Seoul National University of Science and Technology

In 2008 we published the first set of guidelines for standardizing research in autophagy. Since then, research on this topic has continued to accelerate, and many new scientists have entered the field. Our knowledge base and relevant new technologies have also been expanding. Accordingly, it is important to update these guidelines for monitoring autophagy in different organisms. Various reviews have described the range of assays that have been used for this purpose. Nevertheless, there continues to be confusion regarding acceptable methods to measure autophagy, especially in multicellular eukaryotes. For example, a key point that needs to be emphasized is thatthere is a difference between measurements that monitor the numbers or volume of autophagic elements (e.g., autophagosomes or autolysosomes) at any stage of the autophagic process versus those that measure flux through the autophagy pathway (i.e., the completeprocess including the amount and rate of cargo sequestered and degraded). In particular, a block in macroautophagy that results in autophagosome accumulation must be differentiated from stimuli that increase autophagic activity, defined as increasedautophagy induction coupled with increased delivery to, and degradation within, lysosomes (inmost higher eukaryotes and some protists such as Dictyostelium) or the vacuole (in plants and fungi). In other words, it is especially important that investigators new to the field understand that the appearance of more autophagosomes does not necessarily equate with more autophagy. In fact, in manycases, autophagosomes accumulate because of a block in trafficking to lysosomes without a concomitant change in autophagosome biogenesis, whereas an increase in autolysosomes may reflect a reduction in degradative activity. It is worth emphasizing here that lysosomal digestion is a stage of autophagy and evaluating its competence is a crucial part of the evaluation of autophagic flux, or complete autophagy. Here, we present a set of guidelines for the selection and interpretation of methods for use by investigators who aim to examine macroautophagy and related processes, as well as forreviewers who need to provide realistic and reasonable critiques of papers that are focused on these processes. These guidelines are not meant to be a formulaic set of rules, because the appropriate assays depend in part on the question being asked and the system being used. In addition, we emphasize that no individual assay is guaranteed to be the most appropriate one in every situation, and we strongly recommend the use of multipleassays to monitor autophagy. Along these lines, because of the potential for pleiotropic effects due to blocking autophagy through genetic manipulation, it is imperative to target by gene knockout or RNA interference more than one autophagyrelated protein. In addition, some individual Atg proteins, or groups of proteins, are involved in other cellular pathways implying that not all Atg proteins can be used as a specific marker for an autophagic process. In these guidelines, we consider these various methods of assessing autophagy and what information can, or cannot, be obtained from them. Finally, by discussing the merits and limits of particular assays, we hope to encourage technical innovation in the field.

Doil Choi and colleagues report the genome sequence of the hot pepper, Capsicum annuum, as well as the resequencing of two cultivated peppers and a wild species, Capsicum chinense. Comparative genomic analysis across Solanaceae provides insights into genome expansion, pungency, ripening and disease resistance in hot peppers. Hot pepper (Capsicum annuum), one of the oldest domesticated crops in the Americas, is the most widely grown spice crop in the world. We report whole-genome sequencing and assembly of the hot pepper (Mexican landrace of Capsicum annuum cv. CM334) at 186.6× coverage. We also report resequencing of two cultivated peppers and de novo sequencing of the wild species Capsicum chinense. The genome size of the hot pepper was approximately fourfold larger than that of its close relative tomato, and the genome showed an accumulation of Gypsy and Caulimoviridae family elements. Integrative genomic and transcriptomic analyses suggested that change in gene expression and neofunctionalization of capsaicin synthase have shaped capsaicinoid biosynthesis. We found differential molecular patterns of ripening regulators and ethylene synthesis in hot pepper and tomato. The reference genome will serve as a platform for improving the nutritional and medicinal values of Capsicum species.

