COMPUTATIONAL CHEMODYNAMICS LABORATORY

Time 2021-08-16 17:07:21

Web Name: COMPUTATIONAL CHEMODYNAMICS LABORATORY

WebSite: http://ccl.rutgers.edu

ID:186683

Keywords:

COMPUTATIONAL,CHEMODYNAMICS,LABORATORY,

Description:

Welcome to CCL CCL is a component of the Environmental and Occupational Health Sciences Institute (EOHSI) at Rutgers The State University of New Jersey, pursuing research in:Multiscale computational modeling ( from molecules to populations ) of environmental and biological systems and of their interactionsEnviroinformatics, bioinformatics, and socioinformatics; predictive big data analytics for human exposures and health outcomes  Objective of the research efforts at CCL is the development and application of methods for: ENVIRONMENTAL MODELING IN A CHANGING CLIMATE: Predicting transport/fate and quantifying concentrations/depositions of chemical and biological stressors in multimedia environments, with special consideration of the effects of climatic change Examples of Publications in this Research AreaZhang Y., Bielory L., Cai T., Mi Z. and Georgopoulos P. (2015). Predicting onset and duration of airborne allergenic pollen season in the United States. Atmospheric Environment 103: 297-306. DOI:10.1016/j.atmosenv.2014.12.019. PMCID:PMC4302955.Zhang Y., Bielory L., Mi Z., Cai T., Robock A. and Georgopoulos P. (2014). Allergenic pollen season variations in the past two decades under changing climate in the United States. Global Change Biology 21(4): 1581-1589. DOI:10.1111/gcb.12755. PMCID:PMC4356643.Zhang Y., Bielory L. and Georgopoulos P.G. (2014). Climate change effect on Betula (birch) and Quercus (oak) pollen seasons in US. International Journal of Biometeorology 58(5): 909-919. DOI:10.1007/s00484-013-0674-7. PMCID:PMC3851577Zhang Y., Isukapalli S., Bielory L. and Georgopoulos P. (2013). Bayesian analysis of climate change effects on observed and projected airborne levels of birch pollen. Atmospheric Environment 68(1): 64-73. DOI:10.1016/j.atmosenv.2012.11.028. PMCID:PMC3601922.Lioy P.J. and Georgopoulos P.G. (2011). New Jersey: A case study of the reduction in urban and suburban air pollution from the 1950s to 2010. Environmental Health Perspectives 119(10): 1351-1355. DOI:10.1289/ehp.1103540. PMCID:PMC3230450.Hogrefe C., Isukapalli S.S., Tang X., Georgopoulos P.G., He S., Zalewsky E.E., Hao W., Ku J.-Y., Key T. and Sistla G. (2011). Impact of biogenic emission uncertainties on the simulated response of O3 and PM2.5 to anthropogenic emission reductions. Journal of the Air and Waste Management Association 61: 92-108. DOI:10.3155/1047-3289.61.1.92. PMCID:PMC3079461.Efstathiou C., Isukapalli S.S. and Georgopoulos P.G. (2011). A mechanistic modeling system for estimating large scale emissions and transport of pollen and co-allergens. Atmospheric Environment 45(13): 2260-2276. DOI:10.1016/j.atmosenv.2010.12.008. PMCID:PMC3079563. EXPOSURE MODELING AND EXPOSOMICS: Estimating multiroute/multipathway exposures of individuals and populations to stressors present in various indoor and outdoor microenvironments Examples of Publications in this Research AreaRoyce S.G., Mukherjee D., Cai T., Xu S.S., Alexander J.A., Mi Z., Calderon L., Mainelis G., Lee K., Lioy P.J., Tetley T.D., Chung K.F., Zhang J. and Georgopoulos P.G. (2014). Modeling population exposures to silver nanoparticles present in consumer products. Journal of Nanoparticle Research. 