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Background: Data on the association between coronavirus disease 2019 (COVID-19) and thyroid have been reported, including overt thyrotoxicosis and suppression of thyroid function. We aimed to evaluate the thyroid hormone profile and its association with the prognosis of COVID-19 in Korean patients.Methods: The clinical data of 119 patients with COVID-19, admitted in the Myongji Hospital, Goyang, South Korea, were retrospectively evaluated. The thyroid hormone profiles were analyzed and compared based on disease severity (non-severe disease vs. severe to critical disease). Clinical outcomes were analyzed according to the tertiles of thyroid hormones.Results: Of the 119 patients, 76 (63.9%) were euthyroid, and none presented with overt thyroid dysfunction. Non-thyroidal illness syndrome was the most common manifestation (18.5%), followed by subclinical thyrotoxicosis (14.3%) among patients with thyroid dysfunction. Thyroid stimulating hormone (TSH) and triiodothyronine (T3) levels were significantly lower in patients with severe to critical disease than in those with non-severe disease (P1.00 ng/mL) T3 tertiles (P

Technological convergence among different industries is an important source of innovation and economic growth. In this study, we propose a new framework for predicting patterns of technological convergence in two different industries. We first construct an inter-process communication co-occurrence network based on association rule mining. We then use a machine learning approach with various link prediction indices to predict future technological convergence patterns. Next, we use latent Dirichlet allocation (LDA) topic modeling to identify the keywords associated with technologies that are predicted to converge. We apply our proposed framework to a dataset of patents from the United States Patent and Trademark Office from 2012 to 2014 in the fields of chemical engineering and environmental technology. The empirical analysis results show that the prediction over a 4-year time interval using the random forest model achieves the highest performance. Moreover, the LDA topic modeling results indicate that the keywords “membrane,” “air,” “separation,” “catalyst,” “gas,” “exhaust,” and “particle” are descriptions of technologies that are likely to converge. This study is expected to contribute to technological and economic growth by predicting new technological fields that are likely to emerge in the future, and hence the directions that firms focusing on technological advancement should prepare for.

Background: Whether hyperthyroidism is an independent risk factor for cardiovascular events remains controversial. We aimed to evaluate the association of overt and subclinical hyperthyroidism with the risk of ischemic heart disease (IHD), stroke, heart failure, and cardiovascular mortality.Methods: Studies regarding the association between hyperthyroidism and cardiovascular events were searched on PubMed and Embase databases. The cardiovascular disease (CVD) risk was classified as high and low, based on pre-existing diseases, including history of coronary, cerebral, or peripheral artery disease; heart failure; atrial fibrillation; diabetes mellitus; or chronic kidney disease.Results: Thirty-seven cohort studies were included in this meta-analysis. The pooled hazard ratio for subjects with overt hyperthyroidism compared with the control group was 1.11 (95% confidence interval [CI], 1.03 to 1.19) for IHD, 1.35 (95% CI, 1.03 to 1.75) for stroke, and 1.20 (95% CI, 1.00 to 1.46) for cardiovascular mortality. For subjects with subclinical hyperthyroidism, the pooled hazard ratio was 1.24 (95% CI, 1.07 to 1.45) for IHD, when compared with the control group. Subgroup analysis by CVD risk showed that the risk of stroke in overt hyperthyroidism was increased in the low CVD risk group; however, these association was not observed in the high CVD risk group. Similarly, the risk of IHD in subjects with subclinical hyperthyroidism was significantly increased in the low CVD risk group.Conclusion: Overt hyperthyroidism is associated with increased risk of IHD, stroke, and cardiovascular mortality, and subclinical hyperthyroidism is associated with increased risk of IHD. These associations were particularly observed in the low risk CVD group without underlying CVD.

Predicting remaining useful life (RUL) is crucial for system maintenance. Condition monitoring makes not only degradation data available for RUL estimation but also categorized health status data for health state identification. However, RUL prediction has been treated as an independent process in most cases even though potential relevance exists with health status detection process. In this paper, we propose a convolution neural network based multi-task learning method to reflect the relatedness of RUL estimation with health status detection process. The proposed method applied to the C-MAPSS dataset for aero-engine unit prognostics supported superior performances to existing baseline models.

Objective This study was designed to investigate whether necroptosis is involved in the pathogenesis of chemoradiation-induced oral mucositis in a murine model and whether 1-palmitoyl-2-linoleoyl-3-acetyl-rac-glycerol (PLAG) ameliorates this disorder. Materials and methods A chemoradiation-induced oral mucositis model was established by treating mice with concurrent 5-fluorouracil (100 mg/kg, i.p.) and head and neck X-irradiation (20 Gy). Phosphate-buffered saline or PLAG (100 mg/kg or 250 mg/kg, p.o.) was administered daily. Body weights were recorded daily, and mice were sacrificed on Day 9 for tongue tissue analysis. Results On Day 9, chemoradiotherapy-treated (ChemoRT) mice had tongue ulcerations and experienced significant weight loss (Day 0:26.18 ± 1.41 g; Day 9:19.44 ± 3.26 g). They also had elevated serum macrophage inhibitory protein 2 (MIP-2) (control: 5.57 ± 3.49 pg/ml; ChemoRT: 130.14 ± 114.54 pg/ml) and interleukin (IL)-6 (control: 198.25 ± 16.91 pg/ml; ChemoRT: 467.25 ± 108.12 pg/ml) levels. ChemoRT-treated mice who received PLAG exhibited no weight loss (Day 0:25.78 ± 1.04 g; Day 9:26.46 ± 1.68 g) and had lower serum MIP-2 (4.42 ± 4.04 pg/ml) and IL-6 (205.75 ± 30.41 pg/ml) levels than ChemoRT-treated mice who did not receive PLAG. Tongue tissues of mice who received PLAG also displayed lower phosphorylation levels of necroptotic signalling proteins. Conclusion 1-Palmitoyl-2-linoleoyl-3-acetyl-rac-glycerol mitigated chemoradiation-induced oral mucositis by modulating necroptosis.

