• Analytical Science and Technology
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• v.28 no.5
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• pp.323-330
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• 2015

Alkaptonuria, a rare inherited metabolic disease, is characterized by a lack of homogentisate dioxygenase and accumulation of homogentisic acid (HGA), leading to homogentisic aciduria, arthritis, and ochronosis. In this study, a rapid analytical method, without an expensive and tedious solid phase extraction step, was developed to quantify HGA in plasma using GC-MS. HGA-spiked pooled plasma samples were subjected to liquid-liquid extraction (LLE) with ethyl acetate, followed by trimethylsilyl derivatization (TMS) and GC-MS quantification using selected ion monitoring. The formation of TMS derivative of the 1 carboxylic and 2 hydroxyl functional groups was performed by reacting BSTFA (with 10% TMCS) for 5 min at 80 ℃. For selected ion monitoring, quantification and confirmation ions were determined based on specific ions (m/z 384, m/z 341 and m/z 252) of the TMS derivative of HGA. Calibration curves of pooled normal plasma specimens showed a linear relationship in the range of 1-100 ng/µL. The precision and accuracy were within a relative standard deviation (RSD) of 1 to 15% and a bias of -5 to 25%. Recoveries were obtained in the range of 99-125% and 95-115% for intra-day and inter-day assay, respectively, at 2, 20 and 80 ng/µL. The limit of detection (LOD) and limit of quantification (LOQ) were 0.4 ng/µL and 4 ng/µL, respectively. No homogentisic acid was excreted from normal Korean plasma samples. Collectively, the results from the present study suggest that this method could be useful for routine diagnosis and therapeutic monitoring of alkaptonuria patients with excellent sensitivity and rapidity.

• The Korean Journal of Nuclear Medicine
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• v.30 no.4
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• pp.476-483
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• 1996

Following radiation therapy for brain tumors, patients often have clinical deterioration due to either radiation necrosis or recurrent tumor progression in the treatment field. The distinction between these entities is important but difficult clinically or even with CT or MRI. T1-201 has been known to accumulate in various tumors and be useful to grade, predict prognosis or detect recurrence of glioma. The aim of this study was to evaluate the usefulness of T1-201 SPECT in the differentiation of recurrent tumor from radiation necrosis. Of 67 patients who did T1-201 brain SPECT imaging with clinically suspected recurrent tumor or radiation necrosis, 20 patients underwent histopathological examination and constituted the study population. T1-201 uptake indices on T1-201 brain SPECT imaging rrere calculated and correlated with histopathological diagnosis. Of 20 patients, 15 were histopathologically confirmed as recurrent original tumor or malignant transformation of benign tumor and 5 were diagnosed as radiation necrosis. On T1-201 SPECT, 18 of 20 had T1-201 index above 2.5 which was regarded as positive indicator for the presence of tumor. Seventeen cases showed concordance, which consisted of 15 true positive and 2 true negative. Discordant 3 cases were all false positive. There was no case of false negative. The sensitivity, specificity, positive and negative predictive value of T1-201 SPECT were 100%, 40%, 83% and 100%. In conclusion, T1-201 brain SPECT is a sensitive diagnostic test in the detection of recurrent tumor following radiation therapy and is useful in the differentiation of recurrent tumor from radiation necrosis. Relatively low specificity should be evaluated further in larger number of patients in consideration of sampling error and referral bias for pathologic examination.

• Journal of Intelligence and Information Systems
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• v.28 no.3
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• pp.259-278
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• 2022

With the spread of Artificial Intelligence (AI), various AI-based services are expanding in the financial sector such as service recommendation, automated customer response, fraud detection system(FDS), credit scoring services, etc. At the same time, problems related to reliability and unexpected social controversy are also occurring due to the nature of data-based machine learning. The need Based on this background, this study aimed to contribute to improving trust in AI-based financial services by proposing a checklist to secure fairness in AI-based credit scoring services which directly affects consumers' financial life. Among the key elements of trustworthy AI like transparency, safety, accountability, and fairness, fairness was selected as the subject of the study so that everyone could enjoy the benefits of automated algorithms from the perspective of inclusive finance without social discrimination. We divided the entire fairness related operation process into three areas like data, algorithms, and user areas through literature research. For each area, we constructed four detailed considerations for evaluation resulting in 12 checklists. The relative importance and priority of the categories were evaluated through the analytic hierarchy process (AHP). We use three different groups: financial field workers, artificial intelligence field workers, and general users which represent entire financial stakeholders. According to the importance of each stakeholder, three groups were classified and analyzed, and from a practical perspective, specific checks such as feasibility verification for using learning data and non-financial information and monitoring new inflow data were identified. Moreover, financial consumers in general were found to be highly considerate of the accuracy of result analysis and bias checks. We expect this result could contribute to the design and operation of fair AI-based financial services.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.29 no.1
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• pp.56-76
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• 2024

We for the first time made a successful longest continuous sectional observation in the East Sea by an underwater glider during 95 days from September 18 to December 21 2020 in the Korea along the 106 Line (129.1 °E ~ 131.5 °E at 37.9 °N) of the regular shipboard measurements by the National Institute of Fishery Science (NIFS) and obtained twelve hydrographic sections with high spatiotemporal resolution. The glider was deployed at 129.1 °E in September 18 and conducted 88-days flight from September 19 to December 15 2020, yielding twelve hydrographic sections, and then recovered at 129.2 °E in December 21 after the last 6 days virtual mooring operation. During the total traveled distance of 2550 km, the estimated deviation from the predetermined zonal path had an average RMS distance of 262 m. Based on these high-resolution long-term glider measurements, we conducted a comparative study with the bi-monthly NIFS measurements in terms of spatial and temporal resolutions, and found distinguished features. One is that spatial features of sub-mesoscale such as sub-mesoscale frontal structure and intensified thermocline were detected only in the glider measurements, mainly due to glider's high spatial resolution. The other is the detection of intramonthly variations from the weekly time series of temperature and salinity, which were extracted from glider's continuous sections. Lastly, there were deviations and bias in measurements from both platforms. We argued these deviations in terms of the time scale of variation, the spatial scale of fixed-point observation, and the calibration status of CTD devices of both platforms.