16(11): 2724. DOI:10.1007/s11051-014-2724-4. PMCID:PMC4346165.Mukherjee D., Royce S.G., Alexander J.A., Buckley B., Isukapalli S.S., Bandera E.V., Zarbl H. and Georgopoulos P.G. (2014). Physiologically-based toxicokinetic modeling of zearalenone and its metabolites: Application to the Jersey Girl study. Plos One 9(12): e113632. DOI:10.1371/journal.pone.0113632. PMCID:PMC4256163.Zhang Y., Isukapalli S., Georgopoulos P. and Weisel C. (2013). Modeling flight attendants’ exposures to pesticide in disinsected aircraft cabins. Environmental Science Technology 47(24): 14275-14281. DOI:10.1021/es403613h. PMCID:PMC3920731Mitchell J., Arnot J.A., Jolliet O., Georgopoulos P., Isukapalli S., Dasgupta S., Pandian M., Wambaugh J., Egeghy P., Cohen-Hubal E.A. and Vallero D.A. (2013). Comparison of modeling approaches to prioritize chemicals based on estimates of exposure and exposure potential. Science of The Total Environment 458–460: 555-567. DOI:10.1016/j.scitotenv.2013.04.051. PMCID:PMC398378.Isukapalli S.S., Brinkerhoff C.J., Xu S., Dellarco M., Landrigan P.J., Lioy P.J. and Georgopoulos P.G. (2013). Exposure indices for the National Children s Study: application to inhalation exposures in Queens County, NY. Journal of Exposure Science and Environmental Epidemiology 23(1): 22-31. DOI:10.1038/jes.2012.99. PMCID:3961756.Yang Y., Xu X. and Georgopoulos P.G. (2010). A Bayesian population PBPK model for multiroute chloroform exposure. Journal of Exposure Science and Environmental Epidemiology 20(4): 326-341. DOI:10.1038/jes.2009.29. PMCID:PMC3063650.Xue J., Zartarian V., Wang S.W., Liu S.V. and Georgopoulos P.G. (2010). Probabilistic modeling of dietary arsenic exposure and dose and evaluation with 2003-2004 NHANES data. Environmental Health Perspectives 118(3): 345-350. DOI:10.1289/ehp.0901205. PMCID:PMC2854761.Vallero D., Isukapalli S., Zartarian V., McCurdy T., McKone T., Georgopoulos P.G. and Dary C. (2010). Modeling and predicting pesticide exposures. Chapter 44. InHayes’ Handbook of Pesticide Toxicology Third Edition. Krieger, R. (ed.), Academic Press: pp.995-1020 Lioy P.J., Isukapalli S., Trasande L., Thorpe L., Dellarco M., Weisel C., Georgopoulos P.G., Yung C., Brown M. and Landrigan P. (2009). Using national and local extant data to characterize environmental exposures in the National Children’s Study (NCS): Queens County, New York. Environmental Health Perspectives 117(10): 1494-1504. DOI:10.1289/ehp.0900623. PMCID:PMC2790501.Georgopoulos P.G., Wang S.-W., Yang Y.-C., Xue J., Zartarian V.G., McCurdy T. and Ozkaynak H. (2008). Biologically based modeling of multimedia, multipathway, multiroute population exposures to arsenic. Journal of Exposure Science and Environmental Epidemiology 18(5): 462-476. DOI:10.1038/sj.jes.7500637. PMCID:PMC3068596. BIOLOGICALLY BASED PHARMACOKINETICS AND DOSIMETRY MODELING: Estimating internal doses for appropriate target tissues, using physiologically-based transport and toxicokinetic modeling Examples of Publications in this Research AreaMukherjee D., Porter A., Ryan M., Schwander S., Chung K.F., Tetley T., Zhang J. and Georgopoulos P. (2015). Modeling interactions of engineered nanoparticles in the pulmonary alveolar lining fluid. Nanomaterials 5(3): 1223-1249. DOI:10.3390/nano5031223. PMCID:PMC4521411.Mukherjee D., Leo B.F., Royce S.G., Porter A.E., Ryan M.P., Schwander S., Chung K.F., Tetley T.D., Zhang J. and Georgopoulos P.G. (2014). Modeling physicochemical