Outbreaks of emerging viral pathogens like severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are a major medical challenge. There is a pressing need for antivirals that can be rapidly deployed to curb infection and dissemination. We determined the efficacy of interferon lambda-1 (IFN-λ) as a broad-spectrum antiviral agent to inhibit SARS-CoV-2 infection and reduce pathology in a mouse model of disease. IFN-λ significantly limited SARS-CoV-2 production in primary human bronchial epithelial cells in culture. Pretreatment of human lung cells with IFN-λ completely blocked infectious virus production, and treatment with IFN-λ at the time of infection inhibited virus production more than 10-fold. To interrogate the protective effects of IFN-λ in response to SARS-CoV-2 infection, transgenic mice expressing the human angiotensin-converting enzyme 2 (ACE-2) were tested. One dose of IFN-λ administered intranasally was found to reduce animal morbidity and mortality. Our study with SARS-CoV-2 also revealed a sex differential in disease outcome. Male mice had higher mortality, reflecting the more severe symptoms and mortality found in male patients infected with SARS-CoV-2. The results indicate that IFN-λ potentially can treat early stages of SARS-CoV-2 infection and decrease pathology, and this murine model can be used to investigate the sex differential documented in COVID-19. IMPORTANCE The COVID-19 pandemic has claimed millions of lives worldwide. In this report, we used a preclinical mouse model to investigate the prophylactic and therapeutic value of intranasal IFN-λ for this acute respiratory disease. Specific vaccines have been responsible for curbing the transmission of SARS-CoV-2 in developed nations. However, vaccines require time to generate and keep pace with antigenic variants. There is a need for broad-spectrum prophylactic and therapeutic agents to combat new emerging viral pathogens. Our mouse model suggests IFN-λ has clinical utility, and it reflects the well-documented finding that male COVID-19 patients manifest more severe symptoms and mortality. Understanding this sex bias is critical for considering therapeutic approaches to COVID-19.

Background Phosphodiesterase type 5 inhibitors restore nitric oxide signaling, that plays a significant role in erectile function, and appears to counteract insulin resistance in animal and human models. This study was aimed to evaluate the glycemic and metabolic effects of low-dose tadalafil once daily in patients with type 2 diabetes and erectile dysfunction. Methods A 6-month, randomized, double-blind, placebo-controlled pilot trial was conducted. Eligible patients were randomly assigned in a ratio of 2:1 to the tadalafil 5 mg and placebo groups; all patients received either tadalafil or placebo once a day. The primary efficacy endpoint was the absolute change in glycated hemoglobin (HbA1c) levels during the 6-month study period. The secondary efficacy endpoints included metabolic parameters and erectile function. Results Of the 68 patients who completed this study, 45 and 23 patients were allocated to the tadalafil and placebo groups, respectively. The mean HbA1c level was significantly different between the groups over the 6-month study period (P = 0.021). After 6 months of treatment, the HbA1c decrement in the tadalafil group was greater than that in the placebo group (− 0.14 ± 0.53% vs. 0.20 ± 0.69%, P = 0.030). The International Index of Erectile Function-5 scores improvement was significantly greater in the tadalafil group than in the placebo group at 6 months (P = 0.003). Conclusion This prospective pilot study showed that low-dose tadalafil administered once a day was effective in improving glycemic control and erectile function in patients with type 2 diabetes and erectile dysfunction. Trial registration KCT0005666

BackgroundAlthough hypothyroidism is associated with various comorbidities, its relationship with increased all-cause mortality remains controversial. The aim of this nationwide retrospective cohort study was to investigate whether hypothyroid patients treated with levothyroxine had increased mortality compared to controls.MethodsHypothyroid subjects were identified through the Korean National Health Insurance Service Claims database between 2008 and 2017. Hypothyroidism in this study was defined as overt hypothyroidism treated with long-term prescription of levothyroxine (>6 months). After 1:3 age-, sex- and index year-matching, 501,882 patients with newly diagnosed hypothyroidism and 1,505,646 controls without hypothyroidism were included.ResultsDuring a mean follow-up of 6 years, 25,954 (5.2%) hypothyroid patients and 59,105 (3.9%) controls died. Hypothyroidism was significantly associated with increased all-cause mortality (adjusted hazard ratio [HR], 1.14; 95% confidence interval [CI] 1.12–1.16) even with levothyroxine treatment. When stratified by age, sex, and cardiovascular disease risk, independent associations between hypothyroidism and mortality remained significant in all subgroups. The risk of mortality was higher in the < 65 age group (HR: 1.25, 95% CI: 1.22–1.29), men (HR: 1.28, 95% CI: 1.25–1.31), and the high cardiovascular disease risk group (HR: 1.31, 95% CI: 1.29–1.34). The mortality rate of hypothyroid patients was highest within 1 year of treatment and decreased with time.ConclusionThis nationwide, population-based cohort study showed that all-cause mortality was significantly higher in levothyroxine-treated hypothyroid patients than in non-hypothyroid controls. This association remained significant regardless of age, sex, and cardiovascular disease risk.

This study presents financial network indicators that can be applied to global stock market investment strategies. We propose to design both undirected and directed volatility networks of global stock market based on simple pair-wise correlation and system-wide connectedness of national stock indices using a vector auto-regressive model. We examine the effect and usefulness of network indicators by applying them as inputs for determining strategies via several machine learning approaches (logistic regression, support vector machine, and random forest). Two strategies are constructed considering stock price indices: (1) global stock market prediction strategy and (2) regional allocation strategy for developed market/emerging market. According to the results of the performance analysis, network indicators were proven to be important supplementary indicators in predicting global stock market and regional relative directions (up/down). In particular, these indicators were more effective during market crisis periods. This study is the first attempt to construct strategies for global portfolio management using financial network indicators and to suggest how network indicators can be used in practical fields.

