Uric acid sensing based on sandwich carbon electrode sets decorated with gold nanoparticles

Department of Mechanical EngineeringThis study reports an enzymatic uric acid sensor with enhanced electrochemical sensing performance by electrodepositing gold nanoparticles on sandwich carbon electrodes. The improvement of sensor performance was based on the structural advantage of sandwich carbon electrode sets, consisting of suspended carbon mesh electrode (SME) and substrate bound interdigitated electrodes (IDE). The uricase enzyme was selectively immobilized to IDE and by-product generated from uricase-uric acid reaction was detected in SME to track the uric acid concentration. As the SME is completely covering the IDE, the by-product can be detected with SME before being diffused into the bulk solution. The electrode structure was fabricated using simple and cost-effective technique known as carbon-microelectromechanical-systems (C-MEMS). The polymer structure was patterned using successive photolithography and converted into carbon electrode by vacuum pyrolysis. This unique technique enabled the wafer-level fabrication of two separate but adjacent electrodesSME and IDE. To enhance the surface reactivity and surface area of electrodes, gold nanoparticles were electrodeposited to the sandwich carbon electrodes. As the surface area of IDE is larger compared to the simple planar electrode, the electrodeposition of gold nanoparticles is improved on IDE. The uricase enzyme was selectively immobilized to the IDE with selective electrochemical surface modification using aryl diazonium reduction. Uricase enzyme was selectively immobilized by bonding with diazonium deposited to IDE. The selective immobilization of enzyme allowed the maintenance of SME surface electroactivity. Uric acid sensing performance was evaluated by conducting chronoamperometry test with the sensor structure for the uric acid concentration range of 0 to 1000 ??M. From structural advantage of sandwich carbon electrodes and high electrochemical reactivity of gold nanoparticles, the developed uric acid sensor was capable of sensitive uric acid sensing with low lower limit of detection (LOD) of 6.25 ??M. As uric acid concentration of healthy person???s blood is ranged from 120 to 450 ??M, the sensing range of this uric acid sensor is appropriate in detecting uric acid concentration in human blood. The sensitivity was calculated as change in current signal per uric acid concentration change divided with sensor operation area. The sandwich electrode structure showed high sensitivity with two linear ranges of uric acid concentration. The calculated sensitivity was 742.11 ??A??mM???1??cm???2 for low concentration range (0 ??? 100 ??M) and 553.26 ??A??mM???1??cm???2 for high concentration range (100 ??? 1000 ??M).clos

Development Cooperation Decentralization by Local Government: A Comparative Study of Aid Policy in the United Kingdom and Germany [국제개발협력의 지방분권화에 대한 소고 : 영국과 독일의 원조정책 비교연구]

This paper aims to discuss effectiveness and obstacles of development cooperation decentralization by employing a comparative case study of United Kingdom and Germany. With SDGs, international community has emphasized the importance of decentralization of development cooperaton, which means that the central governments admits roles and importance of local governments in aid activities, and allows decentralized approach by the local governments towards developing countries at the local level. Findings of this study have confirmed that decentralization can improve aid effectiveness in developing countries at the local level. At the same time, the German experience implies that we can minimize obstacles of decentralization in practice. This research suggests to conduct a further research on more case studies of decentralization so that we can contribute to development and advancement of decentralized approach of development cooperation in order to achieve development effectiveness both at the international level and local level. In the end, we expect that the results of the study, which employed a methodology of combining a theoretical approach into the policy cases, can contribute to the field of Area Studies as well as Development Studies

DeepCompass: AI-driven Location-Orientation Synchronization for Navigating Platforms

In current navigating platforms, the user's orientation is typically estimated based on the difference between two consecutive locations. In other words, the orientation cannot be identified until the second location is taken. This asynchronous location-orientation identification often leads to our real-life question: Why does my navigator tell the wrong direction of my car at the beginning? We propose DeepCompass to identify the user's orientation by bridging the gap between the street-view and the user-view images. First, we explore suitable model architectures and design corresponding input configuration. Second, we demonstrate artificial transformation techniques (e.g., style transfer and road segmentation) to minimize the disparity between the street-view and the user's real-time experience. We evaluate DeepCompass with extensive evaluation in various driving conditions. DeepCompass does not require additional hardware and is also not susceptible to external interference, in contrast to magnetometer-based navigator. This highlights the potential of DeepCompass as an add-on to existing sensor-based orientation detection methods.Comment: 7page with 3 supplemental page

Infection-related and lifestyle-related cancer burden in Kampala, Uganda: Projection of the future cancer incidence up to 2030

