Acute cardiopulmonary effects induced by the inhalation of concentrated ambient particles during seasonal variation in the city of São Paulo
Jôse Mára de Brito, Mariângela Macchione, Kelly Yoshizaki, Alessandra Choqueta Toledo-Arruda, Beatriz Mangueira Saraiva-Romanholo, Maria de Fátima Andrade, Thaís Mauad, Dolores Helena Rodriguez Ferreira Rivero and Paulo Hilário Nascimento Saldiva J Appl Physiol 117:492-499, 2014. First published 10 July 2014; doi:10.1152/japplphysiol.00156.2014 You might find this additional info useful... This article cites 39 articles, 4 of which can be accessed free at: /content/117/5/492.full.html#ref-list-1 Updated information and services including high resolution figures, can be found at: /content/117/5/492.full.html Additional material and information about Journal of Applied Physiology can be found at: http://www.the-aps.org/publications/jappl
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J Appl Physiol 117: 492–499, 2014. First published July 10, 2014; doi:10.1152/japplphysiol.00156.2014.
Acute cardiopulmonary effects induced by the inhalation of concentrated ambient particles during seasonal variation in the city of São Paulo Jôse Mára de Brito,1 Mariângela Macchione,1 Kelly Yoshizaki,1 Alessandra Choqueta Toledo-Arruda,2 Beatriz Mangueira Saraiva-Romanholo,2 Maria de Fátima Andrade,3 Thaís Mauad,1 Dolores Helena Rodriguez Ferreira Rivero,1 and Paulo Hilário Nascimento Saldiva1 1
Department of Pathology, Laboratory of Experimental Air Pollution, School of Medicine, University of São Paulo, São Paulo, Brazil; 2Department of Medicine, Laboratory of Experimental Therapeutics, School of Medicine, University of São Paulo, São Paulo, Brazil and City of São Paulo University, São Paulo, Brazil; and 3Institute of Astronomy, Geophysics, and Atmospheric Sciences, University of São Paulo, São Paulo, Brazil Submitted 18 February 2014; accepted in final form 7 July 2014
particulate matter; climatic change; toxicity; inflammation; responsiveness THE METROPOLITAN AREA OF SÃO PAULO is one of the largest megacities in the world, with more than 19 million inhabitants in an area of 1,523 km2 at an altitude of 824 m, with an increasing mobile fleet of 7 million vehicles (18). Automobile sources are, therefore, major contributors to air pollution in São Paulo (3, 25). Significant detrimental effects have been re-
Address for reprint requests and other correspondence: J. M. de Brito, Faculdade de Medicina USP, Departamento de Patologia, Av. Dr. Arnaldo 455, 1 andar, sala 1220, Cerqueira César, São Paulo/SP, CEP, 01246-903 Brazil (e-mail: [email protected]). 492
ported in relation to ambient levels of air pollution in São Paulo, predominantly associated with particles (11, 21, 22). The tropical and extra-tropical climate defines singular characteristics in São Paulo city. The climate variability could be defined in two broad categories: 1) cold and dry (mean: temperature, 18°C; relative humidity, 80%; precipitation, 70 mm), which occurs between April and September and is characterized by high concentrations of primary pollutants due to the higher occurrence of thermal inversions, low humidity, and reduced wind; and 2) warm and humid (mean: temperature, 21°C; relative humidity, 81%; precipitation, 218 mm), which occurs between October and March and is characterized by relatively higher concentrations of secondary pollutants, especially ozone, due to high atmospheric temperatures (10). Air pollution is characterized as a composite mixture with variable compositions among different locations. The general understanding of air pollution composition is complicated by the direct effects that regional characteristics, climatic variability, and fuel types have on particle composition. Particles are grossly classified as primary and secondary pollutants. The primary pollutants are directly emitted by several sources, such as industry, forest fires, and vehicles. The secondary pollutants are formed in the atmosphere as a consequence of photochemical processes. The relative toxicity of primary and secondary particles is not fully understood. In several studies, both primary and secondary particles have been shown to have adverse health effects on biological systems (12, 13, 31), while other studies have shown that secondary pollutants of particles appear to be a main source of these effects (26, 33). Experimental models using concentrated ambient particles (CAPs) can provide useful information to verify the seasonal variation of particle toxicity. Recently, a study conducted in California showed that particulate matter ⱕ2.5 m (PM2.5) generated during the winter season was associated with relatively higher systemic and pro-coagulant effects in mice (35). The location of São Paulo, given the complexities of the climate variation there, presents an opportunity to investigate the influence of weather conditions on particle toxicity because only a small number of studies have measured the effects of pollutants at specific locations (19, 35). Therefore, the objectives of the present study were 1) to determine whether acute exposure to low levels of particles promotes measurable acute systemic and cardiopulmonary effects; and 2) to assess if the magnitude of the observed alterations are influenced by season. For these purposes, controlled exposures to CAPs were conducted in mice.
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de Brito JM, Macchione M, Yoshizaki K, Toledo-Arruda AC, Saraiva-Romanholo BM, Andrade MF, Mauad T, Rivero DHRF, Saldiva PHN. Acute cardiopulmonary effects induced by the inhalation of concentrated ambient particles during seasonal variation in the city of São Paulo. J Appl Physiol 117: 492– 499, 2014. First published July 10, 2014; doi:10.1152/japplphysiol.00156.2014.—Ambient particles may undergo modifications to their chemical composition as a consequence of climatic variability. The determination of whether these changes modify the toxicity of the particles is important for the understanding of the health effects associated with particle exposure. The objectives were to determine whether low levels of particles promote cardiopulmonary effects, and to assess if the observed alterations are influenced by season. Mice were exposed to 200 g/m3 concentrated ambient particles (CAPs) and filtered air (FA) in cold/ dry and warm/humid periods. Lung hyperresponsiveness, heart rate, heart rate variability, and blood pressure were evaluated 30 min after each exposure. After 24 h, blood and tissue samples were collected. During both periods (warm/humid and cold/dry), CAPs induced alterations in red blood cells and lung inflammation. During the cold/dry period, CAPs reduced the mean corpuscular volume levels and increased erythrocytes, hemoglobin, mean corpuscular hemoglobin concentration, and red cell distribution width coefficient variation levels compared with the FA group. Similarly, CAPs during the warm/humid period decreased mean corpuscular volume levels and increased erythrocytes, hemoglobin, hematocrit, and red cell distribution width coefficient variation levels compared with the FA group. CAPs during the cold/dry period increased the influx of neutrophils in the alveolar parenchyma. Short-term exposure to low concentrations of CAPs elicited modest but significant pulmonary inflammation and, to a lesser extent, changes in blood parameters. In addition, our data support the concept that changes in climate conditions slightly modify particle toxicity because equivalent doses of CAPs in the cold/dry period produced a more exacerbated response.
Toxicity by Concentrated Ambient Particles MATERIALS AND METHODS
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to minimize suffering. Four experimental groups were defined as follows: cold/dry exposed to CAPs (n ⫽ 46) and a corresponding control group exposed simultaneously to filtered air (FA) (n ⫽ 44), and warm/humid CAP-exposed (n ⫽46) and control groups (n ⫽ 44). All animals were exposed for 1 h at the same time each day (11 AM to 12 PM). During the intervals between the exposure periods, the animals were maintained in ventilated racks with FA (high efficiency particulate air), a controlled temperature (22–25°C), and a light-dark cycle of 12 h. CAPs exposure protocol. Male Balb/c mice were exposed to concentrated ambient PM2.5 from the city of São Paulo using a Harvard ambient particle concentrator located within the main campus of the School of Medicine of the University of São Paulo. In this system, a jet of particle-laden air is injected, and a series of impactors are used to classify particles according to their aerodynamic size. The PM2.5 was accelerated through a nozzle and concentrated by inertial forces, while aspirating peripheral airflow and increasing the concentration of particles in the size range of 0.1–2.5 m, while maintaining their physicochemical characteristics, as previously described (34). Animals were exposed to the same amount of particles. The concentration of CAPs was monitored in real time using a particulate monitor (DataRam4, Thermo Fisher Scientific) to precisely adjust concentration during the exposure duration. To achieve an accumulated dose (concentration vs. time product) of 200 g/m3, the time of the exposure was controlled to ensure the same concentration for all groups. Groups of seven to eight animals for CAPs and seven to eight animals for controls (FA) were frequently exposed for less than 1 h inside of the inhalation chambers. For each season (cold/dry or warm/humid) and for each group, 6 exposures were conducted on different days to achieve the final number of 46 CAP-exposed mice and 44 controls for each season (Table 1). Exposure protocols were conducted on the following days: 1) cold: July 7, July 19, and August 11, 2010; May 10, May 25, and June 7, 2011; and 2) warm: October 20, October 26, and November 3, 2011; February 15, March 1, and March 8, 2012. Meteorological data corresponding to the period between 2007 and 2012, as well as to the exposure dates, are presented in Table 2. Heart rate, heart rate variability, and blood pressure. Thirty minutes after the completion of the CAPs or FA exposure, the animals were anesthetized with a mixture of isoflurane (inhalatory anesthesia) and O2. A rodent-specific cuff was attached to the base of the tails of the mice and was coupled to a Powerlab system (digital system for acquisition data, ADInstruments) for 3 min of recording. The following parameters were obtained as described previously by Brito et al. (4): heart rate (HR), HR variability (HRV) for the time domain