User-centered innovation has attracted considerable interest for exploiting emerging business ideas. We suggest a novel framework for discovering emerging business ideas and their combination with user-centered innovation in the software industry based on design thinking processes. We apply topic modeling to projects on Kickstarter which is one of the largest crowdfunding platforms in the world. We adopt conjoint analysis to find which topics are most preferred upon the platform in terms of the amount of funding that they have received. From our findings, the convergence of smart assistant services with various domains, such as tutoring mathematics and seeking job opportunities, is recommended as an emerging idea for software businesses. We also find that the ideas preferred in the US are different from those preferred in other countries. Our findings can be exploited effectively for decision support in establishing a new business model. Finally, this study contributes to discovering emerging business ideas by connecting user-centered innovation with a design thinking perspective.

3D printing content, which has been increasingly shared through the open communities over the last decade, has both aesthetic and functional features. There has been growing concern over whether current licensing policies provide sufficient options for contributors to the open communities. To suggest a direction for alternative license options, it is necessary to understand contributors’ license preferences for sharing diverse 3D printing content. Using a logit model based on information collected from Thingiverse, this study investigates the relationship between the various features of 3D printing content and contributors’ choices among the Creative Commons licenses currently available. The result indicates that preferences are clearly distinguished by the features of the content, whether the content is functional or non-functional in nature. However, there is no significant difference, in terms of license choice, for the numerous 3D printing content items that contain both functional and non-functional features. This result implies that there is a deficiency in the current licenses that cover 3D printing content. Implications for future license policies are discussed.

Background: Few small-scale studies have reported a genetic and familial predisposition in Hashimoto's thyroiditis (HT), however, quantified familial risk estimates from population-level data are u...

The growing risk of accidental radiation exposure due to increased usage of ionizing radiation, such as in nuclear power, industries and medicine, has increased the necessity for the development of radiation countermeasures. Previously, we demonstrated the therapeutic potential of the acetylated diacylglycerol, 1-palmitoyl-2-linoleoyl-3-acetyl-rac-glycerol (PLAG), as a radiation countermeasure by mitigating radiation-associated mortality and hematopoietic acute radiation syndrome (H-ARS) in BALB/c mice after a lethal dose (LD70/30) of gamma-ray total-body irradiation (TBI). In this study, we show that PLAG mitigates symptoms of H-ARS, as characterized by mature blood cell recovery and restoration of bone marrow cellularity, by regulating systemic inflammation. Log-rank test demonstrated that high levels of WBCs, lymphocytes and neutrophils on day 10 post-TBI resulted in significantly improved survival rate. PLAG significantly enhanced the nadir values of all major blood cell types as well as bone marrow cellularity. A single TBI at LD70/30 induced an immediate increase in the blood levels of CXCL1 (12.5 fold), CXCL2 (1.5 fold), IL-6 (86.9 fold), C-reactive protein (CRP; 1.3 fold) and G-CSF (15.7 fold) at 6 h post-TBI, but the cytokine levels returned to baseline level afterward. When the irradiated mice started to die around 15 days post-TBI, they exhibited a second surge in blood levels of CXCL1 (49.3 fold), CXCL2 (87.1 fold), IL-6 (208 fold), CRP (3.6 fold) and G-CSF (265.7 fold). However, PLAG-treated groups showed a significant decrease in these same blood levels (P < 0.001). Considering the inverse correlation between inflammatory cytokine levels and hematological nadirs, PLAG exerts its therapeutic effects on H-ARS by regulating inflammatory cytokine production. These data suggest that PLAG has high potential as a radiation countermeasure to mitigate H-ARS after accidental exposure to radiation.

Although deep learning exhibits advantages in various applications involving multimodal data, it cannot effectively solve the class-imbalance problem. Herein, we propose a hybrid neural network with a cost-sensitive support vector machine (hybrid NN-CSSVM) for class-imbalanced multimodal data. We used a fused multiple-network structure obtained by extracting the features of different modality data, and used cost-sensitive support vector machines (SVMs) as a classifier. To alleviate the insufficiency of learning from minority-class data, our proposed cost-sensitive SVM loss function reflects different weights of misclassification errors from both majority and minority classes, by controlling cost parameters. Additionally, we present a theoretical setting of the cost parameters in our model. The proposed model is validated on real datasets that range from low to high imbalance ratios. By exploiting the complementary advantages of two architectures, the hybrid NN-CSSVM performs excellently, even with data having a minor-class proportion of only 2%.

The effectiveness of chemotherapy and radiotherapy to treat lung cancer is limited because of highly metastatic nature. Novel strategies and drugs to attenuate metastatic activity are urgently required. In this study, red fluorescence proteins (RFP)-labeled A549 human lung cancer cells were orthotopically implantation, where they developed primary tumors. Metastasis in brain and intestines were reduced by up to 80% by treatment with 100 mpk 1-palmitoyl-2-linoleoyl-3-acetyl-rac-glycerol (PLAG) compared with that in control mice. PLAG treatment also reduced the migration of the primary tumors. Interestingly, substantial neutrophil infiltration was observed in the tumors in control mice. The neutrophil contribution to A549 cell metastatic activity was examined in in vitro co-culture system. Metastatic activity could be achieved in the A549 cells through epidermal growth factor receptor (EGFR) transactivation mediated by protease activating receptor 2 (PAR2) receptor. Neutrophil elastase secreted from tumor-infiltrating neutrophils stimulated PAR2 and induced EGFR transactivation. However, this transactivation was inhibited by inducing PAR2 degradation following PLAG treatment and metastatic activity was effectively inhibited. PLAG attenuated cancer metastatic activity via modulated PAR2/EGFR transactivation by accelerating PAR2 degradation. These results suggest PLAG as potential therapeutic agent to combat tumor metastasis via regulating the activation signal pathway of PAR2 by tumor infiltrate-neutrophils.

Background: Hyperthyroidism is associated with various cardiovascular risk factors. However, the relationship between hyperthyroidism and myocardial infarction (MI) or stroke has not been fully elu...