OBJECTIVES: In Uganda, infection-related cancers have made the greatest contribution to cancer burden in the past; however, burden from lifestyle-related cancers has increased recently. Using the Kampala Cancer Registry data, we projected incidence of top five cancers, namely, Kaposi sarcoma (KS), cervical, breast and prostate cancer, and non-Hodgkin\u27s lymphoma (NHL) in Uganda. DESIGN: Trend analysis of cancer registry data. SETTING: Kampala Cancer Registry, Uganda. MAIN OUTCOME MEASURE: Cancer incidence data from 2001 to 2015 were used and projected to 2030. Population data were obtained from the Uganda Bureau of Statistics. Age-standardised incidence rates (ASRs) and their trends over the observed and projected period were calculated. Percentage change in cancer incidence was calculated to determine whether cancer incidence changes were attributable to cancer risk changes or population changes. RESULTS: It was projected that the incidence rates of KS and NHL continue to decrease by 22.6% and 37.3%, respectively. The ASR of KS was expected to decline from 29.6 per 100 000 population to 10.4, while ASR of NHL was expected to decrease from 7.6 to 3.2. In contrast, cervical, breast and prostate cancer incidence were projected to increase by 35.3%, 57.7% and 33.4%, respectively. The ASRs of cervical and breast were projected to increase up to 66.1 and 48.4 per 100 000 women. The ASR of prostate cancer was estimated to increase from 41.6 to 60.5 per 100 000 men. These changes were due to changes in risk factors and population growth. CONCLUSION: Our results suggest a rapid shift in the profile of common cancers in Uganda, reflecting a new trend emerging in low/middle-income countries. This change in cancer spectrum, from infection-related to lifestyle-related, yields another challenge to cancer control programmes in resource-limited countries. Forthcoming cancer control programmes should include a substantial focus on lifestyle-related cancers, while infectious disease control programmes should be maintained

Cream: Visually-Situated Natural Language Understanding with Contrastive Reading Model and Frozen Large Language Models

Advances in Large Language Models (LLMs) have inspired a surge of research exploring their expansion into the visual domain. While recent models exhibit promise in generating abstract captions for images and conducting natural conversations, their performance on text-rich images leaves room for improvement. In this paper, we propose the Contrastive Reading Model (Cream), a novel neural architecture designed to enhance the language-image understanding capability of LLMs by capturing intricate details typically overlooked by existing methods. Cream integrates vision and auxiliary encoders, complemented by a contrastive feature alignment technique, resulting in a more effective understanding of textual information within document images. Our approach, thus, seeks to bridge the gap between vision and language understanding, paving the way for more sophisticated Document Intelligence Assistants. Rigorous evaluations across diverse tasks, such as visual question answering on document images, demonstrate the efficacy of Cream as a state-of-the-art model in the field of visual document understanding. We provide our codebase and newly-generated datasets at https://github.com/naver-ai/crea

NKT cells promote antibody-induced joint inflammation by suppressing transforming growth factor β1 production

Although NKT cells has been known to exert protective roles in the development of autoimmune diseases, the functional roles of NKT cells in the downstream events of antibody-induced joint inflammation remain unknown. Thus, we explored the functional roles of NKT cells in antibody-induced arthritis using the K/BxN serum transfer model. NKT cell–deficient mice were resistant to the development of arthritis, and wild-type mice administrated with α-galactosyl ceramide, a potent NKT cell activator, aggravated arthritis. In CD1d−/− mice, transforming growth factor (TGF)-β1 was found to be elevated in joint tissues, and the blockade of TGF-β1 using neutralizing monoclonal antibodies restored arthritis. The administration of recombinant TGF-β1 into C57BL/6 mice reduced joint inflammation. Moreover, the adoptive transfer of NKT cells into CD1d−/− mice restored arthritis and reduced TGF-β1 production. In vitro assay demonstrated that interleukin (IL)-4 and interferon (IFN)-γ were involved in suppressing TGF-β1 production in joint cells. The adoptive transfer of NKT cells from IL-4−/− or IFN-γ−/− mice did not reverse arthritis and TGF-β1 production in CD1d−/− mice. In conclusion, NKT cells producing IL-4 and IFN-γ play a role in immune complex–induced joint inflammation by regulating TGF-β1

A new marine ciliate, Metaurostylopsis antarctica nov. spec. (Ciliophora, Urostylida) from the Antarctic Ocean

In this study, a new marine urostylid ciliate, Metaurostylopsis antarctica nov. spec. collected from the Antarctic Ocean was investigated using morphological, morphometrical, and molecular methods. Metaurostylopsis antarctica nov. spec. is characterized as follows: slender to ellipsoid form in body shape; two types of cortical granules, ellipsoid large one (type I, yellow-green, 1.5 × 1 μm) in rows along dorsal kineties and cirri, circular small one (type II, colourless, 0.3 μm in diameter) scattered throughout whole body; 19–24 adoral membranelles, 4 frontal cirri, 2–5 frontoterminal cirri, 1 buccal and 2 transverse cirri; 3–5 midventral pairs, 10–15 cirri of midventral row; 1 right and 2 left marginal rows; 3 dorsal kineties; about 43 macronuclear nodules. This new species mainly differs from the congeners by the number of marginal rows (1 vs. 3 or more on right side; 2 vs. 3 or more on left side). In addition, proter’s oral primordium  developed on the right side of the oral cavity (vs. in center of oral cavity), and the rightmost anlage splits into two parts, nam ely, the frontoterminal cirri and a transverse cirrus (vs. only frontoterminal cirri). Inter-specific dissimilarities of the SSU rRNA gene between the congeners range from 3.3 to 4.4%