2003 Progress Report: Long Term Health Effects of Concentrated Ambient PM2.5

EPA Grant Number: R827351C013
Subproject: this is subproject number 013 , established and managed by the Center Director under grant R827351
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).

Center: EPA NYU PM Center: Health Risks of PM Components
Center Director: N/A
Title: Long Term Health Effects of Concentrated Ambient PM2.5
Investigators: Chen, Lung Chi , Lippmann, Morton
Institution: New York University School of Medicine
EPA Project Officer: Chung, Serena
Project Period: June 1, 1999 through May 31, 2005 (Extended to May 31, 2006)
Project Period Covered by this Report: June 1, 2002 through May 31, 2003
RFA: Airborne Particulate Matter (PM) Centers (1999) RFA Text |  Recipients Lists
Research Category: Air Quality and Air Toxics , Particulate Matter , Air

Objective:

The objective of this research project is to perform data analysis of the heart rate and heart rate variability data collected in last year’s subchronic concentrated ambient particles (CAPs) study (Summer 2003 Study) as well as additional biological assays such as gene expression, and histopathological evaluation of the lung, heart, aorta, and brain of the animals.

This is one of the projects funded by the New York University (NYU) PM Center. The progress for the other projects is reported separately (see reports for R827351C001 through R827351C012, and R827351C014 through R827351C016).

Progress Summary:

Acute and Chronic Effects of CAPs on Heart Rate, Heart Rate Variance, and Body Temperature

As described in Hwang, et al. (2004a), we used our recently developed “Fishing License” method (Nadziejko, et al., 2004) to estimate the times that mean heart rates, body temperature, and physical activity differed significantly between the CAPs- and sham-exposed groups. As shown in Figure 1, CAPs exposure most affected heart rate between 1:30 a.m.-4:30 a.m., and the greatest effects were seen at the end of the exposure series. With the response variables being the average heart rate, body temperature, and physical activity, we adopted a two-stage modeling approach to obtain the estimates of chronic and acute effects on the changes of these three response variables. In the first stage, a time-varying model estimated daily crude effects. In the second stage, the true mean of the estimated crude effects were modeled with a polynomial function of time for chronic effects, an index function of daily CAPs exposure for acute effects, and a random component for unknown noise. A Bayesian framework combined these two stages. There were significant decreasing patterns of heart rate (Figure 2), body temperature (Figure 3), and physical activity (Figure 4) for the apolipoprotein E (ApoE)-/- mice over the 5 months of CAPs exposure, with smaller and nonsignificant changes for the C57 mice. Based on cross correlations among the measurements series, we found that heart rate series led body temperature series by about 5 minutes. Response variables also were defined for examining variances of 5-minute heart rates within long (i.e., 3-6 hours) and short time periods (i.e., ~ 15 minutes). The results for the ApoE-/- mice showed that variation of heart rates within the longer periods increased to 1.35-fold by the end of the exposure experiment (Figure 5), whereas the variation of heart rates within 15 minutes decreased to 0.7-fold (Figure 6).

The Group Mean 24-Hour Heart Rate of ApoE

Figure 1. The Group Mean 24-Hour Heart Rate of ApoE-/- Mice Averaged Over the Last 5 Days of the Exposure Experiment

The Posterior Means (Solid) and 95 Percent Equal-Tail Credible Intervals1

Figure 2. The Posterior Means (Solid) and 95 Percent Equal-Tail Credible Intervals (Dotted) of Chronic Effect Changes for ApoE-/- Mice Heart Rate During 1:30 a.m.-4:30 a.m. Obtained From the Bayesian Model in the Second Stage. The circles in the lots are daily crude effects estimated in the first stage (full for exposure day and empty for nonexposure day). The period during which the animal housing room light did not go off at night is marked with vertical bars.

The Posterior Means (Solid) and 95 Percent Equal-Tail Credible Intervals2

Figure 3. The Posterior Means (Solid) and 95 Percent Equal-Tail Credible Intervals (Dotted) of Chronic Effect Changes for ApoE-/- Mice Body Temperature During 1:30 a.m.-4:30 a.m. Obtained From the Bayesian Model in the Second Stage. The circles in the plots are daily crude effects estimated in the first stage (full for exposure day and empty for nonexposure day). The period during which the animal housing room light did not go off at night is marked with vertical bars.