Table 1. Outline of the experimental protocol, number of animals per group, and average exposure concentrations Animals/Group Date
Period
FA
CAPs
Mean CAPs Mass Concentration, g/m3
Exposure, min
CAPs Accumulate (Concentration vs. Time)
Temperature, °C
Humidity, %
7/7/10 7/19/10 8/11/10 5/10/11 5/25/11 6/7/11 10/20/11 10/26/11 11/3/11 2/15/12 3/1/13 3/8/12 Mean Mean
1 1 1 1 1 1 2 2 2 2 2 2 1 2
7 7 8 7 7 8 7 7 8 7 7 8 44 44
8 8 7 8 8 7 8 8 7 8 8 7 46 46
200.19 504.16 488.36 197.37 506.84 452.90 427.17 296.95 408.04 214.46 387.28 347.28 391.63 346.86
60 24 25 60 25 27 28 40 30 58 32 35 36 37
202.19 201.66 203.48 197.37 211.18 203.81 199.34 197.96 204.02 207.31 206.55 202.58 203.28 202.96
24 24 20 29 27 27 26 25 28 25 31 29 25.16 27.33
54 66 66 52 45 45 45 63 38 64 43 47 54.66 50.00
Period 1, cold/dry; period 2, warm/humid; FA, filtered air; CAPs, concentrated ambient particles. J Appl Physiol • doi:10.1152/japplphysiol.00156.2014 • www.jappl.org
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Ethics statement. This study was approved by the Ethics Committee of the School of Medicine of the University of São Paulo (permit no.: 149/10). Sampling and PM2.5 elementary characterization. Air pollution in São Paulo has been characterized as mainly vehicular in origin (22). To characterize PM2.5 in the two periods (cold/dry and warm/humid), we used data from previously collected PM2.5 samples at the School of Medicine of the University of São Paulo between June 2007 and 2008. The climatic conditions were similar to those of the study period. The PM2.5 samples generated during the cold/dry season had a higher PM2.5, black carbon, and elemental silicon, potassium, calcium, titanium, vanadium (V), iron (Fe), nickel, zinc, bromine (Br) (P ⫽ 0.001) content, and lead (Pb) (P ⫽ 0.031) level compared with the samples generated during the warm/humid season. The identification of absolute principal component analysis was based on eigenvalues ⬎ 1 before rotation analysis. This method was used to estimate the contribution of each factor to the mass concentration variation. The absolute principal component analysis identified four factors: factor 1 was related to fossil fuel combustion and secondary pollutants, which have high levels of phosphorus, sulfur, V, sulfate, and ammonium, explaining their contribution of 12% of the PM2.5 mass (3.4 g/m3); factor 2 was associated with the burning of heavy-duty diesel and biomass due to the high loading for PM2.5, black carbon, Br, and potassium, accounting for 48% of the PM2.5 mass (13.5 g/m3); factor 3 was related to crustal emissions (soil and construction) due to the high loadings for silicon, calcium, titanium, and Fe and constituted 11% of the PM2.5 mass (3.2 g/m3); and factor 4 was associated with light-duty vehicle emissions due to the presence of zinc, Pb, and other metals, accounting for 5% of the PM2.5 mass (1.4 g/m3). A regression analysis of the four “absolute factor scores” showed that 21% of the PM2.5 mass in São Paulo was not explained by any factor. The polycyclic aromatic hydrocarbon (PAH) concentrations have been characterized by Vasconcellos et al. (38). Total PAH concentrations were 10.6 ng/m3 in the warm/humid season and 25.9 ng/m3 in the cold/dry season. Experimental groups. Adult male Balb/C mice (6 – 8 wk of age) weighing ⬃25 g were obtained from the animal house at the School of Medicine of the University of São Paulo. The animals were maintained at 22–23°C with controlled humidity and a 12:12-h lightdark cycle. Food and water were available ad libitum. All animals received care in compliance with the “Principles of Laboratory Animal Care” published by the National Institutes of Health. All surgery procedures were performed under anesthesia, and efforts were made
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Table 2. Mean values (temperature and relative humidity) and sum (precipitation index) of the meteorological parameters obtained from 2007 to 2012 in São Paulo, Brazil Parameters
Temperature, °C
Relative humidity, %
Precipitation, mm
Year
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2007 2008 2009 2010 2011 2012 2007 2008 2009 2010 2011 2012 2007 2008 2009 2010 2011 2012
22 21 22 23 23 21 83 82 82 84 83 82 126 263 234 653 466 333
23 22 23 24 23 23 80 82 82 77 81 79 274 219 219 394 328 255
23 21 22 22 21 22 77 80 82 81 87 79 205 75 247 148 91 150
21 20 20 20 21 20 82 82 83 82 82 84 78 122 52 130 102 177
17 17 18 18 17 17 81 78 81 82 83 82 54 57 56 81 24 49
17 16 15 16 15 17 76 82 81 79 81 86 26 57 42 13 65 191
15 16 16 17 16 16 79 74 87 80 79 78 161 0 200 90 12 88
17 18 17 16 17 18 75 78 77 75 77 74 1 89 51 4 65 2
19 17 19 19 17 19 74 79 84 77 77 75 4 42 203 97 4 22
20 20 19 18 19 21 79 82 86 83 80 77 96 146 138 77 176 92
20 20 23 20 19 20 80 82 80 80 79 81 123 113 234 159 111 163
22 20 22 22 21 24 80 80 84 84 79 81 198 256 209 281 236 345
Source: Institute of Astronomy, Geophysics and Atmospheric Science, University of São Paulo. Values in bold are the exposure months of the mice in the CAP groups.
mean corpuscular hemoglobin (MCH), MCH concentration (MCHC), coefficient variation of the red cell distribution width (RDW-CV), standard deviation of the red cell distribution width (RDW-SD), platelets, reticulocytes, leukocytes, polymorphonuclear neutrophils, lymphocytes, and monocytes. Complete blood counts of red blood cells (RBCs), platelets, and white blood cells were performed using a hematological analyzer (Bayer). Lung histology, immunohistochemistry, and morphometric analysis. The lungs were removed and fixed by intratracheal instillation of a 10% buffered formalin solution for 24 h and then embedded in paraffin. Five-micrometer-thick sections of lung tissues were deparaffinized, rehydrated, and stained with hematoxylin and eosin for the quantification of neutrophil density. For immunohistochemical staining analysis, the lung sections were deparaffinized, rehydrated, and blocked for endogenous peroxidase followed by antigen retrieval performed with high-temperature citrate buffer (pH ⫽ 6.0). The following primary antibodies were used: anti-endothelin A receptor (anti-ET-Ar) (1:250, Santa Cruz Biotechnology), anti-endothelin B receptor (anti-ET-Br) (1:250, Santa Cruz Biotechnology), and anti-vascular cell adhesion molecule (VCAM)-1A (1:200, Santa Cruz Biotechnology). Anti-goat, -rat, or -rabbit antibodies (Vectastain Abc Kit, Vector Laboratories) were used as secondary antibodies. Sections were counterstained with hematoxylin. Bovine serum albumin was used in substitution for primary antibodies for controls.
Table 3. Median (IQR: 25–75) values of the HR variability, HR, and BP for groups exposed to FA and CAPs during cold/ dry and warm/humid periods FA Cold/dry (n ⫽ 34)
2
SDNN, ms RMSSD, ms2 LF, ms HF, ms LF/HF HR, beats/min BP, mmHg
Warm/humid (n ⫽ 43)
CAPs All (n ⫽ 77)
Cold/dry (n ⫽ 34)
Warm/humid (n ⫽ 44)
All (n ⫽ 78)
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
15.79 20.16 14.44 10.65 1.67 400.75 89.05
12.88–20.77 16.50–28.09 8.76–30.29 5.07–20.73 1.39–2.18 366.86–427.45 69.67–129.83
14.40 18.58 7.66 4.80 1.40 401.27 91.25
11.88–19.53 14.45–24.77 4.04–14.85 2.72–11.96 1.10–2.43 381.36–448.98 74.87–117.13
15.09 19.38 11.14 7.91 1.50 400.81 91.25
12.45–20.17 14.90–26.60 4.58–24.19 3.81–13.71 1.14–2.21 379.77–436.54 72.37–120.55
17.66 21.49 10.41 7.61 1.29 404.14 94.13
14.40–20.87 16.87–28.36 6.53–17.16 5.33–12.98 1.02–2.36 362.90–433.55 58.74–134.44
14.36 17.43 10.55 6.94 1.46 409.34 85.03
11.86–18.06 14.76–22.99 4.18–15.46 3.07–13.46 1.00–1.93 396.79–431.08 76.53–121.01
15.43 18.55 10.41 7.29 1.35 409.16 86.88
12.55–20.07 15.39–25.47 5.81–15.95 4.80–13.43 1.01–2.01 384.43–431.94 71.33–125.02
n, No. of animals. IQR, interquartile range; SDNN, standard deviation of normal beats; RMSSD, root mean square of successive differences in the heartbeat interval; LF, low frequency; HF, high frequency; LF/HF, ratio of low to high frequency; HR, heart rate; BP, blood pressure. The groups were subdivided and were exposed to the following conditions: cold/dry-FA, warm/humid-FA, all-FA, cold/dry-CAPs, warm/humid-CAPs, and all-CAPs. J Appl Physiol • doi:10.1152/japplphysiol.00156.2014 • www.jappl.org
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(standard deviation of normal beats and root mean square of successive differences in the heart beat interval), frequency domain (low frequency, high frequency, and low-frequency-to-high-frequency ratio), and blood pressure (BP). Lung hyperresponsiveness. Lung hyperresponsiveness of conscious mice was measured during a dose-response curve to aerosolized methacholine (MCh) through a whole body plethysmography system (BUXCO, Winchester, UK) after HR and BP acquisition. Briefly, each mouse was placed in a chamber, and continuous measurements of the box pressure-time wave were made using a transducer that was connected to a computer data-acquisition system. The main indicator of air bronchoconstriction was enhanced pause (Penh), which shows correlation with airway resistance, as measured according to standard evaluation methods in Balb/c mice (1). After the measurement of baseline Penh, either aerosolized saline or MCh in increasing concentrations (6.25, 12.5, 25, and 50 mg/ml) was nebulized through an inlet of the chamber for 3 min. Penh values for each dose were collected for 3 min and then averaged. The maximum Penh and area under the curve were calculated. Blood analysis. After 24 h, the animals were anesthetized with a mixture of ketamine/xylazine (50 mg/kg by intraperitoneal injection). Blood samples were collected by heart puncture and then stored in ethylenediaminetetraacetic acid K3 tubes for complete blood and reticulocyte counts. The parameters evaluated were as follows: erythrocytes, hemoglobin, hematocrit, mean corpuscular volume (MCV),
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Fig. 1. Mean (⫾SE) values of enhanced pause (Penh) obtained by a dose-response curve to methacholine. A: cold. B: warm. C: all. The open circles represent filtered air (FA), and the solid circles represent concentrated ambient particles (CAPs). In A, CAPs ⫽ FA: *P ⫽ 0.012, #P ⫽ 0.038.
