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The relationship of particulate matter retention in the lung to the severity of chronic obstructive pulmonary… Ling, Sean Hilton 2009

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THE RELATIONSHIP OF PARTICULATE MATTER RETENTION IN THE LUNG TO THE SEVERITY OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE  by SEAN HILTON LING B.Sc., The University of Alberta, 2006  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE  in  THE FACULTY OF GRADUATE STUDIES  (Experimental Medicine)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  August 2009  © Sean Hilton Ling, 2009  Abstract Particulate matter (PM) deposited into the lung is removed predominantly by ciliary action of epithelial cells in the airways and by macrophages that phagocytose these particles in the peripheral air space. We hypothesizethat the particle load or burden in the lungs’ ofpatients with Chronic Obstructive Pulmonary Disease (COPD) are responsible for perpetuating the chronic inflammatory response in the lung ofsubjects with COPD (even after smoking cessation). Samples were selected to cover the whole range of severity of COPD. Quantitative histological methods were used to quantif’ and characterize the particle burden in the lung tissue. The volume fraction (Vv) of PM in the lung tissue, including the parenchyma, airways, alveolar macrophages, blood vessels, and lymphoid follicles was determined using the aforementioned methods. To determine the chemical composition of the PM, Raman spectroscopy was used to analyze samples in situ. PM could be found in virtually all compartments of the lung: the parenchyma, blood vessels, airways, lymphoid follicles, and alveolar macrophages. The total burden of PM in all tissues of the lung was higher in subjects with COPD compared to controls  (p<O.OO1) as well as in smokers with normal lung function (p<O.O1). There was an incremental increase in PM with increased COPD severity that peaks at GOLD 2 and then falls off in the GOLD 3/4 group. These fmdings were very similar in analysis to the lung parenchyma, but the same relationship was not found in the blood vessels and lymphoid follicles. An increase in lung PM burden correlated with a decline in /FVC and pack years smoking. The PM in the lung tissue was found to have a 1 FEV similar Raman spectrum to that of carbonaceous soot. 11  We conclude that PM is retained in the lung of COPD subjects. Whether just the burden of exposure or whether poor clearance of PM from the lungs is responsible, remains unclear from our data. We speculate that this retained PM could perpetuate the chronic inflammatory response in the lung and contribute to the progression of COPD.  111  Table of Contents Abstract  .  ii  Table of Contents  iv  List of Tables  vii  List of Figures  viii  Acknowledgements  xi  Dedication  xii  1  Chapter One: Chronic Obstructive Pulmonary Disease 1.1 Definition 1.1.1 COPD Severity Categories Burden of COPD 1.2.1 Prevalence 1.2.2 Morbidity and Mortality 1.2.3 Economic and Social Costs 1.3 Risk Factors 1.3.1 Smoking 1.3.2 Air Pollution 1.3.3 Occupational Exposure 1.3.4 Gender 1.3.5 Genetics 1.3.6 Infections 1.4 Pathology of COPD 1.4.1 Pathogenesis 1.4.2 Pathophysiology 1.4.3 Exacerbations 1.2  2  Chapter Two: Particulate Matter 2.1 Definition 2.1.1 ParticleSize 2.1.2 Composition 2.2 Sources of Particles 2.2.1 Coal 2.2.2 Petroleum 2.2.3 Traffic 2.2.4 Biomass 2.3 Epidemiology  2 3 3 5 6 7 7 7 8 9 9 10  11 11 15 18 20 20 20 22 22 22 23 24 24  Deposition and Clearance of PM from the Lung  26 28  2.4.1 Deposition 2.4.2 Clearance 2.5 Mechanisms of PM-induced Lung Inflammation 2.5.1 AM Response 2.5.2 Lung Epithelial Cell Response 2.5.3 PM-induced Lung Inflammation  28 29 31 31 32 33  2.4  3  1 1  Chapter Three: Research Working Hypothesis  3.1  35 35 iv  3.2  Specific Aims  .36  4  Chapter Four: Materials and Methods 4.1 Sample Selection 4.1.1 iCapture BioBank and Patient Enrollment 4.1.2 Tissue Specimen Collection 4.1.3 Lung Tissue Processing and Preparation 4.1.4 Sectioning of Lung Tissue Cores 4.2 Histology 4.3 Stereology 4.3.1 Concepts 4.3.2 Equipment and Software 4.3.3 Image Capture Protocol 4.3.4 Statistical Analysis 4.4 Gene Expression 4.4.1 Concepts and Rationale 4.4.2 RNA Isolation and Assessment 4.4.3 Amplified cDNA 4.4.4 Quantitative Polymerase Chain Reaction 4.4.5 Gelatin Zymography 4.4.6 Statistical Analysis 4.5 Raman Microspectroscopy 4.5.1 Concepts 4.5.2 Rationale 4.5.3 Equipment and Software 4.5.4 Microscope Protocol  38 38 38 39 42 43 44 46 46 49 50 53 55 55 56 56 57 57 58 59 59 60 61 62  5  Chapter Five: Results 5.1 Total Lung Burden 5.1.1 Observations 5.1.2 Comparison to Clinical and Histological 5.1.3 Comparison to mRNA Expression 5.2 Alveolar Wall 5.2.1 Comparison to Clinical and Histological 5.2.2 Comparison to mRNA Expression 5.3 Blood Vessel Burden 5.3.1 Comparison to Clinical and Histological 5.3.2 Comparison to mRNA Expression 5.4 Lymphoid Follicle Burden 5.4.1 Comparison to Clinical and Histological 5.5 Alveolar Macrophage Burden 5.5.1 Comparison to Clinical and Histological 5.6 Raman Spectroscopy  65 65 65 67 71 71 71 75 76 76 83 86 86 90 90 93  6  Chapter Six: Discussion and Conclusion 6.1 PM Burden in the Lung 6.1.1 AllTissue 6.1.2 Alveolar Wall 6.1.3 Blood Vessels 6.1.4 Lymphoid Follicles 6.1.5 Alveolar Macrophages 6.2 Raman Spectroscopy  Data  Data  Data  Data Data  94 94 94 96 96 98 98 98 V  6.3  Conclusion  .100  References  .102  Appendix  115  vi  List of Tables 2 Table 1 Classification of COPD based on spirometry as outlined in the GOLD report. vital capacity forced FVC: in 1 second. FEV,: forced expiratory volume  19  ’ 2 Table 2 Causes of COPD exacerbations’ Table 3 List of cases with accompanying clinical data, NS NA = not available  3  =  non-smoker, ND  =  not done, 40  Table 4 List of wound-healing genes in COPD  58  Table 5 Correlation of PM burden in all compartments of the lung with clinical and histological values  69  Table 6 Correlation of the PM burden in the alveolar wall with clinical and histological 73 values Table 7 Correlation of the PM burden in the blood vessel wall with clinical and histological values  78  Table 8 Correlation of blood vessel wall thickness and clinical and histological values..81 Table 9 Correlation of mRNA expression with blood vessel wall thickness  84  Table 10 Correlation of the PM burden in the lymphoid follicles with clinical and histological values  87  Table 11 Correlation of the PM burden in the alveolar macrophages with clinical and histological values  91  Table 12 List of Abbreviations  115  vii  List of Figures .15  77 Figure 1 Inflammatory mechanisms in COPD 77 Figure 2 Mechanism of airflow limitation in COPD  16  ° 8 Figure 3 Possible mechanisms for systemic effects of COPD  18  133 Figure 4 Relative contributions of PM by mass  21  10 exposure Figure 5 Association between FEV 1 (L) or COPD (R) and long-term PM (five-year mean). Data points are means of each place and year of study  28  203 Figure 6 Possible mechanism for PM-induced C0PD  36  Figure 7 Steps in lung tissue preparation and sampling. A) Lung inflated with Cryomatrix and saline B) Lung frozen over liquid nitrogen vapours C) Meat saw D) Hole saw E) 43 Lung slice with missing lung cores F) Frozen lung core Figure 8 A) Cropped digital image of alveolar wall tissue stained with H&E at 20x objective magnification. B) Example of black pigment in the H&E stained tissue at 44 20x objective magnification Figure 9 A cartoon depicting how as the magnification increases, it decreases (by great 46 206 amount) the proportion of the object being studied Figure 10 The hierarchical nature of sampling in microscopy. The need for uniformly 48 206 random sampling is paramount to make an accurate and precise estimate. Figure 11 A) Coarse grid (196 points) overlaid onto digital image of tissue. B) Fine grid 49 (1500 points) overlaid onto digital image of tissue at 20x magnfication 50  Figure 12 Fields of view excluded (red) and included (green) in this study  Figure 13 Steps in the program for the automated blood vessel analysis. A) Inner lumen traced. B) Inner lumen area quantified (in pixels). C) Al D) Perimeter of adventitia traced. E) Black pigment quantified (in pixels) within the perimeter of the adventitia. 52 F)A5 Figure 14 Tissue samples sectioned and melted onto aluminum foil wrapped around uncoated glass slide for Raman microspectroscopy use  62  Figure 15 Images captured from light microscope of the Raman system. A) The lighter colour is tissue, whereas the deep black pigment was the object of interest. B) The crosshairs would indicate the exact point where the laser would strike the tissue. .63 . .  Figure 16 PM (black pigment) can be found in (A) the parenchyma, (B) alveolar macrophages, (C) airway wall, (D) blood vessel wall, and (E) lymphoid follicles.. .66  viii  Figure 17: PM burden in non-smokers with normal lung function and those with COPD (L) and the PM burden in smokers with normal lung function (GOLD 0) and those 67 with abnormal lung function (GOLD 1-4) (R) Figure 18 Vv of PM in all lung tissues across non-smoking controls and groups of increasing COPD severity. Non-smoking controls and GOLD 2 groups were significantly different (p<0.05)  68  Figure 19 Burden of PM with increasing levels of COPD severity  69  /FVC B) vs. FEV 1 1 C) vs. Lm D) vs. airway Figure 20 Vv of PM in all tissue A) vs. FEV 70 wall thickness B) vs. age F) vs. pack years Figure 21 Vv of PM in all tissue vs. expression of FGG in the parenchyma  71  Figure 22 Vv of PM in the alveolar wall across the non-smoking group and the COPD 72 severity groups /FVC B) vs. FEV 1 1 C) vs. Lm D) vs. Figure 23 Vv of PM in the alveolar wall vs. A) FEV 74 airway wall thickness B) vs. age F) vs. pack years. AlvWall = Alveolar wall Figure 24 Vv of PM in all lung tissue vs. Vv of PM in the alveolar wall  75  Figure 25 Vv of PM in the alveolar wall vs. expression of FGG in the alveolar wall  76  Figure 26 Vv of PM in the blood vessel walls across the non-smoking group and the COPD severity groups  77  1 C) vs. Lm D) /FVC B) vs. FEV 1 Figure 27 Vv of PM in the blood vessel wall A) vs. FEV 79 vs. airway wall thickness E) vs. age F) vs. pack years Figure 28 A) Vv of PM in all lung tissue vs. Vv of PM in the blood