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Bioactive phytol from Thymus vulgaris, a promising source of alternative medicine to combat bla KPC and bla OXA-48 genotypes of Klebsiella pneumoniae : A retrospective in vitro and in silico approach

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Microbial Pathogenesis 2025年 206卷

作者： Shibasini Murugan Vijay Karuppiah Sangavi Pandi Mani Govindasamy Kavitha Thangavel Department of Microbiology Science Campus Alagappa University Karaikudi Tamil Nadu India Department of Microbiology Thiagarajar College (An Autonomous institution Affiliated to Madurai Kamaraj University) Madurai Tamil Nadu India Department of Bioinformatics Science Campus Alagappa University Karaikudi Tamil Nadu India Department of Microbiology Center for Bioinformatics Karpagam Academy of Higher Education Coimbatore Tamil Nadu 641 021 India International Ph.D Program in Innovative Technology of Biomedical Engineering and Medical Devices Ming Chi University of Science and Technology New Taipei City 24303 Taiwan

Carbapenem-resistant Klebsiella pneumoniae (CRKP) poses a significant public health challenge due to its multidrug resistance and limited treatment options. This study investigates the antibacterial potential of Thymus vulgaris ethanolic extract and its bioactive compounds against multidrug-resistant K. pneumoniae strains harboring bla KPC and bla OXA-48 carbapenemase genes. The presence of these resistance genes was confirmed by multiplex PCR. The extract exhibited a dose-dependent inhibitory effect, with a maximum inhibition zone of 18 ± 1.5 mm at 100 μg. Chromatographic techniques, including thin-layer chromatography (TLC) and column chromatography, yielded six fractions, among which fraction F3 showed the strongest antibacterial activity. Gas chromatography–mass spectrometry (GC-MS) and ultra-performance liquid chromatography (UPLC) analyses identified phytol as the predominant bioactive constituent. Further evaluation of phytol revealed a minimum inhibitory concentration (MIC) of 125 μg/mL and a minimum bactericidal concentration (MBC) of 250 μg/mL against CRKP. Alamar Blue viability assays and bacterial culture confirmed phytol's bacteriostatic and bactericidal effects, independent of the ethanol solvent. These findings suggest that phytol inhibits bacterial growth, possibly through membrane-targeting mechanisms. Notably, this study is among the first to comprehensively assess phytol's efficacy against carbapenem-resistant K. pneumoniae strains carrying bla KPC and bla OXA-48 genes, integrating molecular characterization, chromatographic purification and antimicrobial activity. Overall, the results highlight phytol as a promising natural agent to combat multidrug-resistant bacterial infections and address the urgent global threat of antibiotic resistance.

关键词： Klebsiella pneumoniae phytol Thymus vulgaris antibacterials carbapenem-resistant enterobacteriacae molecular docking

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Anethole mitigates H2O2-induced inflammation in HIG-82 synoviocytes by suppressing the aquaporin 1 expression and activating the protein kinase A pathway

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Environmental Toxicology 2024年第2期39卷 965-978页

作者： Huang, Tai-Lung Chang, Yu-Chun Tsai, Bruce Chi-Kang Chen, Tung-Sheng Kao, Shih-Wen Tsai, Yung-Yun Lin, Shinn-Zong Yao, Chun-Hsu Lin, Kuan-Ho Kuo, Wei-Wen Huang, Chih-Yang Department of Biological Science and Technology College of Life Sciences China Medical University Taichung Taiwan Department of Orthopedics Chung-Kang Branch Cheng Ching General Hospital Taichung Taiwan Cardiovascular and Mitochondrial Related Disease Research Center Hualien Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Hualien Taiwan School of Life Science National Taiwan Normal University Taipei Taiwan Department of Orthopaedic Surgery Chung-Shan Medical University Hospital Taichung Taiwan Department of Physical Therapy Asia University Taichung Taiwan Department of Neurosurgery Hualien Tzu Chi Hospital Buddhist Tzu Chi Medical Foundation Hualien Taiwan Bioinnovation Center Buddhist Tzu Chi Medical Foundation Hualien Taiwan Department of Biomedical Imaging and Radiological Science China Medical University Taichung Taiwan School of Chinese Medicine China Medical University Taichung Taiwan Biomaterials Translational Research Center China Medical University Hospital Taichung Taiwan Department of Bioinformatics and Medical Engineering Asia University Taichung Taiwan Division of Cardiovascular Medicine Department of Internal Medicine China Medical University Hospital Taichung Taiwan Department of Emergency Medicine China Medical University Hospital Taichung Taiwan College of Medicine China Medical University Taichung Taiwan Ph.D. Program for Biotechnology Industry China Medical University Taichung Taiwan Department of Medical Research China Medical University Hospital China Medical University Taichung Taiwan Graduate Institute of Biomedical Sciences 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