RESULTS
HR, HRV, and BP. There were no effects on HR, BP, and all parameters of HRV (Table 3). Lung hyperresponsiveness. The CAPs produced during the cold/dry period elevated the Penh in the baseline dose group (P ⫽ 0.012) as well as in the MCh 6.25 mg/ml dose group (P ⫽ 0.038) compared with the FA group (Fig. 1). There were no effects observed for the available parameters as evaluated by area under the curve and maximum Penh (Fig. 2). Blood. Independent of the exposure period, CAPs induced a reduction of MCV (P ⫽ 0.001) and an increase in hematocrit (P ⫽ 0.019), MCHC (P ⫽ 0.004), erythrocytes, hemoglobin, and RDW-CV (P ⫽ 0.001) compared with the FA group (Table 4). Exposure to CAPs generated during the cold/dry period promoted a reduction in MCV (P ⫽ 0.010) and an increase in erythrocytes (P ⫽ 0.018), hemoglobin (P ⫽ 0.022), MCHC (P ⫽ 0.016), and RDW-CV (P ⫽ 0.021) compared with that of the FA group. Similarly, exposure to CAPs generated during the warm/humid period induced a decrease in MCV (P ⫽ 0.001) and an increase in the number of erythrocytes, hemoglobin (P ⫽ 0.001), hematocrit (P ⫽ 0.024), and RDW-CV (P ⫽ 0.006) compared with the FA group (Table 4). The increase in RDW-CV (P ⫽ 0.015) was higher for CAPs generated during the cold/dry period than those generated during the warm/humid period, whereas hemoglobin levels (P ⫽ 0.034) were increased after exposure to CAPs generated in warm/humid periods (Table 4).
Fig. 2. Mean (⫾SE) values of maximum Penh (Penhmax; A) and area under the curve (AUC; B).
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An eyepiece with a coherent system of 50 lines and 100 points with a known area attached to the ocular lens of the microscope was used for conventional morphometry. The density of neutrophils and macrophages was assessed by point counting. Using a 100-point grid with a known area (67.500 m2 at ⫻1,000 magnification) attached to the microscope ocular lens, we counted the number of points that contacted alveolar tissue in each field. Alveolar tissue area in each field was calculated as the number of points that contacted alveolar tissue as a proportion of the total grid area. Data are expressed as neutrophil cell density or macrophage cell density per alveolar area (cells/mm2) (5, 36). Counting was performed in 20 fields of alveolar parenchyma for each animal at a magnification of ⫻1,000. Image analysis. Positively immunostained areas for the ET-Ar, ET-Br, and VCAM 1 in peribronchiolar vessels were determined using image analysis. Analyses were performed using Image-Pro Plus 4.1 software for Windows (Media Cybernetics, Silver Spring, MD) using a light microscope-coupled digital camera (Olympus Q-Color 5, Tokyo, Japan) connected to a personal computer. We also assessed ET-Ar, ET-Br, and VCAM in five peribronchiolar vessels at ⫻200 magnification. The results were expressed as positively immunostained area per perimeter of the outer muscular layer of the vessel (m2/m) (5). Coded slides were used to ensure that the analysis was blinded. All measurements were performed by the same observer. Statistical analysis. The distribution of the biological effects data was checked for all variables by Kolmogorov-Smirnov analyses. Normally distributed variables are reported as means ⫾ SD, and the significance was determined using the independent-samples T-test. The nonnormally distributed variables were reported as median and interquartile range (25–75%), and the significance was determined using the Mann-Whitney U-test. The significance of the lung mechanics was determined using the general linear model for repeated measures. The level of significance was set at 5%. Statistical analyses were performed using SPSS 15.0.
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Table 4. Descriptive values of hematological parameters for groups exposed to FA and CAPs during cold/dry and warm/ humid periods FA Parameters
1) 2) 3) 4) 5) 6) 7) 8) 9) 10) 11) 12) 13) 14)
Erytrocytes, ml/mm3 Hemoglobin, g/dl Hematocrit, % Mean corpuscular volume, fl Mean corpuscular hemoglobin, pg Mean corpuscular hemoglobin concentration, g/dl Red distribution with variation coefficient, % Red distribution with size distribution, fl Platelets, ml/mm3 Reticulocytes, % Leucocytes, ml/mm3 PMN, ml/mm3 Lymphocytes, ml/mm3 Monocytes, ml/mm3
CAPs
a) Cold/dry (n ⫽ 34)
b) Warm/humid (n ⫽ 39)
c) All (n ⫽ 73)
d) Cold/dry (n ⫽ 39)
e) Warm/humid (n ⫽ 40)
f) All (n ⫽ 79)
10.18 ⫾ 0.47 15.13 ⫾ 0.60 44.76 ⫾ 1.74 43.99 ⫾ 1.05 14.86 ⫾ 0.29
10.28 ⫾ 0.46 15.30 ⫾ 0.74 45.64 ⫾ 1.91 44.41 ⫾ 1.03 14.89 ⫾ 0.54
10.23 ⫾ 0.47 15.22 ⫾ 0.68 45.23 ⫾ 1.87 44.21 ⫾ 1.05 14.88 ⫾ 0.44
10.50 ⫾ 0.63 15.53 ⫾ 0.82 45.29 ⫾ 1.91 43.22 ⫾ 1.37 14.81 ⫾ 0.27
10.75 ⫾ 0.53 15.95 ⫾ 0.89 46.67 ⫾ 2.01 43.45 ⫾ 1.20 14.83 ⫾ 0.54
10.62 ⫾ 0.59 15.74 ⫾ 0.87 45.99 ⫾ 2.07 43.33 ⫾ 1.29 14.82 ⫾ 0.43
33.81 ⫾ 0.71
33.54 ⫾ 1.29
33.67 ⫾ 1.06
34.28 ⫾ 0.87
34.18 ⫾ 1.49
34.23 ⫾ 1.21
22.89 ⫾ 0.77
21.97 ⫾ 1.10
22.40 ⫾ 1.06
23.47 ⫾ 1.25
22.75 ⫾ 1.33
23.10 ⫾ 1.33
28.95 ⫾ 1.49 890.68 ⫾ 220.85 3.19 ⫾ 0.83 2.89 ⫾ 1.33 0.31 ⫾ 0.21 2.45 ⫾ 1.16 0.10 ⫾ 0.16
28.13 ⫾ 1.67 786.29 ⫾ 229.20 3.46 ⫾ 0.77 3.92 ⫾ 1.54 0.58 ⫾ 0.35 3.17 ⫾ 1.29 0.17 ⫾ 0.12
28.52 ⫾ 1.63 835.58 ⫾ 229.78 3.34 ⫾ 0.80 3.43 ⫾ 1.52 0.45 ⫾ 0.32 2.83 ⫾ 1.28 0.14 ⫾ 0.14
29.17 ⫾ 1.54 979.18 ⫾ 226.92 3.03 ⫾ 0.86 3.19 ⫾ 1.38 0.37 ⫾ 0.32 2.71 ⫾ 1.22 0.11 ⫾ 0.12
28.23 ⫾ 1.56 817.63 ⫾ 201.47 3.17 ⫾ 0.83 4.55 ⫾ 1.69 0.70 ⫾ 0.35 3.71 ⫾ 1.49 0.17 ⫾ 0.12
28.69 ⫾ 1.61 897.38 ⫾ 228.01 3.10 ⫾ 0.84 3.88 ⫾ 1.68 0.54 ⫾ 0.37 3.22 ⫾ 1.44 0.14 ⫾ 0.12
Lung histology. Both CAPs produced during the cold/dry and the warm/humid periods elevated the number of neutrophils and macrophages (P ⫽ 0.001) compared with the FA group. However, the increase of neutrophils (P ⫽ 0.001) was higher in the exposure conducted during the cold/dry period (Table 5). Immunohistochemistry. There were no differences between groups for VCAM, ET-Ar, and ET-Br expression in lung vessels (Table 6). Summary of effects. Table 7 summarizes the statistically significant (P ⬍ 0.05) effects of all parameters studied in mice exposed to CAPs compared with mice exposed to FA, such as the electric activity of the heart through HRV, lung hyperresponsiveness during a dose-response curve to aerosolized MCh, systemic inflammation by blood parameters, lung inflammation by lung histology, and immunohistochemical markers. DISCUSSION
We observed that a single exposure to a low concentration of CAPs derived from a São Paulo urban region evoked lung inflammation and alterations in RBC count in mice. Neutrophilic lung inflammation was more prominent in mice exposed to CAPs generated during the cold/dry period compared with
mice exposed to CAPs generated in the warm/humid period. To our knowledge, this is the first study to address the seasonal effects of PM in São Paulo on biological outcomes in mice. Principal component analyses of São Paulo PM2.5 elements showed that, during the cold/dry seasons, there was a predominance of factors related to the burning of heavy-duty diesel as well as due to biomass and crustal emissions (soil and construction). It is believed that the weather conditions during the cold/dry seasons are unfavorable for the dispersion of pollutants, thus worsening the air quality in major urban centers. In contrast, warm/humid weather conditions perpetuate the formation of secondary aerosols in the atmosphere due the action of solar radiation on PM2.5. Tablin et al. (35) demonstrated an association between increased concentrations of PM0.1 metals and PAHs during winter periods in Fresno, CA and a greater systemic proinflammatory and procoagulant response. Little is known about the seasonal effects on particle composition in São Paulo city, where differences in temperature and humidity are milder compared with other regions of the globe. The effect of climate alterations on particle composition and size in the city of São Paulo has been well documented by Albuquerque et al. (2), who showed that meteorological conditions have a major influence on the suspended aerosol con-
Table 5. Descriptive values of the lung neutrophils and macrophages for groups exposed to FA and CAPs during cold/dry and warm/humid periods FA
CAPs
Parameters (105 cells/mm2)
a) Cold/dry (n ⫽ 44)
b) Warm/humidy (n ⫽ 44)
c) All (n ⫽ 88)
d) Cold/dry (n ⫽ 46)
e) Warm/humid (n ⫽ 45)
f) All (n ⫽ 91)
1) Neutrophils 2) Macrophages
5.36 ⫾ 1.68 6.99 ⫾ 1.11
4.99 ⫾ 1.92 6.82 ⫾ 1.01
5.18 ⫾ 1.80 6.91 ⫾ 1.06
8.67 ⫾ 2.10 11.38 ⫾ 1.45
7.40 ⫾ 1.25 10.79 ⫾ 1.43
8.04 ⫾ 1.84 11.08 ⫾ 1.47
Values are means ⫾ SD; n, no. of animals. The groups were subdivided and were exposed to the following conditions: a) cold/dry-AF; b) warm/humid-AF, c) all-AF; d) cold/dry-CAPs; e) warm/humid-CAPs; f) all-CAPs. Group c ⫽ group f (parameters 1 and 2: P ⫽ 0.001). Group d ⫽ group e (parameter 1: P ⫽ 0.001). Group a ⫽ group d (parameters 1 and 2: P ⫽ 0.001). Group b ⫽ group e (parameters 1 and 2: P ⫽ 0.001). J Appl Physiol • doi:10.1152/japplphysiol.00156.2014 • www.jappl.org
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Values are means ⫾ SD; n, no. of animals. PMN, polymorphonuclear neutrophils. The groups were subdivided and were exposed to the following conditions: a) cold/dry-AF; b) warm/humid-AF, c) all-AF; d) cold/dry-CAPs; e) warm/humid-CAPs; f) all-CAPs. Group c ⫽ group f (parameters 1, 2, 4, and 7: P ⫽ 0.001; 3: P ⫽ 0.019; and 6: P ⫽ 0.004). Group d ⫽ group e (parameters 3: P ⫽ 0.003; and 7: P ⫽ 0.015). Group a ⫽ group d (parameters 1: P ⫽ 0.018; 2: P ⫽ 0.022; 4: P ⫽ 0.010; 6: P ⫽ 0.016; and 7: P ⫽ 0.021). Group b ⫽ group e (parameters 1, 2, and 4: P ⫽ 0.001; 3: P ⫽ 0.024; and 7: P ⫽ 0.006).
