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Assessing the skin-whitening property of plant extracts from taiwanese species using zebrafish as a rapid screening platform

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Arabian Journal of Chemistry 2023年第9期16卷

作者： Hsiao, Sui-Wen Kuo, I-Chih Syu, Li-Ling Lee, Tzong-Huei Cheng, Chia-Hsiung Mei, Hui-Ching Lee, Ching-Kuo Ph.D. Program in Drug Discovery and Development Industry College of Pharmacy Taipei Medical University Taipei11031 Taiwan School of Biomedical Engineering University of British Columbia VancouverBC Canada Graduate Institute of Pharmacognosy Taipei Medical University Taipei11031 Taiwan Institute of Fisheries Science National Taiwan University Taipei10617 Taiwan Department of Biochemistry and Molecular Cell Biology School of Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan Department of Science Education National Taipei University of Education Taipei10671 Taiwan School of Pharmacy Taipei Medical University Taipei11031 Taiwan

Zebrafish can be used as a phenotype-based fast-screening platform for the discovery of skin-whitening products by observing the formation of melanin in vivo through a dissecting microscope. In this study, we first evaluated commercial whitening ingredients to confirm the potency of the zebrafish model. The zebrafish screening system verified that verbascoside and 5 other commonly used commercial skin-whitening compounds– including sodium ascorbate, azelaic acid, transamin, kojic acid, and PTU- significantly reduce melanin content in a dose-dependent manner. We subsequently conducted preliminary screening of 123 natural sources to identify those with whitening property. Through a two-step screening process, anti-melanogenesis effects of 4 and 9 candidates at low and high concentration were verified respectively. The toxicity, mortality, and malformation of zebrafish embryo were also evaluated. We further investigated the components of C. manghas L. and found 6 major compounds, one of which was manghaslin, a compound known for its melanin-suppressing effect on zebrafish without cytotoxicity. With these properties, manghaslin is a promising candidate as a skin lightening agent or a treatment for melanoma. © 2023 The Authors

关键词： Melanin

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Low-concentration imiquimod treatment promotes enhanced skin barrier functions through epidermal melanization reaction regulation

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Environmental Toxicology 2024年第9期39卷 4360-4371页

作者： Lin, Tzu-Kai Tsai, Chia-Lun Tsai, Bruce Chi-Kang Kuo, Chia-Hua Ho, Tsung-Jung Hsieh, dennis Jine-Yuan Kuo, Wei-Wen Huang, Chih-Yang Department of Dermatology Hualien Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Hualien Taiwan School of Medicine Tzu Chi University Hualien Taiwan Cardiovascular and Mitochondrial Related Disease Research Center Hualien Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Hualien Taiwan Institute of Sports Sciences University of Taipei Taipei Taiwan Laboratory of Exercise Biochemistry Institute of Sports Sciences University of Taipei Tianmu Campus Taipei Taiwan Department of Kinesiology and Health Science College of William and Mary WilliamsburgVA United States Department of Chinese Medicine Hualien Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Hualien Taiwan Integration Center of Traditional Chinese and Modern Medicine Hualien Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Hualien Taiwan School of Post-Baccalaureate Chinese Medicine College of Medicine Tzu Chi University Hualien Taiwan School of Medical Laboratory and Biotechnology Chung Shan Medical University Taichung Taiwan Clinical Laboratory Chung Shan Medical University Hospital Taichung Taiwan Department of Biological Science and Technology College of Life Sciences China Medical University Taichung Taiwan Ph.D. Program for Biotechnology Industry China Medical University Taichung Taiwan School of Pharmacy China Medical University Taichung Taiwan Graduate Institute of Biomedical Sciences China Medical University Taichung Taiwan Department of Medical Research China Medical University Hospital China Medical University Taichung Taiwan Department of Medical Laboratory Science and Biotechnology Asia University Taichung Taiwan Center of General Education Buddhist Tzu Chi Medical Foundation Tzu Chi University of Science and Technology Hualien Taiwan

