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Correction to: Modified Pemberton Pelvic Osteotomy Through Inner Ilium Approach for Treatment of developmental Dysplasia of the Hip in Children

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Indian journal of orthopaedics 2022年第9期56卷 1667页

作者： Yuxi Su Guoxin Nan Department II of Orthopaedics Chongqing Key Laboratory of Pediatrics Ministry of Education Key Laboratory of Child Development and Disorders National Clinical Research Center for Child Health and Disorders China International Science and Technology Cooperation Base of Child Development and Critical Disorders Children's Hospital of Chongqing Medical University Yuzhong District Zhongshan 2road 136# Chongqing 400014 China.

[This corrects the article DOI: 10.1007/s43465-022-00676-7.].

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Correction: A photoexcited halogen-bonded EDA complex of the thiophenolate anion with iodobenzene for C(sp3)-H activation and thiolation

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Chemical science 2021年第47期12卷 15770页

作者： Tao Li Kangjiang Liang Jiaying Tang Yuzhen Ding Xiaogang Tong Chengfeng Xia Key Laboratory of Medicinal Chemistry for Natural Resource Ministry of Education Yunnan Provincial Center for Research & Development of Natural Products School of Chemical Science and Technology Yunnan University Kunming 650091 China xiacf@***.

[This corrects the article DOI: 10.1039/D1SC03667J.].

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Spatiotemporal Variations and Risks Assessment of Pah-Bound Suspended Particles Across Different Asian Countries: Insights from Multi-City Sampling and Source Apportionment

SSRN

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SSRN 2025年

作者： Chi, Kai Hsien Hsu, Yen-Shun Lin, Sheng-Lun Chou, Charles C.-K. Chantara, Somporn Sereeter, Lodoisamba Tuyet-Hanh, Tran Thi Delgerzul, Lodoisamba Hsu, Yuan Cheng Wu, Chih-Da Ngo, Tuan Hung Pan, Shih Yu Institute of Environmental and Occupational Health Sciences National Yang Ming Chiao Tung University Taipei112 Taiwan Department of Environmental Engineering National Cheng Kung University Tainan70101 Taiwan Research Center for Environmental Changes Academia Sinica Taipei115 Taiwan Ulaanbaatar Mongolia Environmental Science Research Center Faculty of Science Chiang Mai University Chiang Mai50200 Thailand Environmental Health Department Hanoi University of Public Health 1A Duc Thang Road North Tu Liem Hanoi Viet Nam Mongolian National University of Medical Sciences Ulaanbaatar Mongolia National Environmental Research Academy Ministry of Environment Taoyuan330 Taiwan Department of Geomatics College of Engineering National Cheng Kung University Tainan701 Taiwan Business Development Department Medigen Vaccine Biologics Corp. Hsinchu302 Taiwan Beijing Institute of Technology China

This study aims to assess the toxicity and mutagenic characteristics of Polycyclic Aromatic Hydrocarbons (PAHs) originating from particulate matter (PM) in different anthropogenic actives in Asian cities. High-volume samplers were used for ambient PM collection in various Asian cities from 2019 to 2023, and subsequent analyses included PAHs, heavy metals, and water-soluble ions (WSIs). Ecological and inhalation cancer risk assessments were computed by multiplying concentrations of individual PAH compounds in Taipei, Chiang Mai, Hanoi, Ulaanbaatar, and Beijing, respectively. The average concentrations of PM2.5 and PAH BaP-TEQ levels were 132±45.3 μg/m3 (23.0±24.8 ng/m3) in Chiang Mai and 63.3±11.9 μg/m3 (2.81±2.64 ng/m3) in Hanoi, while 12.6±6.02 μg/m3 (4.75±8.88 ng/m3) in Taipei. In Ulaanbaatar, total suspended particles (TSP) and PAH levels during dust storm events were 2.08 to 8.13 times higher (TSP: 601 μg/m3, PAH: 91.0 ng /m3). Similarly, in Beijing, TSP and PAHs levels were 2.49 to 10.4 times higher during dust storm events (TSP: 701-1,135 μg/m3, PAHs: 27.8±24.6 ng/m3). PMF results revealed 47.5 to 79.8% contributions from vehicles in Ulaanbaatar, Chiang Mai, and Hanoi. The ecological risk assessment toxicity of PAHs indicated low risk (RI © 2025, The Authors. All rights reserved.

