• 대한임상검사과학회지
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• 제56권1호
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• pp.43-51
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• 2024

[⁶⁸Ga]Ga-FAPI-04는 암세포에 과발현 되어 있는 fibroblast activation protein (FAP)에 특이적으로 결합하는 FAP 저해제(FAP inhibitor, FAPI)에 방사성동위원소 ⁶⁸Ga을 표지한 방사성의약품이다. 본 연구에서는 국내에서 제작된 카세트기반 자동합성장치를 사용하여 [⁶⁸Ga]Ga-FAPI-04를 제조하는 방법을 개발하였다. [⁶⁸Ga]Ga-FAPI-04의 합법을 개발하기 위해 완충액 HEPES의 농도, 반응시간, FAPI-04 전구체 양, 반응온도에 따른 표지효율을 확인하였다. [⁶⁸Ga]Ga-FAPI-04는 2 M HEPES를 사용하여 pH 3.85에서 반응할 경우 가장 높은 표지효율을 획득할 수 있었고, 반응시간이 10분일 경우와 25 ㎍의 FAPI-04 전구체를 사용할 경우 및 100℃에서 반응할 경우 가장 높은 표지효율을 획득할 수 있었다. 또한 최종 합성된 [⁶⁸Ga]Ga-FAPI-04는 모든 품질기준을 만족하여 본 연구를 통해 개발된 [⁶⁸Ga]Ga-FAPI-04의 합성법은 FAPI 기반 방사성의 약품생산에 활용도가 높을 것으로 예상된다.

• 전자공학회논문지
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• 제51권5호
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• pp.177-187
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• 2014

본 논문에서는 고속 부공간 추적 기법인 FAPI (Fast Approsimated Power Iteration)에 GVFF RLS (Gradient-based Variable Forgetting Factor Recursive Least Square Error)를 적용한 GVFF FAPI 를 제안한다. 기존의 FAPI는 신호의 공분산 행렬을 추정하기 위해 고정 망각 인자를 사용하기에, 부공간이 지속적으로 변하는 비정재 환경에 적용하기 여려운 단점이 있다. 이러한 문제점을 해결하기 위해, GVFF FAPI는 개선된 MSE (Mean Square Error)의 분석으로부터 유도된 MSE의 기울기 기반의 시변 망각 인자를 사용한다. 또한 GVFF RLS의 망각 인자 업데이트 식을 개선하여 부공간이 지속적으로 변하는 비정재 환경에서 부공간 에러를 줄인다. 개선된 망각 인자 업데이트 식은 MSE의 기울기가 양수이면 망각 인자를 빠르게 감소하게 하고 MSE의 기울기가 음수이면 망각 인자를 천천히 증가시킨다. 모의실험을 통해서 도래각이 지속적으로 변하는 환경에서 GVFF FAPI 알고리즘이 기존의 FAPI 알고리즘보다 작은 부공간 에러를 가지는 것을 보이고, 추적된 부공간을 도래각 추정기법에 적용하였을 때 추적된 도래각의 RMSE (Root Mean Square Error)가 더 작은 것을 확인한다.

• 대한방사성의약품학회지
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• 제9권1호
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• pp.49-55
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• 2023

Tumors are encircled by various non-cancerous cell types in the extracellular matrix, including fibroblasts, endothelial cells, immune cells, and cytokines. Fibroblasts are the most critical cells in the tumor stroma and play an important role in tumor development, which has been highlighted in some epithelial cancers. Many studies have shown a tight connection between cancerous cells and fibroblasts in the last decade. Regulatory factors secreted into the tumor environment by special fibroblast cells, cancer-associated fibroblasts (CAFs), play an important role in tumor and vessel development, metastasis, and therapy resistance. This review addresses the development of FAP inhibitors, emphasizing the first, second, and latest generations. First-generation inhibitors exhibit low selectivity and chemical stability, encouraging researchers to develop new scaffolds based on preclinical and clinical data. Second-generation enzymes such as UAMC-1110 demonstrated enhanced FAP binding and better selectivity. Targeted treatment and diagnostic imaging have become possible by further developing radionuclide-labeled fibroblast activation protein inhibitors (FAPIs). Although all three FAPIs (01, 02, and 04) showed excellent preclinical and clinical findings. The final optimization of these FAPI scaffolds resulted in FAPI-46 with the highest tumor-to-background ratio and better binding affinity.

• International Journal of Aeronautical and Space Sciences
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• 제17권2호
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• pp.184-194
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• 2016

In existing identification methods for on-orbit spacecraft, such as eigensystem realization algorithm (ERA) and subspace method identification (SMI), singular value decomposition (SVD) is used frequently to estimate the modal parameters. However, these identification methods are often used to process the linear time-invariant system, and there is a lower computation efficiency using the SVD when the system order of spacecraft is high. In this study, to improve the computational efficiency in identifying time-varying modal parameters of large spacecraft, a faster recursive algorithm called fast approximated power iteration (FAPI) is employed. This approach avoids the SVD and can be provided as an alternative spacecraft identification method, and the latest modal parameters obtained can be applied for updating the controller parameters timely (e.g. the self-adaptive control problem). In numerical simulations, two large flexible spacecraft models, the Engineering Test Satellite-VIII (ETS-VIII) and Soil Moisture Active/Passive (SMAP) satellite, are established. The identification results show that this recursive algorithm can obtain the time-varying modal parameters, and the computation time is reduced significantly.

• Korean Journal of Radiology
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• 제25권1호
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• pp.86-102
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• 2024

Early diagnosis, accurate assessment, and localization of peritoneal metastasis (PM) are essential for the selection of appropriate treatments and surgical guidance. However, available imaging modalities (computed tomography [CT], conventional magnetic resonance imaging [MRI], and 18fluorodeoxyglucose positron emission tomography [PET]/CT) have limitations. The advent of new imaging techniques and novel molecular imaging agents have revealed molecular processes in the tumor microenvironment as an application for the early diagnosis and assessment of PM as well as real-time guided surgical resection, which has changed clinical management. In contrast to clinical imaging, which is purely qualitative and subjective for interpreting macroscopic structures, radiomics and artificial intelligence (AI) capitalize on high-dimensional numerical data from images that may reflect tumor pathophysiology. A predictive model can be used to predict the occurrence, recurrence, and prognosis of PM, thereby avoiding unnecessary exploratory surgeries. This review summarizes the role and status of different imaging techniques, especially new imaging strategies such as spectral photon-counting CT, fibroblast activation protein inhibitor (FAPI) PET/CT, near-infrared fluorescence imaging, and PET/MRI, for early diagnosis, assessment of surgical indications, and recurrence monitoring in patients with PM. The clinical applications, limitations, and solutions for fluorescence imaging, radiomics, and AI are also discussed.