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Synergistic effect of silicon availability and salinity on metal adsorption in a common estuarine diatom

Journal of environmental sciences 2025年第2期148卷 364-374页

作者： Fengyuan Chen Jie Ma Ke Pan SZU-HKUST Joint PhD Program in Marine Environmental Science Shenzhen UniversityShenzhen 518060China Shenzhen Key Laboratory of Marine Microbiome Engineering Institute for Advanced StudyShenzhen UniversityShenzhen 518060China Department of Ocean Science The Hong Kong University of Science and TechnologyHong Kong 999077China

Increasing nitrogen and phosphorus discharge and decreasing sediment input have made silicon(Si)a limiting element for diatoms in *** in nutrient structure and salinity fluctuation can greatly affect metal uptake by estuarine ***,the combined effects of Si and salinity on metal accumulation in these diatoms have not been *** this study,we aimed to investigate how salinity and Si availability combine to influence the adsorption of metals by a widely distributed diatom Phaeodactylum *** data indicate that replete Si and low salinity in seawater can enhance cadmium and copper adsorption onto the diatom *** the single-cell level,surface potential was a dominant factor determining metal adsorption,while surface roughness also contributed to the highermetal loading capacity at lower *** a combination of noninvasive micro-test technology,atomic force microscopy,X-ray photoelectron spectroscopy,and Fourier transform infrared spectroscopy,we demonstrate that the diversity and abundance of the functional groups embedded in diatom cell walls vary with salinity and Si *** results in a change in the cell surface potential and transient metal *** study provides novel mechanisms to explain the highly variable metal adsorption capacity of a model estuarine diatom.

关键词： Diatom Metal adsorption Silicon Salinity Functional group Surface potential

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Effects of ambient silicic acid concentration on the physiology of marine cyanobacterial Synechococcus

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Marine environmental Research 2025年 209卷 107220页

作者： Ou, Qiang Xu, Huo Zhang, Zhen Ma, Jie Pan, Ke Shenzhen Key Laboratory of Marine Microbiome Engineering Institute for Advanced Study Shenzhen University Shenzhen China SZU-HKUST Joint PhD Program in Marine Environmental Science Shenzhen University Shenzhen China Department of Ocean Science The Hong Kong University of Science and Technology Hong Kong

The marine cyanobacterium Synechococcus can accumulate significant amounts of silicon (Si) within its cells, potentially contributing to the vertical transport of biogenic Si in the ocean. This has prompted interest in understanding the uptake, subcellular distribution, and chemical forms of Si in Synechococcus. The surprisingly high intracellular Si concentration could have important impacts on Synechococcus physiology, but these effects have been relatively unexplored. In this study, we investigated the effects of external Si concentrations, [Si(OH)4], on the cell physiology of two strains of Synechococcus (CC9311 and WH7803). Increased ambient [Si(OH)4] significantly enhanced total cellular and water-soluble Si content in Synechococcus, but had little effect on their growth. However, the cell size, volume and photosynthetic performance were significantly reduced in strain WH7803, indicating some harmful effects in the cell. Increases in ambient [Si(OH)4] also altered the Derjaguin-Muller-Toporov (DMT) modulus, adhesion, surface potential and elemental composition of the Synechococcus cells. Notably, significant changes in area-specific adsorbed metals and volume-specific metal content were observed at higher [Si(OH)4] levels, suggesting Si availability in seawater could markedly impact the interactions between Synechococcus cell and environment. Overall, this study provides new insights into the physiological adaptations of marine cyanobacterium Synechococcus to varying environmental silicic acid concentrations. © 2025 Elsevier Ltd

关键词： Psychophysiology

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MiR-1 Is Regulated by Hydrogen Peroxide via MAPK and Limits Cell Migration and Invasion

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environmental Toxicology 2025年 2025 May 16页