interactions affecting in vitro cellular dosimetry of engineered nanomaterials: application to nanosilver. Journal of Nanoparticle Research 16 (10): 2616. DOI:10.1007/s11051-014-2616-7. PMCID:PMC4295810.Mukherjee D., Royce S.G., Alexander J.A., Buckley B., Isukapalli S.S., Bandera E.V., Zarbl H. and Georgopoulos P.G. (2014). Physiologically-based toxicokinetic modeling of zearalenone and its metabolites: Application to the Jersey Girl study. Plos One 9(12): e113632. DOI:10.1371/journal.pone.0113632. PMCID:PMC4256163.Sasso A., Georgopoulos P.G., Krishnan K. and Isukapalli S. (2012). Bayesian analysis of a lipid-based physiologically-based toxicokinetic model of a PCB mixture in rats. Journal of Toxicology Article ID 895391. DOI:10.1155/2012/895391. PMCID:PMC3270437.Sasso A., Isukapalli S. and Georgopoulos P. (2010). A generalized physiologically-based toxicokinetic modeling system for chemical mixtures containing metals. Theoretical Biology and Medical Modelling 7(1): 17. DOI:10.1186/1742-4682-7-17. PMCID:PMC2903511.Yang Y., Xu X. and Georgopoulos P.G. (2010). A Bayesian population PBPK model for multiroute chloroform exposure. Journal of Exposure Science and Environmental Epidemiology 20(4): 326-341. DOI:10.1038/jes.2009.29. PMCID:PMC3063650.Xue J., Zartarian V., Wang S.W., Liu S.V. and Georgopoulos P.G. (2010). Probabilistic modeling of dietary arsenic exposure and dose and evaluation with 2003-2004 NHANES data. Environmental Health Perspectives 118(3): 345-350. DOI:10.1289/ehp.0901205. PMCID:PMC2854761.Ierapetritou M.G., Georgopoulos P.G., Roth C.M. and Androulakis I.P. (2009). Tissue level modeling of xenobiotic metabolism in liver: An emerging tool for enabling clinical translational research. Clinical and Translational Science 2(3): 228 237. DOI:10.1111/j.1752-8062.2009.00092.x. PMCID:PMC3068531.Isukapalli S.S., Roy A. and Georgopoulos P.G. (2007). Physiologically Based Pharmacokinetic Modeling: Inhalation, Ingestion, and Dermal Absorption (Chapter 43). In Pharmacometrics: the Science of Quantitative Pharmacology. Ette, E. I. and Williams, P. J. (eds.), Wiley: pp.1069-1108 COMPUTATIONAL TOXICOLOGY: Quantifying effects of xenobiotic dose to cells, tissues, organs and the whole organism, using multiscale toxicodynamic modeling for dose-response assessments Examples of Publications in this Research AreaMukherjee D., Royce S.G., Sarkar S., Thorley A., Schwander S., Ryan M.P., Porter A.E., Chung K.F., Tetley T.D., Zhang J. and Georgopoulos P.G. (2014). Modeling in vitro cellular responses to silver nanoparticles. Journal of Toxicology. ID 852890. DOI:10.1155/2014/852890. PMCID:PMC4206931.Mukherjee D., Leo B.F., Royce S.G., Porter A.E., Ryan M.P., Schwander S., Chung K.F., Tetley T.D., Zhang J. and Georgopoulos P.G. (2014). Modeling physicochemical interactions affecting in vitro cellular dosimetry of engineered nanomaterials: application to nanosilver. Journal of Nanoparticle Research 16 (10): 2616. DOI:10.1007/s11051-014-2616-7. PMCID:PMC4295810.Mukherjee D., Botelho D., Gow A., Zhang J. and Georgopoulos P.G. (2013). Computational multiscale toxicodynamic modeling of silver and carbon nanoparticle effects on mouse lung function. PLOS One8(12): e80917. DOI:10.1371/journal.pone.0080917. PMCID:PMC3849047.Stamatelos S.K., Androulakis I.P., Kong A.