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Table 6. Median (IQR: 25–75) values of the lung immunohistochemistry for groups exposed to FA and CAPs during cold/ dry and warm/humid periods FA Cold/dry (n ⫽ 39)
CAPs
Warm/humid (n ⫽ 44)
All (n ⫽ 83)
Cold/dry (n ⫽ 41)
Warm/humid (n ⫽ 44)
All (n ⫽ 84)
Parameters
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
Endothelin-A Endothelin-B VCAM-1
0.28 0.63 0.09
0.14–0.42 0.37–1.03 0.05–0.13
0.16 0.08 0.16
0.06–0.34 0.03–0.27 0.11–0.23
0.23 0.34 0.11
0.10–0.36 0.08–0.69 0.06–0.20
0.26 0.56 0.07
0.13–0.49 0.41–0.94 0.03–0.17
0.14 0.11 0.16
0.04–0.28 0.04–0.23 0.11–0.27
0.21 0.29 0.12
0.07–0.36 0.09–0.59 0.05–0.21
The groups were subdivided and were exposed to the following conditions: cold/dry-AF, warm/humid-AF, all-AF, cold/dry-CAPs, warm/humid-CAPs, and all-CAPs.
centrations in the atmosphere. Epidemiological studies have shown that interactions between air pollution and weather conditions are associated with increases in mortality and morbidity of respiratory and cardiovascular diseases (14, 15, 24). Few studies have addressed biological outcomes in animals exposed to particles generated in different climates (28, 35).
Our results show that acute, short exposure to ambient particles induced lung inflammation in both cold/dry and warm/humid periods, with increases in neutrophils and macrophages in the lung tissue. Previous studies have demonstrated that exposure to CAPs caused an increase in lung neutrophils in rats, which correlated with the V and bromide
Table 7. Summary of the effects
System/Parameters
HR variability SDNN RMSSD LF HF LF/HF HR BP Lung hyperresponsiveness Baseline Penh Penh saline Penh 6.25 MCh Penh 12.5 MCh Penh 25 MCh Penh 50 MCh Penhmax AUC Blood MCV Erythrocytes Hemoglobin Hematocrit MCHC RDW-CV RDW-SD Leucocytes totals Monocytes Lymphocytes PMN Platelets Lung histology Neutrophils Macrophages Vessels peribronchiolar Endothelin-A receptor Endothelin-B receptor VCAM-1
CAPs
CAPs
Cold
Warm
Cold
Warm
— — — — — — —
— — — — — — —
— — — — — — —
— — — — — — —
— — — — — — —
— — — — — — — —
1 — 1 — — — — —
— — — — — — — —
— — — — — — — —
— — — — — — — —
2 1 1 1 1 1 — — — — — —
2 1 1 — 1 1 — — — — — —
2 1 1 1 — 1 — — — — — —
— — — — — 1 — — — — — —
— — 1 — — — — — — — — —
1 1
1 1
1 1
1 —
— —
— — —
— — —
— — —
— — —
— — —
The CAPs, cold, and warm columns under FA compare CAPs group in relation group FA. The cold and warm columns under CAPs compare CAPs cold vs. CAPs warm. Penh, enhanced pause; Penh saline, Penh with 6.25, 12.5, 25, and 50 mg/ml of methacholine, respectively; Penhmax, maximum Penh; AUC, area under the curve; MCV, mean corpuscular volume; MCHC, mean corpuscular hemoglobin concentration; RDW-CV, coefficient variation of the red cell distribution width; RDW-SD, standard deviation of the red cell distribution width; 1, increase; 2, decrease; —, unchanged. Significance: P ⬍ 0.05. J Appl Physiol • doi:10.1152/japplphysiol.00156.2014 • www.jappl.org
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FA
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mation, with an increase in the RDW level in canines. The mechanisms that promote the release of circulating RBCs from the bone marrow by CAPs are unclear, and there is a lack of literature focusing on this physiopathological process. CAPs exposure induced no alterations in HR, HRV, and BP, parameters that are predictive of cardiovascular disease, as described in previous studies of exposure to CAPs (17), PM2.5 (29), diesel exhaust particles (4), and interactions between temperature and ozone levels (29, 39). Similarly, no alterations in lung adhesion molecules and endothelial receptor values were observed. Exposure to 14 days of air pollution caused vascular constriction with increased ET-Ar expression (21). It is possible that the lack of changes related to endothelial dysfunction in our model is related to the acute, short exposure that we employed. It is important to note the limitations of the present study. We used historical data from 2007–2008 to analyze PM elements. In the present study, the climatic conditions were similar to the climatic conditions during the period 2007–2012. Considering that the quality of the fuel and vehicular engines did not change during that period, we considered it valid to use historical PM2.5 composition data. The collection of ambient particles does not capture potential pollutants that are in gaseous or vapor forms; therefore, this exposure was not simulated through these experiments. The tail-cuff system used in this study is a system of limited value to detect small differences for HR, BP, and HRV and could explain the lack of significant results in the present study. In summary, short-term exposure to low concentrations of CAPs elicited modest but significant pulmonary inflammation and, to a lesser extent, changes in blood parameters. In addition, our data support the concept that changes in climate conditions slightly modify particle toxicity because equivalent doses of CAPs from the cold/dry period produced a more exacerbated response. GRANTS This work was supported by grants from Fundação de Amparo a Pesquisa do Estado de São Paolo (São Paulo, Brazil, 2010/50841–3). T. Mauad is funded by Conselho Nacional de Desenvolvimento Científico e Tecnológico. DISCLOSURES No conflicts of interest, financial or otherwise, are declared by the author(s). AUTHOR CONTRIBUTIONS Author contributions: J.M.B. and P.H.S. conception and design of research; J.M.B., K.Y., and B.M.S.-R. performed experiments; J.M.B., M.M., K.Y., A.C.T.-A., M.d.F.A., and T.M. analyzed data; J.M.B., M.M., A.C.T.-A., M.d.F.A., and T.M. interpreted results of experiments; J.M.B. prepared figures; J.M.B. and M.M. drafted manuscript; J.M.B., M.M., A.C.T.-A., T.M., and D.H.R.F.R. edited and revised manuscript; J.M.B. and P.H.S. approved final version of manuscript. REFERENCES 1. Adler A, Cieslewicz G, Irvin CG. Unrestrained plethysmography is an unreliable measure of airway responsiveness in BALB/c and C57BL/6 mice. J Appl Physiol 97: 286 –292, 2004. 2. Albuquerque TT, Andrade MF, Ynoue RY. Characterization of atmospheric aerosols in the city of São Paulo, Brazil: comparisons between polluted and unpolluted periods. Environ Monit Assess 184: 969 –984, 2012. 3. Andrade MD, Miranda RM, Fornaro A, Kerr A, Oyama B, Andre PA, Saldiva P. Vehicle emissions and PM2.5 mass concentration in six Brazilian cities. Air Qual Atmos Health 5: 79 –88, 2012.
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concentrations in the particles (6, 8, 31). Maciejczyk et al. (20) demonstrated an association between lung inflammatory response in mice and the presence of manganese, Fe, nickel, and Pb in CAPs. We found a greater neutrophilic inflammatory response in mice exposed to the cold/dry CAPs. We speculate that these differences are related to the increased concentration of metals and organic compounds and variation in the composition of such that occur in this seasonal period (2, 21). We found an increase in RBCs in animals exposed to CAPs generated during both the cold/dry and warm/humid periods, suggesting that bone marrow stimulation causes the release of erythropoietin. The increase of hematocrit could increase blood viscosity, contributing to the pathogenesis of pollution-related cardiac events (37, 40). Previous work has shown that ambient air particles promote significant effects on hematological parameters after inhalation (9, 16, 27), and that the composition of fine particles can determine the blood response to inhaled particles (23). However, the alterations in hematological parameters during the two analyzed periods of this study were similar. The increase in the circulation of blood cells and lung inflammatory cell measurements in the FA group may be due to secondary aerosol formation (ozone) generated during the warm/humid period because the animals were exposed for 1 h between 11 AM and 12 PM, a period that has a greater predominance of sunlight, a predisposing factor for the formation of secondary aerosol. Furthermore, CAPs is a system that filters only particles. The hematopoietic system is very sensitive to toxic substances due to the characteristic intensive cell proliferation. Environmental pollution includes many chemicals, including benzene, pesticides (dithiocarbamines), ethylene oxide, and metals (mercury, cadmium, chrome, cobalt, lead, aluminum) that exert their toxic effect on the hematopoietic system. One explanation of the observed hematological alterations is that the PM2.5 contains substances with a lower solubility that have the capacity to reach the systemic circulation. Medeiros et al. (23) developed a study designed to measure the hematological parameters and bone marrow after acute exposure to oil fly ash. They concluded that exposure to oil fly ash increases the reticulocyte levels in the peripheral blood and stimulates the bone marrow to increase the production of erythroblasts. They have concluded that erythroblasts in the bone marrow received a stimulus provoked by inhaled toxic particles without evidence of a hemolytic process or red cell loss. The number of circulating RBCs is dependent on the bone marrow. This is an important factor for understanding the pathogenesis of pollution-related heart diseases because increased RBCs may induce changes in blood viscosity, which may increase the mechanical load in the heart, as well as to blood clotting. Previous studies have observed that exposure to ambient particles increased the number of leucocytes in mice (30), canines (9), and humans (32). Additionally, we observed an increase in the levels of MCHC and RDW that may be related to pulmonary inflammation observed by neutrophilic infiltrate. RDW measures the variability of RBC sizes and is an index of the heterogeneity of the erythrocytes with immature types (i.e., anisocytosis) (7). The potential mechanism causing elevated levels of RDW may be inflammation or changes in erythrocyte volume and function of the heart. Zao et al. (41) described a correlation between oxidative stress and inflam-
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Jôse Mára de Brito, Mariângela Macchione, Kelly Yoshizaki, Alessandra Choqueta Toledo-Arruda, Beatriz Mangueira Saraiva-Romanholo, Maria de Fátima Andrade, Thaís Mauad, Dolores Helena Rodriguez Ferreira Rivero and Paulo Hilário Nascimento Saldiva J Appl Physiol 117:492-499, 2014. First published 10 July 2014; doi:10.1152/japplphysiol.00156.2014 You might find this additional info useful... This article cites 39 articles, 4 of which can be accessed free at: /content/117/5/492.full.html#ref-list-1 Updated information and services including high resolution figures, can be found at: /content/117/5/492.full.html Additional material and information about Journal of Applied Physiology can be found at: http://www.the-aps.org/publications/jappl
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J Appl Physiol 117: 492–499, 2014. First published July 10, 2014; doi:10.1152/japplphysiol.00156.2014.