Rheumatoid arthritis (RA) is an autoimmune inflammatory disease affecting approximately 1% of the global population, with a higher prevalence in women than in men. Chronic inflammation and oxidative stress play pivotal roles in the pathogenesis of RA. Anethole, a prominent compound derived from fennel (Foeniculum vulgare), possesses a spectrum of therapeutic properties, including anti-arthritic, anti-inflammatory, antioxidant, and tumor-suppressive effects. However, its specific impact on RA remains underexplored. This study sought to uncover the potential therapeutic value of anethole in treating RA by employing an H2O2-induced inflammation model with HIG-82 synovial cells. Our results demonstrated that exposure to H2O2 induced the inflammation and apoptosis in these cells. Remarkably, anethole treatment effectively countered these inflammatory and apoptotic processes triggered by H2O2. Moreover, we identified the aquaporin 1 (AQP1) and protein kinase A (PKA) pathway as critical regulators of inflammation and apoptosis. H2O2 stimulation led to an increase in the AQP1 expression and a decrease in p-PKA-C, contributing to cartilage degradation. Conversely, anethole not only downregulated the AQP1 expression but also activated the PKA pathway, effectively suppressing cell inflammation and apoptosis. Furthermore, anethole also inhibited the enzymes responsible for cartilage degradation. In summary, our findings highlight the potential of anethole as a therapeutic agent for mitigating H2O2-induced inflammation and apoptosis in synovial cells, offering promising prospects for future RA treatments. © 2023 Wiley Periodicals LLC.

关键词： Cell death

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dexamethasone and dexmedetomidine: A Synergistic Approach to Reduce Postoperative Nausea and Vomiting in Bariatric Surgery Patients

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Obesity surgery 2024年第6期34卷 2253-2254页

作者： Po-Chih Chang Ya-Wei Huang Chih-Kun Huang Ting-Wei Chang School of Medicine College of Medicine National Sun Yat-Sen University Kaohsiung City Taiwan. Division of Thoracic Surgery Department of Surgery Kaohsiung Medical University Hospital/Kaohsiung Medical University Kaohsiung City Taiwan. Weight Management Center Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung City Taiwan. Ph. D. Program in Biomedical Engineering College of Medicine Kaohsiung Medical University Kaohsiung City Taiwan. Department of Sports Medicine College of Medicine Kaohsiung Medical University Kaohsiung City Taiwan. Department of Nursing Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung City Taiwan. Body Science and Metabolic Disorders International Medical Center China Medical University Hospital Taichung City Taiwan. Division of Thoracic Surgery Department of Surgery Kaohsiung Medical University Hospital/Kaohsiung Medical University Kaohsiung City Taiwan. drchangtingwei@***. Weight Management Center Kaohsiung Medical University Hospital Kaohsiung Medical University Kaohsiung City Taiwan. drchangtingwei@***.

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Impact of Scheduled Acceleration on Weekends on Labor Productivity-Case Studies of Construction in Taiwan

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Journal of the Chinese Institute of Civil and Hydraulic engineering 2020年第1期32卷 23-33页

作者： Lin, Chien-Liang Lai, Yu-Che Construction Engineering National Kaohsiung University of Science and Technology Kaohsiung81164 Taiwan Ph. D Program in Engineering Science and Technology National Kaohsiung University of Science and Technology Kaohsiung82445 Taiwan