vessel wall B) Vv of 80 PM in parenchyma vs. Vv of PM in the blood vessel wall Figure 29 PM area in the blood vessel vs. the wall area of the blood vessel  81  1 C) vs. Lm D) /FVC B) vs. FEy 1 Figure 30 Blood vessel wall area thickness A) vs. FEV 82 vs. airway wall thickness E) vs. age. F) vs. pack years Figure 31 A) Vv of PM in all lung tissue vs. blood vessel wall area thickness B) Vv of 83 PM in parenchyma vs. blood vessel wall area thickness Figure 32 Blood vessel wall area thickness A) vs. IL-4 B) vs. IL-13 C) vs. PDGFRB D) 85 vs. TGFB1 E) vs. TNF F) vs. VEGF Figure 33 Vv of PM in the lymphoid follicles across COPD severity groups  86  1 C) vs. Lm D) /FVC B) vs. FEy 1 Figure 34 Vv of PM in lymphoid follicles A) vs. FEV 88 vs. airway wall thickness E) vs. age F) vs. pack years  ix  Figure 35 Vv of PM in the lymphoid follicles vs. A) blood vessel thickness, B) Vv of PM in the blood vessel wall, C) Vv of PM in the parenchyma, and D) Vv of PM in all tissue 89 Figure 36 Vv of PM in alveolar macrophages across the non-smoking and COPD severity groups 90 1 C) vs. Lm Figure 37 Vv of PM in alveolar macrophages A) vs. FEV /FVC B) vs. FEy 1 92 D) vs. airway wall thickness E) vs. age. F) vs. pack years Figure 38 Raman spectra of Case 1984  93  x  Acknowledgements First and foremost, I would like to thank my supervisor, Dr. Stephan van Eeden, for his dedication and valued advice in my career as a scientist. His thoughts and presence have helped me through both good and challenging times in my work. Secondly, I would like to thank Dr. James Hogg, who I have worked with as a summer student before I began my undergraduate education and for giving me the opportunity to work in a world-renowned research centre summer after summer, later recommending me to Dr. van Eeden for graduate studies. I would also like to thank my other committee members: Dr. Shizu Hayashi, who supervised me through a directed studies course as a graduate student, and has offered excellent advice and constructive criticism of my methodology and writing skills and Dr. Harvey Coxson who has also offered guidance on this project. I would like to take this opportunity to thank some of the staff and students in the lab. John McDonough has always been willing to help me with my project and offer advice at any time as a colleague, and as a friend. Dr. Mark Elliott and Crystal Leung have offered their invaluable expertise in the histology side of my project. My Raman spectroscopy experiments would not have been possible with the generous donation of time at the Michael Smith Laboratories, and I thank Drs. Michael Blades and Robin Turner, as well as, Kadek Okuda for their help on my project. I would also like to thank my parents, Dr. Hilton and Elizabeth Ling, and my sister, Dr. Bernice Ling, for their unwavering support in all my endeavours.  xi  To Mom, Dad, and Bernice  xli  1  Chapter One: Chronic Obstructive Pulmonary Disease  1.1  Definition  Chronic obstructive pulmonary disease (COPD) is clinically defined as “a respiratory disorder” caused by the inhalation of noxious gasses and particulate matter predominantly from cigarette smoking “and is characterized by progressive partial reversible airways obstruction, lung hyperinflation, systemic manifestations and increasing frequency and severity of exacerbations.” Pathologically, COPD is typically a combination of small airways disease (obstructive bronchiolitis) and parenchymal 2 Both parts of the disease make a varying contribution destruction (emphysema). depending on the individual; but, ultimately, result in the clinical hallmark of COPD: 3 This airflow limitation is airflow limitation that is not or just partially reversible. typically progressive, and combined with the presence of the continuing inflammation, results in structural changes and narrowing of the airways, and the destruction of the parenchyma. These changes results in the reduction of alveolar connections to the 2 airways and loss of elastic recoil. Although these pathological changes are lung-specific, there are a significant number of systemic manifestations such as nutritional abnormalities, weight loss, skeletal 5 which act as co-morbidities ’ 4 muscle dysfunction, and cardiovascular complications 6 As mentioned previously, the course of COPD varies from impacting disease prognosis. individual to individual, but is generally progressive in nature, particularly if exposure to 2 However, if that exposure is removed, the deleterious particles and gases is maintained.  1  result can be an improvement in lung function and may even halt the progression of the disease. 1.1.1  COPD Severity Categories  With the limitation of airflow being a pillar of the disease, spirometry is the best 2 Spirometry is the technique measurement because of its availability and reproducibility. to measure the flow and volume of air an individual can inhale and exhale. The report from the GOLD (Global Initiative for Chronic Obstructive Lung Disease) Scientific Committee suggests that the severity of COPD should be delineated into 4 stages based )•2 on the individual’s spirometric results (Table 1 Firstly, Stage I is characterized by mild  airflow limitation, possibly with symptoms of a chronic cough and sputum production, and typically the individual is not aware that his lung function is abnormal. Stage II is characterized by deteriorating airflow limitation, shortness of breath after exercise, symptoms of chronic cough and sputum production, and usually a need to seek medical attention because of the symptoms or some form of exacerbation of the disease. Stage III is characterized by poorer airflow limitation, increased incidences of shortness of breath, poor exercise ability, fatigue, and exacerbations that severely affect the individual’s quality of life. Finally, Stage IV is characterized by the most severe airflow limitation and respiratory failure resulting in frequent exacerbations that are potentially fatal. A group that was previously mentioned in earlier GOLD Reports, Stage 0, who were labeled “at risk” for COPD, but had normal lung function, are no longer included as there was inconclusive evidence that they would progress to Stage I.  2  Table 1 Classification of COPD based on spirometry as outlined in the GOLD 2 FEV report. : forced expiratory volume in 1 second. FVC: forced vital capacity. 1  Stage  Severity  Spirometry  I  Mild  /FVC 1 FEV  <  0.70, FEV1  II  Moderate  /FVC 1 FEV  <  0.70, 50 %  1 FEy  <  80% predicted  III  Severe  /FVC 1 FEV  <  0.70, 30 %  1 FEV  <  50% predicted  Very  /FVC 1 FEV  <  0.70, FEV 1  severe  +  80% predicted  <  1 30% predicted or FEy  <  50% predicted  IV chronic respiratory failure  1.2  Burden of COPD  1.2.1  Prevalence  The prevalence of COPD worldwide is estimated to be around 1% of the population across all age groups, but rises dramatically to 9-10% among those 40 years or 7 From the years 1970 to 2002, the death rates doubled from 21.4 to 43.4 (rates per older. 8 In a large meta-analysis by Halbert et 100,000 people, age-adjusted) in the United States. 9 COPD prevalence significantly increases in sub-groups of smokers (15.4%), males al., (9.8%), and people living in urban settings (10.2%). As COPD is a worldwide problem, major studies looking at the prevalence of the disease have been conducted outside of North America. The Latin American Project for the Investigation of Obstructive Lung Disease (PLATINO), made up of Brazil, Chile, Mexico, Uruguay, and Venezuela, found 3  that Stage I COPD increases strongly with age and found distinct prevalence differences (18.4% to 32.1%) between countries.’ 0 Another study looking at twelve Asia-Pacific countries, found that the overall prevalence rate was much lower at 6.3%. Surprisingly, mild forms and even severe forms of COPD go undiagnosed even though spirometers are relatively inexpensive and usually readily available. Populationbased studies confirm that COPD suffers from a lack of treatment and diagnoses, which has been a prevalent and historical belief in the scientific  12  Unfortunately,  the morbidity, mortality, and the cost of this particular disease goes neglected compared to other diseases and therefore, the true burden of the disease goes relatively unnoticed by healthcare providers. 7 On the other hand, this group of individuals may be the most important, as they are usually those that require healthcare services and therefore generate relevant costs. 2 One of the major studies to disseminate a standard set of techniques and measurements was the Burden of Obstructive Lung Disease Initiative 3 The rationale behind BOLD was to develop a set of methods and practices for (BOLD).’ measuring the prevalence of COPD to act as a framework available to help train, maintain quality control, and provide data analysis. However, the prevalence of COPD is made more difficult by the heterogeneity in measurements of COPD severity. ’ 9  14  Diagnostic definitions can vary between locations  9 Although taking spirometry and usually underestimate the prevalence of the disease. measurements is convenient and inexpensive, there is variation in the administration of the lung function test and different applications of quality control. In addition, as the 5A severity of the disease increases, the reproducibility of the measurements decreases.’ 6 showed that using the various standards for measurement of study by Viegi et al.,’  4  COPD from the American Thoracic Society (ATS) and the European Thoracic Society (ETS) would result in a range of 11-57% when describing obstruction. In summary, it seems that all forms of measurement, which could include doctor diagnosis, patientreported diagnosis, or spirometric measurements all affect the reporting of COPD 4 Ultimately, measurements of COPD prevalence benefit having consistent, prevalence.’ reproducible, and standardized techniques. 1.2.2  Morbidity and Mortality  Morbidity is defined as another term for the presence of illness or disease and is typically measured in hospital (including the need for hospitalization) and physician 2 However, with increasing age, an individual afflicted with COPD is likely to have visits. other diseases at the same time, known as co-morbidities. 