Monetary policy document analysis for prediction of monetary policy board decision.

In terms of market capitalization, the bond market is larger than the stock market, and the bond market is affected by macroeconomic indicators. Despite this, there has been relatively little research, making it a good candidate for the use of data mining techniques. In this paper, a novel approach designed to predict the vote results of the Korean Monetary Policy Committee regarding the base interest rate was proposed. To predict sentence sentiment, prior monetary policy decision text was used as input for classification models. The sentence sentiment prediction model showed 83.7% performance when using a support vector machine. In addition, it was observed that the bigrams extracted from documents provided important descriptions of the Korean economy at the time. Finally, the document sentiment of monetary policy decision was calculated using aggregating sentence sentiment, and the vote results were predicted using this sentiment. As a result, when using the support vector machine to predict the Monetary Policy Committee vote results, the performance improved by 29.5% over the baseline model. Statistical tests confirmed whether there is a difference in document sentiments between unanimous and non-unanimous, and the null hypothesis was rejected at a significance level of 5%.

Enhanced Photoluminescence of Crystalline Alq3 Micro-Rods Hybridized with Silver Nanowires.

An enhancement of the local electric field at the metal/dielectric interface of hybrid materials due to the localized surface plasmon resonance (LSPR) phenomenon plays a particularly important role in versatile research fields resulting in a distinct modification of the electrical, as well as optical, properties of the hybrid material. In this paper, we succeeded in visually confirming the LSPR phenomenon in the crystalline tris(8-hydroxyquinoline) aluminum (Alq3) micro-rod (MR) hybridized with silver (Ag) nanowire (NW) in the form of photoluminescence (PL) characteristics. Crystalline Alq3 MRs were prepared by a self-assembly method under the mixed solution of protic and aprotic polar solvents, which could be easily applied to fabricate hybrid Alq3/Ag structures. The hybridization between the crystalline Alq3 MRs and Ag NWs was confirmed by the component analysis of the selected area electronic diffraction attached to high-resolution transmission electron microscope. Nanoscale and solid state PL experiments on the hybrid Alq3/Ag structures using a lab-made laser confocal microscope exhibited a distinct enhancement of the PL intensity (approximately 26-fold), which also supported the LSPR effects between crystalline Alq3 MRs and Ag NWs.

An empirical evaluation of sampling methods for the classification of imbalanced data.

In numerous classification problems, class distribution is not balanced. For example, positive examples are rare in the fields of disease diagnosis and credit card fraud detection. General machine learning methods are known to be suboptimal for such imbalanced classification. One popular solution is to balance training data by oversampling the underrepresented (or undersampling the overrepresented) classes before applying machine learning algorithms. However, despite its popularity, the effectiveness of sampling has not been rigorously and comprehensively evaluated. This study assessed combinations of seven sampling methods and eight machine learning classifiers (56 varieties in total) using 31 datasets with varying degrees of imbalance. We used the areas under the precision-recall curve (AUPRC) and receiver operating characteristics curve (AUROC) as the performance measures. The AUPRC is known to be more informative for imbalanced classification than the AUROC. We observed that sampling significantly changed the performance of the classifier (paired t-tests P < 0.05) only for few cases (12.2% in AUPRC and 10.0% in AUROC). Surprisingly, sampling was more likely to reduce rather than improve the classification performance. Moreover, the adverse effects of sampling were more pronounced in AUPRC than in AUROC. Among the sampling methods, undersampling performed worse than others. Also, sampling was more effective for improving linear classifiers. Most importantly, we did not need sampling to obtain the optimal classifier for most of the 31 datasets. In addition, we found two interesting examples in which sampling significantly reduced AUPRC while significantly improving AUROC (paired t-tests P < 0.05). In conclusion, the applicability of sampling is limited because it could be ineffective or even harmful. Furthermore, the choice of the performance measure is crucial for decision making. Our results provide valuable insights into the effect and characteristics of sampling for imbalanced classification.

Direct Visualization of UV-Light on Polymer Composite Films Consisting of Light Emitting Organic Micro Rods and Polydimethylsiloxane.

