• BMB Reports
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• v.48 no.5
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• pp.256-265
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• 2015

Cardiovascular and neurodegenerative diseases are major health threats in many developed countries. Recently, target tissues derived from human embryonic stem (hES) cells and induced pluripotent stem cells (iPSCs), such as cardiomyocytes (CMs) or neurons, have been actively mobilized for drug screening. Knowledge of drug toxicity and efficacy obtained using stem cell-derived tissues could parallel that obtained from human trials. Furthermore, iPSC disease models could be advantageous in the development of personalized medicine in various parts of disease sectors. To obtain the maximum benefit from iPSCs in disease modeling, researchers are now focusing on aging, maturation, and metabolism to recapitulate the pathological features seen in patients. Compared to pediatric disease modeling, adult-onset disease modeling with iPSCs requires proper maturation for full manifestation of pathological features. Herein, the success of iPSC technology, focusing on patient-specific drug treatment, maturation-based disease modeling, and alternative approaches to compensate for the current limitations of patient iPSC modeling, will be further discussed. [BMB Reports 2015; 48(5): 256-265]

• Journal of Genetic Medicine
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• v.9 no.2
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• pp.67-72
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• 2012

The generation of induced pluripotent stem cells (iPSCs) derived from patients' somatic cells provides a new paradigm for studying human genetic diseases. Human iPSCs which have similar properties of human embryonic stem cells (hESCs) provide a powerful platform to recapitulate the disease-specific cell types by using various differentiation techniques. This promising technology has being realized the possibility to explore pathophysiology of many human genetic diseases at the molecular and cellular levels. Furthermore, disease-specific human iPSCs can also be used for patient-based drug screening and new drug discovery at the stage of the pre-clinical test in vitro. In this review, we summarized the concept and history of cellular reprogramming or iPSC generation and highlight recent progresses for disease modeling using patient-specific iPSCs.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.2
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• pp.867-870
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• 2014

Purpose: This study used receiver operating characteristic curve to analyze Surveillance, Epidemiology and End Results (SEER) ependymoma data to identify predictive models and potential disparity in outcome. Materials and Methods: This study analyzed socio-economic, staging and treatment factors available in the SEER database for ependymoma. For the risk modeling, each factor was fitted by a Generalized Linear Model to predict the outcome ('brain and other nervous systems' specific death in yes/no). The area under the receiver operating characteristic curve (ROC) was computed. Similar strata were combined to construct the most parsimonious models. A random sampling algorithm was used to estimate the modeling errors. Risk of ependymoma death was computed for the predictors for comparison. Results: A total of 3,500 patients diagnosed from 1973 to 2009 were included in this study. The mean follow up time (S.D.) was 79.8 (82.3) months. Some 46% of the patients were female. The mean (S.D.) age was 34.4 (22.8) years. Age was the most predictive factor of outcome. Unknown grade demonstrated a 15% risk of cause specific death compared to 9% for grades I and II, and 36% for grades III and IV. A 5-tiered grade model (with a ROC area 0.48) was optimized to a 3-tiered model (with ROC area of 0.53). This ROC area tied for the second with that for surgery. African-American patients had 21.5% risk of death compared with 16.6% for the others. Some 72.7% of patient who did not get RT had cerebellar or spinal ependymoma. Patients undergoing surgery had 16.3% risk of death, as compared to 23.7% among those who did not have surgery. Conclusion: Grading ependymoma may dramatically improve modeling of data. RT is under used for cerebellum and spinal cord ependymoma and it may be a potential way to improve outcome.

