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1,417 results on '"Kim, Tae Kyung"'

2. Spatially resolved analysis of pancreatic cancer identifies therapy-associated remodeling of the tumor microenvironment

Author

Shiau, Carina, Cao, Jingyi, Gong, Dennis, Gregory, Mark T., Caldwell, Nicholas J., Yin, Xunqin, Cho, Jae-Won, Wang, Peter L., Su, Jennifer, Wang, Steven, Reeves, Jason W., Kim, Tae Kyung, Kim, Youngmi, Guo, Jimmy A., Lester, Nicole A., Bae, Jung Woo, Zhao, Ryan, Schurman, Nathan, Barth, Jamie L., Ganci, Maria L., Weissleder, Ralph, Jacks, Tyler, Qadan, Motaz, Hong, Theodore S., Wo, Jennifer Y., Roberts, Hannah, Beechem, Joseph M., Castillo, Carlos Fernandez-del, Mino-Kenudson, Mari, Ting, David T., Hemberg, Martin, and Hwang, William L.

Published
2024
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7. A Novel Knapsack-based Financial Portfolio Optimization using Quantum Approximate Optimization Algorithm

Author

Huot, Chansreynich, Kea, Kimleang, Kim, Tae-Kyung, and Han, Youngsun

Subjects
Quantum Physics
Abstract

Portfolio optimization is a primary component of the decision-making process in finance, aiming to tactfully allocate assets to achieve optimal returns while considering various constraints. Herein, we proposed a method that uses the knapsack-based portfolio optimization problem and incorporates the quantum computing capabilities of the quantum walk mixer with the quantum approximate optimization algorithm (QAOA) to address the challenges presented by the NP-hard problem. Additionally, we present the sequential procedure of our suggested approach and demonstrate empirical proof to illustrate the effectiveness of the proposed method in finding the optimal asset allocations across various constraints and asset choices. Moreover, we discuss the effectiveness of the QAOA components in relation to our proposed method. Consequently, our study successfully achieves the approximate ratio of the portfolio optimization technique using a circuit layer of p >= 3, compared to the classical best-known solution of the knapsack problem. Our proposed methods potentially contribute to the growing field of quantum finance by offering insights into the potential benefits of employing quantum algorithms for complex optimization tasks in financial portfolio management.

Published
2024

11. Inflammation promotes synucleinopathy propagation.

Author

Kim, Tae-Kyung, Bae, Eun-Jin, Jung, Byung, Choi, Minsun, Shin, Soo, Park, Sung, Kim, Jeong, Jung, Min, Ulusoy, Ayse, Song, Mi-Young, Lee, Jun, Lee, He-Jin, Di Monte, Donato, and Lee, Seung-Jae

Subjects
Mice, Animals, alpha-Synuclein, Synucleinopathies, Brain, Neurodegenerative Diseases, Inflammation, Disease Models, Animal
Abstract

The clinical progression of neurodegenerative diseases correlates with the spread of proteinopathy in the brain. The current understanding of the mechanism of proteinopathy spread is far from complete. Here, we propose that inflammation is fundamental to proteinopathy spread. A sequence variant of α-synuclein (V40G) was much less capable of fibril formation than wild-type α-synuclein (WT-syn) and, when mixed with WT-syn, interfered with its fibrillation. However, when V40G was injected intracerebrally into mice, it induced aggregate spreading even more effectively than WT-syn. Aggregate spreading was preceded by sustained microgliosis and inflammatory responses, which were more robust with V40G than with WT-syn. Oral administration of an anti-inflammatory agent suppressed aggregate spreading, inflammation, and behavioral deficits in mice. Furthermore, exposure of cells to inflammatory cytokines increased the cell-to-cell propagation of α-synuclein. These results suggest that the inflammatory microenvironment is the major driver of the spread of synucleinopathy in the brain.

