担当区分：筆頭著者   記述言語：英語   掲載種別：研究論文（国際会議プロシーディングス）

Microalgae-based methods used in heavy metal (HM)-polluted wastewater treatment have attracted increasing attention in recent decades, due to their eco-friendliness, profitability, and sustainability. Unfortunately, their low HM removal efficiency hinders them from practical use. In this work, we report an AI-on-a-chip method, a combination of AI and lab-on-a-chip technology, for identifying Euglena gracilis (a microalgal species) cells with high HM removal efficiency through a morphological meta-feature. In the near future, the implementation of the morphological meta-feature in a high-throughput cell sorting process will pave the way for realizing directed-evolution-based development of microalgae with extremely high HM removal efficiency for practical wastewater treatment worldwide.

DOI： 10.1109/Transducers50396.2021.9495554

Kyutacar

Scopus

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記述言語：英語   掲載種別：研究論文（学術雑誌）

The advent of intelligent image-activated cell sorting (iIACS) has enabled high-throughput intelligent image-based sorting of single live cells from heterogeneous populations. iIACS is an on-chip microfluidic technology that builds on a seamless integration of a high-throughput fluorescence microscope, cell focuser, cell sorter, and deep neural network on a hybrid software-hardware data management architecture, thereby providing the combined merits of optical microscopy, fluorescence-activated cell sorting (FACS), and deep learning. Here we report an iIACS machine that far surpasses the state-of-the-art iIACS machine in system performance in order to expand the range of applications and discoveries enabled by the technology. Specifically, it provides a high throughput of ∼2000 events per second and a high sensitivity of ∼50 molecules of equivalent soluble fluorophores (MESFs), both of which are 20 times superior to those achieved in previous reports. This is made possible by employing (i) an image-sensor-based optomechanical flow imaging method known as virtual-freezing fluorescence imaging and (ii) a real-time intelligent image processor on an 8-PC server equipped with 8 multi-core CPUs and GPUs for intelligent decision-making, in order to significantly boost the imaging performance and computational power of the iIACS machine. We characterize the iIACS machine with fluorescent particles and various cell types and show that the performance of the iIACS machine is close to its achievable design specification. Equipped with the improved capabilities, this new generation of the iIACS technology holds promise for diverse applications in immunology, microbiology, stem cell biology, cancer biology, pathology, and synthetic biology. This journal is

DOI： 10.1039/d0lc00080a

Scopus

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記述言語：英語   掲載種別：研究論文（学術雑誌）

Optofluidic time-stretch quantitative phase imaging (OTS-QPI) is a potent tool for biomedical applications as it enables high-throughput QPI of numerous cells for large-scale single-cell analysis in a label-free manner. However, there are a few critical limitations that hinder OTS-QPI from being widely applied to diverse applications, such as its costly instrumentation and inherent phase-unwrapping errors. Here, to overcome the limitations, we present a QPI-free OTS-QPI method that generates "virtual" phase images from their corresponding bright-field images by using a deep neural network trained with numerous pairs of bright-field and phase images. Specifically, our trained generative adversarial network model generated virtual phase images with high similarity (structural similarity index >0.7) to their corresponding real phase images. This was also supported by our successful classification of various types of leukemia cells and white blood cells via their virtual phase images. The virtual OTS-QPI method is highly reliable and cost-effective and is therefore expected to enhance the applicability of OTS microscopy in diverse research areas, such as cancer biology, precision medicine, and green energy.

DOI： 10.1063/1.5134125

Kyutacar

Scopus

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担当区分：筆頭著者   記述言語：英語   掲載種別：研究論文（学術雑誌）

The evaluation of single carbon particle catalysts is critical to better understand the relationship between structure and properties. Here, we use an electrochemical collision method to study the electrocatalytic behaviour of single hollow porous carbon catalyst on gold nanoband electrodes (AuNBE). We observed the catalytic current of oxygen reduction of single carbon particle and quantified the contribution of the porous structure to the catalytic performance. We find that the meso/microporous and hollow structures contribute to the electrocatalytic current. Our research provides direct evidence that the hollow/porous structures improve the electrocatalytic performance.

DOI： 10.1002/cphc.201801028

Scopus

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記述言語：英語   掲載種別：研究論文（学術雑誌）

An absorbance enhanced probe based on gold nanoparticles (GNPs) was proposed for a protein assay in the cerebrospinal fluid of a rat brain. The GNPs, assembled with two aptamers by proximity ligation, have high anti-salt properties, and good selectivity and response toward proteins, such as interferon-gamma, in the brain.

DOI： 10.1039/c7cc08636a

Scopus

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記述言語：英語   掲載種別：研究論文（学術雑誌）

DOI： 10.1021/acs.analchem.5b04055

開催期間： 2024年10月13日 - 2024年10月16日   記述言語：英語  

開催期間： 2024年09月16日 - 2024年09月20日   記述言語：英語  

開催期間： 2024年03月01日 - 2024年03月02日   記述言語：英語  

開催期間： 2023年11月14日   記述言語：英語  

開催期間： 2022年05月21日 - 2022年05月22日   記述言語：日本語  

開催期間： 2020年10月26日 - 2020年10月28日   記述言語：英語  

開催期間： 2020年06月17日   記述言語：英語  

開催期間： 2019年11月09日 - 2019年11月11日   記述言語：英語