Pohang University of Science and Technology

The last decade has seen a sharp increase in the number of scientific publications describing physiological and pathological functions of extracellular vesicles (EVs), a collective term covering various subtypes of cell-released, membranous structures, called exosomes, microvesicles, microparticles, ectosomes, oncosomes, apoptotic bodies, and many other names. However, specific issues arise when working with these entities, whose size and amount often make them difficult to obtain as relatively pure preparations, and to characterize properly. The International Society for Extracellular Vesicles (ISEV) proposed Minimal Information for Studies of Extracellular Vesicles ("MISEV") guidelines for the field in 2014. We now update these "MISEV2014" guidelines based on evolution of the collective knowledge in the last four years. An important point to consider is that ascribing a specific function to EVs in general, or to subtypes of EVs, requires reporting of specific information beyond mere description of function in a crude, potentially contaminated, and heterogeneous preparation. For example, claims that exosomes are endowed with exquisite and specific activities remain difficult to support experimentally, given our still limited knowledge of their specific molecular machineries of biogenesis and release, as compared with other biophysically similar EVs. The MISEV2018 guidelines include tables and outlines of suggested protocols and steps to follow to document specific EV-associated functional activities. Finally, a checklist is provided with summaries of key points.

Using inorganic carbon measurements from an international survey effort in the 1990s and a tracer-based separation technique, we estimate a global oceanic anthropogenic carbon dioxide (CO2) sink for the period from 1800 to 1994 of 118 +/- 19 petagrams of carbon. The oceanic sink accounts for approximately 48% of the total fossil-fuel and cement-manufacturing emissions, implying that the terrestrial biosphere was a net source of CO2 to the atmosphere of about 39 +/- 28 petagrams of carbon for this period. The current fraction of total anthropogenic CO2 emissions stored in the ocean appears to be about one-third of the long-term potential.

We propose a novel semantic segmentation algorithm by learning a deep deconvolution network. We learn the network on top of the convolutional layers adopted from VGG 16-layer net. The deconvolution network is composed of deconvolution and unpooling layers, which identify pixelwise class labels and predict segmentation masks. We apply the trained network to each proposal in an input image, and construct the final semantic segmentation map by combining the results from all proposals in a simple manner. The proposed algorithm mitigates the limitations of the existing methods based on fully convolutional networks by integrating deep deconvolution network and proposal-wise prediction, our segmentation method typically identifies detailed structures and handles objects in multiple scales naturally. Our network demonstrates outstanding performance in PASCAL VOC 2012 dataset, and we achieve the best accuracy (72.5%) among the methods trained without using Microsoft COCO dataset through ensemble with the fully convolutional network.

This review provides insight into the various ways to functionalize graphene and graphene derivatives, thereby expanding the number of potential applications for graphenebased materials. The functionalization modes can be classified according to the method and materials used and as such have been categorized as covalent functionalization, noncovalent functionalization, substitutional doping of graphene, and hybridization with nanoparticles, nanowires, and other materials. These various methods of functionalization offer various ways to expand on the current uses of graphene, that is, bioimaging or band gap opening, which can be used in electronics.

Organic-inorganic hybrid perovskites are emerging low-cost emitters with very high color purity, but their low luminescent efficiency is a critical drawback. We boosted the current efficiency (CE) of perovskite light-emitting diodes with a simple bilayer structure to 42.9 candela per ampere, similar to the CE of phosphorescent organic light-emitting diodes, with two modifications: We prevented the formation of metallic lead (Pb) atoms that cause strong exciton quenching through a small increase in methylammonium bromide (MABr) molar proportion, and we spatially confined the exciton in uniform MAPbBr3 nanograins (average diameter = 99.7 nanometers) formed by a nanocrystal pinning process and concomitant reduction of exciton diffusion length to 67 nanometers. These changes caused substantial increases in steady-state photoluminescence intensity and efficiency of MAPbBr3 nanograin layers.