As global environmental problems are worsening, the efficiency of storage systems for renewable energy are gaining importance. The redox flow battery (RFB), a promising energy storage system (ESS), is a device that generates or stores electricity through reduction&ndash, oxidation reactions between active materials constituting electrolytes. Herein, we proposed a flow frame design that reduces flow resistance in the flow path and causes uniform flow distribution in the electrode to develop an efficient redox flow battery. Through computational fluid dynamics (CFD) and experimental verification, we investigated the flow characteristics and flow uniformity inside the conventional redox flow battery cell. An analysis of the flow characteristics of the conventional flow frame revealed a non-uniform distribution of the flow discharged to the electrodes, owing to the complex (branched) flow path geometry of the inlet channel. To address this problem, we proposed a new flow frame design that removed and integrated bifurcations in the flow path. This new design significantly improved flow uniformity parameters, such as the symmetry coefficient (), variability range coefficient (), and maximum flow rate deviation (). Ultimately, we decreased the pressure drop by 15.3% by reducing the number of flow path bifurcations and chevron repositioning.

Many green technologies have been invented to prevent CO2 emission. But the alarming increased in CO2 emissions in the last half-century can also induce the advancement of green technology. In order to evaluate the effect of changes in CO2 emissions on green R&D investment and the generation of related patents, a new logarithmic mean Divisia index (LMDI) decomposition method is proposed. The method identifies the effect of CO2 changes on patent applications via R&D investment using the following six factors: production, energy intensity, fuel mix, CO2 emission coefficient, R&D reaction, and R&D efficiency. Using the data from 2004 to 2012, we apply the proposed method to the four countries (France, Germany, Italy, and the United Kingdom) in order to compare the main factors driving green patent applications in each country. The findings provide insight for effective generation of green technology patents.

5-Fluorouracil (5-FU) is an antimetabolite chemotherapy widely used for the treatment of various cancers. However, many cancer patients experience hematological side effects following 5-FU treatment. Here, we investigated the protective effects of 1-palmitoyl-2-linoleoyl-3-acetyl-rac-glycerol (PLAG) as a mitigator against 5-FU-induced hematologic toxicity, including neutropenia, monocytopenia, thrombocytopenia, and thrombocytosis, in Balb/c mice injected with 5-FU (100 mg/kg, i.p.). Administration of PLAG significantly and dose-dependently reduced the duration of neutropenia and improved the nadirs of absolute neutrophil counts (ANCs). Moreover, while the ANCs of all mice in the control fell to the severely neutropenic range, none of the mice in the PLAG 200 and 400 mg/kg-treated groups experienced severe neutropenia. Administration of PLAG significantly delayed the mean first day of monocytopenia and reduced the duration of monocytopenia. PLAG also effectively reduced extreme changes in platelet counts induced by 5-FU treatment, thus preventing 5-FU-induced thrombocytopenia and thrombocytosis. PLAG significantly decreased plasma levels of the chemokine (C&ndash, X&ndash, C motif) ligand 1 (CXCL1), CXCL2, interleukin (IL)-6, and C-reactive protein (CRP), which were elevated consistently with the occurrence time of neutropenia, monocytopenia, and thrombocytopenia. When compared with olive oil and palmitic linoleic hydroxyl glycerol (PLH), only PLAG effectively mitigated 5-FU-induced hematological toxicity, indicating that it has a distinctive mechanism of action. In conclusion, PLAG may have therapeutic potential as a mitigator for 5-FU-induced neutropenia and other hematological disorders.

Spatial accessibility to public transit changes with population shifts during the day in association with time-varying transit supply levels. In this study, we propose a strategy for the utilization of mobile phone-based floating population data to measure the accessibility to public transit. We used the Huff model-based, floating catchment area method to measure the time-varying accessibility in Seoul, Korea, during rush-hours and late night hours. We compared the floating population-based access measures with the census data for these hours. Our results imply that utilization of the phone-based floating population data can provide reliable and fine-grained results in cases of evening rush hour and late night hours. Therefore, it can replace static census data typically used for the estimation of the accessibility index.

Background: There are limited side effects with ICI therapy such as not responding or reduced therapeutic effect caused by its tolerance. In particular, adenosine-induced tumor progression and drug adaptability are the obstacles in use of ICI therapy. Removing adenosine around the tumor is a prerequisite factor of improving the effect of ICI therapy along with suppression of tumor progression. Methods: To investigate the anti-tumor effect of PLAG with the PD-1 antibody (aPD-1), the syngeneic model was used (n=6/group). LLC-1 lung carcinoma cells were implanted into the C57BL/6 mice via subcutaneous. PLAG was daily administrated for 4 weeks with or without 5 mpk of aPD-1 (RMP1-14). it was delivered via IP injection biweekly. The adenosine levels and infiltrated immune cell populations in the tumor and blood were analyzed weekly until the sacrifice day. Results: The tumor size decreased by 23%/65%/81% in a dose-dependently compared to the positive control. Especially, the tumor completely disappeared in 1 animal in treated with aPD-1 and 50 mpk of PLAG, and the 2 animals in treated with 100 mpk. The adenosine levels of blood and tumor burden in the PLAG-treated group decreased by more than 50% compared to the positive control group. It was also confirmed that the adenosine level was about 25% lower in the PLAG-treated group compared to the aPD-1 alone. We found that the expression of A2B receptor in the tumor was significantly reduced in PLAG-treated group. Interestingly, the tumor growth inhibitory effect of PLAG was about 23% better than MRS1754, an A2B receptor antagonist. MRS1754-treated group showed significantly high adenosine level in the blood and tumor, whereas, in the PLAG-treated group, similar adenosine level in blood was continuously maintained as the negative control and its level in the tumor was decreased compared to the positive control. Increasing cancer cell growth and adenosine secretion were shown at 8 h post-treatment of adenosine. PLAG co-treatment decreased the adenosine level by half rapidly and then reduced continuously. In particular, degradation of the A2B receptor was observed after 4 h in PLAG-treated cells. Also intracellular ROS generated during the trafficking of the receptor was elevated within a short period by PLAG and then rapidly decreased at the same time as the signal protein change. PLAG may induce intracellular ROS regulation and A2B receptor degradation through overexpression of αARR. The effect of PLAG disappeared when αARR was knock-down. Conclusion: Extracellular adenosine level of tumor in ICI therapy could be the critical factor to be a successful anticancer treatment. To attenuate adenosine levels, a number of targeted therapies are being developed. Unlike these targeted therapeutics, PLAG fundamentally blocks cancer growth by adenosine clearance. Therefore, PLAG has its own anti-cancer effect and can maximize the effect of ICI therapy. Citation Format: Guen Tae Kim, Sun Young Yoon, Kaapjoo Park, Heesoo Kim, Ki-Young Sohn, Jae Wha Kim. Suppressive effect of PLAG on tumor progression and its synergistic therapeutic effect with ICI therapy through adenosine clearance [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1447.