Most previous research has revealed that labour efficiency deteriorates with the increase of days worked, especially for schedule acceleration carried out 6 or 7 days per week. It means that labor productivity on weekdays is better than on weekends. However, the phenomenon may not be universally applicable to everywhere. To clarify the impact of schedule acceleration on weekends on labor productivity, this study investigates the efficiency of acceleration from three construction projects in Taiwan. data Envelopment Analysis (dEA) was utilized to examine work hours as the input and the physical quantity of completed work as the output. Further interview for construction workers was performed. The results revealed that (1) acceleration on weekends will not cause the deduction of labor productivity in construction industry in Taiwan;(2) inefficiency was not found on Saturdays because labors are used to work overtime and get higher pay in construction industry in Taiwan;(3) except for getting higher pay, better efficiency was measured on Sundays because the effect of less congestion. The main contribution of this paper is to reveal that the labor productivity on weekends could be better than on weekdays, and further investigate the reasons of the result. Not only this finding reverses previous perspective from construction industry and academic, but also it implies that labor productivity will be influenced by many factors. Furthermore, it reveals the importance of continuing planning and management. In the process of revising Labor Standard Act, the results can provide insights for legislator and industry practitioners in appropriately allocating human resources. © 2020, Chinese Institute of Civil and Hydraulic engineering. All right reserved.

关键词： Construction industry

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Estimating Aboveground Carbon dynamic of China Using Optical and Microwave Remote-Sensing datasets from 2013 to 2019

Journal of Remote Sensing

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Journal of Remote Sensing 2023年第1期3卷 19-34页

作者： Zhongbing Chang Lei Fan Jean-Pierre Wigneron Ying-Ping Wang philippe Ciais Jérôme Chave Rasmus Fensholt Jing MChen Wenping Yuan Weimin Ju Xin Li Fei Jiang Mousong Wu Xiuzhi Chen Yuanwei Qin Frédéric Frappart Xiaojun Li Mengjia Wang Xiangzhuo Liu Xuli Tang Sanaa Hobeichi Mengxiao Yu Mingguo Ma Jianguang Wen Qing Xiao Weiyu Shi dexin Liu Junhua Yan Key Laboratory of Vegetation Restoration and Management of Degraded Ecosystems South China Botanical GardenChinese Academy of SciencesGuangzhou 510650China University of Chinese Academy of Sciences Beijing 100049China Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station School of Geographical SciencesSouthwest UniversityChongqing 400715China INRAE UMR1391 ISPAUniversite de BordeauxF-33140 Villenave d’OrnonFrance CSIRO Oceans and Atmosphere AspendaleVIC 3195Australia Laboratoire des Sciences du Climat et de l’Environnement CEA/CNRS/UVSQ/Universite Paris SaclayGif-sur-YvetteFrance Laboratoire Evolution et Diversite Biologique Universite Paul SabatierToulouseFrance Department of Geosciences and Natural Resource Management University of CopenhagenCopenhagenDenmark Department of Geography and Program in Planning University of TorontoTorontoON M5S 3G3Canada College of Geographical Science Fujian Normal UniversityFuzhou 3500007FujianChina School of Atmospheric Sciences Sun Yat-sen UniversityZhuhai 519082GuangdongChina Southern Marine Science and Engineering Guangdong Laboratory Zhuhai 519000GuangdongChina Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology International Institute for Earth System ScienceNanjing UniversityNanjing 210023China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing 210023China Institute of Tibetan Plateau Research Chinese Academy of SciencesBeijing 100101China CAS Center for Excellence in Tibetan Plateau Earth Sciences Chinese Academy of SciencesBeijing 100101China Department of Microbiology and Plant Biology Center for Spatial AnalysisUniversity of OklahomaNormanOKUSA LEGOS Universite de ToulouseCNESCNRSIRDUPS-14 avenue Edouard Belin31400 ToulouseFrance State Key Laboratory of Remote Sensing Science Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China Climate Change Research Centre University of N

