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Fucoxanthin induces human melanoma cytotoxicity by thwarting the JAK2/STAT3/BCL-xL signaling axis

Environmental Toxicology 2024年第6期39卷 3356-3366页

作者： Kuo, Min-Yung Dai, Wen-Chyi Chang, Jie-Li Chang, Jo-Shu Lee, Tse-Min Chang, Chia-Che Pediatric Surgery Division Department of Surgery Tungs' Taichung MetroHarbor Hospital Taichung Taiwan Doctoral Program in Biotechnology Industrial Innovation and Management National Chung Hsing University Taichung Taiwan Taichung Municipal Taichung First Senior High School Taichung Taiwan Department of Chemical and Materials Engineering Research Center for Smart Sustainable Circular Economy Tunghai University Taichung Taiwan Department of Life Sciences National Chung Hsing University Taichung Taiwan Department of Marine Biotechnology and Resources National Sun Yat-sen University Kaohsiung Taiwan Graduate Institute of Biomedical Sciences Master Program in Precision Health Doctoral Program in Translational Medicine Rong Hsing Research Center for Translational Medicine The iEGG and Animal Biotechnology Research Center National Chung Hsing University Taichung Taiwan Department of Medical Laboratory Science and Biotechnology Asia University Taichung Taiwan Department of Medical Research China Medical University Hospital Taichung Taiwan Traditional Herbal Medicine Research Center Taipei Medical University Hospital Taipei Taiwan

Melanoma is the most lethal skin malignancy. Fucoxanthin is a marine carotenoid with significant anticancer activities. Intriguingly, Fucoxanthin's impact on human melanoma remains elusive. Signal Transducer and Activator of Transcription 3 (STAT3) represents a promising target in cancer therapy due to its persistent activation in various cancers, including melanoma. Herein, we revealed that Fucoxanthin is cytotoxic to human melanoma cell lines A2758 and A375 while showing limited cytotoxicity to normal human melanocytes. Apoptosis is a primary reason for Fucoxanthin's melanoma cytotoxicity, as the pan-caspase inhibitor z-VAD-fmk drastically abrogated Fucoxanthin-elicited clonogenicity blockage. Besides, Fucoxanthin downregulated tyrosine 705-phosphorylated STAT3 (p-STAT3 (Y705)), either inherently present in melanoma cells or inducible by interleukin 6 (IL-6) stimulation. Notably, ectopic expression of STAT3-C, a dominant-active STAT3 mutant, abolished Fucoxanthin-elicited melanoma cell apoptosis and clonogenicity inhibition, supporting the pivotal role of STAT3 blockage in Fucoxanthin's melanoma cytotoxicity. Moreover, Fucoxanthin lowered BCL-xL levels by blocking STAT3 activation, while ectopic BCL-xL expression rescued melanoma cells from Fucoxanthin-induced killing. Lastly, Fucoxanthin was found to diminish the levels of JAK2 with dual phosphorylation at tyrosine residues 1007 and 1008 in melanoma cells, suggesting that Fucoxanthin impairs STAT3 signaling by blocking JAK2 activation. Collectively, we present the first evidence that Fucoxanthin is cytotoxic selectively against human melanoma cells while sparing normal melanocytes. Mechanistically, Fucoxanthin targets the JAK2/STAT3/BCL-xL antiapoptotic axis to provoke melanoma cell death. This discovery implicates the potential application of Fucoxanthin as a chemopreventive or therapeutic strategy for melanoma management. © 2024 Wiley Periodicals LLC.

关键词： Carotenoids

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Development of Simultaneous Quantitative Analytical Method for Three Active Components of Agastache Rugosa in Human Plasma Using Ultra-High-Performance Liquid Chromatography–Tandem Mass Spectrometry

SSRN

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SSRN 2023年

作者： Rinik, Urmi Rahman Kim, Ji Eon Lee, Eunok Kwon, Oran Jung, Byung Hwa Center for Advanced Biomolecular Recognition Korea Institute of Science and Technology Seoul02792 Korea Republic of Division of Bio-medical Science and Technology KIST School University of Science and Technology Daejeon34113 Korea Republic of Department of Nutritional Science and Food Management Graduate Program in System Health Science and Engineering Ewha Womans University Korea Republic of