We experimentally demonstrate the direct visualization of ultraviolet (UV) light using flexible polymer composite films consisting of crystalline organic tris-(8-hydroxyquinoline) aluminum (Alq3) micro-rods and polydimethylsiloxane (PDMS). The representative organic mono-molecule Alq3, which is a core material of organic light-emitting diodes, was used to detect light in the invisible UV region and visualize photoluminescence (PL). Alq3 shows absorption in the UV region and light-emitting characteristics in the green region, making it an optimal material for UV visualization because of its large Stokes transition. Crystalline Alq3 micro-rods were fabricated in a deionized water solution through a sequential process of reprecipitation and self-assembly. Highly bright photoluminescence was observed on the highly crystalline Alq3 micro-rods under UV light excitation, indicating that the crystalline structures of Alq3 molecules affect the visible emission decay of excitons. The Alq3 micro-rods were manufactured as flexible polymer composite films using a PDMS solution to observe UV photodetector characteristics according to UV intensity, and it was confirmed that the intensity of the fine UV light reaching the earth's surface can be visualized by making use of this UV photodetector.

Antibody Responses to SARS-CoV-2 in Children With COVID-19.

BACKGROUND: The immunologic features of children with coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are not clearly delineated. This study was conducted to evaluate SARS-CoV-2-specific antibody responses in children with COVID-19. METHODS: The levels of anti-spike (S) IgG, anti-SARS-CoV-2 IgG, and neutralizing antibody (NAb) were measured during various time points in children <19 years of age with COVID-19 in South Korea from February 2020 to September 2020. RESULTS: One hundred sixty-five blood samples from 114 children with COVID-19 (43.9% asymptomatic and 56.1% mildly symptomatic) were analyzed. In both asymptomatic and mildly symptomatic children, the positive rates of anti-S IgG, anti-SARS-CoV-2 IgG, and NAb were low within 7 days after onset, but they soon reached 100% 14 to <28 days after onset. In symptomatic children, the geometric mean titers (GMTs) of antibodies were all below the positive cutoff during the first 2 weeks from onset and peaked at 28 to <56 days (5.6 for anti-S IgG, 383.6 for anti-SARS-CoV-2 IgG, and 55.0 for NAb, P < .001, respectively). Antibody levels remained detectable up to 3 months after infection. The antibody GMTs during the period 14 to <56 days after symptom onset were highest in children aged 0-4 years. CONCLUSIONS: These results collectively present the humoral immune responses during SARS-CoV-2 infection in children. A further longitudinal study is needed to thoroughly understand the immune system and for effective vaccine development in children during the COVID-19 pandemic.

Generation of human induced pluripotent stem cell line, KRIBBi003-A, from urinary cells of a patient with glycogen storage disease type IXa.

Glycogen storage disease type IXa (GSD IXa) is a rare genetic disorder characterized by phosphorylase kinase (PhK) deficiency, which leads to excessive glycogen accumulation in the liver. Urinary cells (UCs) were isolated from a GSD IXa patient and reprogrammed into induced pluripotent stem cells (iPSCs) using Sendai virus. The established iPSC line, KRIBBi003-A, exhibited pluripotency marker expression and a normal karyotype. The differentiation capacity of the cell line was confirmed by the differentiation of the three germ layers in vitro. The established iPSC line is a potential useful resource for disease modeling of GSD IXa.

Semi-supervised learning for an improved diagnosis of COVID-19 in CT images.

Coronavirus disease 2019 (COVID-19) has been spread out all over the world. Although a real-time reverse-transcription polymerase chain reaction (RT-PCR) test has been used as a primary diagnostic tool for COVID-19, the utility of CT based diagnostic tools have been suggested to improve the diagnostic accuracy and reliability. Herein we propose a semi-supervised deep neural network for an improved detection of COVID-19. The proposed method utilizes CT images in a supervised and unsupervised manner to improve the accuracy and robustness of COVID-19 diagnosis. Both labeled and unlabeled CT images are employed. Labeled CT images are used for supervised leaning. Unlabeled CT images are utilized for unsupervised learning in a way that the feature representations are invariant to perturbations in CT images. To systematically evaluate the proposed method, two COVID-19 CT datasets and three public CT datasets with no COVID-19 CT images are employed. In distinguishing COVID-19 from non-COVID-19 CT images, the proposed method achieves an overall accuracy of 99.83%, sensitivity of 0.9286, specificity of 0.9832, and positive predictive value (PPV) of 0.9192. The results are consistent between the COVID-19 challenge dataset and the public CT datasets. For discriminating between COVID-19 and common pneumonia CT images, the proposed method obtains 97.32% accuracy, 0.9971 sensitivity, 0.9598 specificity, and 0.9326 PPV. Moreover, the comparative experiments with respect to supervised learning and training strategies demonstrate that the proposed method is able to improve the diagnostic accuracy and robustness without exhaustive labeling. The proposed semi-supervised method, exploiting both supervised and unsupervised learning, facilitates an accurate and reliable diagnosis for COVID-19, leading to an improved patient care and management.

Seroprevalence of scrub typhus, murine typhus and spotted fever groups in North Korean refugees.