ADVERTISEMENT RETURN TO ISSUEPREVReviewNEXTHomochiral Metal–Organic Frameworks for Asymmetric Heterogeneous CatalysisMinyoung Yoon, Renganathan Srirambalaji, and Kimoon Kim*View Author Information Center for Smart Supramolecules, Department of Chemistry, and Division of Advanced Materials Science (WCU project), Pohang University of Science and Technology, San 31 Hyojadong, Pohang 790-784, Republic of Korea*E-mail: [email protected]Cite this: Chem. Rev. 2012, 112, 2, 1196–1231Publication Date (Web):November 15, 2011Publication History Received10 August 2011Published online15 November 2011Published inissue 8 February 2012https://pubs.acs.org/doi/10.1021/cr2003147https://doi.org/10.1021/cr2003147review-articleACS PublicationsCopyright © 2011 American Chemical SocietyRequest reuse permissionsArticle Views30667Altmetric-Citations2671LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-Alertsclose SUBJECTS:Catalysts,Ions,Ligands,Metal organic frameworks,Metals Get e-Alerts

We propose a novel visual tracking algorithm based on the representations from a discriminatively trained Convolutional Neural Network (CNN). Our algorithm pretrains a CNN using a large set of videos with tracking ground-truths to obtain a generic target representation. Our network is composed of shared layers and multiple branches of domain-specific layers, where domains correspond to individual training sequences and each branch is responsible for binary classification to identify target in each domain. We train each domain in the network iteratively to obtain generic target representations in the shared layers. When tracking a target in a new sequence, we construct a new network by combining the shared layers in the pretrained CNN with a new binary classification layer, which is updated online. Online tracking is performed by evaluating the candidate windows randomly sampled around the previous target state. The proposed algorithm illustrates outstanding performance in existing tracking benchmarks.

Secreted membrane-enclosed vesicles, collectively called extracellular vesicles (EVs), which include exosomes, ectosomes, microvesicles, microparticles, apoptotic bodies and other EV subsets, encompass a very rapidly growing scientific field in biology and medicine. Importantly, it is currently technically challenging to obtain a totally pure EV fraction free from non-vesicular components for functional studies, and therefore there is a need to establish guidelines for analyses of these vesicles and reporting of scientific studies on EV biology. Here, the International Society for Extracellular Vesicles (ISEV) provides researchers with a minimal set of biochemical, biophysical and functional standards that should be used to attribute any specific biological cargo or functions to EVs.

Rising atmospheric carbon dioxide (CO2) concentrations over the past two centuries have led to greater CO2 uptake by the oceans. This acidification process has changed the saturation state of the oceans with respect to calcium carbonate (CaCO3) particles. Here we estimate the in situ CaCO3 dissolution rates for the global oceans from total alkalinity and chlorofluorocarbon data, and we also discuss the future impacts of anthropogenic CO2 on CaCO3 shell-forming species. CaCO3 dissolution rates, ranging from 0.003 to 1.2 micromoles per kilogram per year, are observed beginning near the aragonite saturation horizon. The total water column CaCO3 dissolution rate for the global oceans is approximately 0.5 +/- 0.2 petagrams of CaCO3-C per year, which is approximately 45 to 65% of the export production of CaCO3.

Magnetite-graphene hybrids have been synthesized via a chemical reaction with a magnetite particle size of approximately 10 nm. The composites are superparamagnetic at room temperature and can be separated by an external magnetic field. As compared to bare magnetite particles, the hybrids show a high binding capacity for As(III) and As(V), whose presence in the drinking water in wide areas of South Asia has been a huge problem. Their high binding capacity is due to the increased adsorption sites in the M-RGO composite which occurs by reducing the aggregation of bare magnetite. Since the composites show near complete (over 99.9%) arsenic removal within 1 ppb, they are practically usable for arsenic separation from water.

Leaf senescence constitutes the final stage of leaf development and is critical for plants' fitness as nutrient relocation from leaves to reproducing seeds is achieved through this process. Leaf senescence involves a coordinated action at the cellular, tissue, organ, and organism levels under the control of a highly regulated genetic program. Major breakthroughs in the molecular understanding of leaf senescence were achieved through characterization of various senescence mutants and senescence-associated genes, which revealed the nature of regulatory factors and a highly complex molecular regulatory network underlying leaf senescence. The genetically identified regulatory factors include transcription regulators, receptors and signaling components for hormones and stress responses, and regulators of metabolism. Key issues still need to be elucidated, including cellular-level analysis of senescence-associated cell death, the mechanism of coordination among cellular-, organ-, and organism-level senescence, the integration mechanism of various senescence-affecting signals, and the nature and control of leaf age.