Abstract: Agastache rugosa contains phenolic compounds and flavonoids, and has been extensively used as a traditional herbal medicine. The major components in Agastache rugosa are rosmarinic acid, tilianin, and acacetin, for which several analytical techniques have been reported. However, these substances have yet to be simultaneously quantified in human plasma. In this study, we aimed to simultaneously determine the three active components of Agastacherugosa in human plasma by developing a reliable quantitative analytical method using ultra-high-performance liquid chromatography–tandem mass spectrometry (UHPLC-MS/MS). Chromatographic separation of the plasma samples was achieved using an ACQUITY UPLC® BEH C18 column with a gradient mobile phase of water and acetonitrile containing 0.1% formic acid. Mass spectrometric detection was performed using a triple quadrupole tandem mass spectrometer in negative electrospray ionization (ESI−) and multiple reaction monitoring (MRM) modes. The developed quantitative method was validated for the three active components. All three analytes exhibited a linear response over the ranges of 0.5–50 ng/mL for rosmarinic acid, 0.1–20 ng/mL for acacetin, and 0.5–20 ng/mL for tilianin with a weighting factor of 1/x (where x is the concentration). At three quality control (QC) concentration levels (low, medium, and high), including the lower limit of quantitation (LLOQ), acceptable accuracy (±15%) was achieved in the intra- and interday validations. The concentration of rosmarinic acid was highest in plasma. Tilianin and acacetin appeared and were eliminated earlier in the plasma than rosmarinic acid. This study provides a successfully validated method that can be used in further clinical applications of Agastache rugosa extracts. © 2023, The Authors. All rights reserved.

关键词： Mass spectrometers

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The last decade epidemiologic concern of drinking water contaminants of emerging concern (CECs) in Asian Countries: A scoping review

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Heliyon 2024年第20期10卷 e39236页

作者： Nathanael, Rinaldy Jose Adyanis, Latonia Nur Oginawati, Katharina Environmental Engineering Program Faculty of Science and Technology Airlangga University Surabaya 60115 Indonesia Department of Environmental Engineering Chung Yuan Christian University Taoyuan 320314 Taiwan Environmental Management Technology Research Group Department of Environmental Engineering Faculty of Civil and Environmental Engineering Bandung Institute of Technology Bandung 40132 Indonesia

With the rapid industrialization and urbanization in Asian countries, the challenge of rising emerging contaminants in the environment, including the water cycle, has become more pronounced. Consequently, the presence of CECs in drinking water systems is inevitable due to their ubiquitous nature in aquatic environments. This scoping review aims to identify epidemiological concerns regarding drinking water CECs in Asian countries over the past decade by describing the types of assessed CECs, their associated health effects, and identifying gaps and future research prospects through a summary of relevant studies. Searches were conducted on PubMed and Scopus up to February 29, 2024. Included were epidemiological studies from the past 10 years (since January 2014) in Asian countries that assessed emerging contaminants in drinking water through direct measurement or analysis as factors. From an initial pool of 3198 results, 15 relevant studies were selected. These studies assessed various types of CECs, including disinfection byproducts (n = 10), endocrine disruptors (n = 2), pesticides (n = 2), and a protozoan pathogen (n = 1). The meticulous assessment of CECs and associated health outcomes in Asian epidemiological studies over the past decade has been deemed inadequate to address the wide range of ubiquitous CECs in drinking water and their potential health effects that have not yet been addressed. While not the sole objective, the primary aim of epidemiological studies is to inform policy decisions and increase awareness among the public and policymakers. Therefore, researchers in Asian countries, particularly in environmental and public health fields, should prioritize the development of research in this area by exploring more CECs type and associated health outcomes. © 2024 The Author(s)

关键词： Asia Drinking water Emerging contaminants Epidemiology Scoping review

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Multimodal Sentiment Analysis using Kernel Based Support Vector Machine 2

Multimodal Sentiment Analysis using Kernel Based Support Vec...