关键词： Risk assessment

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In Silico functional prediction of CAS2, a protein specifically expressed in appressorium and required for pathogenicity of Colletotrichum gloeosporioides

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AIP Conference Proceedings 2022年第1期2462卷

作者： Tri Puji Priyatno Farah Diba Abu Bakar Rohaiza Ahmad Redzuan Abdul Munir Abdul Murad Ifa Manzila 1Indonesian Center for Agricultural Biotechnology and Genetic Resources Research and Development IAARD Jln. Tentara Pelajar No. 3A Bogor 16111 West Java Indonesia 2School of Biosciences and Biotechnology Faculty of Science and Technology Universiti Kebangsaan Malaysia Bangi 43600 Selangor Malaysia

Colletotrichum appressoria specific gene (CAS2) expressed during appressorium formation of Colletotrichum gloeosporioides play important role as virulence factors. Determination of the CAS2 protein structure could help deduction of its function and interaction with other factors. The current study aimed to assess in the functional and structural properties of the CAS2 by in silico analyses. CAS2 sequence submitted to the online tool Gene Ontology Functional Enrichment Annotation Tool (GO FEAT) in order to search for homology. The biological importance of the annotated products were characterized based on the analyses of physicochemical properties, subcellular localization, molecular function, protein-protein interaction networks, and 3D structural protein modelling. The results showed that CAS2 is a hydrophobic protein with an average molecular weight of around 46.2 kDa. The N-terminal amino acid (aa) sequence of CAS2 was composed of 22 amino acid residues of signal peptide. The high score probability (1.840) of subcellular location prediction showed that this protein located in plasma membrane. Based on putative transmembrane prediction software, the CAS2 protein is composed of three alpha-helical transmembrane domains with the longest of C-terminal of amino acid residues in cytoplasm. CELLO2GO server predicted that the CAS2 is a structural protein functioning as enzyme and ion binding. Protein interaction network resolved by STRING web server revealed 10 potential interacting protein associates with CAS2. These in silico analysis offered excellent and reliable information for functional characterization of CAS2 protein by using the advanced tools and techniques of computational biology.

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Intelligent traffic congestion forecasting using BiLSTM and adaptive secretary bird optimizer for sustainable urban transportation

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Scientific reports 2025年第1期15卷 18423页

作者： Lalitha Krishnasamy Siva C Rajesh Kumar Dhanaraj Mahmoud Ahmad Al-Khasawneh Taher Al-Shehari Nasser A Alsadhan Shitharth Selvarajan Department of Artificial Intelligence and Data Science Nandha Engineering College Erode Tamil Nadu India. Department of Information Technology Nandha Engineering College Erode Tamil Nadu India. Symbiosis Institute of Computer Studies and Research (SICSR) Symbiosis International (Deemed University) Pune India. School of Computing Skyline University College University City Sharjah 1797 Sharjah UAE. Applied Science Research Center Applied Science Private University Amman Jordan. Computer Skills Department of Self-Development Skill Common First Year Deanship King Saud University 11362 Riyadh Saudi Arabia. Computer Science Department College of Computer and Information Sciences King Saud University 12372 Riyadh Saudi Arabia. Department of Computer Science Kebri Dehar University 250 Kebri Dehar Ethiopia. ShitharthS@kdu.edu.et. Department of Computer Science and Engineering Chennai Institute of Technology Chennai India. ShitharthS@kdu.edu.et. Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura 140401 India. ShitharthS@kdu.edu.et. School of Built Environment Engineering and Computing Leeds Beckett University LS6 3HF Leeds UK. ShitharthS@kdu.edu.et.

Traffic congestion forecasting is one of the major elements of the Intelligent Transportation Systems (ITS). Traffic congestion in urban road networks significantly influences sustainability by increasing air pollution levels. Efficient congestion management enables drivers to bypass heavily trafficked areas and reducing pollutant emissions. However, properly forecasting congestion spread remains challenging due to complex, dynamic, and non-linear nature of traffic patterns. The advent of Internet of Things (IoT) devices has introduced valuable datasets that can support the development of intelligent and sustainable transportation for modern cities. This work presents a Deep Learning (DL) approach of Reinforcement Learning (RL) based Bidirectional Long Short-Term Memory (BiLSTM) with Adaptive Secretary Bird Optimizer (ASBO) for traffic congestion prediction. The experimentation is evaluated on Traffic Prediction Dataset and achieved better Mean Square Error (MSE) and Mean Absolute Error (MAE) with results of 0.015 and 0.133 respectively. Compared to the existing algorithms like RL, Deep Q Learning (DQL), LSTM and BiLSTM, the RL - BiLSTM with ASBO outperformed with the parameters MSE, RMSE, R2, MAE and MAPE with 37%, 27.44%, 26%, 33.52% and 35.8% respectively. The better performance demonstrates that RL- BiLSTM with ASBO is well-suited to predict congestion patterns in road networks.