Published
2022

20. TNF-α promotes α-synuclein propagation through stimulation of senescence-associated lysosomal exocytosis.

Author

Bae, Eun-Jin, Choi, Minsun, Kim, Jeong, Kim, Dong-Kyu, Jung, Min, Kim, Changyoun, Kim, Tae-Kyung, Lee, Jun, Jung, Byung, Shin, Soo, Rhee, Ka, and Lee, Seung-Jae

Subjects
Exocytosis, Humans, Inflammation, Lysosomes, Tumor Necrosis Factor-alpha, alpha-Synuclein
Abstract

Cell-to-cell propagation of α-synuclein is thought to be the underlying mechanism of Parkinsons disease progression. Recent evidence suggests that inflammation plays an important role in the propagation of protein aggregates. However, the mechanism by which inflammation regulates the propagation of aggregates remains unknown. Here, using in vitro cultures, we found that soluble factors secreted from activated microglia promote cell-to-cell propagation of α-synuclein and further showed that among these soluble factors, TNF-α had the most robust stimulatory activity. Treatment of neurons with TNF-α triggered cellular senescence, as shown by transcriptomic analyses demonstrating induction of senescence-associated genes and immunoanalysis of senescence phenotype marker proteins. Interestingly, secretion of α-synuclein was increased in senescent neurons, reflecting acquisition of a senescence-associated secretory phenotype (SASP). Using vacuolin-1, an inhibitor of lysosomal exocytosis, and RNAi against rab27a, we demonstrated that the SASP was mediated by lysosomal exocytosis. Correlative light and electron microscopy and immunoelectron microscopy confirmed that propagating α-synuclein aggregates were present in electron-dense lysosome-like compartments. TNF-α promoted the SASP through stimulation of lysosomal exocytosis, thereby increasing the secretion of α-synuclein. Collectively, these results suggest that TNF-α is the major inflammatory factor that drives cell-to-cell propagation of α-synuclein by promoting the SASP and subsequent secretion of α-synuclein.

Published
2022

22. Conformation-specific Antibodies Targeting Aggregated Forms of α-synuclein Block the Propagation of Synucleinopathy.

Author

Choi, Minsun, Kim, Tae-Kyung, Ahn, Jinhyung, Lee, Jun, Jung, Byung, An, Sungwon, Kim, Dongin, Lee, Min, Mook-Jung, Inhee, Lee, Sang, and Lee, Seung-Jae

Subjects
Immunotherapy, Microglia, Parkinson’s disease, Synuclein
Abstract

Abnormal aggregation of α-synuclein is a key element in the pathogenesis of several neurodegenerative diseases, including Parkinsons disease (PD), dementia with Lewy bodies, and multiple system atrophy. α-synuclein aggregation spreads through various brain regions during the course of disease progression, a propagation that is thought to be mediated by the secretion and subsequent uptake of extracellular α-synuclein aggregates between neuronal cells. Thus, aggregated forms of this protein have emerged as promising targets for disease-modifying therapy for PD and related diseases. Here, we generated and characterized conformation-specific antibodies that preferentially recognize aggregated forms of α-synuclein. These antibodies promoted phagocytosis of extracellular α-synuclein aggregates by microglial cells and interfered with cell-to-cell propagation of α-synuclein. In an α-synuclein transgenic model, passive immunization with aggregate-specific antibodies significantly ameliorated pathological phenotypes, reducing α-synuclein aggregation, gliosis, inflammation, and neuronal loss. These results suggest that conformation-specific antibodies targeting α-synuclein aggregates are promising therapeutic agents for PD and related synucleinopathies.