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2nd IEEE International Conference on Advanced Technologies in Intelligent Control, Environment, Computing and Communication engineering, ICATIECE 2022

作者： Kumar, V Sunil Pareek, Piyush Kumar De Albuquerque, Victor Hugo Costa Khanna, Ashish Gupta, Deepak Madhumala, R.B. Nitte Meenakshi Institute of Technology Department Artificial Intelligence and Machine Learning Bengaluru India Graduate Program in Telecommunication Engineering Federal Institute of Education Science and Technology of Ceará Fortaleza Brazil Federal University of Ceará Department of Teleinformatics Engineering Brazil Maharaja Agrasen Institute of Technology GGSIPU CSE Dept India Dayananda Sagar Academy of Technology and Management Department of ISE Bangalore India

ISBN: (纸本)9781665493963

There has been a steady expansion in the number of social websites, electronic media outlets, and blogging services, all of which contribute a large number of user messages such as comments, reviews, and opinions from customers. The quantity of these signals, which are used to evaluate the quality of a wide variety of goods and services, is rather substantial. As a result, it is challenging to monitor and identify the feelings of customers. As a result, a method known as Sentiment Analysis (SA), also known as Opinion Mining (OM), was developed. This method gathers data from the internet by using Natural Language Processing (NLP) strategies and then analyses people's thoughts. It does this by extracting subjective information from the words, assessing opinions, and quantifying positive and negative evaluations. The end result is a conclusion about the specific entity, which may be an organisation, the public, or a product. The NLP first gathers the views, and then those opinions are sorted into positive, neutral, and negative categories. Both the marketing promotion and the customer's ability to choose the most appropriate product for their needs may be improved by doing an analysis. The purpose of this study is to evaluate the use of different machine learning and swarm intelligence optimization methods to perform sentiment analysis on data derived from movie reviews. This study helps many businesses increase their profits while simultaneously lowering the number of problems caused by a certain product. Within the scope of this investigation, three distinct models of sentiment analysis were investigated. An effective method for doing sentiment analysis known as a Hybrid Kernel based Support Vector Machine (HKSVM) has been presented. The preprocessing that is described here is meant to cut down on the data inconsistencies and get rid of the data that isn't needed. After that, the Expectation Maximization (EM) technique is used in order to identify an outlier. After t

关键词： Sentiment analysis

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Experimentation of Integrating Roadmapping and Sci-Fi Prototyping Methods

Experimentation of Integrating Roadmapping and Sci-Fi Protot...

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Portland International Conference on management of engineering and Technology (PICMET)

作者： Miwa Nishinaka Kunio Shirahada Yusuke Kishita Dohjin Miyamoto Hirotaka Osawa Sachiko Kiyokawa Hideaki Takeda The Graduate School of Management Kagawa University Takamatsu Kagawa Japan School of Knowledge Science Transformative Knowledge Management Research Area Japan Advanced Institute of Science and Technology (JAIST) Nomi Ishikawa Japan Department of Precision Engineering The University of Tokyo Tokyo Japan Communication in Science and Technology Education and Research Program Hokkaido University Sapporo Japan Faculty of Science and Technology Keio University Yokohama Kanagawa Japan Graduate School of Education The University of Tokyo Tokyo Japan National Institute of Informatics Tokyo Japan

ISBN: (数字)9781890843458

ISBN: (纸本)9798350369137

In 2023, we proposed a hypothetical knowledge management framework that incorporates science fiction prototyping (SFP) into the traditional roadmapping (RM) method to make RM more innovative and create a future beyond what we can currently imagine. Our main objective is to create a new organizational knowledge co-creation method for generating innovative ideas by incorporating humanistic factors utilizing SFP into RM. In the current article, we present the exploratory study we conducted to examine the hypothetical framework. Experimental workshops were held in November 2023 to compare the integrated method, in which SFP is applied to RM, with the original RM method. We followed a crossover design in the workshops and analyzed the results qualitatively and quantitatively following the perspectives proposed in the hypothetical framework. The qualitative analysis revealed successful integration regarding diverse and broader perspectives. The quantitative analysis utilizing Wilcoxon signed rank tests showed that the scores of the integrated method were significantly higher than those of RM for variables evaluating the effectiveness of the integration, while not for variables related to participants' feelings and satisfaction with the workshops, and sustainability. These findings indicate that the integration was successful in terms of its effectiveness as a method, while participants' subjective feelings toward the workshops were not different in both methods. As for sustainability, which requires a long-term perspective, no apparent differences were observed in these short-term workshops.

