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1,497 results on '"Kim, Jinhyun"'

1. Particle on a Rod: Surface-Tethered Catalyst on CdS Nanorods for Enzymatically Active Nicotinamide Cofactor Generation

Author

Jayasinghe, Lihini, Wei, Jiaxi, Kim, Jinhyun, Lineberry, Elizabeth, and Yang, Peidong

Subjects
Chemical Sciences, Physical Chemistry, Affordable and Clean Energy, Cadmium Compounds, Nanotubes, Sulfides, Catalysis, Light, NAD, Surface Properties, Semiconductors, Electron Transport, CdS Nanorods, Photocatalysis, Charge transfer, Redox cofactors, Nanoscience & Nanotechnology
Abstract

The photochemical generation of nicotinamide cofactor 1,4-NADH, facilitated by inorganic photosensitizers, emerges as a promising model system for investigating charge transfer phenomena at the interface of semiconductors and bacteria, with implications for enhancing photosynthetic biohybrid systems (PBSs). However, extant semiconductor nanocrystal model systems suffer from achieving optimal conversion efficiency under visible light. This study investigates quasi-one-dimensional CdS nanorods as superior light absorbers, surface modified with catalyst Cp*Rh(4,4'-COOH-bpy)Cl2 to produce enzymatically active NADH. This model subsystem facilitates easy product isolation and achieves a turnover frequency (TOF) of 175 h-1, one of the highest efficiencies reported for inorganic photosensitizer-based nicotinamide cofactor generation. Charge transfer kinetics, fundamental for catalytic solar energy conversion, range from 106 to 108 s-1 for this system highlighting the superior electron transfer capabilities of NRs. This model ensures efficient cofactor production and offers critical insights into advancing systems that mimic natural photosynthesis for sustainable solar-to-chemical synthesis.

Published
2024

2. A red-light-powered silicon nanowire biophotochemical diode for simultaneous CO2 reduction and glycerol valorization

Author

Kim, Jimin, Lin, Jia-An, Kim, Jinhyun, Roh, Inwhan, Lee, Soohyung, and Yang, Peidong

Subjects
Engineering, Nanotechnology, Affordable and Clean Energy, Inorganic chemistry, Physical chemistry, Chemical engineering
Abstract

A bias-free photochemical diode, in which a p-type photocathode is connected to an n-type photoanode to harness light for driving photoelectrochemical reduction and oxidation pairs, serves as a platform for realizing light-driven fuel generation from CO2. However, the conventional design, in which cathodic CO2 reduction is coupled with the anodic oxygen evolution reaction (OER), requires substantial energy input. Here we present a photochemical diode device that harnesses red light (740 nm) to simultaneously drive biophotocathodic CO2-to-multicarbon conversion and photoanodic glycerol oxidation as an alternative to the OER to overcome the above thermodynamic limitation. The device consists of an efficient CO2-fixing microorganism, Sporomusa ovata, interfaced with a silicon nanowire photocathode and a Pt–Au-loaded silicon nanowire photoanode. This photochemical diode operates bias-free under low-intensity (20 mW cm−2) red light irradiation with ~80% Faradaic efficiency for both the cathodic and anodic products. This work provides an alternative photosynthetic route to mitigate excessive CO2 emissions and efficiently generate value-added chemicals from CO2 and glycerol. (Figure presented.)

Published
2024

16. High-Photovoltage Silicon Nanowire for Biological Cofactor Production

Author

Lineberry, Elizabeth, Kim, Jinhyun, Kim, Jimin, Roh, Inwhan, Lin, Jia-An, and Yang, Peidong

Subjects
Engineering, Affordable and Clean Energy, Climate Action, Nanowires, NAD, Silicon, Nanostructures, Benchmarking, Chemical Sciences, General Chemistry, Chemical sciences
Abstract