6 These co-morbidities act as further challenges to the individual and healthcare system, but may only be related indirectly to COPD. 2 The problem with looking at morbidity resides in the health care system itself, as the rates of hospitalization are based on the ability of the hospital to provide beds. Mortality, on the other hand, is defined as the fatal outcome of the morbidity. The lack of diagnosis and reporting of the disease also influences mortality information. However, the burden of the disease is undeniable. COPD, as one of the fastest growing chronic diseases in the developed and developing world, is an extremely important public health problem.’ 7 This disease has been projected to be the mortality and the  th 5  rd 3  leading cause of total  leading cause of disability by 2020.18, 19 In economically developed  countries, this disease is the  th 4  leading cause of death.’ 8 As the population ages and  5  smoking continues to spread across age groups, the mortality resulting from COPD will 20 It has been shown that COPD causes almost as many deaths as HIV/AIDS. increase. ’ 2 1.2.3  Economic and Social Costs  So far, few studies have looked at the relative contributions of the direct and indirect costs of COPD outside of the European Union and North America. 22 Direct costs are defined as being related to the diagnosis, treatment, and prevention of the given 7 Indirect costs, on the other hand, account for the morbidity and mortality of the disease. disease and also typically evaluate the reduction in national production. According to a study by Jemal et al., 8 the direct costs of COPD were 18 billion USD and indirect costs accounted for 14.1 billion USD. Although asthma is arguably more studied, it is less prevalent than COPD in adults, and shows in the related health care costs due to a greater amount of hospitalizations. 7 An important point brought up by the GOLD Report is that all these costs are attributed to services in the hospital, and does not take into account the 23 ’ 2 monetary value of the care given by family members and in-home caregivers. However, the financial burden is not the only cost of this disease. Disability Adjusted Life Years (DALYs) are defined as the sum of years lost due to premature mortality and years dealing with the disability.’ 8 From 1990, where COPD was the leading cause of DALYs in the world, the disease is projected to be the  th 5  th 12  leading cause  of DALYs in 2020.  6  1.3  Risk Factors  1.3.1  Smoking  The single greatest risk factor for COPD is cigarette smoking, be it either passive or ’ 2 active. 2 4 COPD mortality can be predicted by a number of smoking-related 5 23 It factors: age of starting smoking, total pack years smoked, and current smoking status. 26 Studies has been shown that 80-90% of COPD mortality is related to tobacco smoking. in China and Japan have shown a dose-response relationship between the risk of 28 Smoking causes accelerated lung function ’ 27 developing COPD and active smoking. 23 To decline, and the frequency of smoking seems to adversely affect lung function. further this link, the cessation of smoking is associated with a return to the rate of decline of a normal, non-smoker. 26 Although many reviews and textbooks cite that only 15 to 20% of smokers go on 29 which is likely to develop COPD, this number is now considered a gross underestimate, ° 3 due to under-diagnosis of the disease. In fact, a study by Lundback and colleagues suggests that as much as 50% of elderly smokers have symptomatic COPD. Rennard and 29 state that nearly all smokers will probably meet the diagnostic criteria for the Vestbo disease. 1.3.2  Air Pollution  Past studies have shown an association between increased levels of outdoor air 32 Lung development ’ 31 pollution and the morbidity and mortality of respiratory diseases. in youth aged between 10 to 18 years was stunted by air pollution and by the time the  7  33 As a consequence of simply youth reached adulthood, their lung function was reduced. 34 showed that there were around banning the sale of coal in Dublin, Ireland, Clancy et al. 116 fewer respiratory and 243 fewer cardiovascular deaths in the year following the ban. With respect to COPD, the prevalence rates of this disease rose in urban and polluted 3538 locations. Air pollution is not restricted to the outdoors. Indoor air pollution is of great 39 importance as the general population tends to spend the majority of their time indoors. Increasingly, biomass smoke from wood or coal burning heating elements in the 41 Not only do ’ 40 developing world, such as China, have become more of a problem. people spend more time indoors, a lack of ventilation may allow concentrations of indoor ° found that 4 23 Liu et al. air pollutants to accumulate and surpass outdoor concentrations. there was a significant association between exposure to biomass smoke and COPD. 1.3.3  Occupational Exposure  Exposure to many toxic chemicals and fumes, plus organic and inorganic dusts in 2 Using a Carcinogen Exposure (CAREX) database, some occupations can lead to COPD. which is based on data from the International Labour Organization (ILO), workplace airborne exposure was found to result in 318,000 COPD-related deaths (270,000 men and 42 Although, as stated before, cigarette smoking is the greatest 78,000 women). contributor to the development of COPD, occupational exposure can double the risk of 43 Using a population in having the disease, even when accounting for a smoking history. 44 found that subjects exposed to biological dusts had Australia, Matheson and colleagues an odds ratio (OR) risk of 2.7 of having COPD.  8  1.3.4  Gender  46 The ’ 45 So far, the role of gender as a risk factor for COPD remains elusive. disease has not been well-studied in women but since gender differences affect other diseases, this factor may have a significant impact on the diagnosis and management of 45 smoking seemed to negatively affect women more than 46 In a study by Xu et al., COPD. men. Looking at prevalence data on morbidity and mortality, more men than women typically have the disease; but, over the past 20 years, COPD prevalence has increased 47 This could partly be due to the fact that in developing countries, the quickly in women. number of women smokers continues to grow, expected to reach 20% by 2025.48 According to Soriano et al., 49 COPD prevalence in men plateaued in the 1990’s, but increased greatly in women older than 65 in the United Kingdom. 1.3.5  Genetics  Perhaps the primary example of COPD as a product of a genetic disorder is the alpha (al)-antitrypsin deficiency, which is both common and under-recognized by ° The protective role of a 1 -antitrypsin is to react with neutrophil elastase in the 5 doctors. lung to reduce the elastolytic burden in the lower airways. Typically, the mutation occurs in the SERPINA1 gene and results in a reduction of al-antitrypsin serum levels, which ’ and liver damage. This disorder accounts 5 increases the risk for panlobular emphysema for 1-3% of patients with COPD. Other genes have been targeted in COPD, including 53 transforming growth factor-betal (TGF-13 1),52 tumor necrosis factor-alpha (TNF-a), 54 as possible genetic risk factors. and microsomal epoxide hydrolase (mEPHX),  9  It also appears as if genetic factors play a role in the susceptibility of developing 55 Kurzius-Spencer ’ 23 COPD (based on a decline of FEy ) in familial correlation studies. 1 and colleagues 56 suggested that there must be a genetic component linking smoking and 1 slopes were correlated more strongly in smoking siblings 1 because sibling FEV FEy than non-smoking siblings. Genetic association and linkage studies have provided conflicting evidence. This evidence suggests that the environment probably plays a large 58 ’ 57 role in regulation of genes leading up to the development of COPD. 1.3.6  Infections  In our lab, adenoviral infection has been shown to amplify the cigarette smoking59 and may also induced inflammation in alveolar epithelial cells in severe emphysema ’ have shown that respiratory viral infections 6 induce steroid resistance. ° Seemungal et al. 6 are associated with a greater frequency and severity of exacerbations of COPD. Several studies suggest that children who suffer severe respiratory infections go on to have 62 Even though the role of human reduced lung function and other respiratory ailments. immunodeficiency virus (HIV), a cause of primary or secondary inflammation in emphysema is unclear, there is a definite association between lung cytotoxic lymphocytes 64 COPD can sometimes occur after a ’ 63 and parenchymal destruction in these patients. 65 tuberculosis (TB) infection and is made worse by smoking.  10  1.4  Pathology of COPD  1.4.1  Pathogenesis  The most widely accepted hypothesis is that disease process starts in the lung with 2 This results in a lung inflammation, which the inhalation of noxious gases and particles. is a normal response, but this response is amplified in individuals with COPD. Inflammatory Cells in COPD Polymorphonuclear leukocytes (PMNs) Neutrophils may contribute to parenchymal destruction by releasing serine proteases, such as, neutrophil elastase, cathepsin G and proteinase-3, and matrix metalloproteinases (MMP) -8 and  9•66  This type of cell’s role is not clear in COPD, but  there is an definite association between an increase in circulating neutrophils and a decline in lung function. 67 While the neutrophil’s role remains unclear, the macrophage 69 ’ 68 can be held responsible for most of the features of the disease. Macrophages In COPD, the numbers of macrophages increase dramatically in the parenchyma, 66 The inflammatory mediators the airways, and bronchial alveolar lavage (BAL) fluid. macrophages release indicate a cellular link to COPD, and these secretions are even 7 Alveolar macrophages ’ 70 greater than those from macrophages of normal smokers. exposed to ambient air pollution also release pro-inflammatory cytokines, such as TNF a, interleukin (IL) -6, IL-i , and others. 72 The increase in numbers of macrophages could be due to monocyte recruitment, but also due to increased propagation and longer 66 Although macrophages are meant to play a role in defense via the survivability.  