作者： Pacurari, Maricica Cox, Irmanecia Farah, Ibrahim Department of Biology College of Science Engineering and Technology Jackson State University Jackson MS United States RCMI Center for Environmental Health College of Science Engineering and Technology Jackson State University Jackson MS United States Environmental Science PhD Program College of Science Engineering and Technology Jackson State University Jackson MS United States

MicroRNA-1 (miR-1) is a conserved microRNA that is highly expressed in skeletal and cardiac muscle tissues. Moreover, miR-1 regulates genes and has critical roles in cell migration and invasion. Downregulation of miR-1 has been found in many pathologies of numerous organs, including the lungs. What exactly contributes to the downregulation of miR-1 is not fully understood, and in the present study, we investigated whether ROS regulate miR-1 and its role in cell migration and invasion. A549 cells were grown and maintained in DMEM:F12 (1:1) and supplemented with 10% FBS and 1000 U of Penicillin/Streptomycin and maintained as recommended by the manufacturer (ATCC). Cell migration and invasion, IHC, Western blot, qPCR, ROS, miR-1 transfection, and qPCR were used to determine miR-1 regulation and its role in cell migration. Exogenous miR-1 decreased the formation of ROS and inhibited cell migration and invasion, whereas inhibition of miR-1 increased ROS formation and stimulated cell migration and invasion. Inhibition of miR-1 induced the formation of actin filaments contractile structures, whereas exogenous miR-1 limited the formation of these structures. Hydrogen peroxide significantly decreased miR-1 level, whereas inhibition of Nox4 had no effect on miR-1 level. Alpha amanitin did not decrease miR-1 level, whereas inhibition of NF-кB temporally decreased miR-1 level. This study demonstrates that ROS suppress miR-1 and that miR-1 is posttranscriptionally regulated via MAPK. Endogenous Nox4-dependent ROS are not involved in miR-1 regulation, whereas exogenous ROS regulates miR-1. NF-κB plays a key role in miR-1 regulation in both redox and nonredox environments. Moreover, Mir-1 limits cell migration and invasion even in the presence of ROS. TSP-1 is a major regulator of TGFβ and its expression is upregulated by ROS. Our work indicates ROS is a major regulator of miR-1 and TSP-1 and could be a potential therapeutic target to limit ROS- and non-ROS-mediated processes in l

关键词： cell migration MAPK miR-1 NF-кB Nox4 posttranscriptional ROS TSP-1

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CIWARS: A Web Server for Antibiotic Resistance Surveillance Using Longitudinal Metagenomic Data

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Journal of Molecular Biology 2025年

作者： Emon, Muhit Islam Cheung, Yat Fei Stoll, James Rumi, Monjura Afrin Brown, Connor Choi, Joung Min Moumi, Nazifa Ahmed Ahmed, Shafayat Song, Haoqiu Sein, Justin Yao, Shunyu Khan, Ahmad Gupta, Suraj Kulkarni, Rutwik Butt, Ali Vikesland, Peter Pruden, Amy Zhang, Liqing Department of Computer Science Virginia Tech Blacksburg 24060 VA United States Fralin Life Science Institute Virginia Tech Blacksburg 24060 VA United States Department of Civil and Environmental Engineering Virginia Tech Blacksburg 24060 VA United States The Interdisciplinary PhD Program in Genetics Bioinformatics and Computational Biology Virginia Tech Blacksburg 24060 VA United States