关键词： Adaptive secretary bird optimization Reinforcement learning Smart cities Traffic congestion

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Co-Processing of Biomass and Plastics Waste Via Integrated Pyrolysis-Gasification Approach: Recent Advances, Challenges, and Opportunities

SSRN

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SSRN 2022年

作者： Yek, Peter Nai Yuh Chan, Yi Herng Foong, Shin Ying Wan Mahari, Wan Adibah Chen, Xiangmeng Peng, Wanxi Liew, Rock Keey Ding, Lu Tsang, Yiu Fai Sonne, Christian Lam, Su Shiung Henan Province International Collaboration Lab of Forest Resources Utilization School of Forestry Henan Agricultural University Zhengzhou450002 China Centre for Research of Innovation and Sustainable Development University College of Technology Sarawak Sarawak Sibu96000 Malaysia Lot 3288 & 3289 Off Jalan Ayer Itam Kawasan Institusi Bangi Selangor Kajang43000 Malaysia Universiti Malaysia Terengganu Kuala Nerus Terengganu 21030 Malaysia College of Science Henan Agricultural University Zhengzhou450002 China NV Western PLT No. 208B Second Floor Macalister Road Penang Georgetown10400 Malaysia Institute of Clean Coal Technology No. 130 Meilong Road Shanghai200237 China Department of Science and Environmental Studies The Education University of Hong Kong Tai Po New Territories Hong Kong Frederiksborgvej 399 PO Box 358 RoskildeDK-4000 Denmark Jiangsu Co-Innovation Center of Efficient Processing Utilization of Forest Resources

The rapid growth of the world population and industrial revolution led to increased demand and production of plastics and biomass waste. However, the current disposal of plastic waste is mainly landfilling which occupies huge space and pollutes the water source and soil nearby. At the same time, there is an abundant resource of biomass waste which is available as a renewable carbonaceous source for bioenergy generation. This review highlights the co-processing of biomass and plastics waste via integrated thermochemical techniques (i.e. pyrolysis and gasification) for effective waste disposal. Co-pyrolysis of plastics and biomass shows the synergistic effects in improving the yield and quality of bio-oil, biochar, and syngas. The addition of plastics in thermochemical reactions can reduce the activation energy and enhance the higher H 2 production in the co-gasification system. The present work also inspects the potential of integrated pyrolysis-gasification system that shows enhanced energy efficiency and significantly makes waste management more sustainable. It was revealed that the integrated system has significantly enhanced the H 2 production via in-line gasification, subsequently improving the yield and selectivity of targeted gaseous products. Adopting microwave, steam purging and acidic catalyst (zeolite) or composite catalyst on porous carbon that contains essential metallic active elements (i.e., Ni, K, Ca, Mg and Al ) assisted in enhancing the heating selectivity, tar cracking and devolatilization. The co-processing approach and integrated system of pyrolysis and gasification have great potential in the waste management system and producing environmentally-friendly energy. © 2022, The Authors. All rights reserved.

关键词： Biomass

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Effects of pressure-cooking and freeze-drying on the quality and functionality of instant black rice: Starch crystallinity, bioactive properties, and digestibility

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International journal of biological macromolecules 2025年 318卷 144754页

作者： Saranya Suwanangul Natthakan Rungraeng Suphat Phongthai Ri Chen Harold Corke Yongfeng Ai Yikai Ren Sukanya Tastub Waraporn Sorndech Phanthipha Laosam Rayudika Aprilia Patindra Purba Supaluck Kraithong Papungkorn Sangsawad Program in Food Science and Technology Faculty of Engineering and Agro-Industry Maejo University Chiang Mai 50290 Thailand. Food Science and Technology Program School of Agro-Industry Mae Fah Luang University 57100 Thailand Research Center of Innovative Food Packaging and Biomaterials School of Agro-Industry Mae Fah Luang University Chiang Rai 57100 Thailand. School of Agro-Industry Faculty of Agro-Industry Chiang Mai University Chiang Mai 50100 Thailand. Faculty of Biotechnology and Food Engineering Technion-Israel Institute of Technology Haifa 3200003 Israel Department of Biotechnology and Food Engineering and Key Laboratory of Science and Engineering for Health and Medicine of Guangdong Higher Education Institutes Guangdong Technion-Israel Institute of Technology Shantou 515063 China. Department of Food and Bioproduct Sciences University of Saskatchewan Saskatoon SK S7N 5A8 Canada. Synchrotron Light Research Institute Nakhon Ratchasima 30000 Thailand. Expert Center of Innovative Health Food Thailand Institute of Scientific and Technological Research Klong Ha Klong Luang Pathum Thani 12120 Thailand. Research and Development Institute Suranaree University of Technology Nakhon Ratchasima 30000 Thailand Postharvest Technology and Innovation in Animal Unit Institute of Agricultural Technology Suranaree University of Technology Nakhon Ratchasima 30000 Thailand. Postharvest Technology and Innovation in Animal Unit Institute of Agricultural Technology Suranaree University of Technology Nakhon Ratchasima 30000 Thailand Department of Health Faculty of Vocational Studies Airlangga University Surabaya 60286 Indonesia. Guangxi Key Laboratory of Marine Drugs Institute of Marine Drugs Guangxi University of Chinese Medicine Nanning 530200 China. Electronic address: supak0504@***. School of Animal Technology and Innovation Institute of Agricultural Technology Suranaree University of Technology Nakhon Ratchasima 30000 Thailand. Electronic address: papungkorn@sut.ac.th.