关键词： Statistical analysis Conferences Knowledge management Sustainable development Creativity

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Sampled-Data Observer Design With Exponential Time-Varying Gains for Semilinear Parabolic PDE Systems

Sampled-Data Observer Design With Exponential Time-Varying G...

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2021 China Automation Congress, CAC 2021

作者： Wang, Zi-Peng Wu, Huai-Ning Li, Han-Xiong Huang, Tingwen Shen, Tao The School of Electrical Engineering University of Jinan Jinan250022 China The Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beihang University Beijing100191 China The Department of Systems Engineering and Engineering Management City University of Hong Kong Hong Kong The Science Program Texas A&M University at Qatar Doha Qatar The HIT Robot Group Co. Ltd China

ISBN: (纸本)9781665426473

For semilinear parabolic PDE systems, the sampled-data observer (SDO) design under spatially point measurements (SPMs) with exponential time-varying gains is concerned. On basis of a Lyapunov functional, a SDO with exponential time-varying gains under SPMs via linear matrix inequalities is presented to guarantee the exponential stability of estimation error PDE system. Lastly, two numerical examples are provided to support the proposed SDO design approach. © 2021 IEEE

关键词： Linear matrix inequalities

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KMD clustering: robust general-purpose clustering of biological data

Communications Biology

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Communications Biology 2023年第1期6卷 1-12页

作者： Zelig, Aviv Kariti, Hagai Kaplan, Noam Data Science & Engineering Program Faculty of Industrial Engineering & Management Technion - Israel Institute of Technology Haifa Israel Department of Physiology Biophysics & Systems Biology Rappaport Faculty of Medicine Technion – Israel Institute of Technology Haifa Israel

The noisy and high-dimensional nature of biological data has spawned advanced clustering algorithms that are tailored for specific biological datatypes. However, the performance of such methods varies greatly between datasets and they require post hoc tuning of cryptic hyperparameters. We present k minimal distance (KMD) clustering, a general-purpose method based on a generalization of single and average linkage hierarchical clustering. We introduce a generalized silhouette-like function to eliminate the cryptic hyperparameter k, and use sampling to enable application to million-object datasets. Rigorous comparisons to general and specialized clustering methods on simulated, mass cytometry and scRNA-seq datasets show consistent high performance of KMD clustering across all datasets. © 2023, The Author(s).

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Overview of Bearing Fault Diagnosis Based on Deep Learning

Overview of Bearing Fault Diagnosis Based on Deep Learning

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Electronic Communications, Internet of Things and Big Data (ICEIB), International Conference on

作者： Xue-Ling Zou Kai-Xu Han Wei Chien Xin-Yan Gan Liu-Yue Shi School of Electric and Information Engineering Beibu Gulf University Qinzhou China School of Information Management and Master’s Program Lunghwa University of Science and Technology Taoyuan City Taiwan Guangxi University of Chinese Medicine Nanning China

Deep learning has excellent learning and feature classification abilities, extracting features in massive, multi-source, and high-dimensional measurement data. It also diagnoses and generalizes models without relying on manual intervention. Thus, it is widely used in equipment fault diagnosis. We introduce the common models of deep learning: deep confidence network, convolutional neural network, and automatic encoder. Using deep learning, the fault diagnosis of rolling bearings is executed, and the result provides the basis for future development.