Acute cardiopulmonary effects induced by the inhalation of concentrated ambient particles during seasonal variation in the city of São Paulo Jôse Mára de Brito,1 Mariângela Macchione,1 Kelly Yoshizaki,1 Alessandra Choqueta Toledo-Arruda,2 Beatriz Mangueira Saraiva-Romanholo,2 Maria de Fátima Andrade,3 Thaís Mauad,1 Dolores Helena Rodriguez Ferreira Rivero,1 and Paulo Hilário Nascimento Saldiva1 1
Department of Pathology, Laboratory of Experimental Air Pollution, School of Medicine, University of São Paulo, São Paulo, Brazil; 2Department of Medicine, Laboratory of Experimental Therapeutics, School of Medicine, University of São Paulo, São Paulo, Brazil and City of São Paulo University, São Paulo, Brazil; and 3Institute of Astronomy, Geophysics, and Atmospheric Sciences, University of São Paulo, São Paulo, Brazil Submitted 18 February 2014; accepted in final form 7 July 2014
particulate matter; climatic change; toxicity; inflammation; responsiveness THE METROPOLITAN AREA OF SÃO PAULO is one of the largest megacities in the world, with more than 19 million inhabitants in an area of 1,523 km2 at an altitude of 824 m, with an increasing mobile fleet of 7 million vehicles (18). Automobile sources are, therefore, major contributors to air pollution in São Paulo (3, 25). Significant detrimental effects have been re-
Address for reprint requests and other correspondence: J. M. de Brito, Faculdade de Medicina USP, Departamento de Patologia, Av. Dr. Arnaldo 455, 1 andar, sala 1220, Cerqueira César, São Paulo/SP, CEP, 01246-903 Brazil (e-mail: [email protected]). 492
ported in relation to ambient levels of air pollution in São Paulo, predominantly associated with particles (11, 21, 22). The tropical and extra-tropical climate defines singular characteristics in São Paulo city. The climate variability could be defined in two broad categories: 1) cold and dry (mean: temperature, 18°C; relative humidity, 80%; precipitation, 70 mm), which occurs between April and September and is characterized by high concentrations of primary pollutants due to the higher occurrence of thermal inversions, low humidity, and reduced wind; and 2) warm and humid (mean: temperature, 21°C; relative humidity, 81%; precipitation, 218 mm), which occurs between October and March and is characterized by relatively higher concentrations of secondary pollutants, especially ozone, due to high atmospheric temperatures (10). Air pollution is characterized as a composite mixture with variable compositions among different locations. The general understanding of air pollution composition is complicated by the direct effects that regional characteristics, climatic variability, and fuel types have on particle composition. Particles are grossly classified as primary and secondary pollutants. The primary pollutants are directly emitted by several sources, such as industry, forest fires, and vehicles. The secondary pollutants are formed in the atmosphere as a consequence of photochemical processes. The relative toxicity of primary and secondary particles is not fully understood. In several studies, both primary and secondary particles have been shown to have adverse health effects on biological systems (12, 13, 31), while other studies have shown that secondary pollutants of particles appear to be a main source of these effects (26, 33). Experimental models using concentrated ambient particles (CAPs) can provide useful information to verify the seasonal variation of particle toxicity. Recently, a study conducted in California showed that particulate matter ⱕ2.5 m (PM2.5) generated during the winter season was associated with relatively higher systemic and pro-coagulant effects in mice (35). The location of São Paulo, given the complexities of the climate variation there, presents an opportunity to investigate the influence of weather conditions on particle toxicity because only a small number of studies have measured the effects of pollutants at specific locations (19, 35). Therefore, the objectives of the present study were 1) to determine whether acute exposure to low levels of particles promotes measurable acute systemic and cardiopulmonary effects; and 2) to assess if the magnitude of the observed alterations are influenced by season. For these purposes, controlled exposures to CAPs were conducted in mice.
8750-7587/14 Copyright © 2014 the American Physiological Society
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de Brito JM, Macchione M, Yoshizaki K, Toledo-Arruda AC, Saraiva-Romanholo BM, Andrade MF, Mauad T, Rivero DHRF, Saldiva PHN. Acute cardiopulmonary effects induced by the inhalation of concentrated ambient particles during seasonal variation in the city of São Paulo. J Appl Physiol 117: 492– 499, 2014. First published July 10, 2014; doi:10.1152/japplphysiol.00156.2014.—Ambient particles may undergo modifications to their chemical composition as a consequence of climatic variability. The determination of whether these changes modify the toxicity of the particles is important for the understanding of the health effects associated with particle exposure. The objectives were to determine whether low levels of particles promote cardiopulmonary effects, and to assess if the observed alterations are influenced by season. Mice were exposed to 200 g/m3 concentrated ambient particles (CAPs) and filtered air (FA) in cold/ dry and warm/humid periods. Lung hyperresponsiveness, heart rate, heart rate variability, and blood pressure were evaluated 30 min after each exposure. After 24 h, blood and tissue samples were collected. During both periods (warm/humid and cold/dry), CAPs induced alterations in red blood cells and lung inflammation. During the cold/dry period, CAPs reduced the mean corpuscular volume levels and increased erythrocytes, hemoglobin, mean corpuscular hemoglobin concentration, and red cell distribution width coefficient variation levels compared with the FA group. Similarly, CAPs during the warm/humid period decreased mean corpuscular volume levels and increased erythrocytes, hemoglobin, hematocrit, and red cell distribution width coefficient variation levels compared with the FA group. CAPs during the cold/dry period increased the influx of neutrophils in the alveolar parenchyma. Short-term exposure to low concentrations of CAPs elicited modest but significant pulmonary inflammation and, to a lesser extent, changes in blood parameters. In addition, our data support the concept that changes in climate conditions slightly modify particle toxicity because equivalent doses of CAPs in the cold/dry period produced a more exacerbated response.
Toxicity by Concentrated Ambient Particles MATERIALS AND METHODS
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to minimize suffering. Four experimental groups were defined as follows: cold/dry exposed to CAPs (n ⫽ 46) and a corresponding control group exposed simultaneously to filtered air (FA) (n ⫽ 44), and warm/humid CAP-exposed (n ⫽46) and control groups (n ⫽ 44). All animals were exposed for 1 h at the same time each day (11 AM to 12 PM). During the intervals between the exposure periods, the animals were maintained in ventilated racks with FA (high efficiency particulate air), a controlled temperature (22–25°C), and a light-dark cycle of 12 h. CAPs exposure protocol. Male Balb/c mice were exposed to concentrated ambient PM2.5 from the city of São Paulo using a Harvard ambient particle concentrator located within the main campus of the School of Medicine of the University of São Paulo. In this system, a jet of particle-laden air is injected, and a series of impactors are used to classify particles according to their aerodynamic size. The PM2.5 was accelerated through a nozzle and concentrated by inertial forces, while aspirating peripheral airflow and increasing the concentration of particles in the size range of 0.1–2.5 m, while maintaining their physicochemical characteristics, as previously described (34). Animals were exposed to the same amount of particles. The concentration of CAPs was monitored in real time using a particulate monitor (DataRam4, Thermo Fisher Scientific) to precisely adjust concentration during the exposure duration. To achieve an accumulated dose (concentration vs. time product) of 200 g/m3, the time of the exposure was controlled to ensure the same concentration for all groups. Groups of seven to eight animals for CAPs and seven to eight animals for controls (FA) were frequently exposed for less than 1 h inside of the inhalation chambers. For each season (cold/dry or warm/humid) and for each group, 6 exposures were conducted on different days to achieve the final number of 46 CAP-exposed mice and 44 controls for each season (Table 1). Exposure protocols were conducted on the following days: 1) cold: July 7, July 19, and August 11, 2010; May 10, May 25, and June 7, 2011; and 2) warm: October 20, October 26, and November 3, 2011; February 15, March 1, and March 8, 2012. Meteorological data corresponding to the period between 2007 and 2012, as well as to the exposure dates, are presented in Table 2. Heart rate, heart rate variability, and blood pressure. Thirty minutes after the completion of the CAPs or FA exposure, the animals were anesthetized with a mixture of isoflurane (inhalatory anesthesia) and O2. A rodent-specific cuff was attached to the base of the tails of the mice and was coupled to a Powerlab system (digital system for acquisition data, ADInstruments) for 3 min of recording. The following parameters were obtained as described previously by Brito et al. (4): heart rate (HR), HR variability (HRV) for the time domain
Table 1. Outline of the experimental protocol, number of animals per group, and average exposure concentrations Animals/Group Date
Period
FA
CAPs
Mean CAPs Mass Concentration, g/m3
Exposure, min
CAPs Accumulate (Concentration vs. Time)
Temperature, °C
Humidity, %