The rise of antibiotic resistance (AR) poses a substantial threat to human and animal health, food security, and economic stability. Wastewater-based surveillance (WBS) has emerged as a powerful strategy for population-level AR monitoring, providing valuable data to guide public health and policy decisions. Metagenomic sequencing is especially promising, as it can yield comprehensive profiles of antibiotic resistance genes (ARGs) and other genes relevant to AR in a single run. However, online analytical platforms to facilitate analysis of longitudinal metagenomic data are lacking. To address this, we introduce CyberInfrastructure for Waterborne Antibiotic Resistance Surveillance (CIWARS), a web server configured for characterizing key AR trends from longitudinal metagenomic WBS data. CIWARS offers comprehensive profiling of ARGs and taxonomic profiling of pathogen-associated bacterial taxonomic groups, identifies potential associations of ARGs with mobile genetic elements (MGEs) and pathogen-containing taxa, and assesses resistome risk based on the co-occurrence of ARGs, MGEs, and pathogen-like sequences. Additionally, it detects anomalous AR indicators over time, aiding in identifying potential events of concern, such as the emergence of resistant strains or outbreaks. Through interactive temporal data visualization, CIWARS enables AR monitoring and can serve as a tool to inform effective and timely interventions to mitigate the spread and transmission of AR. Here, CIWARS is demonstrated using longitudinal metagenomic data from a wastewater treatment plant (WWTP) influent and effluent, but it can be extended to any environment. CIWARS provides a valuable tool to support global efforts to combat the evolution and spread of AR, while also guiding agricultural and public health efforts aimed at optimizing antibiotic use. The web server is freely available at https://***/. © 2025 Elsevier Ltd

关键词： anomaly detection antibiotic resistance (AR) AR indicator profiling longitudinal metagenomics wastewater-based surveillance

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A multi-nutrient nanocomposite enhances UV stress tolerance and modulates nutrient accumulation in lettuce

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environmental science: Nano 2025年

作者： Thangavelu, Raja muthuramalingam da Silva, Washington Hernandez-Viezcas, Jose A. Oyanedel-Craver, Vinka Gardea-Torresdey, Jorge L. Dimkpa, Christian O. White, Jason C. Mena, Nubia Zuverza Connecticut Agricultural Experiment Station New Haven 06511 CT United States Department of Chemistry and Biochemistry The University of Texas at El Paso 500 West University Avenue El Paso 79968 TX United States Department of Civil and Environmental Engineering University of Rhode Island Kingston RI United States Environmental Science and Engineering PhD Program University of Texas at El Paso El Paso United States

This study introduces a novel multielement (Zn-Mg-Mn-Fe) nanocomposite that serves both as a UV-protective agent and a nutrient delivery system for Lactuca sativa (lettuce). Plants were grown indoors in a potting soil-like mix, under artificial lighting (from light emitting diodes, LEDs) or under LED + UV radiation to simulate excessive sunlight exposure (light stress). Lettuce was treated with foliar applications of the nanocomposite at 100 mg L⁻¹, 200 mg L⁻¹, and 300 mg L⁻¹, with 1 mL applied per plant during the fifth week of growth (a total of 0.1, 0.2 or 0.3 mg of the composite respectively per plant). Plants were exposed to UV radiation (360-400 nm) for 10 hours daily over two weeks. The 300 mg L⁻¹ treatment significantly enhanced photosynthetic efficiency and plant growth, increasing chlorophyll content (66.7% ± 3.5), leaf area (45% ± 2.1), and dry biomass (43.68% ± 1.8) compared to untreated and ionic controls. It also mitigated UV-induced stress, reducing UV-induced damage scores by 73% compared to controls and lowering stress markers, with flavonoid production reduced to 30.5% ± 2.3 of control levels and SOD activity reduced to 25.8% ± 1.8 of control levels. The composite's-controlled nutrient release mechanism facilitated rapid Mg uptake (220 mg kg⁻¹ dry weight in leaves within 4 days) and sustained delivery of Zn, Mn, and Fe over a 7-10-day period. Long-term nutrient uptake analysis showed increases in Mn (55.3% ± 3.2), Mg (47.8% ± 2.7), and Fe (62.5% ± 4.1). Enhanced P (28.5% ± 2.2) and K (35.7% ± 3.1) accumulation further boosted the nutritional quality of edible tissues. Additionally, the nanocomposite demonstrated the unique ability to convert harmful UV radiation into visible light, providing dual benefits of UV protection and enhanced photosynthetic activity. These findings highlight the potential of this multi-functional nanocomposite as a sustainable solution to improve crop resilience, optim

关键词： Lettuce

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Interactive Visualization and App Development for Precipitation Data in Sub-Saharan Africa

Interactive Visualization and App Development for Precipitat...