The primary function of the skin is to form a mechanical, permeability, antimicrobial, and ultraviolet radiation barrier, which is essential for maintaining physiological homeostasis. Our previous studies demonstrated that cutaneous pigmentation could promote skin barrier function in addition to providing anti-ultraviolet irradiation defense. The present study aimed to develop a new regimen that enhances skin barrier function by regulating skin pigmentation using low-concentration imiquimod. Results showed that topical application of low-concentration imiquimod effectively induced skin hyperpigmentation in the dorsal skin and external ear of mice without inducing inflammatory cell infiltration. An in vitro study also revealed that low-concentration imiquimod did not induce any cytotoxic effects on melanoma cells but triggered excessive melanin synthesis. In coculture systems, low-concentration imiquimod was noted to increase tyrosinase activity in a broader cellular context, revealing the potential role of neighboring cells in melanin production. The next-generation sequencing result indicated that PKCη and dnm3 might regulate melanin synthesis and release during imiquimod treatment. Overall, our study presents new insights into the regulation of melanin production by low-concentration imiquimod, both in a mice model and cultured cells. Furthermore, our study highlights the potential benefits of imiquimod in promoting melanin synthesis without causing skin disruptions or inducing inflammation, validating its potential to serve as a method for enhancing skin barrier functions by regulating the epidermal melanization reaction. © 2024 Wiley Periodicals LLC.

关键词： Irradiation

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Snake-scale stimulated robust biomimetic composite triboelectric layer for energy harvesting and smart health monitoring

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Nano Energy 2024年 122卷

作者： Huang, Ming-Zheng Parashar, Parag Chen, An-Rong Shi, Shih-Chen Tseng, Yao-Hsuan Lim, Kee Chin Yeh, Hsuan-Yu Pal, Arnab Kang, dun-Yen Lin, Zong-Hong Institute of Biomedical Engineering National Tsing Hua University Hsinchu 30013 Taiwan Department of Biomedical Engineering National Taiwan University Taipei 10617 Taiwan Department of Chemical Engineering National Taiwan University Taipei 10617 Taiwan Department of Materials Science and Engineering National Tsing Hua University Hsinchu 30013 Taiwan Department of Mechanical Engineering National Cheng Kung University Tainan 70101 Taiwan International Intercollegiate Ph.D. Program National Tsing Hua University Hsinchu 30013 Taiwan Department of Power Mechanical Engineering National Tsing Hua University Hsinchu 30013 Taiwan Internet of Senses Research Center National Tsing Hua University Hsinchu 30013 Taiwan

Extreme frictional wear of triboelectric layers severely hinders long-term sustainability of triboelectric nanogenerators (TENGs) for efficient ambient energy harvesting. The state-of-the-art solutions necessitate sophisticated structural designs and complex packaging constraints, impeding the feasibility of TENGs for practical applications. Herein, inspired by the structures and compositions of snake scales, a biomimetic composite (BC) film is fabricated as a wear-resistant triboelectric contact layer. The successful formation of disulfide bond-facilitated cross-linkage of cysteine proteins in the keratin-based BC film promotes excellent mechanical resilience and durability, thereby solving the material abrasion challenges associated with solid-solid triboelectric layers. The BC film, with toothed microstructure, exhibits improved charge transfer, low friction, and consistent long-term stable outputs compared to commercial films. Furthermore, a self-powered BC film-based TENG is integrated into a bicycle for biomechanical energy harvesting, lightening warning signals for safer night ride with stable 300 V electrical output for at least 6 h. Moreover, a smart health monitoring system is further proposed by embedding TENG-based sensors into the bicycle saddle, accurately capturing the rider's pelvic-saddle interactions on varying terrain slopes. By leveraging the unique biomechanical information, machine learning-assisted user identification and terrain slope data classifications are achieved with high accuracies, laying a foundation for futuristic smart healthcare applications. This work provides a strategy to reduce material abrasion by exploiting the unique characteristics of a biomimetic material, facilitating a basis for efficient environmental energy harvesting and smart sensing. © 2024 Elsevier Ltd

关键词： Biomechanical energy harvesting Biomimetic Smart healthcare Snake-scales Triboelectric nanogenerator Wear resistance

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Current Progress of COPd Early detection: Key Points and Novel Strategies

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International Journal of COPd 2023年 18卷 1511-1524页

作者： Lin, Ching-Hsiung Cheng, Shih-Lung Chen, Chiung-Zuei Chen, Chia-Hung Lin, Sheng-Hao Wang, Hao-Chien Division of Chest Medicine Changhua Christian Hospital Changhua 500 Taiwan Institute of Genomics and Bioinformatics National Chung Hsing University Taichung 402 Taiwan Ph.D. Program in Translational Medicine National Chung Hsing University Taichung Taiwan Department of Recreation and Holistic Wellness MingDao University Changhua Taiwan Department of Internal Medicine Far Eastern Memorial Hospital Taipei 220 Taiwan Department of Chemical Engineering and Materials Science Yuan Ze University Taoyuan 320 Taiwan Division of Pulmonary Medicine Department of Internal Medicine National Cheng Kung University Hospital College of Medicine National Cheng Kung University Tainan Taiwan Division of Pulmonary and Critical Care Medicine Department of Internal Medicine China Medical University Hospital Taichung 404 Taiwan Department of Internal Medicine National Taiwan University Hospital Taipei 100 Taiwan