We examined the overall trends in biometric technology based on patent documents. Using PATSTAT database, we extracted 37,462 patent documents applied at the Big Five patent offices between 1990 and 2016. Latent Dirichlet allocation was applied to their abstracts to observe annual trends by topic. Our results are as follows: Fingerprint-enabled car anti-theft systems have been undergoing rapid technological development since 2014. In response, biometric signal transmitting models are becoming popular owing to concerns about theft of biometric templates. While fingerprint, face, and iris authentication technologies continue to advance, finger vein, voice, and signature authentication technologies are lagging. Use of biometric technologies in financial transactions, server networks, and digital media content security are decreasing as well. A citation analysis discovered key topics and patent applicants: Surprisingly, the quantitative growth rate of topics and the effect on the knowledge network showed an inverse relationship. US firms had the most citations, but fewer backward citations of own work, unlike Japanese companies. We provide practical insights to stakeholders of biometric technology.

Background Distant metastases, although uncommon, represent maximum disease-related mortality in differentiated thyroid carcinoma (DTC). Lungs are the most frequent sites of metastases. We aimed to evaluate long-term outcomes and identify prognostic factors in metastatic DTC limited to the lungs. Methods This retrospective study included 89 patients with DTC and metastases limited to the lungs, who were treated between 1996 and 2012 at Samsung Medical Center. Progression-free survival (PFS) and cancer-specific survival (CSS) rates were evaluated according to clinicopathologic factors. Cox regression analysis was used to identify independent factors associated with structural progressive disease (PD) and cancer-specific death. Results With a median follow-up of 84 months, the 5- and 10-year CSS rates were 78% and 73%, respectively. Older age at diagnosis (≥55 years), radioactive iodine (RAI) nonavidity, preoperative or late diagnosis of metastasis and macro-nodular metastasis (≥1 cm) were predictive of decreased PFS and CSS. Multivariate analysis identified older age (P = .002), RAI nonavidity (P = .045) and preoperative (P = .030) or late diagnosis (P = .026) as independent predictors of structural PD. RAI avidity was also independent predictor of cancer-specific death (P = .025). Conclusion Patients with DTC and metastatic disease limited to the lungs had favourable long-term outcomes. Age, RAI avidity and timing of metastasis were found to be major factors for predicting prognosis.

// Young-Jun Kim 1,* , Jae Min Shin 1,* , Su-Hyun Shin 1 , Joo Heon Kim 2 , Ki-Young Sohn 3 , Heung-Jae Kim 3 , Jong-Koo Kang 4 , Sun Young Yoon 3 and Jae Wha Kim 1 1 Cell Factory Research Center, Division of Systems Biology and Bioengineering, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Republic of Korea 2 Department of Pathology, EulJi University School of Medicine, Daejeon, Republic of Korea 3 Enzychem Lifesciences, Daejeon, Republic of Korea 4 Department of Laboratory Animal medicine, College of Veterinary medicine, Chungbuk National University, Cheongju, Republic of Korea * These authors have contributed equally to this work Correspondence to: Jae Wha Kim, email: // Sun Young Yoon, email: // Keywords : PLAG, collagen-induced arthritis, IL-6, STAT3, neutrophil, Immunology and Microbiology Section, Immune response, Immunity Received : December 05, 2016 Accepted : July 06, 2017 Published : July 19, 2017 Abstract The pathogenesis of rheumatoid arthritis (RA) has been implicated neutrophil extracellular traps (NETs) formation which could generate autoantigen. Neutrophil contributes to initiate and maintain the inflammatory process in the joint. In this study, we show that 1-palmitoyl-2-linoleoyl-3-acetyl-rac-glycerol (PLAG) decreases neutrophil migration by regulating the activity of STAT3, a regulator of IL-6 and MIP-2 expression. PLAG caused a decrease in IL-6 production in the RAW264.7 macrophage cell line and in rheumatoid arthritis–fibroblast-like synoviocytes via the regulation of STAT3 signaling without affecting NF-κB signaling. In a mouse model of collagen-induced arthritis (CIA), arthritic symptoms were recapitulated, with increased IL-6 level in the synovium, and PLAG treatment restored IL-6 to a level comparable to that achieved with commercial therapeutics (such as Remicade or methotrexate). Staining of joint tissue with neutrophil-specific antibody showed that PLAG significantly reduced the infiltration of neutrophils into the joint synovium of CIA mice. The inhibitory effect of PLAG on IL-6/STAT3 or MIP-2 signaling also reduced the migration of differentiated neutrophils in vitro . Therefore, PLAG inhibits the infiltration of destructive neutrophils into inflammatory sites, and can be utilized as a potent therapeutic agent for the treatment of sustained inflammation and joint destruction.

For sustainable and effective innovation, who should own an academic patent obtained as a result of funded research? The issue of ownership can influence the motivation of academic researchers. In this paper, we address this issue from the perspective of engineering graduate students who have experience of RD and patent ownership policies within university. In this paper, we carried out classification tree analyses of preferred ownership categories, using various factors related to ‘researchers and the environment for R&D,’ ‘technology,’ ‘patenting activities,’ ‘sponsors,’ ‘currently existing ownership policy,’ and ‘compensation policy’. Our findings can help design an effective ownership policy that promotes innovation by incorporating the views of students who will be important asset for future innovation.

Taxi vacancy duration is a major efficiency measure for taxi services. A clear understanding of the various factors and their effect on vacancy duration is necessary for the optimal operational management of taxis. Previous research has only dealt with vacancy duration by assuming probability distributions and has not investigated heterogeneity in the data caused by various factors. We develop a parametric duration model using not only new operational characteristics but also variables associated with taxi demand, such as weather, land use, demographics, socioeconomic variables, and accessibility of public transportation. The model is applied to a large-scale New York City (NYC) taxi trip dataset that covers operations for 2013. The results show that all the attributes have significant associations with vacancy duration that follows a log-normal distribution. Our study is expected to help improve the efficiency of taxi operations by decreasing the time spent in vacant states.