Published
2022

23. Spatial database of planted forests in East Asia

Author

Abbasi, Akane O., Tang, Xiaolu, Harris, Nancy L., Goldman, Elizabeth D., Gamarra, Javier G. P., Herold, Martin, Kim, Hyun Seok, Luo, Weixue, Silva, Carlos Alberto, Tchebakova, Nadezhda M., Mitra, Ankita, Finegold, Yelena, Jahanshahi, Mohammad Reza, Alvarez, Cesar Ivan, Kim, Tae Kyung, Ryu, Daun, and Liang, Jingjing

Published
2023
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30. High-plex imaging of RNA and proteins at subcellular resolution in fixed tissue by spatial molecular imaging

Author

He, Shanshan, Bhatt, Ruchir, Brown, Carl, Brown, Emily A., Buhr, Derek L., Chantranuvatana, Kan, Danaher, Patrick, Dunaway, Dwayne, Garrison, Ryan G., Geiss, Gary, Gregory, Mark T., Hoang, Margaret L., Khafizov, Rustem, Killingbeck, Emily E., Kim, Dae, Kim, Tae Kyung, Kim, Youngmi, Klock, Andrew, Korukonda, Mithra, Kutchma, Alecksandr, Lewis, Zachary R., Liang, Yan, Nelson, Jeffrey S., Ong, Giang T., Perillo, Evan P., Phan, Joseph C., Phan-Everson, Tien, Piazza, Erin, Rane, Tushar, Reitz, Zachary, Rhodes, Michael, Rosenbloom, Alyssa, Ross, David, Sato, Hiromi, Wardhani, Aster W., Williams-Wietzikoski, Corey A., Wu, Lidan, and Beechem, Joseph M.

Published
2022
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33. Reasons for Discontinuing Active Surveillance: Assessment of 21 Centres in 12 Countries in the Movember GAP3 Consortium

Author

Van Hemelrijck, Mieke, Ji, Xi, Helleman, Jozien, Roobol, Monique J, van der Linden, Wim, Nieboer, Daan, Bangma, Chris H, Frydenberg, Mark, Rannikko, Antti, Lee, Lui S, Gnanapragasam, Vincent J, Kattan, Mike W, Trock, Bruce, Ehdaie, Behfar, Carroll, Peter, Filson, Christopher, Kim, Jeri, Logothetis, Christopher, Morgan, Todd, Klotz, Laurence, Pickles, Tom, Hyndman, Eric, Moore, Caroline M, Gnanapragasam, Vincent, Dasgupta, Prokar, Bangma, Chris, Roobol, Monique, Villers, Arnauld, Valdagni, Riccardo, Perry, Antoinette, Hugosson, Jonas, Rubio-Briones, Jose, Bjartell, Anders, Hefermehl, Lukas, Shiong, Lee Lui, Kakehi, Yoshiyuki, Chung, Byung Ha, van der Kwast, Theo, Obbink, Henk, Hulsen, Tim, de Jonge, Cees, Kattan, Mike, Xinge, Ji, Muir, Kenneth, Lophatananon, Artitaya, Fahey, Michael, Steyerberg, Ewout, Zhang, Liying, Santa Olalla, Aida, Beckmann, Kerri, Denton, Brian, Hayen, Andrew, Boutros, Paul, Guo, Wei, Benfante, Nicole, Cowan, Janet, Patil, Dattatraya, Tolosa, Emily, Kim, Tae-Kyung, Mamedov, Alexandre, La Pointe, Vincent, Crump, Trafford, Kimberly-Duffell, Jenna, Santaolalla, Aida, Olivier, Jonathan, Rancati, Tiziana, Ahlgren, Helén, Mascarós, Juanma, Löfgren, Annica, Lehmann, Kurt, Lin, Catherine Han, Hirama, Hiromi, Lee, Kwang Suk, Jenster, Guido, Auvinen, Anssi, Haider, Masoom, van Bochove, Kees, Carter, Ballentine, Gledhill, Sam, Buzza, Mark, and Bruinsma, Sophie