The Posterior Means (Solid) and 95 Percent Equal-Tail Credible Intervals3

Figure 4. The Posterior Means (Solid) and 95 Percent Equal-Tail Credible Intervals (Dotted) of Chronic Effect Changes for ApoE-/- Mice Activity During 1:30 a.m.-4:30 a.m. Obtained From the Bayesian Model in the Second Stage. The circles in the plots are daily crude effects estimated in the first stage (full for exposure day and empty for nonexposure day). The period during which the animal housing room light did not go off at night is marked with vertical bars.

The Posterior Means (Solid) and 95 Percent Equal-Tail Credible Intervals4

Figure 5. The Posterior Means (Solid) and 95 Percent Equal-Tail Credible Intervals (Dotted) of Chronic Effect Changes of Log 10 Spectrum Powers Over Low Frequency Band 0.0125-0.0229 for ApoE-/- Mice Heart Rate Obtained From the Bayesian Model in the Second Stage. The circles in the plots are daily crude effects estimated in the first stage.

The Posterior Means (Solid) and 95 Percent Equal-Tail Credible Intervals5

Figure 6. The Posterior Means (Solid) and 95 Percent Equal-Tail Credible Intervals (Dotted) of Chronic Effect Changes of Log 10 Spectrum Powers Over High Frequency Band 0.3-0.3146 for ApoE-/- Mice Heart Rate Obtained From the Bayesian Model in the Second Stage. The circles in the plots are daily crude effects estimated in the first stage.

As described by Chen, et al. (2004), histopathological examination was performed at the end of exposure on the surviving (C57 and ApoE-/- low-density lipoprotein [LDL]r-/- double knockout [DK]) mice. The number of mice in each group is shown below. Six mice had inadequate sections and were not scored. From one to five coronary artery profiles were seen per section. Most sections had one to two coronary artery profiles. There was very close agreement between the two sections.

Table 1. The Number of Mice in Each Group

The Number of Mice in Each Group

Ten of 32 mice had 1 or more coronary artery profiles with some degree of lipid deposition. Three of 32 mice had histological evidence of old myocardial infarction (MI). Extent of coronary artery disease (CAD) was scored by estimating how much of the luminal surface was affected. Severity was scored by determining whether lipid deposition extended into the muscular layer (“bad CAD”) or whether it was confined to the endothelium. Calcification of the plaque was a second criterion for “bad CAD.” No abnormalities were seen in any of the C57 mice.

Table 2. Results for the DK Mice

Results for the DK Mice

In many cases, only one coronary artery profile was abnormal, and the other branch or branches were normal. We did not attempt to adjust the data for the number of coronary arteries seen per animal because CAD is known to be very focal. In addition, all of the scoring and data summarization were performed blind.

Figures 7 and 8 show the lesion areas and cellularity of aortas of DK mice after exposures to filtered air or CAPs for 5 months. All animals regardless of exposure had developed extensive lesions in the aortic sinus regions, with lesion areas that covered more than 79 percent of the total area. These images clearly showed the formation of atherosclerotic plaques protruded into the aorta lumens. Although the lesion areas appeared to be enhanced by CAPs, with changes in male DK mice approaching statistical significance, the differences in the increased lesion areas were probably functionally insignificant. In addition, plaque cellularity was increased by 6 percent (p = 0.04 in male DK mice, see Figure 8).

After the aorta tree was opened longitudinally, digital images were obtained and processed to measure the size of the plaques. Figure 9 shows the retouched digital images of the aorta of a DK mouse after a 5-month exposure to CAPs. Plaques stained red with Sudan IV were clearly visible and were distributed throughout the aortic tree. Visual examination of all of the images suggested that plaques tend to form in clusters concentrating near the aortic arch and the iliac bifurcations. Figure 10 is the aorta of an air-exposed DM mouse and Figure 11 is the aorta of a CAPs-exposed C57 mouse. The densities of plaques in the filtered air-exposed animals or in both CAPs- and filtered air-exposed C57 were sparser than those found in CAPs-exposed DK mice. In C57 mice, the plaques were so small (indicated by arrows in Figure 11) that they were difficult to spot using the low-power dissecting scope. Quantitative measurements showed that CAPs exposure increased the size of aortic plaques by 24 percent in the ApoE mice (p = 0.05). Changes produced by CAPs in male (10% increase) or female DK mice were not statistically significant. Because the image analysis was performed on two-dimensional longitudinal images, and because plaques clearly were protruding inward, this technique would underestimate the size of the plaques in these measurements.

