• Journal of Radiopharmaceuticals and Molecular Probes
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• v.9 no.1
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• pp.9-16
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• 2023

Liposomes as drug delivery system have proved useful carrier for various disease, including cancer. In addition, perfluorocarbon cored microbubbles are utilized in conjunction with high-intensity focused-ultrasound (HIFU) to enable simultaneous diagnosis and treatment. However, microbubbles generally exhibit lower drug loading efficiency, so the need for the development of a novel liposome-based drug delivery material that can efficiently load and deliver drugs to targeted areas via HIFU. This study aims to develop a liposome-based drug delivery material by introducing a substance that can burst liposomes using ultrasound energy and confirm the ability to target tumors using PET imaging. Liposomes (Lipo-DOX, Lipo-DOX-Au, Lipo-DOX-Au-RGD) were synthesized with gold nanoparticles using an avidin-biotin bond, and doxorubicin was mounted inside by pH gradient method. The size distribution was measured by DLS, and encapsulation efficiency of doxorubicin was analyzed by UV-vis spectrometer. The target specificity and cytotoxicity of liposomes were assessed in vitro by glioblastoma U87mg cells to HIFU treatment and analyzed using CCK-8 assay, and fluorescence microscopy at 6-hour intervals for up to 24 hours. For the in vivo study, U87mg model mouse were injected intravenously with 1.48 MBq of ⁶⁴Cu-labeled Lipo-DOX-Au and Lipo-DOX-Au-RGD, and PET images were taken at 0, 2, 4, 8, and 24 hours. As a result, the size of liposomes was 108.3 ± 5.0 nm at Lipo-DOX-Au and 94.1 ± 12.2 nm at Lipo-DOX-Au-RGD, and it was observed that doxorubicin was mounted inside the liposome up to 52%. After 6 hours of HIFU treatment, the viability of U87mg cells treated with Lipo-DOX-Au decreased by around 20% compared to Lipo-DOX, and Lipo-DOX-Au-RGD had a higher uptake rate than Lipo-DOX. In vivo study using PET images, it was confirmed that ⁶⁴Cu-Lipo-DOX-Au-RGD was taken up into the tumor immediately after injection and maintained for up to 4 hours. In this study, drugs released from liposomes-gold nanoparticles via ultrasound and RGD targeting were confirmed by non-invasive imaging. In cell-level experiments, HIFU treatment of gold nanoparticle-coupled liposomes significantly decreased tumor survival, while RGD-liposomes exhibited high tumor targeting and rapid release in vivo imaging. It is expected that the combination of these models with ultrasound is served as an effective drug delivery material with therapeutic outcomes.

• Journal of the Korean earth science society
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• v.44 no.6
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• pp.578-593
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• 2023

Intense convective activity and heavy precipitation inundated Seoul and its metropolitan area on July 15, 2017. This study investigated the synoptic-scale meteorological drivers of cold cloud genesis of this event. The WRF-Chem (Weather Research and Forecasting model coupled with Chemistry) model was employed to explore the intricate interplay between meteorological factors and the indirect effects of PM_2.5 aerosols originating from eastern China. The PM_2.5 aerosols' indirect effect was quantified by contrasting outcomes between the comprehensive Aerosol Radiation Interaction experiment (encompassing aerosol radiation feedback, cloud chemistry processes, and wet scavenging in the WRF-Chem model) and ACR (Aerosol Cloud Radiation interaction) experiment. The ACR experiment specifically excluded aerosol radiation feedback while incorporating only cloud chemistry processes and wet scavenging. Results indicated that in the early hours of July 15, 2017, a convergence of warm, moisture-laden airflow originating from southeast China and the East China Sea unfolded over the Yellow Sea. This convergence was driven by the juxtaposition of a low-pressure system over the Chinese mainland and Northwest Pacific high. Notably, at approximately 12 km altitude, the resultant convective clouds were characterized by the presence of ice crystals, a hallmark of continental-origin cold clouds. The WRF-Chem model simulations elucidated the role of PM_2.5 aerosols from eastern China, attributing 5.7, 10.4, and 10.8% to cloud water, ice crystal column, and liquid water column formation, respectively, within the developing cold clouds. Thus, this study presented a meteorological mechanism elucidating the formation of deep convective clouds over the Yellow Sea and the indirect effects of PM_2.5 aerosols originating from eastern China.