Over the past 2 to 3 decades,Chinese forests are estimated to act as a large carbon sink,yet the magnitude and spatial patterns of this sink differ considerably among *** 3 microwave(L-and X-band vegetation optical depth[VOd])and 3 optical(normalized difference vegetation index,leaf area index,and tree cover)remote-sensing vegetation products,this study compared the estimated live woody aboveground biomass carbon(AGC)dynamics over China between 2013 and *** results showed that tree cover has the highest spatial consistency with 3 published AGC maps(mean correlation value R=0.84),followed by L-VOd(R=0.83),which outperform the other *** AGC estimation model was proposed to combine all indices to estimate the annual AGC dynamics in China during 2013 to *** performance of the AGC estimation model was good(root mean square error=0.05 Pg C and R^(2)=0.90 with a mean relative uncertainty of 9.8% at pixel scale[0.25°]).Results of the AGC estimation model showed that carbon uptake by the forests in China was about+0.17 Pg C year^(-1) from 2013 to *** the regional level,provinces in southwest China including Guizhou(+22.35 Tg C year^(-1)),Sichuan(+14.49 Tg C year^(-1)),and Hunan(+11.42 Tg C year^(-1))provinces had the highest carbon sink rates during 2013 to *** of the carbon-sink regions have been afforested recently,implying that afforestation and ecological engineering projects have been effective means for carbon sequestration in these regions.

关键词： estimation Remote microwave

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Citizen science in environmental and ecological sciences

NATURE REVIEWS METHODS PRIMERS

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NATURE REVIEWS METHOdS PRIMERS 2022年第1期2卷 1-20页

作者： Morneau, dominique Novel Data Ecosystems for Sustainability Research Group Advancing Systems Analysis Program International Institute for Applied Systems Analysis (IIASA) Laxenburg Austria Centre d’écologie et des sciences de la conservation Muséum national d’Histoire naturelle Paris France Faculté de droit Université de Namur Namur Belgium Citizen Science Lab Leiden University Leiden Netherlands Department of Mechanical Engineering University of Bath Bath UK Nordic Foundation for Development and Ecology (NORDECO) Copenhagen Denmark Department of Biology Brandeis University Waltham MA USA Ornamental Plant Pathology Department of Plant Pathology Puyallup Research and Extension Center Washington State University Puyallup WA USA Environmental and Sustainability Participatory Information Systems Group Institute of Marine Sciences (ICM-CSIC) Barcelona Spain Electron Microscopy Science Technology Platform The Francis Crick Institute London UK Departamento de Biologia Marina Facultad Ciencias del Mar Universidad Católica del Norte Coquimbo Chile Millennium Nucleus Ecology and Sustainable Management of Oceanic Island (ESMOI) Coquimbo Chile Centro de Estudios Avanzados en Zonas Áridas (CEAZA) Coquimbo Chile Department of Geography University College London (UCL) London UK

This PrimeView highlights the utility of citizen science across a range of ecological and environmental science research.

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Analysis of discharge and area of the debris flow based on geological structural and rainfall levels in the slopes of Mount Abang, Kintamani

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IOP Conference Series: Materials science and engineering 2021年第2期1098卷

作者： I N Sinarta P I Wahyuni P Aryastana Department of Civil Engineering Universitas Warmadewa Jl. Terompong No.24 Denpasar Bali Indonesia International Ph.D. Program in Environmental Science and Technology (University System of Taiwan) National Central University Taiwan

Geological structural and rainfall intensity causes the parameters of soil shear strength to decline, especially in the surface layer of soil in volcanic rocks that have not experienced weathering. Study of geological structures and rainfall intensity against the hazard of a landslide was destroyed on the slopes of Mount Abang in the Abang Batudinding Village. Soil investigations using the Geoelectric method and sampling at 6 boreholes. Geological analysis on interpretation of slope outcrops, average rainfall analysis of the Thiessen Polygon method and analysis of design flood discharge using the NHSU method. Analysis results show the morphology of the slopes of Mount Abang with a slope of more than 40% and lithology of weathered volcanic rocks consisting of volcanic breccias, and tuffs breccias in conditions rather mild to moderate weathering, if have average effective rainfall for 10-50 years at 238 mm/day. The results also show that the peak discharge of debris flow was 98.639 m3/sec with the volume of debris flow 50072.85 m3 and the width of the range was 49.5 m. This debris flow volume indicated that residents around the river with a range of 49.5 m are at risk of debris flow sediment with a thickness of 1-1.5 m.