This study examines trends in academic research on personal information privacy. Using Scopus DB, we extracted 2356 documents covering journal articles, reviews, book chapters, conference papers, and working papers published between 1972 and August 2015. Latent Dirichlet allocation (LDA) is applied to the abstracts of those extracted documents to identify topics. Topics discovered from all documents focus mainly on technology, and the findings indicate that algorithms, Facebook privacy, and online social networks have become prominent topics. In contrast, it was observed that journal articles put more emphasis on both the e-business and healthcare. These results identify a research gap in the area of personal information privacy and offer a direction for future research.

For consistent and effective CO 2 reduction, many countries need to improve not only the technical efficiency of CO 2 mitigation, but also environmental responsibility. In this study, we examine both the technical efficiency and voluntary environmental consciousness (VEC) of 12 European countries using a two-stage data envelopment analysis (DEA). In the first stage, we measured the technical efficiency of green energy technologies (GET) associated with fossil fuels, renewable energy, and storage technologies of each country for energy generation with regard to CO 2 emissions by surveying GET-related patents. Using the logarithmic mean Divisia index (LMDI), we decomposed CO 2 emissions into the following technological factors: energy intensity, fuel mix, and CO 2 emission coefficient. In the second stage, we quantified the VEC in each country by investigating GET patent changes via research and development (R&D) investment at given changes in CO 2 emissions. The results show different aspects for each country in terms of technical efficiency and VEC, suggesting potential levels of both efficient CO 2 reductions and desirable GET development by using reference countries as a benchmark. Our study methodology and results can contribute to establishing effective national technology policy and aid in calls for common responsibility and the active participation of nations in addressing climate change.

A 74-year-old man presented with recurrent vomiting and aspiration pneumonia in the left lower lobe. He entered the intensive care unit to manage the pneumonia and septic shock. Although a percutaneous endoscopic gastrostomy tube was implanted for recurrent vomiting, vomiting and aspiration recurred frequently during admission. Subsequently, he complained of neck pain when in an upright position. A videofluoroscopic swallowing study showed compression of the esophagus by cervical osteophytes and tracheal aspiration caused by an abnormality at the laryngeal inlet. Cervical spine X-rays and computed tomography showed anterior cervical osteophytes at the C3-6 levels. Surgical decompression was scheduled, but was cancelled due to his frailty. Unfortunately, further recurrent vomiting and aspiration resulted in respiratory arrest leading to hypoxic brain damage and death. Physicians should consider cervical spine disease, such as diffuse skeletal hyperostosis as an uncommon cause of recurrent aspiration pneumonia.

According to property rights theory, national plant genetic resources (PGRs) are sovereign properties rather than resources belonging to the common heritage of humankind. Consequently, provider states can claim compensation from users of their national PGRs, leading to the need for bilateral or multilateral agreements to share national PGRs' commercial benefits. However, as benefit-sharing agreements are made exante, estimating the potential profit is difficult. Thus, issues around asymmetric information about the commercial value of such resources have emerged. In this paper, we use a patent portfolio as a proxy to estimate the potential commercial benefits of national PGRs and propose new evaluation indicators. We propose a comprehensive evaluation process that covers constructing a patent portfolio for each PGR, establishing indicators in terms of marketability, technology, and exclusiveness, and assigning weights to the indicators using fuzzy analytic hierarchy. In addition, we illustrate this process using a case of Korean national PGRs based on the opinions of stakeholders and experts. This research is expected to help promote national PGR transactions with equitable access and benefit sharing agreements.

This study investigated the association of subclinical hypothyroidism (SCH) with metabolic syndrome (MetS) and its components in adolescents. The study population included 1006 adolescents (aged 10–18 years) from the Korea National Health and Nutrition Examination Surveys; SCH subjects were compared with euthyroid subjects. MetS was defined using the International Diabetes Federation criteria. The risks of MetS and its components in SCH and euthyroid subjects were calculated using binary logistic regression analyses. Study subjects had a mean age of 14.2 ± 2.5 years, and 53% were male. The prevalence of MetS was 2.5% in the overall study population (3.2% of males and 1.7% of females). Among the 1006 subjects, 143 (14.2%) had SCH. The risk of MetS was not higher in SCH subjects than in euthyroid subjects (odds ratio [OR], 1.50; 95% confidence interval [CI], 0.54–4.11); however, among the components of MetS, the risk of abdominal obesity was higher in SCH subjects than in euthyroid subjects (OR, 2.08; 95% CI, 1.04–4.15) after adjusting for age, sex, and body mass index (BMI). Although not statistically significant, a trend toward increased risk of elevated blood pressure (BP) was observed in SCH subjects relative to euthyroid subjects after further adjusting for age, sex, and BMI (OR, 2.01; 95% CI, 0.89–4.52). Furthermore, non-obese SCH subjects had higher systolic BP compared with non-obese euthyroid subjects after adjusting for age, sex, and BMI (P = 0.014). SCH was not associated with the presence of MetS. However, SCH may be associated with abdominal obesity and possibly elevated BP in adolescents.

Machine learning models have been actively utilized to quantitatively predict the default probability based on the personal information obtained from loan applicants. Although the relationship between loan applicants is receiving attention as important soft information, only the simple individual network features and their relation have been reflected in the prediction model. In this study, we propose a graph convolutional network (GCN)-based credit default prediction model, which can reflect nonlinear relationships between borrower’s attributes and default risk as well as high-order relationships between the borrowers. Three types of information pertaining to the borrowers are separately employed for their relations, namely loan information, credit history information, and soft information. We compare our GCN model to baseline models using the data from an online peer-to-peer lending platform. The results show that our approach outperforms existing classification models and identifies the relative contribution of input attributes.