• Journal of Food Hygiene and Safety
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• v.27 no.4
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• pp.375-387
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• 2012

The objective of this study is investigation of contamination levels and assessment of health risk effects of heavy metals in herbal pills. 31 Items and 93 samples were obtained for this investigation from major herbal medicine producing areas, herbal markets and on-line supermarkets from Jan to Jun in 2010. Inductively coupled plasma mass spectrometer method was conducted for the quantitative analysis of Pb, Cd and As. In addition, the mercury analyzer system was conducted for that of Hg without sample digestion. The average contents of heavy metals in samples were as follows : 0.87 mg/kg for Pb, 0.08 mg/kg for Cd, 2.87 mg/kg for As and 0.16 mg/kg for Hg, respectively. In addition, the average contents of heavy metals in different parts of plants, including cortex, fructus, herba, radix, seed, algae and others were 0.63 mg/kg, 3.94 mg/kg, 1.42 mg/kg, 1.05 mg/kg, 0.16 mg/kg, 22.31 mg/kg and 10.17 mg/kg, respectively. After the estimations of dietary exposure, the acceptable daily intake (ADI), the average daily dose (ADD), the provisional tolerable weekly intake (PTWI) and the relative hazard of heavy metals were evaluated. As the results, the relative hazards compared to PTWI in samples were below the recommended standard of JECFA as Pb 3.1%, Cd 0.9%, Hg 0.5%. Cancer risks through slope factor (SF) by Ministry of Environment Republic Korea and Environmental Protection Agency was $4.24{\times}10^{-7}$ for Pb and $3.38{\times}10^{-4}$ for As (assuming that the total arsenic content was equal to the inorganic arsenic). Based on our results, possible Pb-induced cancer risks in herbal pills according to parts used including cortex, fructus, herba, radix, seed, algae and others were $1.95{\times}10^{-7}$, $1.45{\times}10^{-6}$, $2.14{\times}10^{-7}$, $6.27{\times}10^{-7}$, $1.99{\times}10^{-8}$, $3.61{\times}10^{-7}$ and $9.64{\times}10^{-8}$, respectively. Possible As-induced cancer risks in herbal pills by parts used including cortex, fructus, herba, radix, seed, algae and others were $1.54{\times}10^{-5}$, $7.24{\times}10^{-5}$, $1.23{\times}10^{-4}$, $2.02{\times}10^{-5}$, $3.25{\times}10^{-6}$, $2.18{\times}10^{-3}$ and $5.67{\times}10^{-6}$ respectively. Taken together, these results indicate that the majority of samples except for some samples with relative high contents of heavy metals were safe.

• Korean Journal of Environmental Agriculture
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• v.37 no.4
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• pp.291-301
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• 2018

BACKGROUND: Rice is one of the main sources for inorganic arsenic among the consumed crops in the world population's diet. Arsenic is classified into Group 1 as it is carcinogenic for humans, according to the IARC. This study was carried out to assess dietary exposure risk of inorganic arsenic in husked rice and polished rice to the Korean population health. METHODS AND RESULTS: Total arsenic was determined using microwave device and ICP-MS. Inorganic arsenic was determined by ICP-MS coupled with HPLC system. The HPLC-ICP-MS analysis was optimized based on the limit of detection, limit of quantitation, and recovery ratio to be $0.73-1.24{\mu}g/kg$, $2.41-4.09{\mu}g/kg$, and 96.5-98.9%, respectively. The inorganic arsenic concentrations of daily exposure (included in body weight) were $4.97{\times}10^{-3}$ (${\geq}20$ years old) $-1.36{\times}10^{-2}$ (${\leq}2$ years old) ${\mu}g/kg\;b.w./day$ (PTWI 0.23-0.63%) by the husked rice, and $1.39{\times}10^{-1}$ (${\geq}20$ years old) $-3.21{\times}10^{-1}$ (${\leq}2$ years old) ${\mu}g/kg\;b.w./day$ (PTWI 6.47-15.00%) by the polished rice. CONCLUSION: The levels of overall exposure to total and inorganic arsenic by the husked and polished rice were far lower than the recommended levels of The Joint FAO/WHO Expert Committee on Food Additives (JECFA), indicating of little possibility of risk.

• Journal of the korean academy of Pediatric Dentistry
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• v.26 no.2
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• pp.399-415
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• 1999