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IOT, Electronics and Mechatronics Conference (IEMTRONICS), IEEE International

作者： Divydharshini Karthikeyan Sudha Shah Aparna S. Varde Clement Alo Department of Computer Science Environmental Management and Science PhD program Department of Earth and Environmental Science Environmental Management and Science PhD program

ISBN: (数字)9781728196152

ISBN: (纸本)9781728196169

Precipitation plays a highly significant part in the hydrological cycle and is responsible for depositing most of the freshwater on earth. It can also impact the climate ecosystem. Considerable work has been performed to understand, model and predict precipitation. However, to the best of our knowledge, hardly any interactive visualizations exist that allow end-users to obtain a better perception of local impacts; also there are no specific apps for this purpose. The two goals of our work are thus: to design a visualization tool that illustrates changes in precipitation in a given time period with analysis; and to design a mobile application (app) that displays Sub-Saharan precipitation patterns, both using big data. This work would be advantageous to environmental scientists, as well as local residents of the respective areas. It would also be beneficial to students interested in conducting climate-based research. It addresses the theme of IoT (Internet of Things) which involves providing ubiquitous access to Internet-Based information on platforms such as smartphones and other mobile devices.

关键词： Data visualization Tools Big Data Meteorology Africa Mobile applications Human computer interaction

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Prediction Tool on Fine Particle Pollutants and Air Quality for environmental Engineering

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SN Computer science 2022年第3期3卷 184页

作者： Varde, Aparna S. Pandey, Abidha Du, Xu Dept. of Computer Science Environmental Science and Management PhD Program Montclair State University Montclair NJ United States Visiting Researcher at Max Planck Institute for Informatics Saarbrücken Germany Department of Computer Science Montclair State University Montclair NJ United States Department of Earth and Environmental Science Environmental Science and Management PhD Montclair State University Montclair NJ United States

This article focuses on the research, design and implementation of a prediction tool for air quality to estimate pollutant concentrations, contributing to environmental engineering. It addresses prediction of fine particle air pollutants of diameter less than 2.5 µm (particulate matter 2.5), their concentration being substantially influenced by urban traffic. We collect worldwide multicity data from health-related public sources on which mining is performed using classical data mining/machine learning paradigms: association rules, clustering and classification. Challenges include adapting appropriate techniques based on data, and capturing subtle domain-specific aspects. The prediction tool is built using knowledge discovered by mining, leveraging health standards, catering to novice, intermediate and expert users. The prediction output is accurate, efficient, interpretable and useful as evident from our experiments. The tool is helpful for urban decision support. This work is beneficial in developing software systems such as intelligent tutors, mobile device apps and smart city tools. It contributes to smart environment, mobility and living, making a positive impact on smart cities and sustainability. In this work, we claim that classical computational paradigms in their fundamental form can be adapted to solve environmental engineering problems, with easy comprehension, as per the Occam’s razor principle that advocates simplicity. This article constitutes applied research: using computational techniques to solve domain-specific problems. Future work includes exploring models in deep learning such as CNN and Bi-LSTM, and considering different types of pollutants as well as other sources besides multicity traffic data, to conduct further studies. This would address additional challenges with enhancements. © 2022, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd.

关键词： Applied research Decision support environmental engineering Health informatics Machine learning Urban studies

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Genomic and transcriptomic dissection of Theionarchaea in marine ecosystem

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science China(Life sciences) 2022年第6期65卷 1222-1234页

作者： Mingwei Cai Changhai Duan Xinxu Zhang Jie Pan Yang Liu Cuijing Zhang Meng Li Archaeal Biology Center Shenzhen Key Laboratory of Marine Microbiome EngineeringInstitute for Advanced StudyShenzhen UniversityShenzhen 518060China SZU-HKUST Joint PhD Program in Marine Environmental Science Shenzhen UniversityShenzhen 518060China