-N.T. and Georgopoulos P.G. (2013). A semi-mechanistic integrated toxicokinetic–toxicodynamic (TK/TD) model for arsenic(III) in hepatocytes. Journal of Theoretical Biology 317: 244–256. DOI:10.1016/j.jtbi.2012.09.019. PMCID:PMC4026948.Stamatelos S.K., Brinkerhoff C.J., Isukapalli S.S. and Georgopoulos P.G. (2011). Mathematical model of uptake and metabolism of arsenic(III) in human hepatocytes – Incorporation of cellular antioxidant response and threshold-dependent behavior. BMC Systems Biology 5(16). DOI:10.1186/1752-0509-5-16. PMCID:PMC3302683.Georgopoulos P.G., Isukapalli S., Androulakis I.P., Ierapetritou M.G. and Welsh W.J. (2011). Multiscale integration of toxicokinetic and toxicodynamic processes: From cell and tissue to organ and “whole body” models. In Handbook of Systems Toxicology. Casciano, D. and Sahu, S. (eds.), John Wiley Sons. pp.619-668 Gerecke D., Chen M., Isukapalli S., Gordon M.K., Chang Y.-C., Tong W., Androulakis I. and Georgopoulos P.G. (2009). Differential gene expression profiling of mouse skin after sulfur mustard exposure: extended time response and inhibitor effect. Toxicology and Applied Pharmacology 234(2): 156-165. DOI:10.1016/j.taap.2008.09.020. PMCID:PMC3066660. GIS, DATA ANALYTICS AND MACHINE LEARNING FOR PUBLIC HEALTH PROBLEMS: Developing and applying methods for mining information from large and complex spatiotemporal datasets relevant to environmental, demographic, socioeconomic and behavioral determinants of health Examples of Publications in this Research AreaPavilonis B.T., Lioy P.J., Guazzetti S., Bostick B.C., Donna F., Peli M., Zimmerman N.J., Bertrand P., Lucas E., Smith D.R., Georgopoulos P.G., Mi Z., Royce S.G. and Lucchini R.G. (2014). Manganese concentrations in soil and settled dust in an area with historic ferromanganese production used in steel. Journal of Exposure Science and Environmental Epidemiology. DOI:10.1038/jes.2014.70. PMCID:PMC4406789.Zhang Y., Bielory L., Mi Z., Cai T., Robock A. and Georgopoulos P. (2014). Allergenic pollen season variations in the past two decades under changing climate in the United States. Global Change Biology 21(4): 1581-1589. DOI:10.1111/gcb.12755. PMCID:PMC4356643.Georgopoulos P.G., Brinkerhoff C.J., Isukapalli S., Dellarco M., Landrigan P.J. and Lioy P.J. (2014). A tiered framework for risk-relevant characterization and ranking of chemical exposures: Applications to the National Children’s Study (NCS). Risk Analysis 34(7): 1299-316. DOI:10.1111/risa.12165. PMCID:PMC4158851.Georgopoulos P.G. and Lioy P.J. (2014). Geographic Information Systems in Children’s Environmental Health. In Textbook of Children s Environmental Health. Landrigan, P. J. and Etzel, R. A. (eds.) New York, NY, Oxford University Press: pp.69-82.Mitchell J., Arnot J.A., Jolliet O., Georgopoulos P., Isukapalli S., Dasgupta S., Pandian M., Wambaugh J., Egeghy P., Cohen-Hubal E.A. and Vallero D.A. (2013). Comparison of modeling approaches to prioritize chemicals based on estimates of exposure and exposure potential. Science of The Total Environment 458–460: 555-567. DOI:10.1016/j.scitotenv.2013.04.051. PMCID:PMC398378.Isukapalli S.S., Brinkerhoff C.J., Xu S., Dellarco M., Landrigan P.J., Lioy P.J. and Georgopoulos P.G. (2013). Exposure indices for the National Children s Study: application to inhalation exposures in Queens County, NY. Journal of Exposure Science and Environmental Epidemiology 23(1): 22-31. DOI:10.1038/jes.2012.99. PMCID:3961756.Carter G.P., Miskewitz R.J., Isukapalli S., Mun Y., Vyas V., Yoon S., Georgopoulos P. and Uchrin