To express the antioxidant capacity of plant foods in a more familiar and easily understood manner (equivalent to vitamin C mg/100 g), two stable radical species, ABTS(*)(-) and DPPH(*), commonly used for antioxidant activity measurements, were employed independently to evaluate their efficacies using apple polyphenolic extracts and seven polyphenolic standards including synthetic Trolox. Their antioxidant activities were expressed as vitamin C equivalent antioxidant capacity (VCEAC) in mg/100 g apple or mg/100 mL of the reference chemical compounds in 10 and 30 min using the ABTS(*)(-) and DPPH(*) scavenging assays, respectively. The antioxidant capacity of Gala apples and seven phenolic standards, determined by both ABTS(*)(-) and DPPH(*) scavenging assays, showed a dose-response of the first-order. Fresh Gala apples had a VCEAC of 205.4 +/- 5.6 mg/100 g using the ABTS assay, and the relative VCEACs of phenolic standards were as follows: gallic acid > quercetin > epicatechin > catechin > vitamin C > rutin > chlorogenic acid > Trolox. With the DPPH radical assay, the VCEAC of fresh Gala apples was 136.0 +/- 6.6 mg/100 g, and the relative VCEACs of seven phenolic standards were, in decreasing order, as follows: gallic acid > quercetin > epicatechin > catechin > or = vitamin C > Trolox > rutin > chlorogenic acid. Because the ABTS assay can be used in both organic and aqueous solvent systems, employs a specific absorbance at a wavelength remote from the visible region, and requires a short reaction time, it is a more desirable method than the DPPH assay. Therefore, it is recommended that antioxidant capacity be expressed as vitamin C mg/100 g equivalent (VCEAC) using the ABTS assay.

Cellulose nanocrystals (CNCs), produced by the acid hydrolysis of wood, cotton or other cellulose-rich sources, constitute a renewable nanosized raw material with a broad range of envisaged uses: for example, in composites, cosmetics and medical devices. The intriguing ability of CNCs to self-organize into a chiral nematic (cholesteric) liquid crystal phase with a helical arrangement has attracted significant interest, resulting in much research effort, as this arrangement gives dried CNC films a photonic band gap. The films thus acquire attractive optical properties, creating possibilities for use in applications such as security papers and mirrorless lasing. In this critical review, we discuss the sensitive balance between glass formation and liquid crystal self-assembly that governs the formation of the desired helical structure. We show that several as yet unclarified observations—some constituting severe obstacles for applications of CNCs—may result from competition between the two phenomena. Moreover, by comparison with the corresponding self-assembly processes of other rod-like nanoparticles, for example, carbon nanotubes and fd virus particles, we outline how further liquid crystal ordering phenomena may be expected from CNCs if the suspension parameters can be better controlled. Alternative interpretations of some unexpected phenomena are provided, and topics for future research are identified, as are new potential application strategies. Cellulose, a renewable biopolymer used throughout history, in particular to make clothing and paper, has recently attracted the interest of materials scientists in its nanocrystalline form. These nanofibers — produced by the acid hydrolysis of for instance cotton or wood — show promise for use in composites, cosmetics and medical devices. A Sweden-South Korea-based team led by Jan Lagerwall and Lennart Bergström now review the self-assembly of cellulose nanocrystals into a “chiral nematic” liquid-crystalline phase, which exhibits long-range ordering and adopts a helical superstructure. They compare the behavior of nanocellulose to other rod-like nanoparticles, such as nanotubes, and discuss the competitive gelation that can occur, which yields a glassy — rather than liquid-crystalline — phase. Through its chiral nematic arrangement, nanocellulose is endowed with interesting mechanical and optical properties. Furthermore, its liquid-crystalline suspensions can be processed into thin films, whose development and potential applications are discussed. The chiral liquid crystalline self-organization of cellulose nanocrystals into helical arrangements, giving the resulting materials photonic crystal properties and enhanced mechanical behavior, are comprehensively summarized and compared with other rod-like nanoparticles, for example, carbon nanotubes and fd virus. The consequences of the sensitive balance between liquid crystal formation and glass/gel formation are discussed in detail, in particular regarding the development toward control of helix pitch and orientation. Important topics for future studies are identified and suggestions for novel applications are made.

