A facile inhibitor screening of SARS coronavirus N protein using nanoparticle-based RNA oligonucleotide

Hundreds of million people worldwide have been infected with severe acute respiratory syndrome (SARS), and the rate of global death from SARS has remarkably increased. Hence, the development of efficient drug treatments for the biological effects of SARS is highly needed. We have previously shown that quantum dots (QDs)-conjugated RNA oligonucleotide is sensitive to the specific recognition of the SARS-associated coronavirus (SARS-CoV) nucleocapsid (N) protein. In this study, we found that a designed biochip could analyze inhibitors of the SARS-CoV N protein using nanoparticle-based RNA oligonucleotide. Among the polyphenolic compounds examined, (−)-catechin gallate and (−)-gallocatechin gallate demonstrated a remarkable inhibition activity on SARS-CoV N protein. (−)-catechin gallate and (−)-gallocatechin gallate attenuated the binding affinity in a concentrated manner as evidenced by QDs-conjugated RNA oligonucleotide on a designed biochip. At a concentration of 0.05 μg mL−1, (−)-catechin gallate and (−)-gallocatechin gallate showed more than 40% inhibition activity on a nanoparticle-based RNA oligonucleotide biochip system

A highly sensitive and selective viral protein detection method based on RNA oligonucleotide nanoparticle

Globally, approximately 170 million people (representing approximately 3% of the population worldwide), are infected with hepatitis C virus (HCV) and at risk of serious liver disease, including chronic hepatitis. We propose a new quantum dots (QDs)-supported RNA oligonucleotide approach for the specific and sensitive detection of viral protein using a biochip. This method was developed by immobilizing a HCV nonstructural protein 5B (NS5B) on the surface of a glass chip via the formation of a covalent bond between an amine protein group and a ProLinker™ glass chip. The QDs-supported RNA oligonucleotide was conjugated via an amide formation reaction from coupling of a 5′-end-amine-modified RNA oligonucleotide on the surface of QDs displaying carboxyl groups via standard EDC coupling. The QDs-conjugated RNA oligonucleotide was interacted to immobilized viral protein NS5B on the biochip. The detection is based on the variation of signal of QDs-supported RNA oligonucleotide bound on an immobilized biochip. It was demonstrated that the value of the signal has a linear relationship with concentrations of the HCV NS5B viral protein in the 1 μg mL−1 to 1 ng mL−1 range with a detection limit of 1 ng mL−1. The major advantages of this RNA-oligonucleotide nanoparticle assay are its good specificity, ease of performance, and ability to perform one-spot monitoring. The proposed method could be used as a general method of HCV detection and is expected to be applicable to other types of diseases as well

Low-activity hotspot investigation method via scanning using deep learning

Small areas of elevated activity are a concern during a final status scan survey of residual radioactivity of decommissioned and contaminated sites. Due to the characteristics of scanning, the lower limit of detection is relatively high because the number of counts is low due to the short measurement time. To overcome this, an algorithm capable of finding hotspots with little information through deep learning was developed. The developed model using an artificial neural network was trained with the scan survey data acquired from a Monte Carlo-based computational simulation. A random mixing method was used to obtain sufficient training data. In order to respond properly to the experimental data, training and verification were conducted in various situations, in this case, in the presence or absence of random background counts and collimators and various source concentrations. Experimental data were obtained using a conventional detector, in this case, the 3″ × 3″ NaI(Tl). The advantages and limitations to the proposed method are as follows. Results were well predicted even in cases at less than 1 Bq/g, which is lower than the scanned minimum detectable concentration (MDC) of the detection system. It is a great advantage that it can detect contaminated areas that are lower than the existing scan’s minimum detectable concentration. However, the limitation is that it cannot be predicted, and the accuracy is low in multi-sourced scans. The source position and size are also important in residual radioactive evaluations, and scanning data images were evaluated in artificial neural network modes with suitable prediction results. The proposed methodology proved the high accuracy of hotspot prediction for low-activity sites and showed that this technology can be used as an efficient and economical hotspot scanning technology and can be extended to an automated system

Versatile poly(diallyl dimethyl ammonium chloride)-layered nanocomposites for removal of cesium in water purification

In this work, we elucidate polymer-layered hollow Prussian blue-coated magnetic nanocomposites as an adsorbent to remove radioactive cesium from environmentally contaminated water. To do this, Fe3O4 nanoparticles prepared using a coprecipitation method were thickly covered with a layer of cationic polymer to attach hollow Prussian blue through a self-assembly process. The as-synthesized adsorbent was confirmed through various analytical techniques. The adsorbent showed a high surface area (166.16 m2/g) with an excellent cesium adsorbent capacity and removal efficiency of 32.8 mg/g and 99.69%, respectively. Moreover, the superparamagnetism allows effective recovery of the adsorbent using an external magnetic field after the adsorption process. Therefore, the magnetic adsorbent with a high adsorption efficiency and convenient recovery is expected to be effectively used for rapid remediation of radioactive contamination

Label Free Inhibitor Screening of Hepatitis C Virus (HCV) NS5B Viral Protein Using RNA Oligonucleotide