The ability to print and pattern all the components that make up a tissue (cells and matrix materials) in three dimensions to generate structures similar to tissues is an exciting prospect of bioprinting. However, the majority of the matrix materials used so far for bioprinting cannot represent the complexity of natural extracellular matrix (ECM) and thus are unable to reconstitute the intrinsic cellular morphologies and functions. Here, we develop a method for the bioprinting of cell-laden constructs with novel decellularized extracellular matrix (dECM) bioink capable of providing an optimized microenvironment conducive to the growth of three-dimensional structured tissue. We show the versatility and flexibility of the developed bioprinting process using tissue-specific dECM bioinks, including adipose, cartilage and heart tissues, capable of providing crucial cues for cells engraftment, survival and long-term function. We achieve high cell viability and functionality of the printed dECM structures using our bioprinting method. The application of 3D printing to biomaterials presents interesting possibilities for tissue engineering. Here, the authors show that a printing medium derived from an extracellular matrix can be applied to printing tissue analogues with enhanced cell compatibility.

The gastrointestinal tract is a specialized organ in which dynamic interactions between host cells and the complex environment occur in addition to food digestion. Together with the chemical barrier of the mucosal layer and the cellular immune system, the epithelial cell layer performs a pivotal role as the first physical barrier against external factors and maintains a symbiotic relationship with commensal bacteria. The tight junction proteins, including occludin, claudins, and zonula occludens, are crucial for the maintenance of epithelial barrier integrity. To allow the transport of essential molecules and restrict harmful substances, the intracellular signaling transduction system and a number of extracellular stimuli such as cytokines, small GTPases, and post-translational modifications dynamically modulate the tight junction protein complexes. An imbalance in these regulations leads to compromised barrier integrity and is linked with pathological conditions. Despite the obscurity of the causal relationship, the loss of barrier integrity is considered to contribute to inflammatory bowel disease, obesity, and metabolic disorders. The elucidation of the role of diseases in barrier integrity and the underlying regulatory mechanisms have improved our understanding of the intestinal barrier to allow the development of novel and potent therapeutic approaches.

During the 1990s, ocean sampling expeditions were carried out as part of the World Ocean Circulation Experiment (WOCE), the Joint Global Ocean Flux Study (JGOFS), and the Ocean Atmosphere Carbon Exchange Study (OACES). Subsequently, a group of U.S. scientists synthesized the data into easily usable and readily available products. This collaboration is known as the Global Ocean Data Analysis Project (GLODAP). Results were merged into a common format data set, segregated by ocean. For comparison purposes, each ocean data set includes a small number of high‐quality historical cruises. The data were subjected to rigorous quality control procedures to eliminate systematic data measurement biases. The calibrated 1990s data were used to estimate anthropogenic CO 2 , potential alkalinity, CFC watermass ages, CFC partial pressure, bomb‐produced radiocarbon, and natural radiocarbon. These quantities were merged into the measured data files. The data were used to produce objectively gridded property maps at a 1° resolution on 33 depth surfaces chosen to match existing climatologies for temperature, salinity, oxygen, and nutrients. The mapped fields are interpreted as an annual mean distribution in spite of the inaccuracy in that assumption. Both the calibrated data and the gridded products are available from the Carbon Dioxide Information Analysis Center. Here we describe the important details of the data treatment and the mapping procedure, and present summary quantities and integrals for the various parameters.

The supramolecular chemistry of cucurbituril, a synthetic receptor, is fascinating because of the remarkable guest binding behavior of the host. Studies in the field, however, have met with limitations, since the only species known was the hexameric macrocyclic compound, cucurbit[6]uril. Recently we synthesized its homologues, cucurbit[n]uril (n = 5, 7, 8), and derivatives. These new members of the cucurbituril family have expanded the scope further, and interest in them has grown enormously. This Account is a compilation of recent literature covering the syntheses of the homologues and derivatives, and their supramolecular chemistry.

Real-time polymerase chain reaction (PCR) is a highly sensitive method that can be used for the detection and quantification of microbial populations without cultivating them in anaerobic processes and environmental samples. This work was conducted to design primer and probe sets for the detection of methanogens using a real-time PCR with the TaqMan system. Six group-specific methanogenic primer and probe sets were designed. These sets separately detect four orders (Methanococcales, Methanobacteriales, Methanomicrobiales, and Methanosarcinales) along with two families (Methanosarcinaceae and Methanosaetaceae) of the order Methanosarcinales. We also designed the universal primer and probe sets that specifically detect the 16S rDNA of prokaryotes and of the domain Bacteria and Archaea, and which are fully compatible with the TaqMan real-time PCR system. Target-group specificity of each primer and probe set was empirically verified by testing DNA isolated from 28 archaeal cultures and by analyzing potential false results. In general, each primer and probe set was very specific to the target group. The primer and probe sets designed in this study can be used to detect and quantify the order-level (family-level in the case of Methanosarcinales) methanogenic groups in anaerobic biological processes and various environments.