Starch molecules in black rice offer exceptional nutritional benefits, however, the effects of processing-induced structural changes on their functional properties remain underexplored. This study evaluated the effects of pressure cooking (PC) and electric rice cooking (RC), combined with three drying methods (hot air, vacuum, and freeze-drying), influences the quality of instant rice from two Thai black rice varieties, Jao Kham Hom Maejo 1A (M1A) and Thai Rice Berry (TRB). Among the 40 treatment combinations, only M1A exhibited starch f for instant rice production. Specifically, pressure cooking for 4 min followed by freeze-drying at -20 °C for 12 h (M1A_PC4_F) most effectively preserved starch functionality while retaining high bioactive compounds, including total phenolics, anthocyanins, and antioxidant activities. Structural analysis using X-ray diffraction and differential scanning calorimetry confirmed that this thermal process initiated partial starch gelatinization while maintaining amylose-amylopectin crystallinity. These structural modifications increased resistant starch content, improved pasting properties, and enhanced rehydration characteristics, with the potential to moderate the glycemic response. Collectively, this study introduces pressure cooking (4 min) followed by freeze-drying as a novel approach for producing instant black rice that uniquely preserves starch crystallinity (26 %) while maintaining anthocyanins and resistant starch content for enhanced nutritional value.

关键词： Black rice Freeze-drying Functional properties Resistant starch Starch gelatinization

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A machine learning-based high-precision density functional method for drug-like molecules

Artificial Intelligence Chemistry

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Artificial Intelligence Chemistry 2024年第1期2卷

作者： Jin Xiao YiXiao Chen LinFeng Zhang Han Wang Tong Zhu Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development Shanghai Frontiers Science Center of Molecule Intelligent Syntheses School of Chemistry and Molecular Engineering East China Normal University Shanghai 200062 P.R. China Program in Applied and Computational Mathematics Princeton University Princeton NJ 08544 USA AI for Science Institute Beijing 100080 P.R. China Laboratory of Computational Physics Institute of Applied Physics and Computational Mathematics Beijing 100088 P.R. China NYU-ECNU Center for Computational Chemistry at NYU Shanghai Shanghai 200062 P.R. China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen 518005 P.R. China

In computer-aided drug discovery, accurately determining the structure and properties of drug-like molecules is of utmost importance. This necessitates the use of precise and efficient electronic structure methods. Here, we developed two deep learning-based density functional methods, namely DeePHF and DeePKS, specifically tailored for drug-like molecules. Notably, DeePKS incorporates self-consistency into its framework. With a limited dataset labelled at the CCSD(T)/def2-TZVP level, both models have been able to achieve chemical accuracy in calculating molecular energies and have demonstrated excellent transferability. We anticipate that further advancements in this field will lead to the development of high-quality density functional methods designed specifically for drug discovery purposes. This research showcases the capabilities of deep learning approaches in simplifying the construction complexity associated with traditional DFT methods.

关键词： Machine Learning Density Functional Theory DeePHF DeePKS

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Early-childhood linear growth faltering in low- and middle-income countries (

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NATURE 2023年第7985期623卷 E2-E2页