The important roles of reactive oxygen species in diseases related to aging and the necessity and benefits of antioxidative nutraceuticals in the prevention of diseases and promotion of healthy aging have been extensively reported in recent years. Oxygen is an essential component of living organisms. The generation of reactive oxygen species such as superoxide anion, hydrogen peroxide, hydroxyl radicals, and singlet oxygen is inevitable in aerobic metabolism of the body. Reactive oxygen species cause lipid oxidation, protein oxidation, DNA strand break and base modification, and modulation of gene expression. In the past several years, unprecedented progress has been made in the recognition and understanding of roles of reactive oxygen species in many diseases. These include atherosclerosis, vasospasms, cancers, trauma, stroke, asthma, hyperoxia, arthritis, heart attack, age pigments, dermatitis, cataractogenesis, retinal damage, hepatitis, liver injury, and periodontis, which are age-related. The body protects itself from the potential damages of reactive oxygen species. Its first line of defense is superoxide dismutases, glutathione peroxidases, and catalase. Scientists have indicated that antioxidant nutraceuticals supplied from daily diets quench the reactive oxygen species or are required as cofactors for antioxidant enzymes. Nutraceuticals play significant roles in the prevention of a number of age-related diseases and are essential for healthy aging. Epidemiological studies also reported the relevance of antioxidative nutraceuticals to health issues and the prevention of age-related diseases. Health-conscious consumers have made antioxidative nutraceuticals the leading trend in the food industry worldwide in recent years.

BACKGROUND: The worldwide demand for the organ replacement or tissue regeneration is increasing steadily. The advancements in tissue engineering and regenerative medicine have made it possible to regenerate such damaged organs or tissues into functional organ or tissue with the help of 3D bioprinting. The main component of the 3D bioprinting is the bioink, which is crucial for the development of functional organs or tissue structures. The bioinks used in 3D printing technology require so many properties which are vital and need to be considered during the selection. Combination of different methods and enhancements in properties are required to develop more successful bioinks for the 3D printing of organs or tissue structures. MAIN BODY: This review consists of the recent state-of-art of polymer-based bioinks used in 3D printing for applications in tissue engineering and regenerative medicine. The subsection projects the basic requirements for the selection of successful bioinks for 3D printing and developing 3D tissues or organ structures using combinations of bioinks such as cells, biomedical polymers and biosignals. Different bioink materials and their properties related to the biocompatibility, printability, mechanical properties, which are recently reported for 3D printing are discussed in detail. CONCLUSION: Many bioinks formulations have been reported from cell-biomaterials based bioinks to cell-based bioinks such as cell aggregates and tissue spheroids for tissue engineering and regenerative medicine applications. Interestingly, more tunable bioinks, which are biocompatible for live cells, printable and mechanically stable after printing are emerging with the help of functional polymeric biomaterials, their modifications and blending of cells and hydrogels. These approaches show the immense potential of these bioinks to produce more complex tissue/organ structures using 3D bioprinting in the future.

In this review article, we focus on the various types of materials used in biomedical implantable devices, including the polymeric materials used as substrates and for the packaging of such devices. Polymeric materials are used because of the ease of fabrication, flexibility, and their biocompatible nature as well as their wide range of mechanical, electrical, chemical, and thermal behaviors when combined with different materials as composites. Biocompatible and biostable polymers are extensively used to package implanted devices, with the main criteria that include gas permeability and water permeability of the packaging polymer to protect the electronic circuit of the device from moisture and ions inside the human body. Polymeric materials must also have considerable tensile strength and should be able to contain the device over the envisioned lifetime of the implant. For substrates, structural properties and, at times, electrical properties would be of greater concern. Section 1 gives an introduction of some medical devices and implants along with the material requirements and properties needed. Different synthetic polymeric materials such as polyvinylidene fluoride, polyethylene, polypropylene, polydimethylsiloxane, parylene, polyamide, polytetrafluoroethylene, poly(methyl methacrylate), polyimide, and polyurethane have been examined, and liquid crystalline polymers and nanocomposites have been evaluated as biomaterials that are suitable for biomedical packaging (section 2). A summary and glimpse of the future trend in this area has also been given (section 3). Materials and information used in this manuscript are adapted from papers published between 2010 and 2015 representing the most updated information available on each material.

