| Budget Amount *help |
¥25,740,000 (Direct Cost: ¥19,800,000、Indirect Cost: ¥5,940,000)
Fiscal Year 2023: ¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2022: ¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2021: ¥5,850,000 (Direct Cost: ¥4,500,000、Indirect Cost: ¥1,350,000)
Fiscal Year 2020: ¥10,010,000 (Direct Cost: ¥7,700,000、Indirect Cost: ¥2,310,000)
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| Outline of Final Research Achievements |
We developed a new methodology to reconstruct three-dimensional complex vascular network from a series of two-dimensional confocal microscope images taken from young zebrafish. The reconstructed three-dimensional structure and the movies of red blood cells at the two-dimensional planes are integrated into deep neural network for estimating the three-dimensional velocity field inside the vascular network. We have also established dissipative particle dynamics (DPD) simulation, and validated its capability of predicting complex interaction between red blood cells and plasma by comparing with experimental data. We also coated nano particles by PEG with different lengths, and demonstrated the possibility of controlling the residence time of nano particles in the blood flow, and thereby providing them the opportunity to reach a target tissue. The present experimental and numerical methods will be useful for the optimal design of nano particles used in the future drag delivery systems.
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