Lesion Areas, Measured as Auto-Fluorescence

Figure 7. Lesion Areas, Measured as Auto-Fluorescence

Cellularity, Cell Nuclei Were Stained With 4',6-Diamidino-2-phenylindole

Figure 8. Cellularity, Cell Nuclei Were Stained With 4',6-Diamidino-2-phenylindole

Aorta of DK Mouse Exposed to CAPs for 5 Months

Figure 9. Aorta of DK Mouse Exposed to CAPs for 5 Months

Aorta of an Air-Exposed DK Mouse

Figure 10. Aorta of an Air-Exposed DK Mouse

Aorta of a CAP-Exposed C57 Mouse

Figure 11. Aorta of a CAP-Exposed C57 Mouse. Arrows indicate the locations of atherosclerotic lesion.

Effects on Gene Expression in the Lung and Heart

As described by Gunnison and Chen (2004), tissues from multiple replicates of C57BL/6 and ApoE/LDL DK were examined for relative exposure-related changes in gene expression. Because of limited resources, the number of replicates was three for each tissue (lung and heart) of each exposure condition (CAPs or air control).

Microarray Data

GeneChip data were loaded into the GeneTraffic program and processed as described above. The data were downloaded from GeneTraffic as log2 (current chip intensity/baseline intensity) ratios, where “current chip” represents each of the three chips in the heart or lung project and “baseline intensity” is an average of the three AIR chips in the appropriate project. These data were analyzed using the SAM program. Initial parameters were set to flag transcripts that were up- or downregulated by 1.5-fold or more with a false discovery rate of less than 10 percent. This procedure identified only one gene in the heart tissue (Rex3) and no genes in the lung tissue. These findings indicate that exposure to subchronic CAPs did not have a consistent and pronounced effect on gene expression in the heart or lung when measured at the end of the exposure period.

A more liberal screening procedure was devised to flag those genes that might be only moderately affected by subchronic CAPs exposure, and therefore not detected by a rigorous statistical analysis of GeneChip data. Two approaches were used to generate such a list of candidate genes. One of these approaches consisted of applying liberal analytical criteria in the SAM program (i.e., a l.5-fold change in normalized signal intensity without regard for the false discovery percentage. The second approach was to make comparisons of the normalized intensity between probe sets of individual pairs of chips. That is, each of the three CAPs chips was compared against each one of the three control (AIR) chips resulting in a total of nine comparisons for each probe set. Any probe set that was up- or downregulated by 1.5-fold or greater in at least four of the nine comparisons was flagged for further examination. The probe sets identified by these 2 liberal screening procedures numbered 32 for heart tissue and 95 for lung tissue.

Among these two lists of flagged probe sets, those with very weak signals were eliminated. Probe sets that contained “Marginal” or “Absent calls” in two or three of the AIR chips and also showed an overall downregulation on the CAPs chips were eliminated from the list. The probe sets remaining then were reexamined in the GeneTraffic program. The three AIR chips were combined to provide a common baseline signal for each probe set of interest, and the same probe sets from each CAPs chip were compared against these baseline values. This comparison provided three expression ratios, one for each CAPs chip, for each probe set on the two lists. A probe set was retained as representing a gene that might be affected by subchonic CAPs exposure only if at least two of these expression ratios showed a 1.5-fold or greater change in the same direction and no change of 1.5-fold or greater in the opposite direction.

Comparison of Expression Ratios Determined From GeneChips and by Quantitative Real-Time Reverse Transcription-Polymerase Chain Reaction (RT-PCR)

There were nine expression ratios of probe set 1448756 of gene S100a9 (S100 calcium binding protein A9 = calgranulin B) obtained by comparing each of the three CAPs-exposed heart samples against each sham air-exposed heart sample. This particular gene was selected because of the wide range of expression ratios observed. Ratios were determined from the GeneChip data normalized in GeneTraffic and from quantitative RT-PCR data (LightCycler data). There was good agreement between the GeneChip and LightCycler ratios determined for the CAPs 3 sample that was upregulated with respect to each AIR sample. The agreement between GeneChip and LightCycler ratios for CAPs 1 and CAPs 2 comparisons, all of which were downregulated, was not as good, although the rank order of sample ratios was the same for the two methods. That is, the order from greatest to least downregulation determined by each method was the same. Because real-time RT-PCR technology is more accurate than DNA microarray technology, especially for low concentrations of mRNA transcripts, the highly negative ratios determined by the LightCycler for CAPs 1 and CAPs 2 samples are probably more accurate than those determined from GeneChip data. Overall, the agreement between LightCycler and GeneChip ratios indicates that the trends of the ratios among samples determined from GeneChip data are valid, although DNA microarray data tend to underestimate the magnitude of expression changes. This has been observed by others (e.g., Dooley, et al., 2003).