• The Korean Journal of Physiology and Pharmacology
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• v.23 no.1
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• pp.63-70
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• 2019

We aimed to propose a novel computational approach to predict the electromechanical performance of pre- and post-mitral valve cerclage annuloplasty (MVCA). Furthermore, we tested a virtual estimation method to optimize the left ventricular basement tightening scheme using a pre-MVCA computer model. The present model combines the three-dimensional (3D) electromechanics of the ventricles with the vascular hemodynamics implemented in a lumped parameter model. 3D models of pre- and post-MVCA were reconstructed from the computed tomography (CT) images of two patients and simulated by solving the electromechanical-governing equations with the finite element method. Computed results indicate that reduction of the dilated heart chambers volume (reverse remodeling) appears to be dependent on ventricular stress distribution. Reduced ventricular stresses in the basement after MVCA treatment were observed in the patients who showed reverse remodeling of heart during follow up over 6 months. In the case who failed to show reverse remodeling after MVCA, more virtual tightening of the ventricular basement diameter than the actual model can induce stress unloading, aiding in heart recovery. The simulation result that virtual tightening of the ventricular basement resulted in a marked increase of myocardial stress unloading provides in silico evidence for a functional impact of MVCA treatment on cardiac mechanics and post-operative heart recovery. This technique contributes to establishing a pre-operative virtual rehearsal procedure before MVCA treatment by using patient-specific cardiac electromechanical modeling of pre-MVCA.

• Journal of Korean Neurosurgical Society
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• v.62 no.5
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• pp.493-501
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• 2019

The generation of human induced pluripotent stem cells (iPSCs) from somatic cells using gene transfer opens new areas for precision medicine with personalized cell therapy and encourages the discovery of essential platforms for targeted drug development. iPSCs retain the genome of the donor, may regenerate indefinitely, and undergo differentiation into virtually any cell type of interest using a range of published protocols. There has been enormous interest among researchers regarding the application of iPSC technology to regenerative medicine and human disease modeling, in particular, modeling of neurologic diseases using patient-specific iPSCs. For instance, Parkinson's disease, Alzheimer's disease, and spinal cord injuries may be treated with iPSC therapy or replacement tissues obtained from iPSCs. In this review, we discuss the work so far on generation and characterization of iPSCs and focus on recent advances in the use of human iPSCs in clinical setting.

• BMB Reports
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• v.52 no.6
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• pp.349-359
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• 2019

After the first research declaring the generation of human induced pluripotent stem cells (hiPSCs) in 2007, several attempts have been made to model neurodegenerative disease in vitro during the past decade. Parkinson's disease (PD) is the second most common neurodegenerative disorder, which is mainly characterized by motor dysfunction. The formation of unique and filamentous inclusion bodies called Lewy bodies (LBs) is the hallmark of both PD and dementia with LBs. The key pathology in PD is generally considered to be the alpha-synuclein (${\alpha}$-syn) accumulation, although it is still controversial whether this protein aggregation is a cause or consequence of neurodegeneration. In the present work, the recently published researches which recapitulated the ${\alpha}$-syn aggregation phenomena in sporadic and familial PD hiPSC models were reviewed. Furthermore, the advantages and potentials of using patient-derived PD hiPSC with focus on ${\alpha}$-syn aggregation have been discussed.

• Korean Medical Education Review
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• v.24 no.2
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• pp.103-112
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• 2022

The purpose of this study was to explore, using topic modeling, the social value of doctors and medicine demanded by society as reflected in published newspaper articles in Korea. Ultimately, this study aimed to reflect social needs in the process of developing the Patient-Centered Doctor's Competency Framework in Korea. For this purpose, a total of 2,068 newspaper articles published from 2016 to 2020 were analyzed. Through topic modeling of these newspaper articles over the past 5 years, 18 topics were derived and divided into four categories. Focusing on the derived topics and keywords, the topics derived in specific years and the proportion of topics by year were analyzed. The results of this study make it possible to grasp the needs of society projected through the press for doctors and medicine. Due to the nature of the press, topics that frequently appeared in newspaper articles were mainly social phenomena related to requirements for doctors, particularly dealing with economic and legal aspects. In particular, it was confirmed that doctors are now required to have a wider range of competencies that go beyond their required medical knowledge and clinical skills. This study helped to establish doctor's competencies by analyzing social needs for doctors through the latest research methods, and the findings could help to establish and improve doctor's competencies through ongoing research in the future.