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OpenMM 8: Molecular dynamics Simulation with Machine Learning Potentials

arXiv

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arXiv 2023年

作者： Eastman, Peter Galvelis, Raimondas Peláez, Raúl P. Abreu, Charlles R.A. Farr, Stephen E. Gallicchio, Emilio Gorenko, Anton Henry, Michael M. Hu, Frank Huang, Jing Krämer, Andreas Michel, Julien Mitchell, Joshua A. Pande, Vijay S. Rodrigues, João P.G.L.M. Rodriguez-Guerra, Jaime Simmonett, Andrew C. Singh, Sukrit Swails, Jason Turner, philip Wang, Yuanqing Zhang, Ivy Chodera, John d. de Fabritiis, Gianni Markland, Thomas E. Department of Chemistry Stanford University StanfordCA94305 United States Acellera Labs C Dr Trueta 183 Barcelona08005 Spain C Dr. Aiguader 88 Barcelona08003 Spain Chemical Engineering Department School of Chemistry Federal University of Rio de Janeiro Rio de Janeiro68542 Brazil Redesign Science Inc. 180 Varick St. New YorkNY10014 United States EaStCHEM School of Chemistry University of Edinburgh EH9 3FJ United Kingdom Department of Chemistry and Biochemistry Brooklyn College The City University of New York NY United States Ph.D. Program in Chemistry Ph.D. Program in Biochemistry The Graduate Center of the City University of New York New YorkNY United States Stream HPC Koningin Wilhelminaplein 1 - 40601 Amsterdam1062 HG Netherlands Computational and Systems Biology Program Sloan Kettering Institute Memorial Sloan Kettering Cancer Center New YorkNY10065 United States Key Laboratory of Structural Biology of Zhejiang Province School of Life Sciences Westlake University 18 Shilongshan Road Zhejiang Hangzhou310024 China Department of Mathematics and Computer Science Freie Universität Berlin Arnimallee 12 Berlin14195 Germany The Open Force Field Initiative Open Molecular Software Foundation DavisCA95616 United States Andreessen Horowitz 2865 Sand Hill Rd Menlo ParkCA94025 United States Department of Structural Biology Stanford University StanfordCA94305 United States Charité Universitätsmedizin Berlin In silico Toxicology and Structural Bioinformatics Virchowweg 6 Berlin10117 Germany Laboratory of Computational Biology National Heart Lung and Blood Institute National Institutes of Health BethesdaMD20892 United States Entos Inc. 9310 Athena Circle La Jolla CA92037 United States College of Engineering Virginia Polytechnic Institute State University BlacksburgVA24061 United States Simons Center for Computational Physical Chemistry Center for Data Science New York University 24 Waverly Place New YorkNY10004 United States T

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy. A higher-level interface allows users to easily model their molecules of interest with general purpose, pretrained potential functions. A collection of optimized CUdA kernels and custom PyTorch operations greatly improves the speed of simulations. We demonstrate these features on simulations of cyclin-dependent kinase 8 (CdK8) and the green fluorescent protein (GFP) chromophore in water. Taken together, these features make it practical to use machine learning to improve the accuracy of simulations at only a modest increase in cost. Copyright © 2023, The Authors. All rights reserved.

关键词： Machine learning

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data-driven Two-Stage Framework for Identification and Characterization of different Antibiotic-Resistant Escherichia coli Isolates Based on Mass Spectrometry data

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Microbiology spectrum 2023年第3期11卷 e0347922页

作者： Chia-Ru Chung Hsin-Yao Wang Chun-Han Yao Li-Ching Wu Jang-Jih Lu Jorng-Tzong Horng Tzong-Yi Lee Department of Computer Science and Information Engineering National Central University Taoyuan Taiwan. Department of Laboratory Medicine Chang Gung Memorial Hospital at Linkou Taoyuan Taiwan. Ph.D. Program in Biomedical Engineering Chang Gung University Taoyuan Taiwan. Department of Biomedical Sciences and Engineering National Central University Taoyuan Taiwan. College of Medicine Chang Gung University Taoyuan Taiwan. Department of Medical Biotechnology and Laboratory Science Chang Gung University Taoyuan Taiwan. Department of Bioinformatics and Medical Engineering Asia University Taichung Taiwan. Institute of Bioinformatics and Systems Biology National Yang Ming Chiao Tung University Hsinchu Taiwan.