7/7/10 7/19/10 8/11/10 5/10/11 5/25/11 6/7/11 10/20/11 10/26/11 11/3/11 2/15/12 3/1/13 3/8/12 Mean Mean
1 1 1 1 1 1 2 2 2 2 2 2 1 2
7 7 8 7 7 8 7 7 8 7 7 8 44 44
8 8 7 8 8 7 8 8 7 8 8 7 46 46
200.19 504.16 488.36 197.37 506.84 452.90 427.17 296.95 408.04 214.46 387.28 347.28 391.63 346.86
60 24 25 60 25 27 28 40 30 58 32 35 36 37
202.19 201.66 203.48 197.37 211.18 203.81 199.34 197.96 204.02 207.31 206.55 202.58 203.28 202.96
24 24 20 29 27 27 26 25 28 25 31 29 25.16 27.33
54 66 66 52 45 45 45 63 38 64 43 47 54.66 50.00
Period 1, cold/dry; period 2, warm/humid; FA, filtered air; CAPs, concentrated ambient particles. J Appl Physiol • doi:10.1152/japplphysiol.00156.2014 • www.jappl.org
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Ethics statement. This study was approved by the Ethics Committee of the School of Medicine of the University of São Paulo (permit no.: 149/10). Sampling and PM2.5 elementary characterization. Air pollution in São Paulo has been characterized as mainly vehicular in origin (22). To characterize PM2.5 in the two periods (cold/dry and warm/humid), we used data from previously collected PM2.5 samples at the School of Medicine of the University of São Paulo between June 2007 and 2008. The climatic conditions were similar to those of the study period. The PM2.5 samples generated during the cold/dry season had a higher PM2.5, black carbon, and elemental silicon, potassium, calcium, titanium, vanadium (V), iron (Fe), nickel, zinc, bromine (Br) (P ⫽ 0.001) content, and lead (Pb) (P ⫽ 0.031) level compared with the samples generated during the warm/humid season. The identification of absolute principal component analysis was based on eigenvalues ⬎ 1 before rotation analysis. This method was used to estimate the contribution of each factor to the mass concentration variation. The absolute principal component analysis identified four factors: factor 1 was related to fossil fuel combustion and secondary pollutants, which have high levels of phosphorus, sulfur, V, sulfate, and ammonium, explaining their contribution of 12% of the PM2.5 mass (3.4 g/m3); factor 2 was associated with the burning of heavy-duty diesel and biomass due to the high loading for PM2.5, black carbon, Br, and potassium, accounting for 48% of the PM2.5 mass (13.5 g/m3); factor 3 was related to crustal emissions (soil and construction) due to the high loadings for silicon, calcium, titanium, and Fe and constituted 11% of the PM2.5 mass (3.2 g/m3); and factor 4 was associated with light-duty vehicle emissions due to the presence of zinc, Pb, and other metals, accounting for 5% of the PM2.5 mass (1.4 g/m3). A regression analysis of the four “absolute factor scores” showed that 21% of the PM2.5 mass in São Paulo was not explained by any factor. The polycyclic aromatic hydrocarbon (PAH) concentrations have been characterized by Vasconcellos et al. (38). Total PAH concentrations were 10.6 ng/m3 in the warm/humid season and 25.9 ng/m3 in the cold/dry season. Experimental groups. Adult male Balb/C mice (6 – 8 wk of age) weighing ⬃25 g were obtained from the animal house at the School of Medicine of the University of São Paulo. The animals were maintained at 22–23°C with controlled humidity and a 12:12-h lightdark cycle. Food and water were available ad libitum. All animals received care in compliance with the “Principles of Laboratory Animal Care” published by the National Institutes of Health. All surgery procedures were performed under anesthesia, and efforts were made
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Table 2. Mean values (temperature and relative humidity) and sum (precipitation index) of the meteorological parameters obtained from 2007 to 2012 in São Paulo, Brazil Parameters
Temperature, °C
Relative humidity, %
Precipitation, mm
Year
Jan
Feb
Mar
Apr
May
Jun
Jul
Aug
Sep
Oct
Nov
Dec
2007 2008 2009 2010 2011 2012 2007 2008 2009 2010 2011 2012 2007 2008 2009 2010 2011 2012
22 21 22 23 23 21 83 82 82 84 83 82 126 263 234 653 466 333
23 22 23 24 23 23 80 82 82 77 81 79 274 219 219 394 328 255
23 21 22 22 21 22 77 80 82 81 87 79 205 75 247 148 91 150
21 20 20 20 21 20 82 82 83 82 82 84 78 122 52 130 102 177
17 17 18 18 17 17 81 78 81 82 83 82 54 57 56 81 24 49
17 16 15 16 15 17 76 82 81 79 81 86 26 57 42 13 65 191
15 16 16 17 16 16 79 74 87 80 79 78 161 0 200 90 12 88
17 18 17 16 17 18 75 78 77 75 77 74 1 89 51 4 65 2
19 17 19 19 17 19 74 79 84 77 77 75 4 42 203 97 4 22
20 20 19 18 19 21 79 82 86 83 80 77 96 146 138 77 176 92
20 20 23 20 19 20 80 82 80 80 79 81 123 113 234 159 111 163
22 20 22 22 21 24 80 80 84 84 79 81 198 256 209 281 236 345
Source: Institute of Astronomy, Geophysics and Atmospheric Science, University of São Paulo. Values in bold are the exposure months of the mice in the CAP groups.
mean corpuscular hemoglobin (MCH), MCH concentration (MCHC), coefficient variation of the red cell distribution width (RDW-CV), standard deviation of the red cell distribution width (RDW-SD), platelets, reticulocytes, leukocytes, polymorphonuclear neutrophils, lymphocytes, and monocytes. Complete blood counts of red blood cells (RBCs), platelets, and white blood cells were performed using a hematological analyzer (Bayer). Lung histology, immunohistochemistry, and morphometric analysis. The lungs were removed and fixed by intratracheal instillation of a 10% buffered formalin solution for 24 h and then embedded in paraffin. Five-micrometer-thick sections of lung tissues were deparaffinized, rehydrated, and stained with hematoxylin and eosin for the quantification of neutrophil density. For immunohistochemical staining analysis, the lung sections were deparaffinized, rehydrated, and blocked for endogenous peroxidase followed by antigen retrieval performed with high-temperature citrate buffer (pH ⫽ 6.0). The following primary antibodies were used: anti-endothelin A receptor (anti-ET-Ar) (1:250, Santa Cruz Biotechnology), anti-endothelin B receptor (anti-ET-Br) (1:250, Santa Cruz Biotechnology), and anti-vascular cell adhesion molecule (VCAM)-1A (1:200, Santa Cruz Biotechnology). Anti-goat, -rat, or -rabbit antibodies (Vectastain Abc Kit, Vector Laboratories) were used as secondary antibodies. Sections were counterstained with hematoxylin. Bovine serum albumin was used in substitution for primary antibodies for controls.
Table 3. Median (IQR: 25–75) values of the HR variability, HR, and BP for groups exposed to FA and CAPs during cold/ dry and warm/humid periods FA Cold/dry (n ⫽ 34)
2
SDNN, ms RMSSD, ms2 LF, ms HF, ms LF/HF HR, beats/min BP, mmHg
Warm/humid (n ⫽ 43)
CAPs All (n ⫽ 77)
Cold/dry (n ⫽ 34)
Warm/humid (n ⫽ 44)
All (n ⫽ 78)
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
15.79 20.16 14.44 10.65 1.67 400.75 89.05
12.88–20.77 16.50–28.09 8.76–30.29 5.07–20.73 1.39–2.18 366.86–427.45 69.67–129.83
14.40 18.58 7.66 4.80 1.40 401.27 91.25
11.88–19.53 14.45–24.77 4.04–14.85 2.72–11.96 1.10–2.43 381.36–448.98 74.87–117.13
15.09 19.38 11.14 7.91 1.50 400.81 91.25
12.45–20.17 14.90–26.60 4.58–24.19 3.81–13.71 1.14–2.21 379.77–436.54 72.37–120.55
17.66 21.49 10.41 7.61 1.29 404.14 94.13
14.40–20.87 16.87–28.36 6.53–17.16 5.33–12.98 1.02–2.36 362.90–433.55 58.74–134.44
14.36 17.43 10.55 6.94 1.46 409.34 85.03
11.86–18.06 14.76–22.99 4.18–15.46 3.07–13.46 1.00–1.93 396.79–431.08 76.53–121.01
15.43 18.55 10.41 7.29 1.35 409.16 86.88
12.55–20.07 15.39–25.47 5.81–15.95 4.80–13.43 1.01–2.01 384.43–431.94 71.33–125.02
n, No. of animals. IQR, interquartile range; SDNN, standard deviation of normal beats; RMSSD, root mean square of successive differences in the heartbeat interval; LF, low frequency; HF, high frequency; LF/HF, ratio of low to high frequency; HR, heart rate; BP, blood pressure. The groups were subdivided and were exposed to the following conditions: cold/dry-FA, warm/humid-FA, all-FA, cold/dry-CAPs, warm/humid-CAPs, and all-CAPs. J Appl Physiol • doi:10.1152/japplphysiol.00156.2014 • www.jappl.org
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(standard deviation of normal beats and root mean square of successive differences in the heart beat interval), frequency domain (low frequency, high frequency, and low-frequency-to-high-frequency ratio), and blood pressure (BP). Lung hyperresponsiveness. Lung hyperresponsiveness of conscious mice was measured during a dose-response curve to aerosolized methacholine (MCh) through a whole body plethysmography system (BUXCO, Winchester, UK) after HR and BP acquisition. Briefly, each mouse was placed in a chamber, and continuous measurements of the box pressure-time wave were made using a transducer that was connected to a computer data-acquisition system. The main indicator of air bronchoconstriction was enhanced pause (Penh), which shows correlation with airway resistance, as measured according to standard evaluation methods in Balb/c mice (1). After the measurement of baseline Penh, either aerosolized saline or MCh in increasing concentrations (6.25, 12.5, 25, and 50 mg/ml) was nebulized through an inlet of the chamber for 3 min. Penh values for each dose were collected for 3 min and then averaged. The maximum Penh and area under the curve were calculated. Blood analysis. After 24 h, the animals were anesthetized with a mixture of ketamine/xylazine (50 mg/kg by intraperitoneal injection). Blood samples were collected by heart puncture and then stored in ethylenediaminetetraacetic acid K3 tubes for complete blood and reticulocyte counts. The parameters evaluated were as follows: erythrocytes, hemoglobin, hematocrit, mean corpuscular volume (MCV),
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Fig. 1. Mean (⫾SE) values of enhanced pause (Penh) obtained by a dose-response curve to methacholine. A: cold. B: warm. C: all. The open circles represent filtered air (FA), and the solid circles represent concentrated ambient particles (CAPs). In A, CAPs ⫽ FA: *P ⫽ 0.012, #P ⫽ 0.038.