作者： Benjamin-Chung, Jade Mertens, Andrew Colford, John M., Jr. Hubbard, Alan E. van der Laan, Mark J. Coyle, Jeremy Sofrygin, Oleg Cai, Wilson Nguyen, Anna Pokpongkiat, Nolan N. Djajadi, Stephanie Seth, Anmol Jilek, Wendy Jung, Esther Chung, Esther O. Rosete, Sonali Hejazi, Nima Malenica, Ivana Li, Haodong Hafen, Ryan Subramoney, Vishak Haggstrom, Jonas Norman, Thea Brown, Kenneth H. Christian, Parul Arnold, Benjamin F. Department of Epidemiology & Population Health Stanford University Stanford CA USA Division of Epidemiology & Biostatistics University of California Berkeley Berkeley CA USA Chan Zuckerberg Biohub San Francisco CA USA Hafen Consulting LLC West Richland WA USA DVPL Tech Dubai United Arab Emirates Cytel Inc. Waltham MA USA Quantitative Sciences Bill & Melinda Gates Foundation Seattle WA USA Department of Nutrition University of California Davis Davis CA USA Center for Human Nutrition Department of International Health Johns Hopkins Bloomberg School of Public Health Baltimore MD USA Francis I. Proctor Foundation University of California San Francisco San Francisco CA USA Department of Ophthalmology University of California San Francisco San Francisco CA USA Department of Public Health and Primary Care Ghent University Ghent Belgium Department of Nutrition University of North Carolina at Chapel Hill Chapel Hill NC USA International Centre for Diarrhoeal Disease Research Bangladesh Dhaka Bangladesh Department of Pediatrics and Child Health The Aga Khan University Karachi Pakistan University of Virginia Charlottesville VA USA JiVitA Project John Hopkins Bangladesh Rangpur Bangladesh Center for Child Adolescent and Maternal Health Research Department of Medicine and Health Technology Tampere University Tampere Finland Tampere University Hospital Tampere Finland World Health Organization Geneva Switzerland Center of Data and Knowledge Integration for Health Fundação Oswaldo Cruz Salvador Brazil UNICEF New York NY USA HIV/AIDS & Global Health Research Programme University of Venda Thohoyandou South Africa Indian Institute of Technology New Delhi India Centre for Health Research and Development Society for Applied Studies New Delhi India Sunder Lal Jain Hospital New Delhi India Centre of Excellence in Women & Child Health Institute for Global Health & Development The Aga Khan University Karachi Pakistan Johns Hopkins University Bl

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Sandwich antibody-based biosensor system for identification of Mycobacterium tuberculosis complex and nontuberculous mycobacteria

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Journal of Immunoassay and Immunochemistry 2019年第6期40卷 590-604页

作者： Chuensirikulchai, Kantinan Laopajon, Witida Phunpae, Ponrut Apiratmateekul, Napaporn Surinkaew, Sirirat Tayapiwatana, Chatchai Pata, Supansa Kasinrerk, Watchara Division of Clinical Immunology Department of Medical Technology Faculty of Associated Medical Sciences Chiang Mai University Chiang Mai Thailand Biomedical Technology Research Center National Center for Genetic Engineering and Biotechnology National Science and Technology Development Agency at the Faculty of Associated Medical Sciences Chiang Mai University Chiang Mai Thailand Division of Clinical Microbiology Department of Medical Technology Faculty of Associated Medical Sciences Chiang Mai University Chiang Mai Thailand Department of Medical Technology Faculty of Allied Health Sciences Naresuan University Pitsanulok Thailand Center of Biomolecular Therapy and Diagnostic Faculty of Associated Medical Sciences Chiang Mai University Chiang Mai Thailand

Mycobacterial infection, leading to pulmonary disease, remains a world health problem. Clinical symptoms of pulmonary disease caused by Mycobacterium tuberculosis complex (MTBC) and nontuberculous mycobacteria (NTM) are very similar. A rapid method for the differentiation of MTBC and NTM infection is essential for appropriate therapy. In this study, we aim to establish an antibody-based biosensor system for the identification of MTBC and NTM infection. Monoclonal antibodies (mAbs) specific for Ag85B proteins of mycobacteria were generated and characterized. The generated anti-Ag85B mAb clones AM85B-5 and AM85B-8 reacted to Ag85B of Mycobacterium spp.;in contrast, clone AM85B-9 specifically reacted to Ag85B of MTBC. By employing the produced mAbs, single and sandwich antibody-based biosensors using bio-layer interferometry were established for determination of Ag85B proteins. The sandwich antibody-based biosensor system was demonstrated to be suitable for detection of Ag85B protein and identification of MTBC and NTM. Using anti-Ag85B mAbs AM85B-8 and AM85B-9 as immobilized antibodies on sensor chips and using mAb AM85B-5 as secondary antibody, the established sandwich antibody-based biosensor could discriminate MTBC and NTM. The developed biosensor system can be used for culture confirmation of mycobacteria and speciation to MTBC and NTM. © 2019, © 2019 Taylor & Francis.

关键词： Ag85B antibody-based biosensor Mycobacterium tuberculosis complex nontuberculous mycobacteria Tuberculosis

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