In clinical microbiology, matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALdI-TOF MS) is frequently employed for rapid microbial identification. However, rapid identification of antimicrobial resistance (AMR) in Escherichia coli based on a large amount of MALdI-TOF MS data has not yet been reported. This may be because building a prediction model to cover all E. coli isolates would be challenging given the high diversity of the E. coli population. This study aimed to develop a MALdI-TOF MS-based, data-driven, two-stage framework for characterizing different AMRs in E. coli. Specifically, amoxicillin (AMC), ceftazidime (CAZ), ciprofloxacin (CIP), ceftriaxone (CRO), and cefuroxime (CXM) were used. In the first stage, we split the data into two groups based on informative peaks according to the importance of the random forest. In the second stage, prediction models were constructed using four different machine learning algorithms-logistic regression, support vector machine, random forest, and extreme gradient boosting (XGBoost). The findings demonstrate that XGBoost outperformed the other four machine learning models. The values of the area under the receiver operating characteristic curve were 0.62, 0.72, 0.87, 0.72, and 0.72 for AMC, CAZ, CIP, CRO, and CXM, respectively. This implies that a data-driven, two-stage framework could improve accuracy by approximately 2.8%. As a result, we developed AMR prediction models for E. coli using a data-driven two-stage framework, which is promising for assisting physicians in making decisions. Further, the analysis of informative peaks in future studies could potentially reveal new insights. Based on a large amount of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry (MALdI-TOF MS) clinical data, comprising 37,918 Escherichia coli isolates, a data-driven two-stage framework was established to evaluate the antimicrobial resistance of E. coli. Five antibiotics, including a

关键词： MALdI-TOF MS antimicrobial resistance cephalosporin cephalosporins fluoroquinolones machine learning matrix-assisted laser desorption ionization–time of flight mass spectrometry penicillin penicillins

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deep learning-based air pollution analysis on carbon monoxide in Taiwan

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Ecological Informatics 2024年 80卷

作者： Cheng-Hong Yang Po-Hung Chen Chih-Hsien Wu Cheng-San Yang Li-Yeh Chuang Department of Information Management Tainan University of Technology Tainan Taiwan Department of Electronic Engineering National Kaohsiung University of Science and Technology Kaohsiung Taiwan Ph. D. Program in Biomedical Engineering Kaohsiung Medical University Kaohsiung Taiwan School of Dentistry Kaohsiung Medical University Kaohsiung Taiwan Drug Development and Value Creation Research Center Kaohsiung Medical University Kaohsiung Taiwan Division of Plastic and Reconstruction Surgery Department of Surgery Ditmanson Medical Foundation Chia-Yi Christian Hospital Chia-Yi Taiwan Department of Chemical Engineering and Institute of Biotechnology and Chemical Engineering I-Shou University Kaohsiung Taiwan

Global air pollution poses a threat to humanity. Specifically, CO directly affects cardiovascular and other organ tissues and leads to numerous chronic diseases and major public health problems. The effective implementation of a deep learning model for predicting variations in CO levels would enable the early formulation of policies for controlling air pollution. In this study, a seasonal gated recurrent unit (SGRU) model, which is a deep learning time-series prediction model, was developed to predict the levels of CO in Taiwan. Atmospheric CO measurements from 2005 to 2021 were collected from the Environmental Protection Administration of Taiwan and preprocessed using the Kalman filter to achieve accurate forecasting. The performance of the proposed SGRU model was compared with that of the autoregressive integrated moving average (ARIMA), seasonal ARIMA, exponential smoothing (ETS), Holt–Winters ETS, support vector regression, and seasonal long short-term memory models in terms of mean absolute percentage error (MAPE) and root mean square error. The SGRU model achieved the lowest MAPE value of 0.94, which demonstrated its superior performance. The construction of an accurate air pollution prediction model can assist government entities in formulating health and social care strategies and in planning future air pollution control measures.

关键词： Air pollution Carbon Monoxide (CO) deep learning Seasonal gated recurrent unit (SGRU)

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