Artificial intelligence (AI) systems offer effective support for online learning and teaching, including personalizing learning for students, automating instructors' routine tasks, and powering adaptive assessments. However, while the opportunities for AI are promising, the impact of AI systems on the culture of, norms in, and expectations about interactions between students and instructors are still elusive. In online learning, learner-instructor interaction (inter alia, communication, support, and presence) has a profound impact on students' satisfaction and learning outcomes. Thus, identifying how students and instructors perceive the impact of AI systems on their interaction is important to identify any gaps, challenges, or barriers preventing AI systems from achieving their intended potential and risking the safety of these interactions. To address this need for forward-looking decisions, we used Speed Dating with storyboards to analyze the authentic voices of 12 students and 11 instructors on diverse use cases of possible AI systems in online learning. Findings show that participants envision adopting AI systems in online learning can enable personalized learner-instructor interaction at scale but at the risk of violating social boundaries. Although AI systems have been positively recognized for improving the quantity and quality of communication, for providing just-in-time, personalized support for large-scale settings, and for improving the feeling of connection, there were concerns about responsibility, agency, and surveillance issues. These findings have implications for the design of AI systems to ensure explainability, human-in-the-loop, and careful data collection and presentation. Overall, contributions of this study include the design of AI system storyboards which are technically feasible and positively support learner-instructor interaction, capturing students' and instructors' concerns of AI systems through Speed Dating, and suggesting practical implications for maximizing the positive impact of AI systems while minimizing the negative ones.

Graphene-substrate-promoted human neural stem cell adhesion and its differentiation into neurons is reported. Microarray studies were performed to explore plausible explanation for this effect. Further, an electrical stimulation on differentiated cells via graphene electrodes is demonstrated. Detailed facts of importance to specialist readers are published as ”Supporting Information”. Such documents are peer-reviewed, but not copy-edited or typeset. They are made available as submitted by the authors. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Obesity is a prevalent and complex disease. The prevalence of obesity in Korea increased from 29.7% in 2010 to 35.7% in 2018, with the prevalence of abdominal obesity being 23.8% in 2018. Obesity contributes to medical costs and socioeconomic burden due to associated comorbidities. The treatment and management of obesity is changing based on new clinical evidence. The 2020 Korean Society for the Study of Obesity Guideline for the Management of Obesity in Korea summarizes evidence-based recommendations and treatment guidelines.

The recent expansion of the Internet of Things (IoT) and the consequent explosion in the volume of data produced by smart devices have led to the outsourcing of data to designated data centers. However, to manage these huge data stores, centralized data centers, such as cloud storage cannot afford auspicious way. There are many challenges that must be addressed in the traditional network architecture due to the rapid growth in the diversity and number of devices connected to the internet, which is not designed to provide high availability, real-time data delivery, scalability, security, resilience, and low latency. To address these issues, this paper proposes a novel blockchain-based distributed cloud architecture with a software defined networking (SDN) enable controller fog nodes at the edge of the network to meet the required design principles. The proposed model is a distributed cloud architecture based on blockchain technology, which provides low-cost, secure, and on-demand access to the most competitive computing infrastructures in an IoT network. By creating a distributed cloud infrastructure, the proposed model enables cost-effective high-performance computing. Furthermore, to bring computing resources to the edge of the IoT network and allow low latency access to large amounts of data in a secure manner, we provide a secure distributed fog node architecture that uses SDN and blockchain techniques. Fog nodes are distributed fog computing entities that allow the deployment of fog services, and are formed by multiple computing resources at the edge of the IoT network. We evaluated the performance of our proposed architecture and compared it with the existing models using various performance measures. The results of our evaluation show that performance is improved by reducing the induced delay, reducing the response time, increasing throughput, and the ability to detect real-time attacks in the IoT network with low performance overheads.

