I-129 Waste form Using Bi-Zn-P-Oxide Glass

AbstractI-129 is a problematic nuclide generated from the recycling of spent fuel by pyroprocess. Gaseous form of radiogenic iodine is trapped by using silver exchanged zeolite (AgX) at Korea Atomic Energy Research Institute (KAERI). We developed the low melting temperature glass system based on Bi2O3-P2O5 composition. Various additives were added to modify glass properties. We found that ingots containing AgI are formed with ZnO, CaCO3, MgO, and Na2CO3 at around 600°C. Analysis of microstructure and chemical durability revealed that AgI was encapsulated by glass matrix and formation of AgI compound is meaningful in fabricating iodine waste form

PIP-EL: A New Ensemble Learning Method for Improved Proinflammatory Peptide Predictions

Proinflammatory cytokines have the capacity to increase inflammatory reaction and play a central role in first line of defence against invading pathogens. Proinflammatory inducing peptides (PIPs) have been used as an antineoplastic agent, an antibacterial agent and a vaccine in immunization therapies. Due to the advancement in sequence technologies that resulted an avalanche of protein sequence data. Therefore, it is necessary to develop an automated computational method to enable fast and accurate identification of novel PIPs within the vast number of candidate proteins and peptides. To address this, we proposed a new predictor, PIP-EL, for predicting PIPs using the strategy of ensemble learning (EL). Our benchmarking dataset is imbalanced. Thus, we applied a random under-sampling technique to generate 10 balanced models for each composition. Technically, PIP-EL is the fusion of 50 independent random forest (RF) models, where each of the five different compositions, including amino acid, dipeptide, composition–transition–distribution, physicochemical properties, and amino acid index contains 10 RF models. PIP-EL achieves the Matthews’ correlation coefficient (MCC) of 0.435 in a 5-fold cross-validation test, which is ~2–5% higher than that of the individual classifiers and hybrid feature-based classifier. Furthermore, we evaluate the performance of PIP-EL on the independent dataset, showing that our method outperforms the existing method and two different machine learning methods developed in this study, with an MCC of 0.454. These results indicate that PIP-EL will be a useful tool for predicting PIPs and for researchers working in the field of peptide therapeutics and immunotherapy. The user-friendly web server, PIP-EL, is freely accessible.

Nuclear structure in Parity Doublet Model

Using an extended parity doublet model with the hidden local symmetry, we study the properties of nuclei in the mean field approximation to see if the parity doublet model could reproduce nuclear properties and also to estimate the value of the chiral invariant nucleon mass $m_0$ preferred by nuclear structure. We first determined our model parameters using the inputs from free space and from nuclear matter properties. Then, we study some basic nuclear properties such as the nuclear binding energy with several different choices of the chiral invariant mass. We observe that our results, especially the nuclear binding energy, approach the experimental values as $m_0$ is increased until $m_0=700$ MeV and start to deviate more from the experiments afterwards with $m_0$ larger than $m_0=700$ MeV, which may imply that $m_0=700$ MeV is preferred by some nuclear properties.Comment: 8 pages, 2 figure

ULTRAFILTRATED FRACTION OF KOREAN RED GINSENG EXTRACT IMPROVES MEMORY IMPAIRMENT OF TG2576 MICE VIA INHIBITION OF SOLUBLE AÎ’ PRODUCTION AND ACETYLCHOLINESTERASE ACTIVITY

Objective: The goal of this study was to research for an effective fraction on memory improvement of Korean red ginseng.Methods: In this study, 80 % ethanol red ginseng extract (RE) was divided into inner fluid (REUI) and outer fluid (REUO) by the ultrafiltration and then REUO was further separated into four fractions namely, REUO-00, REUO-30, REUO-50 and REUO-70, respectively, by Diaion HP-20 column chromatography.Results: REUO has protected more significantly the H2O2-induced SHSY-5Y cell death than REUI. Interestingly, the hydrophobic parts of the REUO (REUO-EtOHs) such as REUO-30,-50 and-70 decreased more significantly the H2O2-induced cell death than its hydrophilic part (REUO-00) in a dose-dependent manner. Then, we focused on the activity of a candidate for cholinergic functions, because memory deficits of neurodegenerative diseases are closely associated with cholinergic dysfunctions. The REUO-EtOHs (1.25 mg/ml) inhibited the activity of the acetylcholinesterase and its half maximal inhibitory concentration (IC50) was about 2.358 mg/ml. Additionally, we investigated whether the intake of the REUO (50 mg/kg/d) during 12 w could improve memory impairment of 12-month old Tg2576 mice and decrease total soluble amyloid-β (Aβ) proteins in the mouse brain cortex. The REUO alleviated significantly the memory impairment and successfully reduced the levels of the soluble Aβ proteins in the mouse cortex.Conclusion: We finally suggest that the REUO, including majorly its hydrophobic part that may be considered as more effective for memory improvement, will be highly considered as valuable candidate for the memory-enhancing ingredients against cholinergic dysfunctions and cognitive impairments of neurodegenerative diseases including Alzheimer's disease.Keywords: Ginseng, Alzheimer's disease, Acetylcholinesterase, Ultrafiltration, MemoryÂ

New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS)

GEMS will monitor air quality over Asia at unprecedented spatial and temporal resolution from GEO for the first time, providing column measurements of aerosol, ozone and their precursors (nitrogen dioxide, sulfur dioxide and formaldehyde). Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled for launch in late 2019 - early 2020 to monitor Air Quality (AQ) at an unprecedented spatial and temporal resolution from a Geostationary Earth Orbit (GEO) for the first time. With the development of UV-visible spectrometers at sub-nm spectral resolution and sophisticated retrieval algorithms, estimates of the column amounts of atmospheric pollutants (O3, NO2, SO2, HCHO, CHOCHO and aerosols) can be obtained. To date, all the UV-visible satellite missions monitoring air quality have been in Low Earth orbit (LEO), allowing one to two observations per day. With UV-visible instruments on GEO platforms, the diurnal variations of these pollutants can now be determined. Details of the GEMS mission are presented, including instrumentation, scientific algorithms, predicted performance, and applications for air quality forecasts through data assimilation. GEMS will be onboard the GEO-KOMPSAT-2 satellite series, which also hosts the Advanced Meteorological Imager (AMI) and Geostationary Ocean Color Imager (GOCI)-2. These three instruments will provide synergistic science products to better understand air quality, meteorology, the long-range transport of air pollutants, emission source distributions, and chemical processes. Faster sampling rates at higher spatial resolution will increase the probability of finding cloud-free pixels, leading to more observations of aerosols and trace gases than is possible from LEO. GEMS will be joined by NASA's TEMPO and ESA's Sentinel-4 to form a GEO AQ satellite constellation in early 2020s, coordinated by the Committee on Earth Observation Satellites (CEOS)

Hyalruronate Conjugated Molybdenum Disulfide for Multi-Modal Cancer Theranosis

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Hyalruronate Conjugated Molybdenum Disulfide for Photoacoustic Cancer Theranosis

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Multi-Modal Cancer Theranosis Using Hyaluronate Conjugatd Molybdenum Disulfide

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Hyaluronate Conjugated Molybdenum Disulfide for Multi-Modal Cancer Theranosis

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