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Developing a novel Temporal Air-quality Risk Index using LSTM autoencoder: A case study with South Korean air quality data

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science of the Total Environment 2025年 978卷 179303页

作者： Park, Hyerim Sohn, Wonho Kang, Eunjin Im, Jungho Lee, Junghye Technology Management Economics and Policy Program Seoul National University 1 Gwanak-ro Seoul08826 Korea Republic of Department of Industrial Engineering Ulsan National Institute of Science and Technology 50 UNIST-gil Ulsan44919 Korea Republic of Department of Civil Urban Earth Environmental Engineering Ulsan National Institute of Science and Technology 50 UNIST-gil Ulsan44919 Korea Republic of Institute of Engineering Research Seoul National University 1 Gwanak-ro Seoul08826 Korea Republic of of Engineering Practice Seoul National University 1 Gwanak-ro Seoul08826 Korea Republic of

As public awareness of environmental and health issues grows, providing accurate and accessible environmental risk information is essential for informed decision-making. Environmental indices simplify the complex impacts of various environmental factors into a single, interpretable score. The Air Quality Index (AQI) and Air Quality Health Index (AQHI), a widely recognized standard, reflects health risks posed by air pollution but has significant limitations. Conventional index calculations often focus on the single most hazardous pollutant or ignore the combined and cumulative effects of multiple pollutants. Additionally, the commonly used linear and arithmetic approaches can misrepresent actual risks and fail to capture the temporal dynamics of environmental factors. To address these limitations, we propose a deep learning framework for developing a more comprehensive air quality index, the Temporal Air-quality Risk Index (TARI). This framework employs a long short-term memory (LSTM) autoencoder to capture complex interactions and temporal dependencies among environmental factors. By incorporating a risk score (RS) that captures non-linear and continuous risks, TARI provides a more accurate assessment of the environmental impact on health. A case study using real air quality data from South Korea demonstrates that TARI outperforms the Korean Comprehensive Air-quality Index (CAI) and AQHI, exhibiting stronger correlations with disease prevalence. These results highlight TARI's improved sensitivity and relevance in assessing health risks, particularly by addressing cumulative and temporal pollutant effects. To our knowledge, this study is the first to apply deep learning to environmental index development, offering a flexible and robust framework with potential applications across diverse environmental systems. © 2025 Elsevier B.V.

关键词： Haze pollution

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A mechanistic study of ciprofloxacin adsorption by goethite in the presence of silver and titanium dioxide nanoparticles

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Journal of Environmental sciences 2022年第8期34卷 46-56页

作者： Jie Tang Yun Wang Qiang Xue Fei Liu Kenneth CCarroll Xiaohua Lu Taogeng Zhou Dengjun Wang MOE Key Laboratory of Groundwater Circulation and Environmental Evolution China University of Geosciences(Beijing)Beijing 100083China Beijing Key Laboratory of Water Resources and Environmental Engineering School of Water Resources and EnvironmentChina University of Geosciences(Beijing)Beijing 100083China Water Science and Management Program New Mexico State UniversityMSC 3QUSA Plant&Environmental Science New Mexico State UniversityLas CrucesNM 88003USA National Institute of Metrology Beijing 100022China Beijing Institute of Technology Beijing 100081China School of Fisheries Aquaculture and Aquatic SciencesAuburn UniversityAuburnAL 36849USA

The adsorption behaviors of ciprofloxacin(CIP),a fluoroquinolone antibiotic,onto goethite(Gt)in the presence of silver and titanium dioxide nanoparticles(AgNPs and TiO_(2)NPs)were *** showed that CIP adsorption kinetics in Gt with or without NPs both followed the pseudo-second-order kinetic *** presence of AgNPs or TiO_(2)NPs inhibited the adsorption of CIP by *** amount of inhibition of CIP sorption due to AgNPs was decreased with an increase of solution pH from 5.0 to *** contrast,in the presence of TiO_(2)NPs,CIP adsorption by Gt was almost unchanged at pHs of 5.0∼6.5 but was decreased with an increase of pH from 6.5 to *** mechanisms of AgNPs and TiO_(2)NPs in inhibiting CIP adsorption by Gt were different,which was attributed to citrate coating of AgNPs resulting in competition with CIP for adsorption sites on Gt,while TiO_(2)NPs could compete with Gt for CIP ***,CIP was adsorbed by Gt or TiO_(2)NPs through a tridentate complex involving the bidentate inner-sphere coordination of the deprotonated carboxylic group and hydrogen bonding through the adjacent carbonyl group on the quinoline *** findings advance our understanding of the environmental behavior and fate of fluoroquinolone antibiotics in the presence of NPs.

关键词： Ciprofloxacin Goethite Silver nanoparticles Titanium dioxide nanoparticles Adsorption

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