Degeneration of Dopaminergic Neurons

Histological Preparation. As described by Veronesi, et al. (2004), the cranium of each mouse was opened and the dorsal brain exposed. The brain was left in its cranial cavity and submerged in cacodylate-buffered 4 percent glutaraldehyde for 3-4 days. After this time, the brains were removed from the cranial cavity with rongeurs, coded, immersed in buffer without fixative, and submitted to the NeuroScience Association (http://www.neuroscienceassociates.com Exit ) for histological preparation.

The brains of CAPs- and air-exposed Apo E-/- mice (6-9/treatment) and CAPs- and air-exposed C57BL/6 (5/treatment) were multiembedded (25 per slide). Serial frozen sections (40 μm) of the brain were taken in the coronal plane, and slides were stained sequentially with tyrosine hydroxylase (TH), an immunocytochemical stain for dopamine-containing neurons (Chan, et al., 1997) ; glial fibrillary acidic protein (GFAP), an immunocytochemical stain for astrocytes; and thionine, a Nissl substance stain. Ten slides that bracketed the SN nuclei reticularis and compacta were selected and microscopically examined in a semiblinded fashion. Two photographs of each section were shot using an apochromatic 10X objective on a Nikon TE300 inverted microscope and a cooled-frame charged coupled device camera (Orca I, Hamamatsu, Inc.) with a green filter to enhance staining differences. Each section was analyzed using Metamorph software (Image 1, West Chester, PA). The total pixel area of TH- or GFAP-stained cell bodies in the nucleus compata was digitized in the integrated morphometric analysis mode. Data from individual values were collected in Excel and transferred to Prism3 for statistical analysis (p < 0.05) and graphics generation (Graphpad Software, Inc., San Diego, CA).

Degeneration of Dopaminergic Neurons. Thionine-stained, coronal sections of the mouse midbrain were examined at 4X power to give a general overview of the ventral midbrain. These regions house the dopaminergic neurons particularly sensitive in human and animal models of Parkinson’s neuropathy (Hirsch, et al., 1997; Betarbet, et al., 2000; Greenamyre, et al., 2003) . TH-immunoreactive cells represent 75-80 percent of neurons in the SN (Liberatore, et al., 1999; McCormack, et al., 2002) . The number of dopaminergic neurons was estimated by counting the pixel area of TH-immunoreactive cells in the SN nucleus compacta. Although the TH staining of the nucleus compacta appeared thinner in the C57/blk6 versus ApoE-/- SN, a quantitative analysis of the TH-stained neurons and their fiber plexus showed no significant differences in the air- or CAPs-exposed C57/blk6 relative to the air-exposed ApoE-/- animals. Quantitative analysis of the TH-stained neurons in the CAPs- and air-exposed C57/blk6 brains showed no difference. There was a 29 percent reduction, however, in TH-stained neurons in the CAPs-exposed versus air-exposed ApoE-/- mice. Gliosis is a pathological feature associated with neurodegeneration in the Parkinsonian brain (Forno, et al., 1992; Hirsch, 2000) . A significant increase (p < 0.05) in GFAP staining (i.e., astrocytes) was measured in the nucleus compacta of CAPs-exposed ApoE-/- relative to air-exposed ApoE-/- brains.

Winter 2004 Subchronic Study

We performed a shorter subchronic study between March and May of 2004 (Winter 2004 Study). In this study, ApoE-/-, AKR, and B129 mice were exposed to CAPs for 6 hours/day, 5 days/week, for 2- and 3-month intervals. ApoE and AKR mice were implanted with electrocardiogram (EKG) transmitters and their heart rate, body temperature, and activity were monitored continuously. Additional animals also were used to evaluate other biological endpoints.

We made extensive improvements to the versatile aerosol concentration enrichment system (VACES) by incorporating semiautomatic monitoring of the exposure parameters. We also used an impactor developed by Dr. Judy Xiong to collect droplets from the VACES instead of the Biosampler so that CAPs samples could be collected every 15 minutes for ionic chromatography analysis and biological assays. The exposure parameters are shown in Table 3.

Table 3. Exposure Parameters of the Winter 2004 Subchronic Study.