Photocathodic conversion of NAD+ to NADH cofactor is a promising platform for activating redox biological catalysts and enzymatic synthesis using renewable solar energy. However, many photocathodes suffer from low photovoltage, consequently requiring a high cathodic bias for NADH production. Here, we report an n+p-type silicon nanowire (n+p-SiNW) photocathode having a photovoltage of 435 mV to drive energy-efficient NADH production. The enhanced band bending at the n+/p interface accounts for the high photovoltage, which conduces to a benchmark onset potential [0.393 V vs the reversible hydrogen electrode (VRHE)] for SiNW-based photocathodic NADH generation. In addition, the n+p-SiNW nanomaterial exhibits a Faradaic efficiency of 84.7% and a conversion rate of 1.63 μmol h-1 cm-1 at 0.2 VRHE, which is the lowest cathodic potential to achieve the maximum productivity among SiNW-sensitized cofactor production.

Published
2023

17. BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

Author

Manubens-Gil, Linus, Zhou, Zhi, Chen, Hanbo, Ramanathan, Arvind, Liu, Xiaoxiao, Liu, Yufeng, Bria, Alessandro, Gillette, Todd, Ruan, Zongcai, Yang, Jian, Radojević, Miroslav, Zhao, Ting, Cheng, Li, Qu, Lei, Liu, Siqi, Bouchard, Kristofer E, Gu, Lin, Cai, Weidong, Ji, Shuiwang, Roysam, Badrinath, Wang, Ching-Wei, Yu, Hongchuan, Sironi, Amos, Iascone, Daniel Maxim, Zhou, Jie, Bas, Erhan, Conde-Sousa, Eduardo, Aguiar, Paulo, Li, Xiang, Li, Yujie, Nanda, Sumit, Wang, Yuan, Muresan, Leila, Fua, Pascal, Ye, Bing, He, Hai-yan, Staiger, Jochen F, Peter, Manuel, Cox, Daniel N, Simonneau, Michel, Oberlaender, Marcel, Jefferis, Gregory, Ito, Kei, Gonzalez-Bellido, Paloma, Kim, Jinhyun, Rubel, Edwin, Cline, Hollis T, Zeng, Hongkui, Nern, Aljoscha, Chiang, Ann-Shyn, Yao, Jianhua, Roskams, Jane, Livesey, Rick, Stevens, Janine, Liu, Tianming, Dang, Chinh, Guo, Yike, Zhong, Ning, Tourassi, Georgia, Hill, Sean, Hawrylycz, Michael, Koch, Christof, Meijering, Erik, Ascoli, Giorgio A, and Peng, Hanchuan

Subjects
Biological Sciences, Networking and Information Technology R&D (NITRD), Bioengineering, Machine Learning and Artificial Intelligence, Benchmarking, Microscopy, Imaging, Three-Dimensional, Neurons, Algorithms, Technology, Medical and Health Sciences, Developmental Biology, Biological sciences
Abstract

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in many neuroscience laboratories interested in neuron tracing. Here, we report generated gold standard manual annotations for a subset of the available imaging datasets and quantified tracing quality for 35 automatic tracing algorithms. The goal of generating such a hand-curated diverse dataset is to advance the development of tracing algorithms and enable generalizable benchmarking. Together with image quality features, we pooled the data in an interactive web application that enables users and developers to perform principal component analysis, t-distributed stochastic neighbor embedding, correlation and clustering, visualization of imaging and tracing data, and benchmarking of automatic tracing algorithms in user-defined data subsets. The image quality metrics explain most of the variance in the data, followed by neuromorphological features related to neuron size. We observed that diverse algorithms can provide complementary information to obtain accurate results and developed a method to iteratively combine methods and generate consensus reconstructions. The consensus trees obtained provide estimates of the neuron structure ground truth that typically outperform single algorithms in noisy datasets. However, specific algorithms may outperform the consensus tree strategy in specific imaging conditions. Finally, to aid users in predicting the most accurate automatic tracing results without manual annotations for comparison, we used support vector machine regression to predict reconstruction quality given an image volume and a set of automatic tracings.