Chronic obstructive pulmonary disease (COPd) is a major cause of morbidity and mortality worldwide, with approxi-mately 70% to 80% of adults with COPd being undiagnosed. Patients with undiagnosed COPd are at increased risk of poor outcomes and a worsened quality of life, making early detection a crucial strategy to mitigate the impact of COPd and reduce the burden on healthcare systems. In the past decade, increased interest has been focused on the development of effective strategies and instrument for COPd early detection. However, identifying undiagnosed cases of COPd is still challenging. Both screening and case-finding approaches have been adopted to identify undiagnosed COPd, with case-finding being recommended by the 2023 Global Initiative for Chronic Obstructive Lung disease (GOLd) guideline and the updated United States Preventive Services Task Force (USPTF) recommendation. Nonetheless, the approaches, criteria, and instruments used for early detection of COPd are varied. However, advances in the taxonomy and risk factors of COPd are continuously being investigated. It is important to continuously assess the current state of knowledge on COPd early detection, given the challenges associated with identifying undiagnosed COPd. This review aims to highlight recent advances in early detection of COPd. To discuss the current challenge and opportunity in COPd early detection, providing an overview of existing literature on COPd case-finding strategies, including the approaches, criteria for subjects, and instruments. The review also summarizes the current progress in COPd case-findings and proposes a COPd case-finding flowchart as an efficient method for identifying at risk COPd patients. © 2023 Lin et al.

关键词： at-risk case-finding COPd early detection undiagnosed

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Faster GröBner Bases Via domain-Specific Ordering in Parameter Identifiability of Ode Models

SSRN

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SSRN 2023年

作者： Bessonov, Mariya Ilmer, Ilia Konstantinova, Tatiana Ovchinnikov, Alexey Pogudin, Gleb Soto, Pedro Brookhaven National Laboratory United States Department of Mathematics CUNY NYC College of Technology New YorkNY United States Ph.D. Program in Computer Science CUNY Graduate Center New YorkNY United States Department of Mathematics CUNY Queens College New YorkNY United States LIX CNRS École Polytechnique Institute Polytechnique de Paris Paris France Mathematical Institute University of Oxford Oxford United Kingdom

We consider a specific class of polynomial systems that arise in parameter identifiability problems of models of ordinary differential equations (OdE) and discover a method for speeding up the Gr¨obner basis computation by using specific variable ordering and weights coming from the structure of the OdE model. We provide empirical results that show improvement across different symbolic computing frameworks. © 2023, The Authors. All rights reserved.

关键词： Ordinary differential equations

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Friction stir welding of AZ31 magnesium alloy: A review

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Materials Today: Proceedings 2021年 47卷 6576-6584页

作者： Ashish M. desai Bharat C. Khatri Vivek Patel Harikrishna Rana Mechanical Engineering Department Government Polytechnic Himatnagar 383001 India Ph.D. Research Scholar Gujarat Technological University Ahmedabad 382424 Gujarat India Mechanical Engineering Department Government Engineering College Modasa 383315 India Department of Engineering Science University West Trollhättan 46186 Sweden Mechanical Engineering Department School of Technology Pandit Deendayal Petroleum University Gandhinagar 382007 India Mechanical Engineering Department LDRP Institute of Technology & Research Gandhinagar 382015 India

Friction Stir Welding (FSW) has been proven to be a unique and substantial development in welding technology for the last two decades. In recent times, the research and advancement in FSW and related knowledge have been emerging quickly worldwide. FSW has several benefits when welding lightweight alloys like magnesium alloys. AZ series of magnesium alloy is widely used in structural applications and have a great scope to cater to customized solutions for several industries like automotive, aerospace, railway, etc. In this review article, the basic principles of FSW along with recent developments in the field of FSW for AZ 31 magnesium alloys have been described in detail. Outlooks to foster the research are recognised.