C.G. (2011). Comparison of kriging and cokriging for the geostatistical estimation of specific capacity in the Newark Basin (NJ) aquifer system. Journal of Environmental Science and Health, Part A: Toxic/Hazardous Substances and Environmental Engineering 46 (4): 371-377. DOI:10.1080/10934529.2011.542373.Lioy P.J., Isukapalli S., Trasande L., Thorpe L., Dellarco M., Weisel C., Georgopoulos P.G., Yung C., Brown M. and Landrigan P. (2009). Using national and local extant data to characterize environmental exposures in the National Children’s Study (NCS): Queens County, New York. Environmental Health Perspectives 117(10): 1494-1504. DOI:10.1289/ehp.0900623. PMCID:PMC2790501.Georgopoulos P.G., Sasso A.F., Isukapalli S.S., Lioy P.J., Vallero D.A., Okino M. and Reiter L. (2009). Reconstructing population exposures to environmental chemicals from biomarkers: Challenges and opportunities. Journal of Exposure Science and Environmental Epidemiology 19(2): 149-171. DOI:10.1038/jes.2008.9. PMCID:PMC3068528.Toggle Content CCL s efforts support the development of computer simulation-based alternatives to animal testing for risk assessment. PANOS GEORGOPOULOS, DIRECTORDr. Georgopoulos is Professor of Environmental and Occupational Health and Justice at the Rutgers School of Public Health – Rutgers Biomedical and Health Sciences, with a joint appointment in the Department of Pharmacology, Robert Wood Johnson Medical School. He has been serving on the faculty of R. W. Johnson Medical School and on the Graduate Faculties of Chemical Biochemical Engineering, Biomedical Engineering, and of Environmental Sciences at Rutgers University since 1989. He is a member of the Environmental and Occupational Health Sciences Institute (EOHSI) of Rutgers where he directs the State-funded Ozone Research Center and the Informatics and Computational Toxicology Core for the NIEHS Center for Environmental Exposures and Disease (CEED). Dr. Georgopoulos received his M.S. and Ph.D. Degrees in Chemical Engineering from the California Institute of Technology (Caltech) and his Dipl. Ing. Degree from the National Technical University of Athens. At EOHSI he established and directs the Computational Chemodynamics Laboratory (CCL), a state-of-the-art high performance computing facility for informatics and modeling of complex environmental and biological systems. More 31st Annual Meeting of ISES (International Society of Exposure Science): August 30 - September 2, 2021Starts: 8:00 amEnds: 8:00 pmNote: The theme of the 2021 Meeting, to be held online, is “Multisector Engagement for Addressing Emerging Environmental Exposures” More details... Rutgers COVID-19 Research-In-Progress Seminar: Organoids, multiomics and AI: Integrative Approaches to Understand Mechanisms of COVID-19 Associated Kidney Injury; Hong Li (NJMS) Evren Azeloglu (Icahn School of Medicine at Mount Sinai)Starts: 12:00 pmEnds: 1:00 pm More details... Special Populations Seminar: Environmental Determinants of Health - Exploring Medicare Outcomes Using Area-Level Data; Soko Setoguchi, Jennifer Miles, Bonnie Quin (Rutgers)Starts: 12:00 pmEnds: 1:00 pm More details... Special Populations Seminar: Theory, Methods, and Data Resources for Research on Mitigation of Structural Racism and Discrimination in Health Care and Social Policy; Olga F. Jarrín Montaner (Rutgers)Starts: 12:00 pmEnds: 1:00 pm More details...

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