As the demand for electrical energy increases worldwide, the amounts of harmful gases in the atmosphere, such as carbon dioxide released by burning fossil fuel, are continuously increasing. As a result, the interest in renewable energy resources has been growing. However, renewable energies have fluctuating output characteristics according to local conditions such as the natural environment and geographical characteristics, which is a major factor deteriorating output quality. Recently, energy storage systems (ESSs) have been actively studied as a solution to this problem. A redox flow battery (RFB) is a system in which an active material dissolved in an electrolyte is oxidized/reduced to charge/discharge. A RFB mainly consists of an electrolyte tank, which determines the capacity, and a cell stack, which determines the output. As these components can be independently controlled, a RFB provides the advantages of a large capacity and a long lifespan. In this study, a new flow channel was designed to maximize the reaction area and reduce the pump loss to improve RFB performance. Computational fluid dynamics (CFD) and visualization experiments were used to analyze the internal flow characteristics of vanadium redox flow battery (VRFB). Additionally, we used the variability range coefficient and maximum velocity deviation to check if the flow discharged to the electrode was uniform. In the conventional flow frame, the flow discharged to the electrode has a non-uniformity distribution in the left and right, due to the S-shaped path of the inlet channel. In addition, it was confirmed that the outlet area into the electrode was reduced to 50%, resulting in a high pressure drop. To address this problem, we proposed a design that simplified the flow channel, which significantly improved flow uniformity parameters. The maximum velocity deviations for the existing and new flow channels were 11.89% and 54.16%, respectively. In addition, in the entire flow frame for the new flow channel, the pressure drop decreased by 44% as compared with the existing flow channel.

OBJECTIVE The aim of this study was to confirm the equivalent efficacy of recombinant human TSH (rhTSH) and thyroid hormone withdrawal (THW) as used in the preparation for low-dose and high-dose radioactive iodine (RAI) ablation in Korean patients with differentiated thyroid carcinoma. SUBJECTS AND METHODS This retrospective study was designed to compare the efficacy of rhTSH and THW when used before ablation with low-dose (30 mCi) and high-dose (100 mCi) RAI, respectively. The study group included 570 patients with DTC with tumors staged T1 to T3, N0 to N1, and M0. Before RAI ablation, 190 patients used rhTSH and 380 patients matched by age, sex, T-stage, and N-stage used THW. The success of ablation was evaluated in each group based on 4 criteria: (1) stimulated thyroglobulin (sTg)

Background Autologous progenitor cell therapy comprising granulocyte-colony stimulating factor (G-CSF) for mobilization of bone-marrow derived progenitor cells (BMPCs) into peripheral blood and inhibition of dipeptidylpeptidase-IV by sitagliptin for enhanced myocardial recruitment of circulating BMPCs has been shown to improve survival after acute myocardial infarction (MI) in preclinical studies. In the SITAGRAMI trial we found that during short-term follow-up G-CSF plus sitagliptin (GS) failed to show a beneficial effect on cardiac function and clinical events in patients with acute MI that underwent successful PCI. The objective of the present analysis was to assess the impact of GS versus placebo treatment on long-term clinical outcomes of the SITAGRAMI trial patient population. Methods In the randomized, prospective, double-blind, placebo-controlled SITAGRAMI trial, 174 patients with acute MI were assigned to GS or placebo in a 1:1 ratio. The primary outcome for the present long-term analysis was the composite of death, MI or stroke on long-term follow-up. Results The median [IQR] follow-up duration was 4.50 [3.56–5.95] years. The primary outcome occurred in 12.8% of patients assigned to placebo and 9.2% assigned to GS (HR 0.69, 95% CI 0.28–1.69; p=0.42). The incidence of the combined cardiovascular outcome was 47.7% in the placebo- and 41.4% in the GS-group (HR 0.75, 95% CI 0.48–1.18; p=0.21). Overall, there was no significant difference in MACCE rates between both treatment groups (p=0.41). Conclusion These long-term follow-up data indicate that GS therapy does not improve clinical outcomes of patients with acute MI.

In recent years, many technologies are converging with information and communication technology (ICT) while several of them are being standardized. In this study, we identify technological convergence in standards related to ICT. We apply the concepts of entropy and gravity, social network analysis, and association rule analysis to the International Patent Classification (IPC) codes of patents that have been declared as essential in the European Telecommunications Standards Institute. Results from our study show the technology fields that have played a major role in technological convergence in standards. In addition, other technology fields that are linked with these important technology fields are identified. During the period 2010–2014, services or facilities specially adapted for wireless communication networks had the highest entropy value and the highest binding force; and visible signaling systems were associated with several technology fields having a high potential to converge with other technology fields. Our findings can contribute to R&D planning for essential patents by suggesting potential technology fields that play a crucial role in technological convergence in related standards and other technological fields that are linked with these potential fields.

Distant metastases uncommonly occur in differentiated thyroid carcinoma (DTC), but they are a frequent cause of thyroid cancer-related death. Genomic alterations in metastatic tumors, and the relationship with their corresponding primary tumors in DTC, are poorly understood. The objective of this study was to investigate whether genetic alterations in primary tumors are concordant with distant metastases in DTC patients.Surgical samples from primary and matched distant metastatic tumor pairs from 17 DTC patients, and three additional unpaired metastatic tumors from two patients, were analyzed using targeted next-generation sequencing (Ion Torrent Ampliseq cancer panel) with a focus on known recurrent somatic mutations in thyroid cancer. Additionally, TERT promoter mutations were assessed by direct sequencing.BRAF mutations were found in 8/10 patients with papillary thyroid carcinoma (PTC). A NRAS mutation was detected in one patient with follicular variant PTC. TERT promoter mutations were detected in 8/10 patients with PTC, and most were coexistent with a BRAF mutation (7/8 BRAF-positive PTC patients, and one BRAF-negative PTC patient). In follicular thyroid carcinoma, NRAS was the most frequently observed mutation (4/9 patients), followed by HRAS (two patients) and KRAS (one patient). TERT promoter mutations were found in 6/7 RAS-positive follicular thyroid carcinoma patients. Key somatic alterations such as BRAF and RAS mutations were highly concordant between primary and matched metastatic tumors without discrepancies. The BRAF or RAS mutant allelic frequency was higher in matched metastatic tumors than in the corresponding primary tumors (35% vs. 25% for BRAF mutation, p = 0.04; and 40% vs. 34% for RAS mutation, p = 0.002). TERT promoter mutations were also mostly concordant in matched tumors (concordance rate 93%).BRAF, RAS, and TERT mutations are highly prevalent in metastatic DTC, and are concordant between primary and metastatic DTC. This high concordance suggests that primary tumors may reflect the key somatic alterations in matched metastatic DTC. Frequent coexistent TERT promoter and BRAF or RAS mutations in metastatic DTC also suggests its important role in the progression of DTC.