关键词： Frictions stir welding Hardness Magnesium alloy Stir zone Tensile strength

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Research on data Security and Privacy of Smart Grids

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International Journal of Network Security 2024年第5期26卷 901-910页

作者： Hwang, Min-Shiang Chang, Yung-Ling Lin, Ko-Yu Lin, Iuon-Chang Yang, Cheng-Ying Department of Computer Science & Information Engineering Asia University 500 Lioufeng Rd. Wufeng Taichung Taichung41354 Taiwan Fintech and Blockchain Research Center Asia University 500 Lioufeng Rd. Wufeng Taichung Taichung41354 Taiwan The Ph.D. Program in Artificial Intelligence Asia University Taiwan Department of Management Information Systems National Chung Hsing University 500 Lioufeng Rd. Wufeng Taichung Taichung41354 Taiwan Department of Computer Science University of Taipei Taipei Taiwan

developing a smart grid is a trend nowadays and an indispensable basic necessity of life. In recent years, the electricity demand has risen rapidly due to economic development and quality of life improvement. The power grid in significant cities is unstable due to old equipment, and power outages occur frequently. The smart grid can adjust the grid’s distribution strategy through the consumer’s real-time electricity demand so that the consumer’s electricity consumption data is always transmitted to the grid. Failure to protect the privacy and security of such information will expose consumers’ habits and even make the grid unnecessarily wasteful. The smart grid’s abnormality detection efficiency determines the overall grid’s stability. Failure to detect anomalies or power theft in the grid promptly will not only lead to the selection of the wrong distribution strategy for the smart grid but also reduce the transmission efficiency of the grid. This research ensures the privacy and security of transmitted data to enhance the efficiency of abnormality detection in the smart grid. The research issues are divided into privacy of transmitted data, data security authentication, and anomaly detection efficiency. © (2024), (International Journal of Network Security). All rights reserved.

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Novel Biodegradable Ca–P/Ti–F Composite Conversion Coatings for Improving the Corrosion Resistance of Medical Magnesium Materials

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SSRN 2024年

作者： Sun, Ying-Sui Chu, Peng-Wei Cheng, An-Yu You, Jhu-Lin Chang, Tsung-Ming Jian, Shun-Yi Chi, Chun-Shang Liu, Yu-Cheng Chang, Chin-Jou School of Dental Technology College of Oral Medicine Taipei Medical University Taipei Taiwan Department of Engineering and System Science National Tsing Hua University Hsinchu300044 Taiwan Department of Chemical & Materials Engineering Chung Cheng Institute of Technology National Defense University Taoyuan335 Taiwan System Engineering and Technology Program National Chiao Tung University Hsinchu300 Taiwan Department of Material Engineering Ming Chi University of Technology New Taipei City24301 Taiwan Center for Plasma and Thin Film Technology Ming Chi University of Technology New Taipei243303 Taiwan Combination Medical Device Technology Division Medical Devices R&D Service Department Metal Industries Research & Development Centre Kaohsiung802 Taiwan

Mg and its alloys are characterized by favorable biocompatibility and nontoxicity, and these properties have stimulated considerable research interest in their application as degradable biomaterials for medical implants. However, the clinical application of these materials is restricted by their rapid degradation. Therefore, this study designed a surface modification method for Mg and Mg alloys to enable them to satisfy clinical requirements. A two-step conversion coating method was applied to pure Mg. Pure Mg samples were first coated with calcium phosphate (Ca–P), following which they were coated with titanium fluoride (Ti–F), resulting in the production of Mg samples coated with a bioactive Ca–P/Ti–F composite. The composition of the coated samples was investigated through energy-dispersive X-ray spectroscopy with transmission electron microscopy, and their morphology was characterized through scanning electron microscopy. Moreover, hydrogen evolution measurements in simulated body fluid (SBF), electrochemical impedance spectroscopy, and polarization curves were employed to evaluate the samples’ corrosion resistance. The prepared composite conversion coatings had an average thickness of approximately 350 nm, and their corroded area was less than 5% of their total area following their immersion in SBF for 72 h. Thus, the prepared Ca–P/Ti–F composite conversion coatings effectively inhibited Mg corrosion in SBF. Moreover, the attachment and differentiation of MG-63 cells on the prepared coatings were observed. © 2024, The Authors. All rights reserved.