Published
2023

20. Association of methotrexate polyglutamates concentration with methotrexate efficacy and safety in patients with rheumatoid arthritis treated with predefined dose: results from the MIRACLE trial

Author

Izumi, Keisuke, Kondo, Yasushi, Yoshimoto, Keiko, Gono, Takahisa, Park, Sung-Hwan, Baek, Han Joo, Lee, Yun Jong, Choi, In Ah, Kim, Jinhyun, Hsu, Ping-Ning, Huang, Chun-Ming, Weng, Meng-Yu, Sung, Wan-Yu, Cheng, Tien-Tsai, Tamai, Hiroya, Ikeda, Kei, Miyamoto, Toshiaki, Taguchi, Hiroaki, Kuo, Chang-Fu, Shin, Kichul, Hirata, Shintaro, Okano, Yutaka, Sato, Shinji, Yasuoka, Hidekata, Kuwana, Masataka, Ishii, Tomonori, Kameda, Hideto, Kojima, Toshihisa, Nishi, Yurie, Mori, Masahiko, Miyagishi, Hideaki, Toshima, Genta, Sato, Yasunori, Tsai, Wen-Chan, Takeuchi, Tsutomu, and Kaneko, Yuko

Published
2025
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21. Author Correction: BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

Author

Manubens-Gil, Linus, Zhou, Zhi, Chen, Hanbo, Ramanathan, Arvind, Liu, Xiaoxiao, Liu, Yufeng, Bria, Alessandro, Gillette, Todd, Ruan, Zongcai, Yang, Jian, Radojević, Miroslav, Zhao, Ting, Cheng, Li, Qu, Lei, Liu, Siqi, Bouchard, Kristofer E., Gu, Lin, Cai, Weidong, Ji, Shuiwang, Roysam, Badrinath, Wang, Ching-Wei, Yu, Hongchuan, Sironi, Amos, Iascone, Daniel Maxim, Zhou, Jie, Bas, Erhan, Conde-Sousa, Eduardo, Aguiar, Paulo, Li, Xiang, Li, Yujie, Nanda, Sumit, Wang, Yuan, Muresan, Leila, Fua, Pascal, Ye, Bing, He, Hai-yan, Staiger, Jochen F., Peter, Manuel, Cox, Daniel N., Simonneau, Michel, Oberlaender, Marcel, Jefferis, Gregory, Ito, Kei, Gonzalez-Bellido, Paloma, Kim, Jinhyun, Rubel, Edwin, Cline, Hollis T., Zeng, Hongkui, Nern, Aljoscha, Chiang, Ann-Shyn, Yao, Jianhua, Roskams, Jane, Livesey, Rick, Stevens, Janine, Liu, Tianming, Dang, Chinh, Guo, Yike, Zhong, Ning, Tourassi, Georgia, Hill, Sean, Hawrylycz, Michael, Koch, Christof, Meijering, Erik, Ascoli, Giorgio A., and Peng, Hanchuan

Published
2024
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23. Light-driven biocatalytic oxidation.

Author

Yun, Chul-Ho, Kim, Jinhyun, Hollmann, Frank, and Park, Chan

Abstract

Enzymes are the catalyst of choice for highly selective reactions, offering nature-inspired approaches for sustainable chemical synthesis. Oxidative enzymes (e.g., monooxygenases, peroxygenases, oxidases, or dehydrogenases) catalyze a variety of enantioselective oxyfunctionalization and dehydrogenation reactions under mild conditions. To sustain the catalytic cycles of these enzymes, constant supply with or withdrawal of reducing equivalents (electrons) is required. Being redox by nature, photocatalysis appears a natural choice to accomplish the electron-relay role, and many photoenzymatic oxidation reactions have been developed in the past years. In this contribution, we critically summarize the current developments in photoredoxbiocatalysis, highlight some promising concepts but also discuss the current limitations.

