularly Selective Magnetic Resonance Imaging.
Tianhe (Rory) Wu, Claire Liu, Anbu Mozhi Thamizhchelvan, Candace Fleischer, Xingui Peng, Guanshu Liu, Hui Mao
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Label-Free Chemically and Molecularly Selective Magnetic Resonance Imaging
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吴天贺
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吴天贺, Robert Ford
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