OBJECTIVES: The aim of this study was to investigate the seroprevalence of antibodies against scrub typhus, murine typhus and spotted fever groups among North Korean refugees within 1 year of their arrival in South Korea. METHODS: We recruited North Korean refugees who had settled in South Korea after a short stay in a third country and did not have any health problems. The antibody titer was measured using a commercial indirect fluorescence assay immunoglobulin G antibody kit. RESULTS: The seroprevalence of antibodies against scrub typhus, murine typhus, and spotted fever groups among the 99 participants was 22.2%, 17.2%, and 10.1%, respectively, with 8.1% of participants testing positive for both spotted fever and murine typhus. CONCLUSIONS: Refugees may be exposed to rickettsial infections in North Korea and their journey from North Korea. This study is the first to report the seroprevalence of antibodies against the 3 common rickettsial diseases among North Korean refugees. The findings suggest that rickettsial infections should be added to the list of differential diagnoses for North Koreans with fever after entering South Korea.

Modulation of Nogo receptor 1 expression orchestrates myelin-associated infiltration of glioblastoma.

As the clinical failure of glioblastoma treatment is attributed by multiple components, including myelin-associated infiltration, assessment of the molecular mechanisms underlying such process and identification of the infiltrating cells have been the primary objectives in glioblastoma research. Here, we adopted radiogenomic analysis to screen for functionally relevant genes that orchestrate the process of glioma cell infiltration through myelin and promote glioblastoma aggressiveness. The receptor of the Nogo ligand (NgR1) was selected as the top candidate through Differentially Expressed Genes (DEG) and Gene Ontology (GO) enrichment analysis. Gain and loss of function studies on NgR1 elucidated its underlying molecular importance in suppressing myelin-associated infiltration in vitro and in vivo. The migratory ability of glioblastoma cells on myelin is reversibly modulated by NgR1 during differentiation and dedifferentiation process through deubiquitinating activity of USP1, which inhibits the degradation of ID1 to downregulate NgR1 expression. Furthermore, pimozide, a well-known antipsychotic drug, upregulates NgR1 by post-translational targeting of USP1, which sensitizes glioma stem cells to myelin inhibition and suppresses myelin-associated infiltration in vivo. In primary human glioblastoma, downregulation of NgR1 expression is associated with highly infiltrative characteristics and poor survival. Together, our findings reveal that loss of NgR1 drives myelin-associated infiltration of glioblastoma and suggest that novel therapeutic strategies aimed at reactivating expression of NgR1 will improve the clinical outcome of glioblastoma patients.

Comprehensive pharmacogenomic characterization of gastric cancer.

BACKGROUND: Gastric cancer is among the most lethal human malignancies. Previous studies have identified molecular aberrations that constitute dynamic biological networks and genomic complexities of gastric tumors. However, the clinical translation of molecular-guided targeted therapy is hampered by challenges. Notably, solid tumors often harbor multiple genetic alterations, complicating the development of effective treatments. METHODS: To address such challenges, we established a comprehensive dataset of molecularly annotated patient derivatives coupled with pharmacological profiles for 60 targeted agents to explore dynamic pharmacogenomic interactions in gastric cancers. RESULTS: We identified lineage-specific drug sensitivities based on histopathological and molecular subclassification, including substantial sensitivities toward VEGFR and EGFR inhibition therapies in diffuse- and signet ring-type gastric tumors, respectively. We identified potential therapeutic opportunities for WNT pathway inhibitors in ALK-mutant tumors, a significant association between PIK3CA-E542K mutation and AZD5363 response, and transcriptome expression of RNF11 as a potential predictor of response to gefitinib. CONCLUSIONS: Collectively, our results demonstrate the feasibility of drug screening combined with tumor molecular characterization to facilitate personalized therapeutic regimens for gastric tumors.

PIP4K2A as a negative regulator of PI3K in PTEN-deficient glioblastoma.

Glioblastoma (GBM) is the most malignant brain tumor with profound genomic alterations. Tumor suppressor genes regulate multiple signaling networks that restrict cellular proliferation and present barriers to malignant transformation. While bona fide tumor suppressors such as PTEN and TP53 often undergo inactivation due to mutations, there are several genes for which genomic deletion is the primary route for tumor progression. To functionally identify putative tumor suppressors in GBM, we employed in vivo RNAi screening using patient-derived xenograft models. Here, we identified PIP4K2A, whose functional role and clinical relevance remain unexplored in GBM. We discovered that PIP4K2A negatively regulates phosphoinositide 3-kinase (PI3K) signaling via p85/p110 component degradation in PTEN-deficient GBMs and specifically targets p85 for proteasome-mediated degradation. Overexpression of PIP4K2A suppressed cellular and clonogenic growth in vitro and impeded tumor growth in vivo. Our results unravel a novel tumor-suppressive role of PIP4K2A for the first time and support the feasibility of combining oncogenomics with in vivo RNAi screen.