Exposure Parameters of the Winter 2004 Subchronic Study

References:

Betarbet R, Sherer TB, MacKenzie G, Garcia-Osuna M, Panov AV, Greenamyre JT. Chronic systemic pesticide exposure reproduces features of Parkinson’s disease. Nature Neuroscience 2000;3(12):1301-1306.

Chan P, Di Monte DA, Langston JW, Janson AM. (+)MK-801 does not present MPTP-induced loss of nigral neurons in mice. The Journal of Pharmacology and Experimental Therapeutics 1997;280:439-446.

Dooley TP, Curto EV, Davis RL, Grammatico P, Robinson ES, Wilborn TW. DNA microarrays and likelihood ratio bioinformatics methods: discovery of human melanocyte biomarkers. Pigment Cell Research 2003;16:245-253.

Forno LS, DeLanney LE, Irwin I, Di Monte D, Langston JW. Astrocytes and Parkinson’s disease. Progress in Brain Research 1992;94:429-436.

Greenamyre JT, Betarbet R, Sherer TB. The rotenone model of Parkinson’s disease: genes, environment and mitochondria. Parkinsonism and Related Disorders 2003;9(S2):S59-S64.

Hirsch EC. Glial cells and Parkinson’s disease. Journal of Neurology 2000;247(S2):1158-1162.

Hirsch EC, Faucheux B, Damier P, Mouatt-Prigent A, Agid Y. Neuronal vulnerability in Parkinson’s disease. Journal of Neural Transmission 1997;50(Suppl):79-88.

Future Activities:

A third subchronic study is planned to commence on July 12, 2004, with ApoE-/- and ApoE-/-, LDLr-/- mice implanted with transmitters. We will attempt to monitor the EKG parameters for longer than the 6-month period of the Summer 2003 Subchronic Study.


Journal Articles on this Report : 8 Displayed | Download in RIS Format

Other subproject views: All 11 publications 11 publications in selected types All 11 journal articles
Other center views: All 111 publications 100 publications in selected types All 88 journal articles
Type Citation Sub Project Document Sources
Journal Article Chen LC, Hwang JS. Effects of subchronic exposures to concentrated ambient particles (CAPs) in mice. IV. Characterization of acute and chronic effects of ambient air fine particulate matter exposures on heart-rate variability. Inhalation Toxicology 2005;17(4-5):209-216. R827351 (Final)
R827351C013 (2003)
R827351C013 (Final)
  • Abstract from PubMed
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  • Journal Article Chen LC, Nadziejko C. Effects of subchronic exposures to concentrated ambient particles (CAPs) in mice: V. CAPs exacerbate aortic plaque development in hyperlipidemic mice. Inhalation Toxicology 2005;17(4-5):217-224. R827351 (2003)
    R827351 (Final)
    R827351C013 (2003)
    R827351C013 (Final)
  • Abstract from PubMed
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  • Journal Article Hwang J-S, Nadziejko C, Chen LC. Effects of subchronic exposures to concentrated ambient particles (CAPs) in mice: III. Acute and chronic effects of CAPs on heart rate, heart-rate fluctuation, and body temperature. Inhalation Toxicology 2005;17(4-5):199-207. R827351 (2003)
    R827351 (Final)
    R827351C013 (2003)
    R827351C013 (Final)
  • Abstract from PubMed
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  • Journal Article Lippmann M, Gordon T, Chen LC. Effects of subchronic exposures to concentrated ambient particles (CAPs) in mice: I. Introduction, objectives, and experimental plan. Inhalation Toxicology 2005;17(4-5):177-187. R827351 (Final)
    R827351C013 (2003)
    R827351C013 (Final)
  • Abstract from PubMed
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  • Journal Article Lippmann M, Gordon T, Chen LC. Effects of subchronic exposures to concentrated ambient particles in mice: IX. Integral assessment and human health implications of subchronic exposures of mice to CAPs. Inhalation Toxicology 2005;17(4-5):255-261. R827351 (2003)
    R827351 (Final)
    R827351C013 (2003)
    R827351C013 (Final)
  • Abstract from PubMed
  • Full-text: Semantic Scholar-Full Text PDF
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  • Abstract: Taylor and Francis-Abstract
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  • Journal Article Maciejczyk P, Zhong MH, Li Q, Xiong J, Nadziejko C, Chen LC. Effects of subchronic exposures to concentrated ambient particles (CAPs) in mice: II. The design of a CAPs exposure system for biometric telemetry monitoring. Inhalation Toxicology 2005;17(4-5):189-197. R827351 (2003)
    R827351 (Final)
    R827351C013 (2003)
    R827351C013 (Final)
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  • Journal Article Maciejczyk P, Chen LC. Effects of subchronic exposures to concentrated ambient particles (CAPs) in mice: VIII. Source-related daily variations in in vitro responses to CAPs. Inhalation Toxicology 2005;17(4-5):243-253. R827351 (Final)
    R827351C013 (2003)
    R827351C013 (Final)
  • Abstract from PubMed
  • Abstract: Taylor and Francis-Abstract
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  • Journal Article Veronesi B, Makwana O, Pooler M, Chen LC. Effects of subchronic exposure to concentrated ambient particles: VII. Degeneration of dopaminergic neurons in Apo E-/-mice. Inhalation Toxicology 2005;17(4-5):235-241. R827351 (Final)
    R827351C013 (2003)
    R827351C013 (Final)
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  • Abstract: Informa healthcare-Abstract
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  • Supplemental Keywords:

    thoracic particles, PM10, fine particles, PM2.5, ultrafine particles, PM0.1, lung dosimetry models, human exposure models, pulmonary responses, cardiovascular responses, immunological responses, criteria air pollutants, concentrated ambient aerosols, aerosol, air pollutants, air pollution, airborne pollutants, airway disease, airway inflammation, airway variability, allergen, ambient air, ambient air quality, analytical chemistry, assessment of exposure, asthma, asthma morbidity, atmospheric monitoring, biological markers, childhood respiratory disease, children, combustion, combustion contaminants, combustion emissions, compliance monitoring, dosimetry, epidemiology, exposure, exposure and effects, health effects, heart rate variability, human exposure, human health, human health effects, incineration, lead, lung, mercury, morbidity, particulates, pulmonary, pulmonary disease, respiratory,, RFA, Health, PHYSICAL ASPECTS, Scientific Discipline, Air, ENVIRONMENTAL MANAGEMENT, particulate matter, Environmental Chemistry, Health Risk Assessment, Risk Assessments, Physical Processes, Environmental Monitoring, Risk Assessment, ambient air quality, atmospheric particulate matter, particulates, air toxics, atmospheric particles, chemical characteristics, toxicology, ambient air monitoring, acute lung injury, PM 2.5, long term exposure, airborne particulate matter, environmental risks, exposure, epidemelogy, air pollution, aerosol composition, atmospheric aerosol particles, human exposure, PM, exposure assessment

    Relevant Websites:

    http://www.med.nyu.edu/environmental/centers/epa/ Exit

    http://www.neuroscienceassociates.com Exit

    Progress and Final Reports:

    Original Abstract
  • 1999
  • 2000
  • 2001
  • 2002
  • 2004
  • Final Report

  • Main Center Abstract and Reports:

    R827351    EPA NYU PM Center: Health Risks of PM Components

    Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
    R827351C001 Exposure Characterization Error
    R827351C002 X-ray CT-based Assessment of Variations in Human Airway Geometry: Implications for Evaluation of Particle Deposition and Dose to Different Populations
    R827351C003 Asthma Susceptibility to PM2.5
    R827351C004 Health Effects of Ambient Air PM in Controlled Human Exposures
    R827351C005 Physicochemical Parameters of Combustion Generated Atmospheres as Determinants of PM Toxicity
    R827351C006 Effects of Particle-Associated Irritants on the Cardiovascular System
    R827351C007 Role of PM-Associated Transition Metals in Exacerbating Infectious Pneumoniae in Exposed Rats
    R827351C008 Immunomodulation by PM: Role of Metal Composition and Pulmonary Phagocyte Iron Status
    R827351C009 Health Risks of Particulate Matter Components: Center Service Core
    R827351C010 Lung Hypoxia as Potential Mechanisms for PM-Induced Health Effects
    R827351C011 Urban PM2.5 Surface Chemistry and Interactions with Bronchoalveolar Lavage Fluid (BALF)
    R827351C012 Subchronic PM2.5 Exposure Study at the NYU PM Center
    R827351C013 Long Term Health Effects of Concentrated Ambient PM2.5
    R827351C014 PM Components and NYC Respiratory and Cardiovascular Morbidity
    R827351C015 Development of a Real-Time Monitoring System for Acidity and Soluble Components in Airborne Particulate Matter
    R827351C016 Automated Real-Time Ambient Fine PM Monitoring System