11  mechanism of phagocytosis, when this mechanism is impaired in COPD, it could result in increased bacterial or particle burden in the lung. Lymphocytes The total number T-lymphocytes are also higher in the parenchyma and airways. CD8+ T cells have the ability to cause apoptosis of alveolar epithelial cells resulting in 73 It is likely that dendritic cells play an important role in COPD, as they are emphysema. a key cell in the activation of other, previously mentioned, cells, such as, macrophages, neutrophils, and T-lymphocytes. 74 Increased numbers of eosinophils have been found in 7 Finally, epithelial unclear. 7 ’ acute exacerbations of COPD, 76 but their role is still 66 ’ 75 cells can be activated by cigarette smoke and secrete various inflammatory mediators and 66 proteases. Inflammatory Mediators in COPD Cytokines Studies have shown that proinflainmatory cytokine production increases with 79 This increase in cytokine production leads to ’ 78 small changes in ambient air pollution. an increase in acute-phase protein production and leukocyte release from the bone ’ and 8 80 TNF-a is found in large quantities in the sputum in patients with COPD marrow. activates nuclear factor kappa-light-chain-enhancer of activated B cells (NF-icB), which in turn, activates epithelial cells and macrophages to secrete other cytokines, chemokines, 70 77 IL-i acts similarly to TNF-cL and is a powerful macrophage activator. and proteases. A number of other interleukins are considered to be mediators involved in COPD, including IL-6, 9, 10, 12, 13, and 17. Granulocyte-macrophage colony stimulating factor (GM-CSF) levels are above normal in COPD and increase substantially during  12  82 Expression of interferon-gamma (IFN-y) is also elevated in exacerbations in BAL. 83 emphysema. Chemokines 84 and there are a Chemokines act together to determine an inflammatory response few known chemokines that play a role in COPD via the recruitment of inflammatory 85 A chemoattractant of neutrophils, IL-8, has shown increased levels that correlate cells. ’ and even more so in individuals with al-antitrypsin 8 with neutrophil numbers in COPD 86 Alveolar macrophages secrete IL-8 in larger quantities in COPD than deficiency. normal smokers 87 and neutrophils themselves secrete IL-8, which may cause a perpetual inflammatory state. 88 Growth-related oncogene-aipha (GRO-ct) is secreted by alveolar 89 and activates neutrophils, monocytes, macrophages and airway epithelial cells ° A number of other chemokines may have a role in the 9 basophils, and T-lymphocytes. disease process, including epithelial cell-derived neutrophil-activating peptide-78 (ENA 78), monocyte chemoattractant protein-i (MCP-i), and eosinophil-selective 77 chemokines. Growth Factors One of the hallmarks of COPD is structural change, and a growth factor, such as, ’ Epidermal growth factor 9 TGF-131 could be a part of the fibrosis process in COPD. 92 and could therefore be a target for therapeutic (EGF) regulates mucus secretion intervention. Vascular endothelial growth factor (VEGF), part of pulmonary vascular remodeling, has increased expression in mild and moderate COPD but suppressed 93 Fibroblast growth factor (FGF) also plays a role in expression in severe COPD. 94 pulmonary vascular remodeling.  13  Proteases Proteases are known to degrade components of connective tissue and elastin 77 In a 1 -antitrypsin degradation is presumed due to a loss of elastic recoil in the lung. , but its role has yet to be 95 disorder, NE can induce emphysema in animal models clarified pending the results of clinical, human trials with NE inhibitors. MMPs regulate extracellular matrix (ECM) degredation 96 and an increasing body of evidence suggests 98 97 and lung function decline. that they play a vital role in emphysema Reactive oxygen species (ROS) Oxidative stress seems to play an important role in COPD by amplifying the 77 Much evidence exists for the increased oxidative stress in inflammation and destruction. patients. 100 ROS activates NF-icB,’°’ constricts airway smooth ’ the lungs of COPD 99 77 and induce 02 may reduce the anti-inflammatory effect of corticosteroids, muscle,’  Other mediators 2 and F Lipid mediators, such as, prostaglandin (PG) E a, thromboxane, 2 77 Nitric oxide leukotrienes, and platelet-activating factor (PAF) also play a role in COPD. (NO) can be expressed in greater quantities by macrophages and in the lung parenchyma in COPD. Peptide mediators, such as endothelins, bradykinin, tachykinins, and complement fragments may play a role in the progression of COPD. An overview of the entire process can be found in Figure 1.  14  77 Figure 1 Inflammatory mechanisms in COPD Cigarette Smoke  / Epithelial Cells  Alveolar Macrophages  .4,  TGF-bcta Fibroblast  Chemotactic fictors, I L-8, chernokincs  Neutrophil  CD$± lymphocyte  \ Fibrosis  1.4.2  PROTEASES  Emphysema  Neutrophil clastases. MMPs  Chronic bronchitis  Pathophysiology  Airflow limitation is thought to be a result of narrowing of the small airways (Figure 2), emphysema, and mucus plugging in the luminal spaces, each playing a role in COPD. However, the relative contributions of each of these processes are still unclear and depend on the disease stage. Chronic bronchitis Chronic bronchitis is a condition that arises from mucus hypersecretion, but also stems from epithelial structural changes, airway inflammation, bronchial mucus glands, 104 This condition is typically associated with the and smooth muscle hypertrophy. 5 Most of all though, mucus hypersecretion is epithelium of the central airways.’°  15  characteristic of chronic bronchitis.’° 4 Data suggests that mucus hypersecretion is associated with airway obstruction, 106 but this is Figure 2 Mechanism of airflow limitation in COPD 77 Normal  Disease State  1’  4. Airway held open by alveolai attahinents  (I  (I Loss of alveolar attachments Mucous hypersecretion and obstruction of lumen  Small airways obstruction For some time now, it has been shown that there is a marked narrowing of the , they concluded that 0 small airways in 8 COPD.’° 109 In a study by Hogg and colleagues” ’ this obstruction is due to a remodeling process that is both a product of tissue repair and a malfunction of mucociliary clearance. Although poorly understood, the fibrosis of the Ogg, the peripheral airways are i airways is likely a repair mechanism. 66 According to 1 the major source of increased airway resistance due to airway narrowing and airway closure. Some studies suggest that mucus plugging in small airways causes airflow 2 In addition, the presence obstruction, but these findings could be a postmortem artifact.”  16  of lymphoid follicles in between the smooth muscle and lumen will reduce the functional lumen area. Emphysema Emphysema, by definition, is the enlargement of the alveolar space.” 3 Both types 4 of emphysema, panacinar and centrilobular, may be present in the lungs of smokers.” Panacinar emphysema is usually seen in al-antitrypsin deficiency, whereas, centrilobular emphysema is found in cigarette smokers.’° 4 The reason for tissue destruction can be attributed to an uncontrolled inflammatory response and a protease/antiprotease imbalance. Ultimately, this leads to a loss of elastic recoil in the lung and a decline in lung function and FEy,. Systemic effects Although COPD is a pulmonary disease, it is associated with extrapulmonary ’ “ The “spillover effect” from the pulmonary 5 effects on other organs and body systems. inflammation suggests that these inflammatory cells and mediators move into the systemic circulation (Figure 3)5 Markers of ROS increased significantly in the plasma of smokers and individuals with COPD.” 6 Circulating, activated inflammatory cells, such as, neutrophils and lymphocytes, and cytokines and acute phase proteins all contribute to the systemic inflammation. 5 In addition to this systemic inflammation, COPD patients suffer from weight loss and nutritional abnormalities. Weight loss is typically from the reduction of skeletal muscle mass 117 and nutritional abnormalities probably due to 18 Skeletal muscle dysfunction is increased basal metabolism with normal caloric intake.’ a common problem in COPD and likely due to two factors: loss of muscle mass and  17  dysfunction of remaining muscle. 5 Cardiovascular disease risk is increased by two to three times in patients with COPD  119  however, this mechanism remains unclear.  ° 8 Figure 3 Possible mechanisms for systemic effects of COPD Lung inflammation 0 PM Cigarette Smoke  IL-i, 6,8 TNF GM-CSF  Cells: • Macrophages • PMNs  Bone marrow  Liver  Acute phase proteins  Leukocytes, platelets Systemic inflammation 1.4.3  Exacerbations  Exacerbations for COPD are defined as a change in the disease state based on a patient’s dyspnea, cough, or sputum that requires some change in management and intervention. 120 The amount of exacerbations is known to increase as the disease severity , as well as the health care 22 121 and this impacts on a patient’s quality of life’ worsens, system. Increased dyspnea during an exacerbation is said to be due to hyperinflation, air trapping, and reduced expiratory flow.’ 23 Hypoxemia is also usually present during an 24 Etiologic factors exacerbation due to a deteriorating ventilation-perfusion mismatch.’ 18  that contribute to an exacerbation include viral infections, bacterial infections, and air pollution (Table  2).121  Table 2 Causes of COPD exacerbations’ ’ 2 Viruses  Bacteria  Pollutants  Rhinovirus  H influenzae  Nitrogen dioxide  Influenza  Spnuemoniae  Particulate matter  Parainfluenza  M catarrhalis  Sulphur dioxide  Coronovirus  Staphylococcus aureus  Ozone  Adenovirus  P aeruginosa  Respiratory syncytial virus Cpnuemoniae  Based on a number of epidemiological studies, air pollution (composed of sulfur dioxide, nitrogen dioxide, and particulate matter) has been shown to negatively affect 25 show an increase in hospital chronic respiratory 125 diseases. 126 Sunyer and colleagues’ ’ admissions during elevated periods of ambient air pollution. Diesel particles have been 29 with the suggestion that these particles cause ’ 127 implicated in a number of studies, 28 Possible mechanisms exist (explained increased production of IL-8 and GM-CSF.’ more fully in the following chapter) that show that increases in air pollution can cause not only exacerbations, but also affect the progression and development of COPD.  19  2  Chapter Two: Particulate Matter  2.1  Definition The Tyrolean Iceman, who lived before the beginning of recorded history 5,300  jg Biomass fuels O years ago, was found in 1991 and had carbon and dust retained his 3 have been used for centuries by man for cooking and heating.’ ’ Recently, however, due 3 to rapid urbanization, cigarette smoking, and a number of industrial combustion sources, humans have had to deal with a greater amounts and more complex forms of particles. Urban particulate matter (PM) has been implicated in a number of epidemiological studies to be associated with a number of adverse health effects.’ 32 Those with chronic lung diseases, such as COPD, are particularly susceptible to exacerbations associated with ambient PM. PM is typically defined in two ways: either by particle size or composition.  2.1.1  Particle Size  PM is most often classified by its size. Total suspended particle (TSP) is a term used to define the total amount of airborne particles.’ 34 Within TSP, the particles can ’ 32 be divided into smaller and smaller fractions. Particles greater than 30 im do not remain suspended in the air very long, when compared to the smaller fractions. These smaller fractions consist of PM 25 (fine) particles with an aerodynamic 10 (coarse) and PM diameter of less than 10 pm and 2.5 rim, respectively. The smallest, commonly described 5 is considered to . 2 , are less than 0.1 im and are known as ultrafine particles. PM PM , as 0 have the most toxic effect on the human respiratory tract for a number of reasons. Firstly, 20  although PM, 0 can penetrate into the lung, it is the fine and ultrafme fractions that are 35 able to penetrate deeper and into the alveolus. As described by Squadrito et al.,’ particles between 5-8 jim in diameter are deposited in the tracheobronichial region, whereas the particles between 1-5 jim in diameter are deposited in the respiratory bronchioles and alveoli. These findings have been confirmed by electron microscopy in a 36 who found that around 96% of the PM in lung parenchyma study by Churg and Brauer,’ was fine particles, whereas only around 5% was ultrafine particles. However, particles smaller than 5 jim remain airborne due to their diffusivity and settling velocities and can be exhaled out again. Finally, these fine particles have a greater surface area (more 34 It is also contact with tissue) and a porous surface (ability to adsorb toxic elements).’ important to note, that by definition, the larger fractions incorporate the smaller ones (Figure 4)133 Ultrafine particles are typically generated from combustion (automobile exhaust) and photochemical activity, whereas coarse particles are generated by 34 mechanical processes (non-combustible elements).’ 133 Figure 4 Relative contributions of PM by mass  Coarse Particles  I PM2.5  PM1O  TSP  UF I I I 21  2.1.2  Composition  As mentioned before, particles can also be classified by their chemical or biological composition. Typically made up of a core of carbon, many other elements, such as, organic and inorganic compounds, aerosols, and metals can be adsorbed or 32 Due to the mechanism that creates TSP and coarse particles, attached to the surface.’ these larger particles are typically from natural materials, such as, insoluble crustal materials, sea salt, pollen, and bacteria. On the other hand, fine and ultra fine particles generally consist of the aforementioned carbonaceous core, with metals and organic 34 These organic compounds encompass polycyclic aromatic compounds adsorbed.’ hydrocarbons (PAH5), metals (iron, nickel, etc.), ions, reactive gases (ozone, peroxides),  and biological elements (bacteria, viruses, pollen).  2.2  Sources of Particles  2.2.1  Coal  Coal has been used extensively for heating (industrial and residential) and 37 Tar and soot are byproducts of the combustion process, and has been known for power.’ quite some time to be associated with respiratory, skin, and scrotal cancers. Coal was ultimately the culprit in the infamous London Fog of 1952 in which over 4000 more 38 and also, previously in deaths than normal occurred due to heart and lung conditions,’ the Meuse Valley, where pollution from the many nearby industrialized sources caused  22  the death of 60 people in 3 days in 1930.139 PAl-Is were quickly identified as the carcinogenic and mutagenic properties of the soot and tar. Depending on the location, ° The 4 power plants that burn coal are a significant source of PM, especially in the USA.’ carcinogenic and mutagenic properties are well known, but more work is required to further look at the impact of modern power plants and their emissions.  2.2.2  Petroleum  Petroleum encompasses a number of other combustible liquids, such as fuel oil, 137 Residual fuel oil, part of the heavier petroleum products, contains gas, and diesel. 4’ Combustion of this fuel oil produces residual oil fly ash (ROFA) carcinogens. known ’ 42 and is said to give off even more particles and emissions than lighter fuels (jet fuel).’ When compared to coal fly ash, ROFA usually contains more toxic trace metals. Diesel and gasoline are also petroleum products and account for sizeable portion of air pollution. Virtually all automobiles, construction equipment, and boats use either of these energy sources. When compared, diesel produces 100 times the elemental carbon more than 37 In urban centers, traffic-related pollution comes almost entirely from gasoline gasoline.’ 143 Lung, bladder, and lymphatic cancers are all associated with and diesel emissions. 37 gasoline has not been as occupational diesel exhaust exposure. According to Lewtas,’ well-studied as diesel due to to the lower particle emission rates of gasoline.  23  2.2.3  Traffic  144 and 5 . 2 Traffic-related PM air pollution has been a major contributor of PM 25 ultrafine particles.’ 32 Not only do emissions itself contribute to the ambient PM concentrations, but the natural wear on tire and roads and resuspension of dust all ’ 146 Traffic density and intensity also play a role in 45 .’ 10 contribute to the levels of PM levels and size composition of PM. The greater the intensity of traffic, the greater the 32 suggest that PM produced from traffic related levels of ambient PM. de Kok et al.’ sources may have a greater capacity to generate ROS based on research by Baulig and 47 Without a solid cutoff for when levels of ambient PM cause exacerbations colleagues.’ of existing health conditions, the belief in the scientific community is that any population 32 will benefit from any kind of reduction through environmental policies.’  2.2.4  Biomass  37 Biomass burning can include anything from forest fires to cigarette smoking.’ When compared to the relatively high efficiency combustion of petroleum, biomass 48 smoke contains higher levels of organic carbon and has higher particle emission rates.’ Wood smoke During the incomplete combustion of wood or during forest fires, the combustion 149 An important products from lignin and cellulose compose the majority of emissions. ° and both are used 5 marker for lignin is methoxyphenol and for cellulose is levoglucosan’ to determine the origin in atmospheric particles and biomass burning. The burning of ’ 5 wood and other vegetation will also produce mutagenic and carcinogenic PAHs.’ 24  However, the type, condition, and location of the combustion all affect the characteristics of the emissions. Agricultural burns are used to quickly destroy old crops or pest plants and have been known to impact nearby communities with the increased ambient air pollution. 137 Cooking Another source of indoor and outdoor pollution are the particles, organic aerosols, 152 Typically, byproducts and carbon that are produced by cooking (frying, charbroiling). of oils, such as, saturated and unsaturated fatty acids, are the major fraction of organic , these particulates are considered to be 53 particulates. According to a number of studies’ carcinogenic in animals (probably humans). Even in home, indoor cooking, the mere act of broiling steaks in the oven or pan-frying bacon produced mutagenic and carcinogenic 54 PAHs and hetercyclic amines.’ Tobacco smoke One of the most relevant sources of PM exposure (especially in COPD) is 55 4000 substances in cigarette smoke, which is made up of over 45,000 chemicals.’ 56 cigarette smoke are known to be carcinogenic, mutagenic, cytotoxic, and antigenic.’ Over time, the composition of cigarettes has changed as there have been changing proportions of bright and burley tobacco, and these changes affect the composition of the 57 Smokers are not the only group affected, as children can be exposed to smoke.’ 58 ETS is known to environmental tobacco smoke (ETS) in schools and public places.’ adversely affect respiratory health in children and in the fetus causes premature 59 deliveries, low birth weight, and malformatjons.’  25  2.3  Epidemiology  There is strong relationship between levels of increased ambient air pollution and 2 This relationship was diseases. 3 ’ the rate of morbidity and mortality from respiratory 31 first brought to light in the 1950’s, which eventually led to research and development into the 60’s and 70’s, resulting in air pollution guidelines and restrictions in higher-income 60 However, increasing traffic and urbanization in these countries, combined countries.’ countries, 161 have ’ with cooking and heating stoves using biomass fuels in low-income 40 contributed to the burden of COPD. ’ most epidemiological studies focus on short6 According to Liu and colleagues,’ term exposure studies in high-income countries, and few have looked at the long-term exposures on the development of COPD. The first of these studies looked at the doubling of the daily death rate during the London Fog of 1952 and also found that the large 38 Of all the ambient air majority of those deaths were due to cardio-respiratory causes.’ 0 seems to have the strongest association with adverse health effects, even pollutants, PM, ’ Even with more stringent air pollution 3 when correcting for a smoking history. 62 found a 19% 161 Schwartz and Dockery’ regulations, mortality has continued to increase. 