RESULTS
HR, HRV, and BP. There were no effects on HR, BP, and all parameters of HRV (Table 3). Lung hyperresponsiveness. The CAPs produced during the cold/dry period elevated the Penh in the baseline dose group (P ⫽ 0.012) as well as in the MCh 6.25 mg/ml dose group (P ⫽ 0.038) compared with the FA group (Fig. 1). There were no effects observed for the available parameters as evaluated by area under the curve and maximum Penh (Fig. 2). Blood. Independent of the exposure period, CAPs induced a reduction of MCV (P ⫽ 0.001) and an increase in hematocrit (P ⫽ 0.019), MCHC (P ⫽ 0.004), erythrocytes, hemoglobin, and RDW-CV (P ⫽ 0.001) compared with the FA group (Table 4). Exposure to CAPs generated during the cold/dry period promoted a reduction in MCV (P ⫽ 0.010) and an increase in erythrocytes (P ⫽ 0.018), hemoglobin (P ⫽ 0.022), MCHC (P ⫽ 0.016), and RDW-CV (P ⫽ 0.021) compared with that of the FA group. Similarly, exposure to CAPs generated during the warm/humid period induced a decrease in MCV (P ⫽ 0.001) and an increase in the number of erythrocytes, hemoglobin (P ⫽ 0.001), hematocrit (P ⫽ 0.024), and RDW-CV (P ⫽ 0.006) compared with the FA group (Table 4). The increase in RDW-CV (P ⫽ 0.015) was higher for CAPs generated during the cold/dry period than those generated during the warm/humid period, whereas hemoglobin levels (P ⫽ 0.034) were increased after exposure to CAPs generated in warm/humid periods (Table 4).
Fig. 2. Mean (⫾SE) values of maximum Penh (Penhmax; A) and area under the curve (AUC; B).
J Appl Physiol • doi:10.1152/japplphysiol.00156.2014 • www.jappl.org
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An eyepiece with a coherent system of 50 lines and 100 points with a known area attached to the ocular lens of the microscope was used for conventional morphometry. The density of neutrophils and macrophages was assessed by point counting. Using a 100-point grid with a known area (67.500 m2 at ⫻1,000 magnification) attached to the microscope ocular lens, we counted the number of points that contacted alveolar tissue in each field. Alveolar tissue area in each field was calculated as the number of points that contacted alveolar tissue as a proportion of the total grid area. Data are expressed as neutrophil cell density or macrophage cell density per alveolar area (cells/mm2) (5, 36). Counting was performed in 20 fields of alveolar parenchyma for each animal at a magnification of ⫻1,000. Image analysis. Positively immunostained areas for the ET-Ar, ET-Br, and VCAM 1 in peribronchiolar vessels were determined using image analysis. Analyses were performed using Image-Pro Plus 4.1 software for Windows (Media Cybernetics, Silver Spring, MD) using a light microscope-coupled digital camera (Olympus Q-Color 5, Tokyo, Japan) connected to a personal computer. We also assessed ET-Ar, ET-Br, and VCAM in five peribronchiolar vessels at ⫻200 magnification. The results were expressed as positively immunostained area per perimeter of the outer muscular layer of the vessel (m2/m) (5). Coded slides were used to ensure that the analysis was blinded. All measurements were performed by the same observer. Statistical analysis. The distribution of the biological effects data was checked for all variables by Kolmogorov-Smirnov analyses. Normally distributed variables are reported as means ⫾ SD, and the significance was determined using the independent-samples T-test. The nonnormally distributed variables were reported as median and interquartile range (25–75%), and the significance was determined using the Mann-Whitney U-test. The significance of the lung mechanics was determined using the general linear model for repeated measures. The level of significance was set at 5%. Statistical analyses were performed using SPSS 15.0.
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Table 4. Descriptive values of hematological parameters for groups exposed to FA and CAPs during cold/dry and warm/ humid periods FA Parameters
1) 2) 3) 4) 5) 6) 7) 8) 9) 10) 11) 12) 13) 14)
Erytrocytes, ml/mm3 Hemoglobin, g/dl Hematocrit, % Mean corpuscular volume, fl Mean corpuscular hemoglobin, pg Mean corpuscular hemoglobin concentration, g/dl Red distribution with variation coefficient, % Red distribution with size distribution, fl Platelets, ml/mm3 Reticulocytes, % Leucocytes, ml/mm3 PMN, ml/mm3 Lymphocytes, ml/mm3 Monocytes, ml/mm3
CAPs
a) Cold/dry (n ⫽ 34)
b) Warm/humid (n ⫽ 39)
c) All (n ⫽ 73)
d) Cold/dry (n ⫽ 39)
e) Warm/humid (n ⫽ 40)
f) All (n ⫽ 79)
10.18 ⫾ 0.47 15.13 ⫾ 0.60 44.76 ⫾ 1.74 43.99 ⫾ 1.05 14.86 ⫾ 0.29
10.28 ⫾ 0.46 15.30 ⫾ 0.74 45.64 ⫾ 1.91 44.41 ⫾ 1.03 14.89 ⫾ 0.54
10.23 ⫾ 0.47 15.22 ⫾ 0.68 45.23 ⫾ 1.87 44.21 ⫾ 1.05 14.88 ⫾ 0.44
10.50 ⫾ 0.63 15.53 ⫾ 0.82 45.29 ⫾ 1.91 43.22 ⫾ 1.37 14.81 ⫾ 0.27
10.75 ⫾ 0.53 15.95 ⫾ 0.89 46.67 ⫾ 2.01 43.45 ⫾ 1.20 14.83 ⫾ 0.54
10.62 ⫾ 0.59 15.74 ⫾ 0.87 45.99 ⫾ 2.07 43.33 ⫾ 1.29 14.82 ⫾ 0.43
33.81 ⫾ 0.71
33.54 ⫾ 1.29
33.67 ⫾ 1.06
34.28 ⫾ 0.87
34.18 ⫾ 1.49
34.23 ⫾ 1.21
22.89 ⫾ 0.77
21.97 ⫾ 1.10
22.40 ⫾ 1.06
23.47 ⫾ 1.25
22.75 ⫾ 1.33
23.10 ⫾ 1.33
28.95 ⫾ 1.49 890.68 ⫾ 220.85 3.19 ⫾ 0.83 2.89 ⫾ 1.33 0.31 ⫾ 0.21 2.45 ⫾ 1.16 0.10 ⫾ 0.16
28.13 ⫾ 1.67 786.29 ⫾ 229.20 3.46 ⫾ 0.77 3.92 ⫾ 1.54 0.58 ⫾ 0.35 3.17 ⫾ 1.29 0.17 ⫾ 0.12
28.52 ⫾ 1.63 835.58 ⫾ 229.78 3.34 ⫾ 0.80 3.43 ⫾ 1.52 0.45 ⫾ 0.32 2.83 ⫾ 1.28 0.14 ⫾ 0.14
29.17 ⫾ 1.54 979.18 ⫾ 226.92 3.03 ⫾ 0.86 3.19 ⫾ 1.38 0.37 ⫾ 0.32 2.71 ⫾ 1.22 0.11 ⫾ 0.12
28.23 ⫾ 1.56 817.63 ⫾ 201.47 3.17 ⫾ 0.83 4.55 ⫾ 1.69 0.70 ⫾ 0.35 3.71 ⫾ 1.49 0.17 ⫾ 0.12
28.69 ⫾ 1.61 897.38 ⫾ 228.01 3.10 ⫾ 0.84 3.88 ⫾ 1.68 0.54 ⫾ 0.37 3.22 ⫾ 1.44 0.14 ⫾ 0.12
Lung histology. Both CAPs produced during the cold/dry and the warm/humid periods elevated the number of neutrophils and macrophages (P ⫽ 0.001) compared with the FA group. However, the increase of neutrophils (P ⫽ 0.001) was higher in the exposure conducted during the cold/dry period (Table 5). Immunohistochemistry. There were no differences between groups for VCAM, ET-Ar, and ET-Br expression in lung vessels (Table 6). Summary of effects. Table 7 summarizes the statistically significant (P ⬍ 0.05) effects of all parameters studied in mice exposed to CAPs compared with mice exposed to FA, such as the electric activity of the heart through HRV, lung hyperresponsiveness during a dose-response curve to aerosolized MCh, systemic inflammation by blood parameters, lung inflammation by lung histology, and immunohistochemical markers. DISCUSSION
We observed that a single exposure to a low concentration of CAPs derived from a São Paulo urban region evoked lung inflammation and alterations in RBC count in mice. Neutrophilic lung inflammation was more prominent in mice exposed to CAPs generated during the cold/dry period compared with
mice exposed to CAPs generated in the warm/humid period. To our knowledge, this is the first study to address the seasonal effects of PM in São Paulo on biological outcomes in mice. Principal component analyses of São Paulo PM2.5 elements showed that, during the cold/dry seasons, there was a predominance of factors related to the burning of heavy-duty diesel as well as due to biomass and crustal emissions (soil and construction). It is believed that the weather conditions during the cold/dry seasons are unfavorable for the dispersion of pollutants, thus worsening the air quality in major urban centers. In contrast, warm/humid weather conditions perpetuate the formation of secondary aerosols in the atmosphere due the action of solar radiation on PM2.5. Tablin et al. (35) demonstrated an association between increased concentrations of PM0.1 metals and PAHs during winter periods in Fresno, CA and a greater systemic proinflammatory and procoagulant response. Little is known about the seasonal effects on particle composition in São Paulo city, where differences in temperature and humidity are milder compared with other regions of the globe. The effect of climate alterations on particle composition and size in the city of São Paulo has been well documented by Albuquerque et al. (2), who showed that meteorological conditions have a major influence on the suspended aerosol con-
Table 5. Descriptive values of the lung neutrophils and macrophages for groups exposed to FA and CAPs during cold/dry and warm/humid periods FA
CAPs
Parameters (105 cells/mm2)
a) Cold/dry (n ⫽ 44)
b) Warm/humidy (n ⫽ 44)
c) All (n ⫽ 88)
d) Cold/dry (n ⫽ 46)
e) Warm/humid (n ⫽ 45)
f) All (n ⫽ 91)
1) Neutrophils 2) Macrophages
5.36 ⫾ 1.68 6.99 ⫾ 1.11
4.99 ⫾ 1.92 6.82 ⫾ 1.01
5.18 ⫾ 1.80 6.91 ⫾ 1.06
8.67 ⫾ 2.10 11.38 ⫾ 1.45
7.40 ⫾ 1.25 10.79 ⫾ 1.43
8.04 ⫾ 1.84 11.08 ⫾ 1.47
Values are means ⫾ SD; n, no. of animals. The groups were subdivided and were exposed to the following conditions: a) cold/dry-AF; b) warm/humid-AF, c) all-AF; d) cold/dry-CAPs; e) warm/humid-CAPs; f) all-CAPs. Group c ⫽ group f (parameters 1 and 2: P ⫽ 0.001). Group d ⫽ group e (parameter 1: P ⫽ 0.001). Group a ⫽ group d (parameters 1 and 2: P ⫽ 0.001). Group b ⫽ group e (parameters 1 and 2: P ⫽ 0.001). J Appl Physiol • doi:10.1152/japplphysiol.00156.2014 • www.jappl.org
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Values are means ⫾ SD; n, no. of animals. PMN, polymorphonuclear neutrophils. The groups were subdivided and were exposed to the following conditions: a) cold/dry-AF; b) warm/humid-AF, c) all-AF; d) cold/dry-CAPs; e) warm/humid-CAPs; f) all-CAPs. Group c ⫽ group f (parameters 1, 2, 4, and 7: P ⫽ 0.001; 3: P ⫽ 0.019; and 6: P ⫽ 0.004). Group d ⫽ group e (parameters 3: P ⫽ 0.003; and 7: P ⫽ 0.015). Group a ⫽ group d (parameters 1: P ⫽ 0.018; 2: P ⫽ 0.022; 4: P ⫽ 0.010; 6: P ⫽ 0.016; and 7: P ⫽ 0.021). Group b ⫽ group e (parameters 1, 2, and 4: P ⫽ 0.001; 3: P ⫽ 0.024; and 7: P ⫽ 0.006).