Unmanned aerial vehicle (UAV) technologies have been fast developing over the past 20 years and are expected to generate extensive spillovers into other industry sectors. However, no previous studies have investigated such spillover effects. In this study, we propose the framework of two-mode network analysis to quantify the spillover effects of UAV technology into various industries using patent citation data of the United States Patent and Trademark Office. A two-mode matrix consists of rows corresponding to UAV technologies and columns corresponding to beneficiary industries, and the value depicts the spillover probability obtained using International Patent Classification codes and the technology/industry concordance table. The out- and in-degree centralities of the spillover network are used to identify strong spillover-generating UAV technologies and strong spillover-receiving industries, respectively. We observed that the weapon industry received extensive spillover effects during the period 2005–2009. Based on Mann–Kendall tests, the spillover effects of UAV-related software technologies exhibited a consistently upward trend during both the last 10 and 20 years. The past significant trend of spillovers can help us to forecast future trends. The proposed quantification method can be readily applied to investigate other specific technology–industry spillover patterns.

Washing machine manufacturers typically advise consumers to maintain the relative humidity in the drum less than 80% for three days after the termination of a washing cycle in order to prevent bacteria proliferation. A vent installed in the back of a washing machine is used to release moisture to satisfy this condition. Up to now, the design and installation of the vent have been based on experiments without understanding its roles and physical phenomena. In this study, various CFD results are presented in order to explain the physical mechanism of moisture release in a washing machine. Two methods of moisture release (diffusion and convection) were studied; diffusion was found to be the dominant process in removing moisture. Experiments were also performed to validate this behavior. In addition, this study will aid in the efficient design of vents to keep the relative humidity low inside the drum.

Several citation-based indicators, including patent h-index, have been introduced to evaluate the patenting activities of research organizations. However, variants developed to complement h-index have not been utilized yet in the domain of intellectual property management. The main purpose of this study is to propose new indices that can be used to evaluate the patenting activities of research and development (R&D) organizations, based on h-type complementary variants along with traditional indicators. Exploratory factor analysis (EFA) is used to identify those indices. By applying the proposed framework to pharmaceutical R&D organizations, which have their patents registered in the United States Patent Trademark Office (USPTO), the following three indices are obtained: the forward citation, impact per unit time, and patent family factors. The ranking obtained from the new indices can represent the productive capacity of the qualified patent, patent commercialization speed, and patent commercialization effort of research organizations. The new proposed indices in this study are expected to contribute to the evaluation of the patenting activities of R&D organizations from various perspectives.

Objectives : The aim of this study was to identify the effect of employment type on health-related quality of life. Methods : This study used data from the Sixth Korea National Health and Nutrition Examination Survey. Data were analyzed with the test, t-test, ANOVA and multiple regression. Results : There were significant statistical differences the health-related quality of life according to employment type. The health-related quality of life of temporary workers was lower than that of regular workers. The significant predictors of the health-related quality of life of regular workers were the subjective health status, stress, age, and education. The significant predictors of the health-related quality of life of temporary workers were the subjective health status, education, stress, sleeping time, and gender. Conclusions : These results suggest that employment type affects the health-related quality of life. The research on social policy is recommended to resolve health inequalities.

The Global Innovation Index (GII) was proposed to observe the innovation capability and efficiency levels of individual countries using input and output factors. However, it does not consider potential structural relationships among factors affecting the innovation performance of a country. In this study, we proposed a structural equation model (SEM) based on the hypothesised national innovation structure among seven factors representing inputs (institution, human capital and research, infrastructure, market sophistication, and business sophistication) and outputs (knowledge and technology outputs, and creative outputs). Using GII data from 2013, we discovered that business sophistication and infrastructure have the strongest direct and indirect effects on creative output, respectively. In addition, a new ranking is obtained based on the fitted SEM. We provide feedback information to improve innovation capabilities.

Understanding technology convergence became crucial for pursuing innovation and economic growth. This paper attempts to predict the pattern of technology convergence by jointly applying the Association Rule and Link Prediction to entire IPCs related to triadic patents filed during the period from 1955 to 2011. We further use a topic model to discover emerging areas of the predicted technology convergence. The results show that the medical area is in the center of convergence, and we predict that technologies for treating respiratory system/blood/sense disorders are associated with the technologies of genetic engineering/peptide/heterocyclic compounds. After eliminating the majority of convergence, we found the convergence pattern among activating catalysts, printing, advanced networking, controlling devices, secured communication with in-memory system, television system with pattern recognition, and image processing and analyzing technologies. The results of our study are expected to contribute to firms that seek new innovative technological domain.

An essential concept in technology management is the early detection of valuable patents. Traditional classification approaches have been utilized to identify effective patents based on the extracted patent topics and indices. However, they cannot consider detailed contextual information or relatively long word sequences in patent documents. In this study, we propose a patent grade evaluation framework based on a deep learning model that can capture the detailed semantic features of patent text. Therefore, this study adopts both a convolution neural network and bidirectional long short-term memory with structured patent text data consisting of abstracts and claims for the classification of three levels of patent grades measured in terms of the average number of forward citations per annum. We further exploit the patent indices identified in the early stage as additional inputs to the model to increase the accuracy. Our model has realized over 75% precision and recall in identifying top-grade semiconductor patents granted by the USPTO from 2000 to 2015. We anticipate that our deep learning-based framework with patent text and indices will play a significant supporting role in mergers and acquisitions, investment decisions, and corporate planning through the early-stage evaluation of a large number of patents.