3 increase in increase in cause-specific mortality for COPD associated with a 100 ig/m TSP. As mentioned before, most of the work has been done to describe the exacerbations of air pollution on pre-existing conditions of COPD. For this disease, 63 Although exacerbations are the major cause for its morbidity and mortality.’ exacerbations are mostly attributed to viral or bacterial infections, there is a growing  26  body of evidence that suggests exposure to ambient PM can initiate or contribute to the ’ 163, 31 infections to cause an exacerbation.’  164  , there 25 3 increase in PM For every 10 .ig/m  64 It seems as though is a doubling in admissions for COPD exacerbations in hospitals.’ regardless of the metric used to describe the PM exposure and health endpoints, most ’ In 3 studies point to an association between ambient PM and COPD exacerbations.’ addition, the mortality rate increases for COPD immediately following exposure to ambient PM. Air quality guidelines can only go so far, as a study from the UK suggests that these levels are consistently above limits and result in 8,000 deaths and 10,000 65 excess hospital visits for airway disease exacerbation.’ However, there are few studies that have looked at the association between PM air pollution and a decline in FEV,, as well as, the development of COPD. Schikowski and 3 38 ran a cross-sectional study on women and showed that with a 7 .Lg/m coworkers 0 over 5 years, they had an OR of 1.33 (95% CI, 1.03-1.72) for increase in ambient PM, developing COPD and had a 5.1% more rapid decrease in FEy, (Figure 5). Women who lived near (less than 100 m) major roads were much more likely to have reduced lung function and an OR of 1.79 (95% CI, 1.06-3.02) of developing COPD when compared to ° assessed two locations in China 4 women who lived further away. A study by Liu et al. and found that there was a significant association between the use of biomass fuels for cooking and the risk for developing COPD using both univariate and multivariate analyses. They concluded that biomass fuel is an important risk factor for the development of COPD, especially in China where the use of biomass fuels and poor ventilation is commonplace. Support for Liu et al.’s conclusions also comes from Kiraz ’ who found that rural Chinese women are more likely to have chronic 4 and colleagues  27  bronchitis and COPD than women (with a higher prevalence of smoking) who lived in urban areas. These studies suggest that factors other than just cigarette smoke can lead to the development of COPD. 10 exposure Figure 5 Association between FEy, (L) or COPD (R) and long-term PM (five-year mean). Data points are means of each place and year of study.  3.0  6 He86  2.9  2.3 35  I  DoNW63  40  55 45 50 long-term PMIO [pglm3]  60  0 35  Bo94 Bo86  40  55 45 50 long-term PMIO [pglm3]  2.4  Deposition and Clearance of PM from the Lung  2.4.1  Deposition  60  The deposition of PM can happen by five different mechanisms: interception, ’ 167 Of the five, 66 impaction, sedimentation, diffusion, and electrostatic precipitation.’ impaction, sedimentation, and diffusion are the most important mechanisms for inhaled particles, as interception usually describes fibrous particles and electrostatic precipitation involves those with high electric mobility (which aerosols have very little of). Impaction typically describes how very large PM (over 100 urn) travel on a given path before a barrier, like a branching airway, stops them. Sedimentation occurs when particles are given the opportunity to fall via gravity and affects particles in the 0.1 tm to 50 tm 28  range. Finally, diffusion occurs via random gas motion and in the small airways and gas exchange regions. 68 Any dose of The major entry point into the body for PM is the respiratory tract.’ inhaled particles in the lung is a function of its ratio of deposition and clearance. Lippman 67 observed that particles would tend to aggregate in the centrilobular et al.’ emphysematous lesions. In another study, PM was found to be in the small airway mucosa of non-smokers living in Mexico City, suggesting that high levels of air pollution 69 could result in remodeling of the airway similar to that of COPD.’ 2.4.2  Clearance  There are several features of the innate immune system that help to clear and protect the respiratory system from inhaled PM according to Hogg and Timens. These features include: an epithelial lining fluid (ELF), mucociliary clearance in the lower respiratory tract, alveolar macrophages, and the tight junctions that join the epithelial cells. Epithelial liningfluid The respiratory tract is lined with a thin, liquid layer called the ELF that covers the epithelial layer and also contains neutralizing agents, such as, antioxidants, lysozyme defensins, lipids, mucins, and proteins.’ 70 The maj or component of the ELF is surfactant, which can also has the unique property of aggregating PM less than 6 pm in diameter to ’ Proteins present in surfactant may help in 7 allow for easier mucociliary clearance.’ ° Macrophages can more easily 7 opsonization and allow macrophages to target PM.’  29  phagocytose particles that are greater than 5 p.m in diameter, and as mentioned before, surfactants act to aggregate particles for these cells. Mucociliary clearance Mucus is produced by goblet cells and submucosal glands and contains 172 Ciliated cells in the airways can be found among the goblet antimicrobial substances. Salvaggio’ suggests, is similar to an escalator. cells and beat in a synchrony and, as 72 Typically most large and insoluble particles will be moved on the mucus layer up to larynx, where they can either be swallowed or coughed out. Alveolar macrophages The first line of defense in the cellular response to deposited PM in the lung is the alveoli.’ 175 ’ alveolar macrophage (AM).’ 73 AMs can be found on both the airways and 74 If the PM caimot be coughed out or swallowed, then the PM is phagocytosed by the AMs.’ 176 The primary role of the AM is to act as another barrier to the PM by ’ 74 ’ 177 Generally, the greater the PM 76 phagocytosing and intracellularly processing them.’ studies’ 180 published fairly recently ’ 78 Several 79 burden, the more AMs can be found.’ 78 from the 1960s. He suggested that the greater the have supported Brain’s observations’ surface area covered by the particles and the larger the number of smaller particles, the more powerful inflammatory response elicited. After phagocyto sing PM that constitutes greater than 60% of their total volume, 73 where their phagocytic and chemotactic activity AMs can go into an “overloaded” state’ is 81 inhibited.’ 182 Even if only 6% of their total volume is taken up by PM, their ability to ’ migrate up the mucociliary elevator was compromised. Furthermore, if the PM is composed of silica, it can irreparably damage the AM, forcing it to release its contents  30  77 The release of these contents, including ROS, and fuel the inflammatory response.’ proteases, pro-inflammatory mediators and growth-regulating proteins can lead to the ’ 175 73 progression of acute and long-term lung inflammation.’  2.5  Mechanisms of PM-induced Lung Inflammation  AMs and the bronchial and alveolar epithelial cells are the primary cells that process deposited PM in the lung. As part of the processing mechanism, these cells release pro-inflammatory mediators that perpetuate a local, but also, a systemic ’ 83 response.’  2.5.1  184  AM Response  As mentioned earlier, AM exposure to PM results in an increase in oxidant 84 When production, release of pro-inflammatory mediators, such as TNF-a and IL-li’ incubated ex vivo with ambient particles, AMs produce other cytokines, such as, IL-6, IL-8, MIP-l and GM-CSF. 72 IL-lO, a known anti-inflammatory cytokine that inhibits the production of IL-6, IL-8, TNF-a, and IL-13, is interestingly not associated with particle , perhaps suggesting that PM does not elicit an anti-inflammatory response. 72 exposure Together, these mediators produced by AMs generate an inflammatory response that is passed onto the epithelial and endothelial cells, which will then recruit leukocytes. PM may also inhibit the AM response to bacteria through an oxygen radical-mediated ’ 129, 27 process,’  185, 186  which suggests that exposure to PM can decrease the lung’s ability 31  to defend itself against biological insult. Ultimately, the burden of PM in the lung can perpetuate and compromise the immune response leading to more COPD exacerbations.  2.5.2  Lung Epithelial Cell Response  Lung epithelial cells form a large surface area that is exposed to inhaled PM and ’ 79 play an important role in the processing of these foreign objects. A number of studies,’ 187-189  ’ 190 have provided evidence to suggest 89 including those from our own laboratory,’  that lung epithelial cells exposed to PM produce a number of pro-inflammatory mediators, such as, GM-CSF, IL-6, IL-8, MCP-l, and leukemia inhibitory factor (LIF). These mediators can attract leukocytes, and PM exposure of epithelial cells also upregulate the expression of inter-cellular adhesion molecule-i (ICAM- 1) to further promote leukocyte recruitment in the airspaces. Persistence and inflammation of the El A adenoviral gene in cigarette smoke-induced COPD when exposed to air pollution suggests another pathway for the retention of PM and contribution to chronic 90193 Lung epithelial cells, coupled with a response from AMs, interact inflammation.’ 88 In a controlled, human volunteer study, synergistically to produce GM-CSF and IL-6.’ exposure to PM induced an inflammatory response in the airways consisting of an 94 and as a consequence of neutrophil attractant increase in neutrophil trafficking’ epithelium.’ 196 These mediators can result in ’ cyto/chemokines, production by bronchial 95 the damaging of the airways, which makes the airways much more susceptible to bacterial, flingal, or viral infections.’ 79 This situation can ultimately lead to the exacerbation of symptoms in COPD.  32  2.5.3  PM-induced Lung Inflammation  A number of similarities exist between the inflammatory mediators that exist in COPD and those that can be associated with PM exposure. There are increased levels of pro-inflammatory mediators such as IL-6, IL-113, TNF-a and IL-8 observed in induced sputum from patients with COPD. ’ Macrophages are, by in large, the major contributors 8 of the following mediators: IL-8, IL-113, TNF-cL, GRO-ct, ENA-78, MCP-1, and IL-lO. Epithelial cells produce IL-8, G-CSF, and MCP- 1 and are involved in neutrophil and 97 Elastase and MMP activation associated with monocyte recruitment into airspaces) neutrophils and macrophages are considered to be important mediators of lung parenchyma tissue destruction in COPD. Recent studies showed that this process is driven by pro-inflammatory cytokines such as TNF-a which appears to be a key initiating 98 Montano et al.,’ mediator.’ 