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Oncology and Carcinogenesis, Prostate Cancer, Aging, Prevention, Urologic Diseases, Cancer, Good Health and Well Being, Aged, Asia, Australia, Biopsy, Cause of Death, Clinical Decision-Making, Databases, Factual, Disease Progression, Early Detection of Cancer, Europe, Humans, Kallikreins, Male, Middle Aged, North America, Patient Dropouts, Predictive Value of Tests, Prostate-Specific Antigen, Prostatic Neoplasms, Risk Assessment, Risk Factors, Time Factors, Watchful Waiting, Prostate cancer, Active surveillance, Discontinuation, Worldwide, Members of the Movember Foundation's Global Action Plan Prostate Cancer Active Surveillance GAP3 consortium, Urology & Nephrology, Clinical sciences
Abstract

BackgroundCareful assessment of the reasons for discontinuation of active surveillance (AS) is required for men with prostate cancer (PCa).ObjectiveUsing Movember's Global Action Plan Prostate Cancer Active Surveillance initiative (GAP3) database, we report on reasons for AS discontinuation.Design, setting, and participantsWe compared data from 10296 men on AS from 21 centres across 12 countries.Outcome measurements and statistical analysisCumulative incidence methods were used to estimate the cumulative incidence rates of AS discontinuation.Results and limitationsDuring 5-yr follow-up, 27.5% (95% confidence interval [CI]: 26.4-28.6%) men showed signs of disease progression, 12.8% (95% CI: 12.0-13.6%) converted to active treatment without evidence of progression, 1.7% (95% CI: 1.5-2.0%) continued to watchful waiting, and 1.7% (95% CI: 1.4-2.1%) died from other causes. Of the 7049 men who remained on AS, 2339 had follow-up for >5yr, 4561 had follow-up for

Published
2019

39. A Hybrid Quantum-Classical Model for Stock Price Prediction Using Quantum-Enhanced Long Short-Term Memory.

Author

Kea, Kimleang, Kim, Dongmin, Huot, Chansreynich, Kim, Tae-Kyung, and Han, Youngsun

Subjects
STOCKS (Finance), STANDARD deviations, QUANTUM computing, TIME series analysis, FINANCIAL markets, QUANTUM computers
Abstract

The stock markets have become a popular topic within machine learning (ML) communities, with one particular application being stock price prediction. However, accurately predicting the stock market is a challenging task due to the various factors within financial markets. With the introduction of ML, prediction techniques have become more efficient but computationally demanding for classical computers. Given the rise of quantum computing (QC), which holds great promise for being exponentially faster than current classical computers, it is natural to explore ML within the QC domain. In this study, we leverage a hybrid quantum-classical ML approach to predict a company's stock price. We integrate classical long short-term memory (LSTM) with QC, resulting in a new variant called QLSTM. We initially validate the proposed QLSTM model by leveraging an IBM quantum simulator running on a classical computer, after which we conduct predictions using an IBM real quantum computer. Thereafter, we evaluate the performance of our model using the root mean square error (RMSE) and prediction accuracy. Additionally, we perform a comparative analysis, evaluating the prediction performance of the QLSTM model against several other classical models. Further, we explore the impacts of hyperparameters on the QLSTM model to determine the best configuration. Our experimental results demonstrate that while the classical LSTM model achieved an RMSE of 0.0693 and a prediction accuracy of 0.8815, the QLSTM model exhibited superior performance, achieving values of 0.0602 and 0.9736, respectively. Furthermore, the QLSTM outperformed other classical models in both metrics. [ABSTRACT FROM AUTHOR]

Published
2024
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48. ETV5 promotes lupus pathogenesis and follicular helper T cell differentiation by inducing osteopontin expression

Author

Park, Jiho, primary, Lee, Jongeun, additional, Hur, Yunjung, additional, Kim, Chan-Johng, additional, Kim, Han Bit, additional, Um, Dahun, additional, Kim, Da Som, additional, Lee, June-Yong, additional, Park, Sungjun, additional, Park, Youngjae, additional, Kim, Tae-Kyung, additional, Im, Sin-Hyeog, additional, Kim, Sung Won, additional, Kwok, Seung-Ki, additional, and Lee, Yoontae, additional

Published
2024
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