Pharmacogenomic landscape of patient-derived tumor cells informs precision oncology therapy.

Outcomes of anticancer therapy vary dramatically among patients due to diverse genetic and molecular backgrounds, highlighting extensive intertumoral heterogeneity. The fundamental tenet of precision oncology defines molecular characterization of tumors to guide optimal patient-tailored therapy. Towards this goal, we have established a compilation of pharmacological landscapes of 462 patient-derived tumor cells (PDCs) across 14 cancer types, together with genomic and transcriptomic profiling in 385 of these tumors. Compared with the traditional long-term cultured cancer cell line models, PDCs recapitulate the molecular properties and biology of the diseases more precisely. Here, we provide insights into dynamic pharmacogenomic associations, including molecular determinants that elicit therapeutic resistance to EGFR inhibitors, and the potential repurposing of ibrutinib (currently used in hematological malignancies) for EGFR-specific therapy in gliomas. Lastly, we present a potential implementation of PDC-derived drug sensitivities for the prediction of clinical response to targeted therapeutics using retrospective clinical studies.

Trend of Daily Sports Participation in Korean Aged Population and Sports Policy: A Review of Research on Public Daily Sports Participation.

BACKGROUND: This study aimed to investigate the trend of physical activity and daily sports participation in the Korean aged population through the review of 'Research on Public Daily Sports Participation' published by the Ministry of Culture, Sports and Tourism. The main purpose was to suggest the best health and sports policy for the future. METHODS: The result of the research conducted by the government was published 13 times in total from 1989 to 2015. The aged were defined as people in their 60s and 70s since 2006. Based on the research published 7 times from 2006 to 2015, this study analyzed the changes and the trend recognition of health status, physical activities, sports activity effects and environment in the aged population in South Korea. RESULTS: Majority of the aged population was found to hardly recognize their health status, but positively aware of physical and sports activity effect, particularly that the sports facility environment has been improving. Therefore, it is encouraged to set up elderly-friendly routine sports environment to motivate their participation and consequently establish healthy exercise culture. CONCLUSION: This study has great significance as it suggests the direction of future health and sports policy by analyzing the trend of previous physical activities and daily sports participation among the aged population based on the government-published research.

A study on macronutrient self-selection after acute aerobic exercise in college females.

[Purpose] This study was conducted to determine whether acute aerobic exercise (climbing) is associated with changes in the dietary intake pattern. [Subjects and Methods] Food intake and physical activity data for 15 female college students were sampled for 3 days and categorized according to routine activity or high-intensity activity such as hiking. Nutrient intake based on the data was analyzed using a nutrition program. [Results] Carbohydrate and protein intake was significantly decreased after exercise compared to before acute aerobic exercise, but lipid intake showed no significant difference. Calorie intake was significantly decreased after exercise compared to before exercise; however, calorie consumption was significantly increased after exercise. [Conclusion] Aerobic exercise causes a decrease in total calories by inducing reduction in carbohydrate and protein intake. Therefore, aerobic exercise is very important for weight (body fat) control since it causes positive changes in the food intake pattern in female students.

Involvement of DDX6 gene in radio- and chemoresistance in glioblastoma.

CCRT (concomitant chemotherapy and radiation therapy) is often used for glioblastoma multiforme (GBM) treatment after surgical therapy, however, patients treated with CCRT undergo poor prognosis due to development of treatment resistant recurrence. Many studies have been performed to overcome these problems and to discover genes influencing treatment resistance. To discover potential genes inducing CCRT resistance in GBM, we used whole genome screening by infecting shRNA pool in patient-derived cell. The cells infected ~8,000 shRNAs were implanted in mouse brain and treated RT/TMZ as in CCRT treated patients. We found DDX6 as the candidate gene for treatment resistance after screening and establishing DDX6 knock down cells for functional validation. Using these cells, we confirmed tumor associated ability of DDX6 in vitro and in vivo. Although proliferation improvement was not found, decreased DDX6 influenced upregulated clonogenic ability and resistant response against radiation treatment in vivo and in vitro. Taken together, we suggest that DDX6 discovered by using whole genome screening was responsible for radio- and chemoresistance in GBM.

In vivo RNAi screen identifies NLK as a negative regulator of mesenchymal activity in glioblastoma.