From bacteria to mammalian cells, one of the most important mediators of intracellular signal transduction mechanisms which regulate a variety of intracellular processes is free calcium. In salivary acinar cells, elevation of intracellular calcium concentration ($[Ca^{2+}]_i$) is essential for the salivary secretion induced by parasympathetic stimulation. However, in addition to $[Ca^{2+}]_i$, gap junctions which couple individual cells electrically and chemically have also been reported to regulate enzyme secretion in pancreatic acinar cells. Since the plasma membrane of salivary acinar cells has a high density of gap junctions, and these cells are electrically and chemically coupled with each other, gap junctions may modulate the secretory function of salivary glands. In this respect, I planned to investigate the role of gap junctions in the modulation of salivary secretion and $[Ca^{2+}]_i$, using mandibular salivary glands of rats. In order to measure the salivary flow rate, fluid was collected from the cannulated duct of the isolated perfused rat mandibular glands at 2 min intervals. $[Ca^{2+}]_i$, was measured from the cells loaded with fura-2 by spectrofluorometry. The results obtained were as follows: 1. CCh-induced salivary secretion was reversibly inhibited by 1 mM octanol, a gap junction blocker. 2. CCh-induced increase in $[Ca^{2+}]_i$, was also reversed by the application of 1 mM octanol. 3. Octanol did not block the initial increase in $[Ca^{2+}]_i$ caused by CCh, which suggested that the reduction of $[Ca^{2+}]_i$, caused by gap junction blockade was not resulted from the inhibition of $Ca^{2+}$ release from intracellular $Ca^{2+}$ stores. 4. Addition of octanol during stimulation with $1{\mu}M$ thapsigargin, a potent microsomal ATPase inhibitor, reduced $[Ca^{2+}]_i$, to the basal level. This suggested that inhibition of gap junction permeability closed plasma membrane $Ca^{2+}$ channels. 5. 2,5-di-tert-butyl-1,4-benzohydroquinone (TBQ) generated $[Ca^{2+}]_i$ oscillations resulting from periodic influx of $Ca^{2+}$ via plasma membrane. The TBQ-induced $[Ca^{2+}]_i$ oscillations were stopped by the application of 1mM octanol which implicated that gap junctions modulate the permeability of plasma membrane $Ca^{2+}$ channels. 6. Glycyrrhetinic acid, another well known gap junction blocker, also inhibited CCh-induced salivary secretion from rat mandibular glands. These results suggested that gap junctions play an important role in the modulation of fluid secretion from the rat mandibular glands and this was probably due to the inhibition of $Ca^{2+}$ influx through the plasma membrane $Ca^{2+}$ channels.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.51-69
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• 2020

Now, it is a stylized fact that a small number of technology firms such as Apple, Alphabet, Microsoft, Amazon, Facebook and a few others have become larger and dominant players in an industry. Coupled with the rise of these leading firms, we have also observed that a large number of young firms have become an acquisition target in their early IPO stages. This indeed results in a sharp decline in the number of new entries in public exchanges although a series of policy reforms have been promulgated to foster competition through an increase in new entries. Given the observed industry trend in recent decades, a number of studies have reported increased concentration in most developed countries. However, it is less understood as to what caused an increase in industry concentration. In this paper, we uncover the mechanisms by which industries have become concentrated over the last decades by tracing the changes in industry concentration associated with a firm's status change in its early IPO stages. To this end, we put emphasis on the case in which firms are acquired shortly after they went public. Especially, with the transition to digital-based economies, it is imperative for incumbent firms to adapt and keep pace with new ICT and related intelligent systems. For instance, after the acquisition of a young firm equipped with AI-based solutions, an incumbent firm may better respond to a change in customer taste and preference by integrating acquired AI solutions and analytics skills into multiple business processes. Accordingly, it is not unusual for young ICT firms become an attractive acquisition target. To examine the role of M&As involved with young firms in reshaping the level of industry concentration, we identify a firm's status in early post-IPO stages over the sample periods spanning from 1990 to 2016 as follows: i) being delisted, ii) being standalone firms and iii) being acquired. According to our analysis, firms that have conducted IPO since 2000s have been acquired by incumbent firms at a relatively quicker time than those that did IPO in previous generations. We also show a greater acquisition rate for IPO firms in the ICT sector compared with their counterparts in other sectors. Our results based on multinomial logit models suggest that a large number of IPO firms have been acquired in their early post-IPO lives despite their financial soundness. Specifically, we show that IPO firms are likely to be acquired rather than be delisted due to financial distress in early IPO stages when they are more profitable, more mature or less leveraged. For those IPO firms with venture capital backup have also become an acquisition target more frequently. As a larger number of firms are acquired shortly after their IPO, our results show increased concentration. While providing limited evidence on the impact of large incumbent firms in explaining the change in industry concentration, our results show that the large firms' effect on industry concentration are pronounced in the ICT sector. This result possibly captures the current trend that a few tech giants such as Alphabet, Apple and Facebook continue to increase their market share. In addition, compared with the acquisitions of non-ICT firms, the concentration impact of IPO firms in early stages becomes larger when ICT firms are acquired as a target. Our study makes new contributions. To our best knowledge, this is one of a few studies that link a firm's post-IPO status to associated changes in industry concentration. Although some studies have addressed concentration issues, their primary focus was on market power or proprietary software. Contrast to earlier studies, we are able to uncover the mechanism by which industries have become concentrated by placing emphasis on M&As involving young IPO firms. Interestingly, the concentration impact of IPO firm acquisitions are magnified when a large incumbent firms are involved as an acquirer. This leads us to infer the underlying reasons as to why industries have become more concentrated with a favor of large firms in recent decades. Overall, our study sheds new light on the literature by providing a plausible explanation as to why industries have become concentrated.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.