In this journal, Rainey and Steinbauer proposed a theory of effective government organizations, and Brewer and Selden conducted an empirical study with data from the 1996 Merit Principles Survey that confirmed most hypothesized relationships in the theoretical model of organizational performance. Following these studies, this study focuses only on the individual-level factors, such as job satisfaction, affective commitment, public service motivation, and organizational citizenship behavior. It empirically tests the effects of these variables on organizational performance in the public sector of Korea. When the survey data of 1,739 public employees in government agencies were analyzed, the hypothesized relationships in the proposed model were confirmed. I discuss the survey results in light of previous studies, especially those of Brewer and Selden.

Flexible tactile sensors capable of measuring mechanical stimuli via physical contact have attracted significant attention in the field of human-interactive systems. The utilization of tactile information can complement vision and/or sound interaction and provide new functionalities. Recent advancements in micro/nanotechnology, material science, and information technology have resulted in the development of high-performance tactile sensors that reach and even surpass the tactile sensing ability of human skin. Here, important advances in flexible tactile sensors over recent years are summarized, from sensor designs to system-level applications. This review focuses on the representative strategies based on design and material configurations for improving key performance parameters including sensitivity, detection range/linearity, response time/hysteresis, spatial resolution/crosstalk, multidirectional force detection, and insensitivity to other stimuli. System-level integration for practical applications beyond conceptual prototypes and promising applications, such as artificial electronic skin for robotics and prosthetics, wearable controllers for electronics, and bidirectional communication tools, are also discussed. Finally, perspectives on issues regarding further advances are provided.

Morphology-controlled nano- and microcrystals of ZnO (see figure) with different ratios of polar to nonpolar faces were synthesized through a soft-solution process. With these crystals, it is clearly demonstrated that a ZnO nanoplate with a large population of polar Zn(0001) faces is the most photocatalytically active morphology, underscoring the importance of the fine-tuning of face orientation in optimizing the activity of photocatalysts.

The growth in international research on public service motivation (PSM) raises a number of important questions about the degree to which the theory and research developed in one country can contribute to our understanding of PSM in other counties. To help address this issue, this study revisits the conceptual and operational definitions of PSM to address weaknesses previously noted in the literature. Although some important steps have been taken to both improve and internationalize the PSM scale, this work has been done incrementally. In contrast, this study takes a more systematic and comprehensive approach by combining the efforts of international PSM scholars to develop and then test a revised measurement instrument for PSM in 12 countries. Although the resulting four dimensional 16-item measure of PSM reported here provides a better theoretical and empirical foundation for the measurement of PSM, our results suggest that the exact meaning and scaling of PSM dimensions are likely to differ across cultures and languages. These results raise serious concerns regarding the ability to develop a single universal scale of PSM, or making direct comparisons of PSM across countries.

This paper proposes a novel tracker which is controlled by sequentially pursuing actions learned by deep reinforcement learning. In contrast to the existing trackers using deep networks, the proposed tracker is designed to achieve a light computation as well as satisfactory tracking accuracy in both location and scale. The deep network to control actions is pre-trained using various training sequences and fine-tuned during tracking for online adaptation to target and background changes. The pre-training is done by utilizing deep reinforcement learning as well as supervised learning. The use of reinforcement learning enables even partially labeled data to be successfully utilized for semi-supervised learning. Through evaluation of the OTB dataset, the proposed tracker is validated to achieve a competitive performance that is three times faster than state-of-the-art, deep network-based trackers. The fast version of the proposed method, which operates in real-time on GPU, outperforms the state-of-the-art real-time trackers.