99 showed macrophage MMP activity and expression was upregulated in COPD patients who had been exposed to wood smoke, suggesting that this situation could result in emphysematous destruction. PM deposited and/or retained in emphysematous regions of the lung could activate the proteolytic pathway (eg. myeloperoxidase, elastase & MIvEP’s) and also stimulate the production of molecules such as IL-8 and ENA-78 involved in neutrophil recruitment and activation. 10 in rats resulted in a neutrophil influx with an Intratracheal instillation of PM 83 This study by Li et a!. showed that PM exposure increase in endothelial permeability.’ resulted in free radical activity as well. PM has also been shown to be genotoxic to alveolar epithelial cells, causing both apoptosis and DNA damage through a ° This oxidative stress could be the 20 mitochondria-related death and free radical pathway. ’ In 20 result of structural damage inflicted onto the mitochondria by intracellular PM. 33  addition, PM exposure of macrophages and human bronchial epithelial cells also results in an induction of heme oxygenase- 1 (HO-i), which is a key marker for oxidative ’ Oxidative stress appears to be a very important pathway for the deleterious 20 stress. effects of PM exposure. 202  34  3  Chapter Three: Research  3.1  Working Hypothesis The general hypothesis that several members in our laboratory work on is that  particulate matter are abnormally retained in lung tissues of subjects with COPD and that these retained PM perpetuate the inflammatory response in the lung contributing to progression of lung disease. For our thesis we will address the specific hypothesis that “the particulate matter burden in the lung tissues ofsubjects with COPD relate to the severity of disease and the inflammatory response in lung tissues.” We suspect that these particles cause a chronic inflammatory response in the lung, which continually stimulates the release of pro-inflammatory mediators that recruit more leukocytes into the airways and lung tissues (Figure 6). This chronic inflammatory response in the lung could also make the lung more susceptible to invading pathogens responsible for COPD exacerbations causing progressive loss in lung function. We also hypothesize that the majority of the PM is carbonaceous in origin because the lung environment would most likely process any heavy metals or organic compounds.  35  203 Figure 6 Possible mechanism for PM-induced C0PD Airway lumen  /  10 PM Macrophage  *4,  UFP, PM 25  ..  /  TLR-4  •  Epithelial Cells  i  (  Mast cell  Cell death (necrosis, apoptosis) Proinflammatory factors: TNFo, IL-i 13, IL-8  Tissue damage and remodelling  COPD 3.2  Inflammation  I  Specific Aims  The overall goal of this project is to quantify the amount of particulate matter in the lung of subjects with COPD and relate it to the severity of the inflammatory response in lung tissues, as well as, the decrease in lung function (severity of COPD as characterized by the GOLD classification). We will pursue the following specific aims: 1)  Quantify the particle load or burden of PM in lung tissues of COPD.  2)  Determine where in these lung tissues PM are retained (airways, parenchyma, blood vessels, lymphoid tissues, macrophages etc).  3)  Correlate particle burden and inflammatory markers with severity of COPD.  4)  Determine the chemical composition of the PM retained in lung tissues through a novel in situ method.  36  These studies will determine the importance of particulate matter in the pathogenesis of COPD and improve our understanding of the mechanisms by which PM induces lung inflammation that could lead to novel therapeutic interventions in the future.  37  4  Chapter Four: Materials and Methods  4.1  Sample Selection  4.1.1  iCapture BioBank and Patient Enrollment  Established in 1979, our laboratory has had a successful patient registry and lung tissue bank. The iCapture BioBank contains 30 years worth of confidential patient information and associated tissue samples, which allows for studies from both a molecular and pathological standpoint. A digital photography system at the iCapture Centre allows stereological studies with digital histological quantification measurements: the principle methodology used for my studies. Lung samples are collected from individuals who need lung resection surgery mostly for small peripheral nodules. These persons are invited to participate in the lung registry and tissue bank. The purpose of the lung resection surgery is to remove a lung or lobe that contained a lung tumour and after the tumour is removed, the remaining tissues are stored for research purposes. The lung registry also contains lung tissues from Barnes Jewish Hospital, Washington University, St. Louis, United States of America. These lung tissues come from subjects undergoing lung reduction surgery or transplantation. All subjects give consent for use of their tissues for research purposes. After the purpose of the study was explained to each individual, their clinical data, such as, preoperative lung function tests, thoracic CT scans, and smoking and occupational histories is collected (provided they gave written consent). Confidentiality is maintained by restricting access to the BioBank and using encrypted, unique identifiers for each individual. An oversight committee approves all past, present and future studies with registry tissue. This 38  committee continues to monitor the progress of the research that uses this BioBank patient information and tissue.  4.1.2  Tissue Specimen Collection  Human lung tissue was obtained from 66 patients in the registry who required lung tissue resection surgery as described above at St. Paul’s Hospital, Vancouver, British Columbia, Canada or removal of an entire lung prior to transplant surgery due to severe, debilitating COPD (Barnes Jewish Hospital, Washington University, St. Louis, United States of America). These cases were chosen to represent the whole range of severity of COPD, from normal lung function to severe impairment requiring lung transplant surgery. To reduce the amount of confounding factors, they were also age and smoking history-matched. Samples from St. Louis were used because GOLD 3 and 4 1 patients rarely undergo lung resection surgery because of their poor lung function (FEV <50% but> 30%, respectively). Patients were then grouped based on their disease severity according to their GOLD classification (Table 3). The GOLD classification is based on the spirometric classification of COPD based on post-bronchodilator volume of ) and also its relationship with forced 1 air that can be forcibly exhaled in 1 second (FEV /FVC<70%). Patients were grouped into a non-smoking control 1 vital capacity (FEV group, smoking control (formerly GOLD 0, at risk for COPD because they smoke but still have normal lung function), GOLD 1 (mild COPD), GOLD 2 (moderate COPD), and GOLD 3 and 4 (severe and very severe COPD, respectively). GOLD 3 and 4 cases were  39  L) 00  .  ( -  -  -  -  -  -  00-_-0000  —  ,_  ON ON ON ON ON ON ON 00 C C 00 SD 00 00 SD 00  —.  00 SD C SD SD 00  I— —  SC SD C SD SD SC SC 00 SD SD 00  0000ONSDSDSDC00-UI  000  CJ0000SDSD00CCJSDCUIC  ONCC00CC00C00.CC-  ON  r)  )  0  —  .e  0  D  —..  -‘)  -  -  C  .)  “J ) L’J ‘J O C C UI UI UI UI L’J L’J C C Q Q UI UI L’J ‘J s) ‘J D C -1 E’J 00 -1 —‘ C C C UI .1 C C 00 00 C C C C SD SD .1 4 ‘J SD k) — L) C C 00 .l 00 C SD ON C SC t’J -1 00 - ON SD C SD C SD 00 UI C SD -.  —CON00SDSDSDCUICCCC4SD UI UI 00 L’) UI t’.J SC ‘J C -3 00 ) ON ) k) — SC ON L) C SD SD SD UI C UI t’J 00 L3 SD  SC  Cj CiJ  —  0  0  0  rM  —  C)  C,) -  C,)  i  CD  CD  CD  C  C  It  C,)  CD  C)  Cl)  Cl)  00 CD  o  00  CD C)  .  ) Cl)  CD  -t  CD  -  CD  CD  CD  P)  o  -4  CD  CD  CD Cl) C)  C)-  C/)  CD  0  C)  0  Cl) C/)  0  Cl)  CD  Cl) -. Cl)  -  0  ‘  -4  CD  CD  CD CD  CD  CD  CD  Cl)  CD  ©  CD  CD  Cl)  Cl) -4 Cl) Cl)  -  i-  C  .)  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After the lung is received from the operating room, it is transferred to the lab where it is weighed. Samples for pathology, such as, nodes and tumour samples, are removed. At this point, tubing can be inserted in the bronchus with saline and the lung can be lavaged for cells. After the lavage, the whole lung is inflated with Cryomatrix (Shandon, Pittsburgh, PA) diluted 1:1 with saline via the bronchus (Figure  7)205  Cryomatrix is an embedding resin that supports frozen tissue, dissolves in water, does not expand when frozen, and freezes quickly. The Cryomatrix is mixed with saline because it would be too viscous to pump in the lung. After the lungs are frozen solid with liquid nitrogen vapours, they are kept frozen at -70°C. The lungs are then cut into 2 cm thick, transverse slices with a meat saw and then sampled (cored) by using a 1.5 cm radius hole saw. This process leaves a cylinder of lung tissue with a radius of 1.5 cm and a height of 2 cm. These cores are sampled in a uniformly random manner to get a good representation of each slice.  42  Figure 7 Steps in lung tissue preparation and sampling. A) Lung inflated with Cryomatrix and saline B) Lung frozen over liquid nitrogen vapours C) Meat saw D) Hole saw E) Lung slice with missing lung cores F) Frozen lung core  :  4.1.4  /  Sectioning of Lung Tissue Cores  The cores of lung tissue are then embedded on the cryostat chuck with OCT (Optimum Cutting Temperature) compound (Tissue-Tek, Sakura Finetek, USA, Inc., Torrance, CA). OCT is an optimal cutting medium that is a water-soluble glycol and resins compound that supports the tissue for cryostat sectioning at temperatures of less than -10°C. The cryostat (Leica CM 1950, ThermoShandon) is a chamber, which contains a microtome for sectioning frozen tissue and it also can maintain very low temperatures. After the blade is cooled, adjusted to the correct angle, and set in the blade holder, the sample is trimmed until a complete section can be cut. After cutting the 43  sections at a thickness of 10 urn, the sections are adhered on to plain glass slides (kept at room temperature) and are allowed to air dry before staining.  