Globally, over 170 million people (ca. 3% of the World’s population) are infected with the hepatitis C virus (HCV), which can cause serious liver diseases such as chronic hepatitis, evolving into subsequent health problems. Driven by the need to detect the presence of HCV, as an essential factor in diagnostic medicine, the monitoring of viral protein has been of great interest in developing simple and reliable HCV detection methods. Despite considerable advances in viral protein detection as an HCV disease marker, the current enzyme linked immunosorbent assay (ELISA) based detection methods using antibody treatment have several drawbacks. To overcome this bottleneck, an RNA aptamer become to be emerged as an antibody substitute in the application of biosensor for detection of viral protein. In this study, we demonstrated a streptavidin-biotin conjugation method, namely, the RNA aptamer sensor system that can quantify viral protein with detection level of 700 pg mL−1 using a biotinylated RNA oligonucleotide on an Octet optical biosensor. Also, we showed this method can be used to screen inhibitors of viral protein rapidly and simply on a biotinylated RNA oligonucleotide biosensor. Among the inhibitors screened, (−)-Epigallocatechin gallate showed high binding inhibition effect on HCV NS5B viral protein. The proposed method can be considered a real-time monitoring method for inhibitor screening of HCV viral protein and is expected to be applicable to other types of diseases

Fucoidan from Marine Brown Algae Inhibits Lipid Accumulation

In this study, we elucidated the inhibitory effect of fucoidan from marine brown algae on the lipid accumulation in differentiated 3T3-L1 adipocytes and its mechanism. The treatment of fucoidan in a dose-dependent manner was examined on lipid inhibition in 3T3-L1 cells by using Oil Red O staining. Fucoidan showed high lipid inhibition activity at 200 μg/mL concentration (P < 0.001). Lipolytic activity in adipocytes is highly dependent on hormone sensitive lipase (HSL), which is one of the most important targets of lipolytic regulation. Here, we examined the biological response of fucoidan on the protein level of lipolysis pathway. The expressed protein levels of total hormone sensitive lipase (HSL) and its activated form, phosphorylated-HSL were significantly increased at concentration of 200 μg/mL fucoidan. Furthermore, insulin-induced 2-deoxy-d-[3H] glucose uptake was decreased up to 51% in fucoidan-treated cells as compared to control. Since increase of HSL and p-HSL expression and decrease of glucose uptake into adipocytes are known to lead to stimulation of lipolysis, our results suggest that fucoidan reduces lipid accumulation by stimulating lipolysis. Therefore, these results suggest that fucoidan can be useful for the prevention or treatment of obesity due to its stimulatory lipolysis

Screening of Crude Plant Extracts with Anti-Obesity Activity

Obesity is a global health problem. It is also known to be a risk factor for the development of metabolic disorders, type 2 diabetes, systemic hypertension, cardiovascular disease, dyslipidemia, and atherosclerosis. In this study, we screened crude extracts from 400 plants to test their anti-obesity activity using porcine pancreatic lipase assay (PPL; triacylglycerol lipase, EC 3.1.1.3) in vitro activity. Among the 400 plants species examined, 44 extracts from plants, showed high anti-lipase activity using 2,4-dinitrophenylbutyrate as a substrate in porcine pancreatic lipase assay. Furthermore, 44 plant extracts were investigated for their inhibition of lipid accumulation in 3T3-L1 cells. Among these 44 extracts examined, crude extracts from 4 natural plant species were active. Salicis Radicis Cortex had the highest fat inhibitory activity, whereas Rubi Fructus, Corni Fructus, and Geranium nepalense exhibited fat inhibitory capacity higher than 30% at 100 μg/mL in 3T3-L1 adipocytes, suggesting anti-obesity activity. These results suggest that four potent plant extracts might be of therapeutic interest with respect to the treatment of obesity

Metabolomics in Radiation-Induced Biological Dosimetry: A Mini-Review and a Polyamine Study

In this study, we elucidate that polyamine metabolite is a powerful biomarker to study post-radiation changes. Metabolomics in radiation biodosimetry, the application of a metabolomics analysis to the field of radiobiology, promises to increase the understanding of biological responses by ionizing radiation (IR). Radiation exposure triggers a complex network of molecular and cellular responses that impacts metabolic processes and alters the levels of metabolites. Such metabolites have potential as biomarkers for radiation dosimetry. Among metabolites, polyamine is one of many potential biomarkers to estimate radiation response. In addition, this review provides an opportunity for the understanding of a radiation metabolomics in biodosimetry and a polyamine case study

Anti-Obesity Effect of Nepetae spica Extract in High-Fat Mice

In recent years, obesity is the most common metabolic disease emerging as a global problem especially in developed nations. The discovery of bioactive compounds from natural plant extracts is one possible way to control obesity and prevent or reduce the risks of getting various obesity-related diseases. In this study, we elucidated that Nepetae spica extract significantly reduced the body weight gain induced through feeding a high-fat diet to C57BL/6 mice. The treatment of Nepetae spica extract significantly reduced the adipose tissue weight to 1.5/100 g of body weight in high-fat mice. When their adipose tissue morphology was investigated for histochemical staining, the distribution of cell size in the high-fat diet groups was hypertrophied compared with those from Nepetae spica extract-treated mice. In addition, in Nepetae spica extract-treated mice, a significant reduction of serum triglyceride and T-cholesterol was observed at to 13% and 16%, respectively. These results suggest that Nepetae spica extract could be useful for prevention or treatment of obesity

Metabolomics in Radiation-Induced Biological Dosimetry: A Mini-Review and a Polyamine Study

In this study, we elucidate that polyamine metabolite is a powerful biomarker to study post-radiation changes. Metabolomics in radiation biodosimetry, the application of a metabolomics analysis to the field of radiobiology, promises to increase the understanding of biological responses by ionizing radiation (IR). Radiation exposure triggers a complex network of molecular and cellular responses that impacts metabolic processes and alters the levels of metabolites. Such metabolites have potential as biomarkers for radiation dosimetry. Among metabolites, polyamine is one of many potential biomarkers to estimate radiation response. In addition, this review provides an opportunity for the understanding of a radiation metabolomics in biodosimetry and a polyamine case study