This paper presents a new sensorless control scheme of a surface-mounted permanent-magnet (SMPM) motor using high-frequency voltage signal injection method based on the high-frequency impedance difference. In the SMPM motor, due to the flux of the permanent magnet, the stator core around the q-axis winding is saturated. This makes the magnetic saliency in the motor. This magnetic saliency has the information about the rotor position. The high-frequency voltage signal is injected into the motor in order to detect the magnetic saliency and estimate the rotor position. In this paper, the relationship between the high-frequency voltages and high-frequency currents is developed using the voltage equations at the high frequency, and the high-frequency impedance characteristics are analyzed experimentally under various conditions. The proposed sensorless control scheme makes it possible to drive the SMPM motor in the low-speed region including zero speed, even under heavy load conditions. The experimental results verify the performance of the proposed sensorless algorithm.

BACKGROUND AND AIMS: Smartphone addiction is a recent concern that has resulted from the dramatic increase in worldwide smartphone use. This study assessed the risk and protective factors associated with smartphone addiction in college students and compared these factors to those linked to Internet addiction. METHODS: College students (N = 448) in South Korea completed the Smartphone Addiction Scale, the Young's Internet Addiction Test, the Alcohol Use Disorders Identification Test, the Beck Depression Inventory I, the State-Trait Anxiety Inventory (Trait Version), the Character Strengths Test, and the Connor-Davidson Resilience Scale. The data were analyzed using multiple linear regression analyses. RESULTS: The risk factors for smartphone addiction were female gender, Internet use, alcohol use, and anxiety, while the protective factors were depression and temperance. In contrast, the risk factors for Internet addiction were male gender, smartphone use, anxiety, and wisdom/knowledge, while the protective factor was courage. Discussion These differences may result from unique features of smartphones, such as high availability and primary use as a tool for interpersonal relationships. CONCLUSIONS: Our findings will aid clinicians in distinguishing between predictive factors for smartphone and Internet addiction and can consequently be utilized in the prevention and treatment of smartphone addiction.

Soft wearable robots are good alternatives to rigid-frame exoskeletons because they are compact and lightweight. This article describes a soft wearable hand robot called the Exo-Glove that uses a soft tendon routing system and an underactuation adaptive mechanism. The proposed system can be used to develop other types of soft wearable robots. The glove part of the system is compact and weighs 194 g. The results conducted using a healthy subject showed sufficient performance for the execution of daily life activities, namely a pinch force of 20 N, a wrap grasp force of 40 N, and a maximum grasped object size of 76 mm. The use of an underactuation mechanism enabled the grasping of objects of various shapes without active control. A subject suffering from paralysis of the hands due to a spinal cord injury was able to use the glove to grasp objects of various shapes.

We propose novel cooperative spectrum sensing (CSS) algorithms for cognitive radio (CR) networks based on machine learning techniques which are used for pattern classification. In this regard, unsupervised (e.g., K-means clustering and Gaussian mixture model (GMM)) and supervised (e.g., support vector machine (SVM) and weighted K-nearest-neighbor (KNN)) learning-based classification techniques are implemented for CSS. For a radio channel, the vector of the energy levels estimated at CR devices is treated as a feature vector and fed into a classifier to decide whether the channel is available or not. The classifier categorizes each feature vector into either of the two classes, namely, the "channel available class" and the "channel unavailable class". Prior to the online classification, the classifier needs to go through a training phase. For classification, the K-means clustering algorithm partitions the training feature vectors into K clusters, where each cluster corresponds to a combined state of primary users (PUs) and then the classifier determines the class the test energy vector belongs to. The GMM obtains a mixture of Gaussian density functions that well describes the training feature vectors. In the case of the SVM, the support vectors (i.e., a subset of training vectors which fully specify the decision function) are obtained by maximizing the margin between the separating hyperplane and the training feature vectors. Furthermore, the weighted KNN classification technique is proposed for CSS for which the weight of each feature vector is calculated by evaluating the area under the receiver operating characteristic (ROC) curve of that feature vector. The performance of each classification technique is quantified in terms of the average training time, the sample classification delay, and the ROC curve. Our comparative results clearly reveal that the proposed algorithms outperform the existing state-of-the-art CSS techniques.