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Table 6. Median (IQR: 25–75) values of the lung immunohistochemistry for groups exposed to FA and CAPs during cold/ dry and warm/humid periods FA Cold/dry (n ⫽ 39)
CAPs
Warm/humid (n ⫽ 44)
All (n ⫽ 83)
Cold/dry (n ⫽ 41)
Warm/humid (n ⫽ 44)
All (n ⫽ 84)
Parameters
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
Median
IQR (25–75%)
Endothelin-A Endothelin-B VCAM-1
0.28 0.63 0.09
0.14–0.42 0.37–1.03 0.05–0.13
0.16 0.08 0.16
0.06–0.34 0.03–0.27 0.11–0.23
0.23 0.34 0.11
0.10–0.36 0.08–0.69 0.06–0.20
0.26 0.56 0.07
0.13–0.49 0.41–0.94 0.03–0.17
0.14 0.11 0.16
0.04–0.28 0.04–0.23 0.11–0.27
0.21 0.29 0.12
0.07–0.36 0.09–0.59 0.05–0.21
The groups were subdivided and were exposed to the following conditions: cold/dry-AF, warm/humid-AF, all-AF, cold/dry-CAPs, warm/humid-CAPs, and all-CAPs.
centrations in the atmosphere. Epidemiological studies have shown that interactions between air pollution and weather conditions are associated with increases in mortality and morbidity of respiratory and cardiovascular diseases (14, 15, 24). Few studies have addressed biological outcomes in animals exposed to particles generated in different climates (28, 35).
Our results show that acute, short exposure to ambient particles induced lung inflammation in both cold/dry and warm/humid periods, with increases in neutrophils and macrophages in the lung tissue. Previous studies have demonstrated that exposure to CAPs caused an increase in lung neutrophils in rats, which correlated with the V and bromide
Table 7. Summary of the effects
System/Parameters
HR variability SDNN RMSSD LF HF LF/HF HR BP Lung hyperresponsiveness Baseline Penh Penh saline Penh 6.25 MCh Penh 12.5 MCh Penh 25 MCh Penh 50 MCh Penhmax AUC Blood MCV Erythrocytes Hemoglobin Hematocrit MCHC RDW-CV RDW-SD Leucocytes totals Monocytes Lymphocytes PMN Platelets Lung histology Neutrophils Macrophages Vessels peribronchiolar Endothelin-A receptor Endothelin-B receptor VCAM-1
CAPs
CAPs
Cold
Warm
Cold
Warm
— — — — — — —
— — — — — — —
— — — — — — —
— — — — — — —
— — — — — — —
— — — — — — — —
1 — 1 — — — — —
— — — — — — — —
— — — — — — — —
— — — — — — — —
2 1 1 1 1 1 — — — — — —
2 1 1 — 1 1 — — — — — —
2 1 1 1 — 1 — — — — — —
— — — — — 1 — — — — — —
— — 1 — — — — — — — — —
1 1
1 1
1 1
1 —
— —
— — —
— — —
— — —
— — —
— — —
The CAPs, cold, and warm columns under FA compare CAPs group in relation group FA. The cold and warm columns under CAPs compare CAPs cold vs. CAPs warm. Penh, enhanced pause; Penh saline, Penh with 6.25, 12.5, 25, and 50 mg/ml of methacholine, respectively; Penhmax, maximum Penh; AUC, area under the curve; MCV, mean corpuscular volume; MCHC, mean corpuscular hemoglobin concentration; RDW-CV, coefficient variation of the red cell distribution width; RDW-SD, standard deviation of the red cell distribution width; 1, increase; 2, decrease; —, unchanged. Significance: P ⬍ 0.05. J Appl Physiol • doi:10.1152/japplphysiol.00156.2014 • www.jappl.org
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mation, with an increase in the RDW level in canines. The mechanisms that promote the release of circulating RBCs from the bone marrow by CAPs are unclear, and there is a lack of literature focusing on this physiopathological process. CAPs exposure induced no alterations in HR, HRV, and BP, parameters that are predictive of cardiovascular disease, as described in previous studies of exposure to CAPs (17), PM2.5 (29), diesel exhaust particles (4), and interactions between temperature and ozone levels (29, 39). Similarly, no alterations in lung adhesion molecules and endothelial receptor values were observed. Exposure to 14 days of air pollution caused vascular constriction with increased ET-Ar expression (21). It is possible that the lack of changes related to endothelial dysfunction in our model is related to the acute, short exposure that we employed. It is important to note the limitations of the present study. We used historical data from 2007–2008 to analyze PM elements. In the present study, the climatic conditions were similar to the climatic conditions during the period 2007–2012. Considering that the quality of the fuel and vehicular engines did not change during that period, we considered it valid to use historical PM2.5 composition data. The collection of ambient particles does not capture potential pollutants that are in gaseous or vapor forms; therefore, this exposure was not simulated through these experiments. The tail-cuff system used in this study is a system of limited value to detect small differences for HR, BP, and HRV and could explain the lack of significant results in the present study. In summary, short-term exposure to low concentrations of CAPs elicited modest but significant pulmonary inflammation and, to a lesser extent, changes in blood parameters. In addition, our data support the concept that changes in climate conditions slightly modify particle toxicity because equivalent doses of CAPs from the cold/dry period produced a more exacerbated response. GRANTS This work was supported by grants from Fundação de Amparo a Pesquisa do Estado de São Paolo (São Paulo, Brazil, 2010/50841–3). T. Mauad is funded by Conselho Nacional de Desenvolvimento Científico e Tecnológico. DISCLOSURES No conflicts of interest, financial or otherwise, are declared by the author(s). AUTHOR CONTRIBUTIONS Author contributions: J.M.B. and P.H.S. conception and design of research; J.M.B., K.Y., and B.M.S.-R. performed experiments; J.M.B., M.M., K.Y., A.C.T.-A., M.d.F.A., and T.M. analyzed data; J.M.B., M.M., A.C.T.-A., M.d.F.A., and T.M. interpreted results of experiments; J.M.B. prepared figures; J.M.B. and M.M. drafted manuscript; J.M.B., M.M., A.C.T.-A., T.M., and D.H.R.F.R. edited and revised manuscript; J.M.B. and P.H.S. approved final version of manuscript. REFERENCES 1. Adler A, Cieslewicz G, Irvin CG. Unrestrained plethysmography is an unreliable measure of airway responsiveness in BALB/c and C57BL/6 mice. J Appl Physiol 97: 286 –292, 2004. 2. Albuquerque TT, Andrade MF, Ynoue RY. Characterization of atmospheric aerosols in the city of São Paulo, Brazil: comparisons between polluted and unpolluted periods. Environ Monit Assess 184: 969 –984, 2012. 3. Andrade MD, Miranda RM, Fornaro A, Kerr A, Oyama B, Andre PA, Saldiva P. Vehicle emissions and PM2.5 mass concentration in six Brazilian cities. Air Qual Atmos Health 5: 79 –88, 2012.
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concentrations in the particles (6, 8, 31). Maciejczyk et al. (20) demonstrated an association between lung inflammatory response in mice and the presence of manganese, Fe, nickel, and Pb in CAPs. We found a greater neutrophilic inflammatory response in mice exposed to the cold/dry CAPs. We speculate that these differences are related to the increased concentration of metals and organic compounds and variation in the composition of such that occur in this seasonal period (2, 21). We found an increase in RBCs in animals exposed to CAPs generated during both the cold/dry and warm/humid periods, suggesting that bone marrow stimulation causes the release of erythropoietin. The increase of hematocrit could increase blood viscosity, contributing to the pathogenesis of pollution-related cardiac events (37, 40). Previous work has shown that ambient air particles promote significant effects on hematological parameters after inhalation (9, 16, 27), and that the composition of fine particles can determine the blood response to inhaled particles (23). However, the alterations in hematological parameters during the two analyzed periods of this study were similar. The increase in the circulation of blood cells and lung inflammatory cell measurements in the FA group may be due to secondary aerosol formation (ozone) generated during the warm/humid period because the animals were exposed for 1 h between 11 AM and 12 PM, a period that has a greater predominance of sunlight, a predisposing factor for the formation of secondary aerosol. Furthermore, CAPs is a system that filters only particles. The hematopoietic system is very sensitive to toxic substances due to the characteristic intensive cell proliferation. Environmental pollution includes many chemicals, including benzene, pesticides (dithiocarbamines), ethylene oxide, and metals (mercury, cadmium, chrome, cobalt, lead, aluminum) that exert their toxic effect on the hematopoietic system. One explanation of the observed hematological alterations is that the PM2.5 contains substances with a lower solubility that have the capacity to reach the systemic circulation. Medeiros et al. (23) developed a study designed to measure the hematological parameters and bone marrow after acute exposure to oil fly ash. They concluded that exposure to oil fly ash increases the reticulocyte levels in the peripheral blood and stimulates the bone marrow to increase the production of erythroblasts. They have concluded that erythroblasts in the bone marrow received a stimulus provoked by inhaled toxic particles without evidence of a hemolytic process or red cell loss. The number of circulating RBCs is dependent on the bone marrow. This is an important factor for understanding the pathogenesis of pollution-related heart diseases because increased RBCs may induce changes in blood viscosity, which may increase the mechanical load in the heart, as well as to blood clotting. Previous studies have observed that exposure to ambient particles increased the number of leucocytes in mice (30), canines (9), and humans (32). Additionally, we observed an increase in the levels of MCHC and RDW that may be related to pulmonary inflammation observed by neutrophilic infiltrate. RDW measures the variability of RBC sizes and is an index of the heterogeneity of the erythrocytes with immature types (i.e., anisocytosis) (7). The potential mechanism causing elevated levels of RDW may be inflammation or changes in erythrocyte volume and function of the heart. Zao et al. (41) described a correlation between oxidative stress and inflam-
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