• Journal of radiological science and technology
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• v.42 no.6
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• pp.447-454
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• 2019

In order to improve and supplement the shielding method for electron beam treatment, we designed a patient-specific shielding method using a 3D printer, and evaluated the usefulness by comparing and analyzing the distribution of electron beam doses to adjacent organs. In order to treat 5 cm sized superficial tumors around the lens, a CT Simulator was used to scan the Alderson Rando phantom and the DICOM file was converted into an STL file. The converted STL file was used to design a patient-specific shield and mold that matched the body surface contour of the treatment site. The thickness of the shield was 1 cm and 1.5 cm, and the mold was printed using a 3D printer, and the patient customized shielding block (PCSB) was fabricated with a cerrobend alloy with a thickness of 1 cm and 1.5 cm. The dosimetry was performed by attaching an EBT3 film on the surface of the Alderson Rando phantom eyelid and measuring the dose of 6, 9, and 12 MeV electron beams on the film using four shielding methods. Shielding rates were 83.89%, 87.14%, 87.39% at 6, 9, and 12 MeV without shielding, 1 cm (92.04%, 87.48%, 86.49%), 1.5 cm (91.13%, 91.88% with PSCB), 92.66%) The shielding rate was measured as 1 cm (90.7%, 92.23%, 88.08%) and 1.5 cm (88.31%, 90.66%, 91.81%) when the shielding block and the patient-specific shield were used together. PCSB fabrication improves shielding efficiency over conventional shielding methods. Therefore, PSCB may be useful for clinical application.

• Journal of Radiation Protection and Research
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• v.42 no.1
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• pp.9-15
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• 2017

Background: The purpose of this study is to assign an appropriate density to virtual phantom for 2D diode array detector with different dose calculation algorithms to guarantee the accuracy of patient-specific QA. Materials and Methods: Ten VMAT plans with 6 MV photon beam and ten VMAT plans with 15 MV photon beam were selected retrospectively. The computed tomography (CT) images of MapCHECK2 with MapPHAN were acquired to design the virtual phantom images. For all plans, dose distributions were calculated for the virtual phantoms with four different materials by AAA and AXB algorithms. The four materials were polystyrene, 455 HU, Jursinic phantom, and PVC. Passing rates for several gamma criteria were calculated by comparing the measured dose distribution with calculated dose distributions of four materials. Results and Discussion: For validation of AXB modeling in clinic, the mean percentages of agreement in the cases of dose difference criteria of 1.0% and 2.0% for 6 MV were $97.2%{\pm}2.3%$, and $99.4%{\pm}1.1%$, respectively while those for 15 MV were $98.5%{\pm}0.85%$ and $99.8%{\pm}0.2%$, respectively. In the case of 2%/2 mm, all mean passing rates were more than 96.0% and 97.2% for 6 MV and 15 MV, respectively, regardless of the virtual phantoms of different materials and dose calculation algorithms. The passing rates in all criteria slightly increased for AXB as well as AAA when using 455 HU rather than polystyrene. Conclusion: The virtual phantom which had a 455 HU values showed high passing rates for all gamma criteria. To guarantee the accuracy of patent-specific VMAT QA, each institution should fine-tune the mass density or HU values of this device.

• The Korean Journal of Physiology and Pharmacology
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• v.23 no.5
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• pp.305-310
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• 2019

The physiomic approach is now widely used in the diagnosis of cardiovascular diseases. There are two possible methods for cardiovascular physiome: the traditional mathematical model and the machine learning (ML) algorithm. ML is used in almost every area of society for various tasks formerly performed by humans. Specifically, various ML techniques in cardiovascular medicine are being developed and improved at unprecedented speed. The benefits of using ML for various tasks is that the inner working mechanism of the system does not need to be known, which can prove convenient in situations where determining the inner workings of the system can be difficult. The computation speed is also often higher than that of the traditional mathematical models. The limitations with ML are that it inherently leads to an approximation, and special care must be taken in cases where a high accuracy is required. Traditional mathematical models are, however, constructed based on underlying laws either proven or assumed. The results from the mathematical models are accurate as long as the model is. Combining the advantages of both the mathematical models and ML would increase both the accuracy and efficiency of the simulation for many problems. In this review, examples of cardiovascular physiome where approaches of mathematical modeling and ML can be combined are introduced.