Glioblastoma (GBM) is the most lethal brain cancer with profound genomic alterations. While the bona fide tumor suppressor genes such as PTEN, NF1, and TP53 have high frequency of inactivating mutations, there may be the genes with GBM-suppressive roles for which genomic mutation is not a primary cause for inactivation. To identify such genes, we employed in vivo RNAi screening approach using the patient-derived GBM xenograft models. We found that Nemo-Like Kinase (NLK) negatively regulates mesenchymal activities, a characteristic of aggressive GBM, in part via inhibition of WNT/ß-catenin signaling. Consistent with this, we found that NLK expression is especially low in a subset of GBMs that harbors high WNT/mesenchymal activities. Restoration of NLK inhibited WNT and mesenchymal activities, decreased clonogenic growth and survival, and impeded tumor growth in vivo. These data unravel a tumor suppressive role of NLK and support the feasibility of combining oncogenomics with in vivo RNAi screen.

Phosphorylation of EZH2 activates STAT3 signaling via STAT3 methylation and promotes tumorigenicity of glioblastoma stem-like cells.

Glioblastoma multiforme (GBM) displays cellular hierarchies harboring a subpopulation of stem-like cells (GSCs). Enhancer of Zeste Homolog 2 (EZH2), the lysine methyltransferase of Polycomb repressive complex 2, mediates transcriptional repression of prodifferentiation genes in both normal and neoplastic stem cells. An oncogenic role of EZH2 as a transcriptional silencer is well established; however, additional functions of EZH2 are incompletely understood. Here, we show that EZH2 binds to and methylates STAT3, leading to enhanced STAT3 activity by increased tyrosine phosphorylation of STAT3. The EZH2-STAT3 interaction preferentially occurs in GSCs relative to non-stem bulk tumor cells, and it requires a specific phosphorylation of EZH2. Inhibition of EZH2 reverses the silencing of Polycomb target genes and diminishes STAT3 activity, suggesting therapeutic strategies.

Patient-specific orthotopic glioblastoma xenograft models recapitulate the histopathology and biology of human glioblastomas in situ.

Frequent discrepancies between preclinical and clinical results of anticancer agents demand a reliable translational platform that can precisely recapitulate the biology of human cancers. Another critical unmet need is the ability to predict therapeutic responses for individual patients. Toward this goal, we have established a library of orthotopic glioblastoma (GBM) xenograft models using surgical samples of GBM patients. These patient-specific GBM xenograft tumors recapitulate histopathological properties and maintain genomic characteristics of parental GBMs in situ. Furthermore, in vivo irradiation, chemotherapy, and targeted therapy of these xenograft tumors mimic the treatment response of parental GBMs. We also found that establishment of orthotopic xenograft models portends poor prognosis of GBM patients and identified the gene signatures and pathways signatures associated with the clinical aggressiveness of GBMs. Together, the patient-specific orthotopic GBM xenograft library represent the preclinically and clinically valuable "patient tumor's phenocopy" that represents molecular and functional heterogeneity of GBMs.

Wnt activation is implicated in glioblastoma radioresistance.

Glioblastoma (GBM) patients have dismal median survival even with the most rigorous treatments currently available. Radiotherapy is the most effective non-surgical therapy for GBM patients; however, patients succumb due to tumor recurrence within a year. To develop a curative therapeutic approach, we need to better understand the underlying molecular mechanism of radiation resistance in GBM. Towards this goal, we developed an in vivo orthotopic GBM model system that mimics the radiation response of human GBM, using both established-GBM cell line and patient-derived freshly dissociated GBM specimen. In-vivo ionizing radiation (IR) treatment prolonged the survival of mice with intracranical tumor derived from U373MG, but failed to prevent tumor recurrence. U373MG and GBM578 cells isolated after in-vivo IR (U373-IR and 578-IR) were more clonogenic and enriched with stem cell-like characteristics, compared with mock-treated control tumor cells. Transcriptomic analyses and quantitative real-time reverse-transcription PCR analyses using these matched GBM cells before and after radiation treatment revealed that Wnt pathways were preferentially activated in post-IR GBM cells. U373-IR cells and 578-IR were enriched with cells positive for both active ß-catenin (ABC) and Sox2 population, and this subpopulation was further increased after additional in-vitro radiation treatment, suggesting that radiation resistance of GBM is mediated due, in part, to the activation of stem cell-associated pathways including Wnt. Finally, pharmacological and siRNA inhibition of Wnt pathway significantly decreased the survival and clonogenicity of GBM cells and reduced their ABC(+)/Sox2(+) population. Together, these data suggest that Wnt activation is a molecular mechanism to confer GBM radioresistance and an important therapeutic target.