Although various carbon nanomaterials including activated carbon, carbon nanotubes, and graphene have been successfully demonstrated for high-performance ultracapacitors, their capacitances need to be improved further for wider and more challenging applications. Herein, using nitrogen-doped graphene produced by a simple plasma process, we developed ultracapacitors whose capacitances (∼280 F/g(electrode)) are about 4 times larger than those of pristine graphene based counterparts without sacrificing other essential and useful properties for ultracapacitor operations including excellent cycle life (>200,000), high power capability, and compatibility with flexible substrates. While we were trying to understand the improved capacitance using scanning photoemission microscopy with a capability of probing local nitrogen-carbon bonding configurations within a single sheet of graphene, we observed interesting microscopic features of N-configurations: N-doped sites even at basal planes, distinctive distributions of N-configurations between edges and basal planes, and their distinctive evolutions with plasma duration. The local N-configuration mappings during plasma treatment, alongside binding energy calculated by density functional theory, revealed that the origin of the improved capacitance is a certain N-configuration at basal planes.

ADVERTISEMENT RETURN TO ISSUEPREVCommunicationNEXTNew Cucurbituril Homologues: Syntheses, Isolation, Characterization, and X-ray Crystal Structures of Cucurbit[n]uril (n = 5, 7, and 8)Jaheon Kim, In-Sun Jung, Soo-Young Kim, Eunsung Lee, Jin-Koo Kang, Shigeru Sakamoto, Kentaro Yamaguchi, and Kimoon KimView Author Information National Creative Research Initiative Center for Smart Supramolecules and Department of Chemistry Pohang University of Science and Technology San 31 Hyojadong, Pohang 790-784, Republic of Korea Chemical Analysis Center, Chiba University 1-33 Yayoicho, Inageku, Chiba 263-8522, Japan Cite this: J. Am. Chem. Soc. 2000, 122, 3, 540–541Publication Date (Web):January 8, 2000Publication History Received17 September 1999Published online8 January 2000Published inissue 1 January 2000https://pubs.acs.org/doi/10.1021/ja993376phttps://doi.org/10.1021/ja993376prapid-communicationACS PublicationsCopyright © 2000 American Chemical SocietyRequest reuse permissionsArticle Views18853Altmetric-Citations1471LEARN ABOUT THESE METRICSArticle Views are the COUNTER-compliant sum of full text article downloads since November 2008 (both PDF and HTML) across all institutions and individuals. These metrics are regularly updated to reflect usage leading up to the last few days.Citations are the number of other articles citing this article, calculated by Crossref and updated daily. Find more information about Crossref citation counts.The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon will load a page at altmetric.com with additional details about the score and the social media presence for the given article. Find more information on the Altmetric Attention Score and how the score is calculated. Share Add toView InAdd Full Text with ReferenceAdd Description ExportRISCitationCitation and abstractCitation and referencesMore Options Share onFacebookTwitterWechatLinked InRedditEmail Other access optionsGet e-AlertscloseSupporting Info (2)»Supporting Information Supporting Information SUBJECTS:Aromatic compounds,Cavities,Crystal structure,Mixtures,Molecules Get e-Alerts

Knowledge distillation aims at transferring knowledge acquired in one model (a teacher) to another model (a student) that is typically smaller. Previous approaches can be expressed as a form of training the student to mimic output activations of individual data examples represented by the teacher. We introduce a novel approach, dubbed relational knowledge distillation (RKD), that transfers mutual relations of data examples instead. For concrete realizations of RKD, we propose distance-wise and angle-wise distillation losses that penalize structural differences in relations. Experiments conducted on different tasks show that the proposed method improves educated student models with a significant margin. In particular for metric learning, it allows students to outperform their teachers' performance, achieving the state of the arts on standard benchmark datasets.

We investigated the electronic structure of 5d transition-metal oxide Sr2IrO4 using angle-resolved photoemission, optical conductivity, x-ray absorption measurements, and first-principles band calculations. The system was found to be well described by novel effective total angular momentum Jeff states, in which the relativistic spin-orbit coupling is fully taken into account under a large crystal field. Despite delocalized Ir 5d states, the Jeff states form such narrow bands that even a small correlation energy leads to the Jeff=1/2 Mott ground state with unique electronic and magnetic behaviors, suggesting a new class of Jeff quantum spin driven correlated-electron phenomena.