Theionarchaea is a recently described archaeal class within the *** it is widely distributed in sediment ecosystems,little is known about its metabolic potential and ecological ***,we used metagenomics and metatranscriptomics to characterize 12 theionarchaeal metagenome-assembled genomes,which were further divided into two subgroups,from coastal mangrove sediments of China and seawater columns of the Yap *** analysis revealed that apart from the canonical sulfhydrogenase,Theionarchaea harbor genes encoding heliorhodopsin,group 4[NiFe]-hydrogenase,and flagellin,in which genes for heliorhodopsin and group 4[NiFe]-hydrogenase were transcribed in mangrove ***,the theionarchaeal substrate spectrum may be broader than previously reported as revealed by metagenomics and metatranscriptomics,and the potential carbon substrates include detrital proteins,hemicellulose,ethanol,and CO_(2).The genes for organic substrate metabolism(mainly detrital protein and amino acid metabolism genes)have relatively higher transcripts in the top sediment layers in mangrove *** addition,co-occurrence analysis suggested that the degradation of these organic compounds by Theionarchaea might be processed in syntrophy with fermenters(e.g.,Chloroflexi)and ***,these observations expand the current knowledge of the metabolic potential of Theionarchaea,and shed light on the metabolic strategies and roles of these archaea in the marine ecosystems.

关键词： Theionarchaea metagenome metatranscriptome metabolic potentials ecological roles

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An Ordinance-Tweet Mining App to Disseminate Urban Policy Knowledge for Smart Governance 19th

An Ordinance-Tweet Mining App to Disseminate Urban Policy Kn...

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19th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2020

作者： Varghese, Christina Varde, Aparna S. Du, Xu Department of Computer Science Montclair State University MontclairNJ United States Department of Earth and Environmental Science Montclair State University MontclairNJ United States Environmental Science and Management PhD Program Montclair State University MontclairNJ United States

ISBN: (纸本)9783030450014

This paper focuses on how populations by the use of technology, more specifically an app, can comprehend the enactment of ordinances (local laws) in an urban area along with their public reactions expressed as tweets. Furthermore, they can understand how well the area is developing and enhancing as a Smart City. The main goal of this research is to develop an Ordinance-Tweet Mining App that disseminates the results of analyzing ordinances and tweets about them, especially related to Smart City Characteristics such as Smart Environment, Smart Mobility etc. This app would be beneficial to various users such as environmental scientists, policy makers, city committees as well as the common public in becoming more aware of legislative bodies, and possibly contributing in different aspects to make the urban area improve as a Smart City. This work fits the realm of Smart Governance due to transparency via public involvement. © 2020, IFIP International Federation for Information Processing.

关键词： Sentiment analysis

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Urban legislation assessment by data analytics with smart city characteristics

Urban legislation assessment by data analytics with smart ci...

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IEEE Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON)

作者： Xu Du Diane Liporace Aparna S. Varde Earth and Environmental Studies Environmental Mgmt PhD Program Montclair State University NJ USA Department of Computer Science Montclair State University Montclair NJ USA Department of Computer Science PhD Program Montclair State University NJ USA

ISBN: (纸本)9781538611050

Smart cities receive great attention today especially in conjunction with ubiquitous computing. People feel the need to access information about their cities anywhere anytime. They wish to be actively involved with local government bodies for policy decisions affecting urban lifestyle. Accordingly, this paper describes our research on urban policy management. We analyze urban legislation, more specifically, ordinances or local laws. We categorize ordinances based on smart city characteristics they address. This work deploys data warehousing, XML data management and data mining over categorized ordinances. Interesting findings include relative importance of smart city characteristics considering the focus given by urban agencies. This research helps agencies assess their current ordinance policies with decision support for the future. It also provides urban residents at-a-glance information about their cities and policies with analysis. This work has broader impacts of enhancing smart cities and ubiquitous computing by making useful information widely accessible with suitable inferences.

关键词： XML Smart cities Weapons Databases Data mining Data warehouses

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