关键词： Energy dispersive spectroscopy

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Machine learning approaches to identify systemic lupus erythematosus in anti-nuclear antibody-positive patients using genomic data and electronic health records

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Biodata Mining 2024年第1期17卷 1-15页

作者： Chung, Chih-Wei Chou, Seng-Cho Hsiao, Tzu-Hung Zhang, Grace Joyce Chung, Yu-Fang Chen, Yi-Ming Department of Information Management National Taiwan University Taipei Taiwan Department of Medical Research Taichung Veterans General Hospital Taichung Taiwan Department of Public Health Fu Jen Catholic University New Taipei Taiwan Institute of Genomics and Bioinformatics National Chung Hsing University Taichung Taiwan Department of Cellular and Physiological Sciences The University of British Columbia Vancouver BC Canada Department of Electrical Engineering Tunghai University Taichung Taiwan Division of Allergy Immunology and Rheumatology Department of Internal Medicine Taichung Veterans General Hospital 1650 Section 4 Boulevard Xitun Dist. Taichung 407 Taiwan Department of Post-Baccalaureate Medicine College of Medicine National Chung Hsing University Taichung Taiwan School of Medicine College of Medicine National Yang Ming Chiao Tung University Taipei Taiwan Rong Hsing Research Center for Translational Medicine & Ph.D. Program in Translational Medicine National Chung Hsing University Taichung Taiwan Precision Medicine Research Center College of Medicine National Chung Hsing University Taichung Taiwan

Background: Although the 2019 EULAR/ACR classification criteria for systemic lupus erythematosus (SLE) has required at least a positive anti-nuclear antibody (ANA) titer (≥ 1:80), it remains challenging for clinicians to identify patients with SLE. This study aimed to develop a machine learning (ML) approach to assist in the detection of SLE patients using genomic data and electronic health records. Methods: Participants with a positive ANA (≥ 1:80) were enrolled from the Taiwan Precision Medicine Initiative cohort. The Taiwan Biobank version 2 array was used to detect single nucleotide polymorphism (SNP) data. Six ML models, Logistic Regression, Random Forest (RF), Support Vector Machine, Light Gradient Boosting Machine, Gradient Tree Boosting, and Extreme Gradient Boosting (XGB), were used to identify SLE patients. The importance of the clinical and genetic features was determined by Shapley Additive Explanation (SHAP) values. A logistic regression model was applied to identify genetic variations associated with SLE in the subset of patients with an ANA equal to or exceeding 1:640. Results: A total of 946 SLE and 1,892 non-SLE controls were included in this analysis. Among the six ML models, RF and XGB demonstrated superior performance in the differentiation of SLE from non-SLE. The leading features in the SHAP diagram were anti-double strand dNA antibodies, ANA titers, AC4 ANA pattern, polygenic risk scores, complement levels, and SNPs. Additionally, in the subgroup with a high ANA titer (≥ 1:640), six SNPs positively associated with SLE and five SNPs negatively correlated with SLE were discovered. Conclusions: ML approaches offer the potential to assist in diagnosing SLE and uncovering novel SNPs in a group of patients with autoimmunity. © 2024, The Author(s).

关键词： Anti-nuclear antibody Machine learning Polygenic risk score Single nucleotide polymorphism Systemic lupus erythematosus

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Export- and import-based economic models for predicting global trade using deep learning

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Expert Systems with Applications 2023年 218卷

作者： Yang, Cheng-Hong Lee, Cheng-Feng Chang, Po-Yin Department of Information Management Tainan University of Technology Tainan City710302 Taiwan Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung80708 Taiwan Ph. D. Program in Biomedical Engineering Kaohsiung Medical University Kaohsiung80708 Taiwan School of Dentistry Kaohsiung Medical University Kaohsiung80708 Taiwan Department of Business Administration National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan Department of Computer Science and Information Engineering National Quemoy University Kinmen County 892 Taiwan

Forecasting global foreign trade is essential for developing government trade policies and management strategies for multinational corporations. However, achieving an accurate trade forecast is challenging because of the complex structural relationships between exports, imports and other economic variables. Many traditional forecasting models, such as time series, econometric, and machine learning, provide less accurate forecasts for trade data. This paper proposes an ensemble learning approach to improve forecasting performance by hybridizing the structural relationships between trade and deep learning models to predict foreign trade for ten major countries. The proposed method first establishes a cointegration relationship between exports and imports and their structural variables. The cointegrated models are then used to predict the future of trade, which is used as a benchmark model for comparison. A hybrid deep learning algorithm uses the cointegrated variables as input variables to predict trade data, and then are compared with time-series forecasts and economic structural models. The experimental results reveal that the ensemble learning method can achieve excellent forecasting performance for the tested periods of trade data. In most cases, the root means square error and mean absolute percentage error values are smaller than the time series and economic structural models. © 2023 Elsevier Ltd

关键词： Forecasting

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