Published
2022

39. Robust Nucleus Detection with Partially Labeled Exemplars

Author

Feng, Linqing, Song, Jun Ho, Kim, Jiwon, Jeong, Soomin, Park, Jin Sung, and Kim, Jinhyun

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Quantitative analysis of cell nuclei in microscopic images is an essential yet challenging source of biological and pathological information. The major challenge is accurate detection and segmentation of densely packed nuclei in images acquired under a variety of conditions. Mask R-CNN-based methods have achieved state-of-the-art nucleus segmentation. However, the current pipeline requires fully annotated training images, which are time consuming to create and sometimes noisy. Importantly, nuclei often appear similar within the same image. This similarity could be utilized to segment nuclei with only partially labeled training examples. We propose a simple yet effective region-proposal module for the current Mask R-CNN pipeline to perform few-exemplar learning. To capture the similarities between unlabeled regions and labeled nuclei, we apply decomposed self-attention to learned features. On the self-attention map, we observe strong activation at the centers and edges of all nuclei, including unlabeled nuclei. On this basis, our region-proposal module propagates partial annotations to the whole image and proposes effective bounding boxes for the bounding box-regression and binary mask-generation modules. Our method effectively learns from unlabeled regions thereby improving detection performance. We test our method with various nuclear images. When trained with only 1/4 of the nuclei annotated, our approach retains a detection accuracy comparable to that from training with fully annotated data. Moreover, our method can serve as a bootstrapping step to create full annotations of datasets, iteratively generating and correcting annotations until a predetermined coverage and accuracy are reached. The source code is available at https://github.com/feng-lab/nuclei.

Published
2019
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41. Reduced versus maximum tolerated methotrexate dose concomitant with adalimumab in patients with rheumatoid arthritis (MIRACLE): a randomised, open-label, non-inferiority trial

Author

Izumi, Keisuke, Kondo, Yasushi, Yoshimoto, Keiko, Gono, Takahisa, Park, Sung-Hwan, Baek, Han Joo, Lee, Yun Jong, Choi, In Ah, Kim, Jinhyun, Hsu, Ping-Ning, Huan, Chun-Ming, Weng, Meng-Yu, Sung, Wan-Yu, Cheng, Tien-Tsai, Tamai, Hiroya, Ikeda, Kei, Miyamoto, Toshiaki, Taguchi, Hiroaki, Kuo, Chang-Fu, Shin, Kichul, Hirata, Shintaro, Okano, Yutaka, Sato, Shinji, Yasuoka, Hidekata, Kuwana, Masataka, Ishii, Tomonori, Kameda, Hideto, Kojima, Toshihisa, Taninaga, Takehiro, Mori, Masahiko, Miyagishi, Hideaki, Sato, Yasunori, Tsai, Wen-Chan, Takeuchi, Tsutomu, and Kaneko, Yuko

Published
2023
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47. Nicotinamide adenine dinucleotide as a photocatalyst.

Author

Kim, Jinhyun, Lee, Sahng, Tieves, Florian, Paul, Caroline, Hollmann, Frank, and Park, Chan

Subjects
Biocatalysis, Electrons, Hydrogenation, Ions, Light, Metals, NAD, Oxidation-Reduction, Oxygen, Water
Abstract

Nicotinamide adenine dinucleotide (NAD+) is a key redox compound in all living cells responsible for energy transduction, genomic integrity, life-span extension, and neuromodulation. Here, we report a new function of NAD+ as a molecular photocatalyst in addition to the biological roles. Our spectroscopic and electrochemical analyses reveal light absorption and electronic properties of two π-conjugated systems of NAD+. Furthermore, NAD+ exhibits a robust photostability under UV-Vis-NIR irradiation. We demonstrate photocatalytic redox reactions driven by NAD+, such as O2 reduction, H2O oxidation, and the formation of metallic nanoparticles. Beyond the traditional role of NAD+ as a cofactor in redox biocatalysis, NAD+ executes direct photoactivation of oxidoreductases through the reduction of enzyme prosthetic groups. Consequently, the synergetic integration of biocatalysis and photocatalysis using NAD+ enables solar-to-chemical conversion with the highest-ever-recorded turnover frequency and total turnover number of 1263.4 hour-1 and 1692.3, respectively, for light-driven biocatalytic trans-hydrogenation.

Published
2019

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