Antioxidant Effects of the Ethanol Extract from Flower of Camellia japonica via Scavenging of Reactive Oxygen Species and Induction of Antioxidant Enzymes

The aim of this study was to investigate the antioxidant properties of the ethanol extract of the flower of Camellia japonica (Camellia extract). Camellia extract exhibited 1,1-diphenyl-2-picrylhydrazyl radical and intracellular reactive oxygen species (ROS) scavenging activity in human HaCaT keratinocytes. In addition, Camellia extract scavenged superoxide anion generated by xanthine/xanthine oxidase and hydroxyl radical generated by the Fenton reaction (FeSO4 + H2O2) in a cell-free system, which was detected by electron spin resonance spectrometry. Furthermore, Camellia extract increased the protein expressions and activity of cellular antioxidant enzymes, such as superoxide dismutase, catalase and glutathione peroxidase. These results suggest that Camellia extract exhibits antioxidant properties by scavenging ROS and enhancing antioxidant enzymes. Camellia extract contained quercetin, quercetin-3-O-glucoside, quercitrin and kaempferol, which are antioxidant compounds

Continuous Autonomous Ship Learning Framework for Human Policies on Simulation

Considering autonomous navigation in busy marine traffic environments (including harbors and coasts), major study issues to be solved for autonomous ships are avoidance of static and dynamic obstacles, surface vehicle control in consideration of the environment, and compliance with human-defined navigation rules. The reinforcement learning (RL) algorithm, which demonstrates high potential in autonomous cars, has been presented as an alternative to mathematical algorithms and has advanced in studies on autonomous ships. However, the RL algorithm, through interactions with the environment, receives relatively fewer data from the marine environment. Moreover, the open marine environment causes difficulties for autonomous ships in learning human-defined navigation rules because of excessive degrees of freedom. This study proposes a sustainable, intelligent learning framework for autonomous ships (ILFAS), which helps solve these difficulties and learns navigation rules specified by human beings through neighboring ships. The application of case-based RL enables the participation of humans in the RL learning process through neighboring ships and the learning of human-defined rules. Cases built as curriculums can achieve high learning effects with fewer data along with the RL of layered autonomous ships. The experiment aims at autonomous navigation from a harbor, where marine traffic occurs on a neighboring coast. The learning results using ILFAS and those in an environment where random marine traffic occurs are compared. Based on the experiment, the learning time was reduced by a tenth. Moreover, the success rate of arrival at a destination was higher with fewer controls than the random method in the new marine traffic scenario. ILFAS can continuously respond to advances in ship manufacturing technology and changes in the marine environment

Optimizing the Multistage University Admission Decision Process

The admission decision process is an important operational management problem for many universities. Admission control processes may, however, differ among universities. In this paper, we focus on the problem at Korea Advanced Institute of Science and Technology (KAIST). We assume that individual applications are evaluated and ranked based on paper evaluations and (optional) interview results. We use the term university admission decision to mean determining the number of admission offers that will meet the target number of enrollments. The major complexity of an admission decision comes from the enrollment uncertainty of admitted applicants. In the method we propose in this paper, we use logistic regression with past data to estimate the enrollment probability of each applicant. We then model the admission decision problem as a Markov decision process from which we formulate optimal decision making. The proposed method outperformed human expert results in meeting the enrollment target for the validation data in 2014 and 2015. KAIST successfully used our method for its admission decisions in academic year 2016

Continuous Autonomous Ship Learning Framework for Human Policies on Simulation

Considering autonomous navigation in busy marine traffic environments (including harbors and coasts), major study issues to be solved for autonomous ships are avoidance of static and dynamic obstacles, surface vehicle control in consideration of the environment, and compliance with human-defined navigation rules. The reinforcement learning (RL) algorithm, which demonstrates high potential in autonomous cars, has been presented as an alternative to mathematical algorithms and has advanced in studies on autonomous ships. However, the RL algorithm, through interactions with the environment, receives relatively fewer data from the marine environment. Moreover, the open marine environment causes difficulties for autonomous ships in learning human-defined navigation rules because of excessive degrees of freedom. This study proposes a sustainable, intelligent learning framework for autonomous ships (ILFAS), which helps solve these difficulties and learns navigation rules specified by human beings through neighboring ships. The application of case-based RL enables the participation of humans in the RL learning process through neighboring ships and the learning of human-defined rules. Cases built as curriculums can achieve high learning effects with fewer data along with the RL of layered autonomous ships. The experiment aims at autonomous navigation from a harbor, where marine traffic occurs on a neighboring coast. The learning results using ILFAS and those in an environment where random marine traffic occurs are compared. Based on the experiment, the learning time was reduced by a tenth. Moreover, the success rate of arrival at a destination was higher with fewer controls than the random method in the new marine traffic scenario. ILFAS can continuously respond to advances in ship manufacturing technology and changes in the marine environment

Nonanimal Euglena gracilis‐Derived Extracellular Vesicles Enhance Skin‐Regenerative Wound Healing

Abstract This study proposes using microalgae‐containing carbohydrate bioactives, an Euglena gracilis‐derived extracellular microvesicle (EMVEG) system, for enhanced skin regeneration. The critical deformation ratio, 1.67, during cell extrusion enables the authors to tune the particle size of the EMVEG at ≈1 µm, thus satisfying the encapsulation yield of β‐1,3‐glucan and the cellular delivery performance. In vitro 5‐bromo‐2'‐deoxyuridine and cell scratch assays reveal that the EMVEG promotes the proliferation and migration of skin cells, thereby increasing both collagen synthesis and the expressions of proliferation‐associated proteins. An ex vivo wound‐healing test using both artificial and porcine skin reveals that similar to that seen using β‐1,3‐glucan, the EMVEG can substantially increase the cell population, expressing the proliferation‐related protein, termed proliferating cell nuclear antigen. These results demonstrate that the EMVEG system shows considerable potential in the field of skin regeneration. This technique is expected to design new types of extracellular vesicles that are applicable for skin regeneration in the pharmaceutical and cosmetic industries

