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Meraz-Cruz N, Manzano-León N, Sandoval-Colin DE, García de León Méndez MDC, Quintana-Belmares R, Tapia LS, Osornio-Vargas AR, Buxton MA, O'Neill MS, Vadillo-Ortega F. Effects of PM 10 Airborne Particles from Different Regions of a Megacity on In Vitro Secretion of Cytokines by a Monocyte Line during Different Seasons. TOXICS 2024; 12:149. [PMID: 38393244 PMCID: PMC10892217 DOI: 10.3390/toxics12020149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Revised: 01/30/2024] [Accepted: 02/01/2024] [Indexed: 02/25/2024]
Abstract
Several epidemiological studies have demonstrated that particulate matter (PM) in air pollution can be involved in the genesis or aggravation of different cardiovascular, respiratory, perinatal, and cancer diseases. This study assessed the in vitro effects of PM10 on the secretion of cytokines by a human monocytic cell line (THP-1). We compared the chemotactic, pro-inflammatory, and anti-inflammatory cytokines induced by PM10 collected for two years during three different seasons in five different Mexico City locations. MIP-1α, IP-10, MCP-1, TNF-α, and VEGF were the main secretion products after stimulation with 80 μg/mL of PM10 for 24 h. The THP-1 cells showed a differential response to PM10 obtained in the different sites of Mexico City. The PM10 from the north and the central city areas induced a higher pro-inflammatory cytokine response than those from the south. Seasonal pro-inflammatory cytokine secretion always exceeded anti-inflammatory secretion. The rainy-season-derived particles caused the lowest pro-inflammatory effects. We concluded that toxicological assessment of airborne particles provides evidence supporting their potential role in the chronic exacerbation of local or systemic inflammatory responses that may worsen the evolution of some chronic diseases.
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Affiliation(s)
- Noemi Meraz-Cruz
- Unidad de Vinculación Científica de la Facultad de Medicina, UNAM en el Instituto Nacional de Medicina Genómica, Mexico City 14610, Mexico
| | - Natalia Manzano-León
- Subdirección de Investigación Básica, Instituto Nacional de Cancerología, Mexico City 14080, Mexico
| | - Daniel Eduardo Sandoval-Colin
- Unidad de Vinculación Científica de la Facultad de Medicina, UNAM en el Instituto Nacional de Medicina Genómica, Mexico City 14610, Mexico
| | | | - Raúl Quintana-Belmares
- Subdirección de Investigación Básica, Instituto Nacional de Cancerología, Mexico City 14080, Mexico
| | - Laura Sevilla Tapia
- Subdirección de Investigación Básica, Instituto Nacional de Cancerología, Mexico City 14080, Mexico
| | - Alvaro R Osornio-Vargas
- Department of Pediatrics, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB T6G 1C9, Canada
| | - Miatta A Buxton
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Marie S O'Neill
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
- Department of Environmental Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Felipe Vadillo-Ortega
- Unidad de Vinculación Científica de la Facultad de Medicina, UNAM en el Instituto Nacional de Medicina Genómica, Mexico City 14610, Mexico
- Department of Environmental Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
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A Novel Tree Ensemble Model to Approximate the Generalized Extreme Value Distribution Parameters of the PM2.5 Maxima in the Mexico City Metropolitan Area. MATHEMATICS 2022. [DOI: 10.3390/math10122056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
We introduce a novel spatial model based on the distribution of generalized extreme values (GEVs) and tree ensemble models to analyze the maximum concentrations levels of particulate matter with a diameter of less than 2.5 microns (PM2.5) in the Mexico City metropolitan area during the period 2003–2021. Spatial trends were modeled through a decision tree in the context of a non-stationary GEV model. We used a tree ensemble model as a predictor of GEV parameters to approximate nonlinear trends. The decision tree was built by using a greedy stagewise approach, the objective function of which was the log-likelihood. We verified the validity of our model by means of the likelihood and Akaike’s information criterion (AIC). The maps of the generalized extreme value parameters on the spatial plane show the existence of differentiated local trends in the extreme values of PM2.5 in the study area. The results indicated strong evidence of an increase in the west–east direction of the study area. A spatial map of risk with maximum concentration levels of PM2.5 in a period of 25 years was built.
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Baca-López K, Fresno C, Espinal-Enríquez J, Martínez-García M, Camacho-López MA, Flores-Merino MV, Hernández-Lemus E. Spatio-Temporal Representativeness of Air Quality Monitoring Stations in Mexico City: Implications for Public Health. Front Public Health 2021; 8:536174. [PMID: 33585375 PMCID: PMC7874227 DOI: 10.3389/fpubh.2020.536174] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 11/09/2020] [Indexed: 11/18/2022] Open
Abstract
Assessment of the air quality in metropolitan areas is a major challenge in environmental sciences. Issues related include the distribution of monitoring stations, their spatial range, or missing information. In Mexico City, stations have been located spanning the entire Metropolitan zone for pollutants, such as CO, NO2, O3, SO2, PM2.5, PM10, NO, NO x , and PM CO . A fundamental question is whether the number and location of such stations are adequate to optimally cover the city. By analyzing spatio-temporal correlations for pollutant measurements, we evaluated the distribution and performance of monitoring stations in Mexico City from 2009 to 2018. Based on our analysis, air quality evaluation of those contaminants is adequate to cover the 16 boroughs of Mexico City, with the exception of SO2, since its spatial range is shorter than the one needed to cover the whole surface of the city. We observed that NO and NO x concentrations must be taken into account since their long-range dispersion may have relevant consequences for public health. With this approach, we may be able to propose policy based on systematic criteria to locate new monitoring stations.
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Affiliation(s)
- Karol Baca-López
- School of Medicine, Autonomous University of the State of Mexico, Toluca de Lerdo, Mexico
- Computational Genomics Division, National Institute of Genomic Medicine, Mexico City, Mexico
| | - Cristóbal Fresno
- Technological Development Office, National Institute of Genomic Medicine, Mexico City, Mexico
| | - Jesús Espinal-Enríquez
- Computational Genomics Division, National Institute of Genomic Medicine, Mexico City, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Mireya Martínez-García
- Sociomedical Research Unit, National Institute of Cardiology ‘Ignacio Chávez’, Mexico City, Mexico
| | | | | | - Enrique Hernández-Lemus
- Computational Genomics Division, National Institute of Genomic Medicine, Mexico City, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico
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An improved particle swarm optimization (PSO): method to enhance modeling of airborne particulate matter (PM10). EVOLVING SYSTEMS 2019. [DOI: 10.1007/s12530-019-09263-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
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