Effect of the Layer-by-Layer (LbL) Deposition Method on the Surface Morphology and Wetting Behavior of Hydrophobically Modified PEO and PAA LbL Films

We demonstrate that the surface morphology and surface-wetting behavior of layer-by-layer (LbL) films can be controlled using different deposition methods. Multilayer films based upon hydrogen-bonding interactions between hydrophobically modified poly(ethylene oxide) (HM-PEO) and poly(acrylic acid) (PAA) have been prepared using the dip- and spin-assisted LbL methods. A three-dimensional surface structure in the dip-assisted multilayer films appeared above a critical number of layer pairs owing to the formation of micelles of HM-PEO in its aqueous dipping solution. In the case of spin-assisted HM-PEO/PAA multilayer films, no such surface morphology development was observed, regardless of the layer pair number, owing to the limited rearrangement and aggregation of HM-PEO micelles during spin deposition. The contrasting surface morphologies of the dip- and spin-assisted LbL films have a remarkable effect on the wetting behavior of water droplets. The water contact angle of the dip-assisted HM-PEO/PAA LbL films reaches a maximum at an intermediate layer pair number, coinciding with the critical number of layer pairs for surface morphology development, and then decreases rapidly as the surface structure is evolved and amplified. In contrast, spin-assisted HM-PEO/PAA LbL films yield a nearly constant water contact angle due to the surface chemical composition and roughness that is uniform independent of layer pair number. We also demonstrate that the multilayer samples prepared using both the dip- and spin-assisted LbL methods were easily peeled away from any type of substrate to yield free-standing films; spin-assisted LbL films appeared transparent, while dip-assisted LbL films were translucent.This work was financially supported by the Korea Science and Engineering Foundation (KOSEF) Grant funded by the Korea Government (MOST) (Acceleration Research Program (No. R17-2007-059-01000-0) and NANO Systems Institute-National Core Research Center (No. R15-2003-032-05001-0)) and by the Brain Korea 21 Program endorsed by the Ministry of Education of Korea. We also acknowledge the Center for Materials Science and Engineering and the Institute for Soldier Nanotechnologies (ISN) at MIT for the use of their facilities. K.C. acknowledges financial support from the SBS Foundation for his sabbatical leave at ISN of MIT, and J.S. acknowledges the Seoul Science Fellowship for her graduate study at SNU

Development of Surface Morphology in Multilayered Films Prepared by Layer-by-Layer Deposition Using Poly(acrylic acid) and Hydrophobically Modified Poly(ethylene oxide)

We report the fabrication of free-standing multilayered thin films based on the layer-by-layer (LbL) deposition method. The isolation of multilayer thin film allows us to characterize the materials properties of such films in great detail. Poly(acrylic acid) (PAA) and hydrophobically modified poly(ethylene oxide) (HM-PEO) multilayer films have been prepared using the LbL method based upon hydrogen-bonding interactions. The LbL film composition and thermal properties were obtained as a function of the number of layer pairs using thermal gravimetric analysis (TGA) as well as differential scanning calorimetry (DSC). Above the critical number of layer pairs, the HM-PEO/PAA multilayer films exhibit complex surface structure owing to the hydrophobic nature of HM-PEO (i.e., micelle formation). The unique surface morphology was studied using optical microscopy and fluorescence microscopy, where pyrene dyes incorporated into the hydrophobic cores of HM-PEO micelles allowed us to monitor the sites of HM-PEO micelles. We demonstrate that the film morphology can be controlled by varying the solvent polarity, temperature, and molecular weight of HM-PEO. It is also noted that the introduction of hydrophobic moieties in PEO significantly facilitates the film isolation from various substrates, yielding free-standing multilayer films.This work was financially supported by the NANO Systems Institute-National Core Research Center from the Korea Science and Engineering Foundation (KOSEF) and the Brain Korea 21 Program endorsed by the Ministry of Education of Korea. We also acknowledge the Center for Material Science and Engineering and the Institute for the Soldier Nanotechnologies (ISN) at MIT for the use of their facilities. K.C. acknowledges the financial support from the SBS Foundation for his sabbatical leave at ISN of MIT, and J.S. acknowledges the Seoul Science Fellowship

Fabrication of Microgel-in-Liposome Particles with Improved Water Retention

Corneocytes represents the main water reservoir of stratum corneum, and that ability intimately arises from their architecture and total composition. Here we describe a novel method for fabricating a microgel-in-liposome (M-i-L) structure consisting of a sodium hyaluronate microgel and a lipid membrane envelop in order to mimic corneocyte cell structures. The essence of our approach is to use a lecithin-based microemulsion with a very low interfacial tension between the water droplet and oil continuous phase. Using this emulsion enables us to stabilize a dispersion of microgel particles without phase separation or aggregation. The addition of excess water produced single-core or multicore microgel particles enveloped in a lipid layer. To demonstrate the applicability of this unique vesicle system, we encapsulated a high concentration of natural moisturizing factor (NMF) in the microgel core and investigated how the M-i-L structure affected the water retention in comparison with other control systems. We have observed that our M-i-L particles with the NMF in the core, which mimicked the corneocyte cell structure, showed an excellent ability to retain water in the system. This experimental result inspired us to investigate how corneocyte cells, which feature a lipid-enveloped hydrogel structure, provide such long-lasting hydration to the skin.close2