4.2  Histology  For microscopic analysis of the lung tissues via the light microscope, the sections were stained with the hemotoxylin and eosin (H&E) stain (Figure 8A). The hemotoxylin stains basophilic structures blue, typically those that contain nucleic acids by a complex, poorly understood mechanism. The eosin stains eosinophilic structures pink, such as the cytoplasm, proteins, and connective fibres. On a qualitative level, H&E allows an observer to distinguish between the various structures in the lung tissue, such as, the parenchyma, small airways, blood vessels, alveolar macrophages, and lymphoid follicles. Figure 8 A) Cropped digital image of alveolar wall tissue stained with H&E at 20x objective magnification. B) Example of black pigment in the H&E stained tissue at 20x objective magnification.  A  For our frozen tissue, the rapid H&E procedure was used, as the typical H&E procedure can overstain certain tissues and in the longer hematoxylin bath step, the tissue  44  may slough off the slide. Firstly, the tissue is fixed appropriately with 10% neutral buffered formalin (NBF) for 1 minute. This step fixes the tissue and preserves the structure of the tissue. After washing in water for 10 seconds, the slide is placed into a hematoxylin bath for 1 minute. After washing again in water for 10 seconds, the blue sections are placed in lithium carbonate (basic solution) for 10 seconds. After washing in water for 10 seconds, the slides are checked microscopically for adequate nuclear staining (nucleus should be blue to blue-black, can be adjusted in this step). The slides are then dipped in 70% alcohol for 10 seconds to condition the tissue (remove water) and then counterstained with eosin for 10-15 seconds. The excess eosin is drained and then the section is dipped (in sequence) in 80% isopropyl alcohol, 90% isopropyl alcohol, and twice in absolute isopropyl alcohol for 10 seconds each, respectively, to finalize the process of dehydrating the tissue before air-drying and coverslipping. The PM could be differentiated from the tissue as its colour is solid black and could be easily distinguished by eye or by computer from the dark blue hemotoxylin stained nuclei (Figure 8B). Predominately carbonaceous in nature, the PM required no additional staining to be visualized microscopically.  45  4.3  Stereology  4.3.1  Concepts  To quantify the PM burden in the lung, we used a stereological method. Stereology is defined as the practical technique(s) for extracting quantitative information about a 3-dimensional (3-D) material from measurements made on a 2-dimensional (2-D) 206 We used a light microscope to visually resolve the tissue compartments and the plane. PM in those structures. The use of a microscope, however, introduces a reducing fraction problem (Figure 9). As the magnification increases, a smaller fraction of the object of interest is actually studied. Figure 9 A cartoon depicting how as the magnification increases, it decreases (by 206 great amount) the proportion of the object being studied Linear magnification lx  5x  th 47 j,  25x  th 111200  125x  625x  1fl30.O(XJth  Approximatc fraction of 2-D object in field of view  Because the whole object could not be studied by microscopy, a well-defined and structured method is used to select the samples or microscopic field of view. Sampling should be uniformly random (every sample having an equal chance of being selected) and 46  once the samples have been chosen, the same method of extracting data must be used for each sample. Allowing every sample an equal chance of being selected will prevent sampling bias from occurring. Systematic bias (incorrect measurement tool, instrument calibration errors) is prevented by using the same methods of estimation for all fields of view and by comparing results of intra and inter-observer error. A hierarchical system (Figure 10) of sampling is used and our study consists of the lung(s), cores of tissue from the lung, sections cut from the cores, and fields of view digitally captured from the sections. Each donor, lung, core, section, and field of view is different and this introduces variability. The variability between individuals (around 70%) is vastly greater than the variability between sections (around 5%) and fields of view (around  2%).206  By only increasing the number of fields measured, the precision of  the measurements will only increase by a relatively small amount. In order to efficiently increase the precision of the measurements, it is important to increase the number of individuals (cases), as opposed to increasing the number of fields of view.  47  Figure 10 The hierarchical nature of sampling in microscopy. The need for uniformly random sampling is paramount to make an accurate and precise 206 estimate.  Obfrct  / Block  E  Section  Ficldsof View  I•II I I I I I II I • I  EEEJ I I  II  •  I  j  j  L11E  Lrn  1111 I II I I •  SIll 1111 II I I I  One of the primary objectives of this study was to look at how much PM was present in any given tissue compartment in the lung. In stereology, points act as probes for volume. These probes are applied in 3-D by physically cutting the specimen into thin sections and then applying a 2-D grid (of points) onto the section. This two-stage process is similar to imaging throwing a 3-D lattice of points into a volume of space. For the sake of efficiency, it is important to use the least number of points, while still maintaining precision and accuracy. By using points, a value for a volume fraction (Vv), which is defined as the volume proportion of one phase within a reference volume, is achieved. For this particular study, the PM is considered to be a rare substance and represents a very small proportion of the reference volume (tissue). Using a coarse grid to estimate the amount of PM would not be very accurate, as much of the PM would be missed. As  48  such, a finer grid (more points) is required and by using a point grid that combines 2 sets of points, the ratio of coarse and fine points can be used to estimate an accurate Vv of PM in each lung tissue compartment (Figure 11). If there were twice as many points on the fine grid (Figure 1 1A) as compared to the coarse grid (Figure 1 1B), the area per point associated with each coarse point is twice that of each fine point. Figure 11 A) Coarse grid (196 points) overlaid onto digital image of tissue. B) Fine grid (1500 points) overlaid onto digital image of tissue at 20x magnfication.  B  4.3.2  Equipment and Software  For the capturing the fields of view digitally, a light microscope (Nikon Eclipse E800) equipped with a digital camera (JVC3-CCD KY F-70, Diagnostic Instruments) was used. To transfer the images to computer, image capture software (KY-FRM) plugin for Adobe Photo shop CS was required. During the course of my experiments, the digital camera was upgraded to a SPOT Flex digital Camera (Diagnostic Instruments, Sterling Heights, MI) and the image capture system to Diagnostic Instrument’s proprietary SPOT Imaging Software. The upgrade allows for better resolution, colour 49  rendition, white balance, and streamlined user interface. For image analysis, I used the digital-image-analysis software Image Pro Plus 4.0 (Media Cybernetics, Bethesda, MD).  4.3.3  Image Capture Protocol  Of the 66 cases available (Table 3), only those that had 5 or more slides (sections) per case were chosen to capture digital fields of view. To resolve the various structures in the lung, as well as the PM, an objective magnification of 20x was necessary (total magnification = 200x). Fields were randomly captured, with coordinates being chosen by a random XY coordinate generator. Fields that were completely devoid of tissue (no usable Vv) and fields that fall on the perimeter of the lung core sections (Figure 12) were excluded. Two fields of view per slide were captured. Figure 12 Fields of view excluded (red) and included (green) in this study  Section  Fields of view excluded  Fields of view included  PM burden in all compartments oflung tissues: To determine the burden of the PM in various compartments of the lung, these variables were assigned tags in Image Pro Plus. 50  A “tag” is a digital marker used to define a certain point on the grid. Using the coarse grid, the alveolar wall, the airspace, and any other type of tissue of interest were tagged (placing a digital tag on each point on the grid) manually. Using the fine grid, the alveolar wall with and without PM, airspace with and without PM, blood vessel wall with and without PM, airway wall with and without PM, alveolar macrophage with and without PM, lymphoid tissue with and without PM were tagged manually. These tag files were then exported to Microsoft Excel (Microsoft) as raw data to be processed. The volume fraction of a defined variable (for example alveolar wall) will then be defined by the number of points falling on that specific object divided by the total number of points on the grid selected. In the case of PM, the total number of points of PM falling on a particular compartment, divided by that compartment, will determine the Vv of PM in a certain compartment of tissue.  PM burden in small blood vessels: After analyzing the results from the PM burden in all tissue, it seemed that we were not able to randomly catch enough blood vessels to make an accurate measurement of the PM burden in that specific compartment. Therefore, by biasing the selection to just blood vessels alone, that specific compartment could be studied more precisely. Instead of using a random coordinate generator used to achieve fields of view for the PM burden in all types of tissue, all small blood vessels (between 0.5 mm and 2.0 mm largest diameter, less than 3:1 ratio of largest diameter to smallest diameter) were captured in all cases via a zigzag search. Blood vessels were arbitrarily cut off at those sizes to keep the 20x magnification constant (2.0 mm would fill the whole field of view at this magnfication) and the 3:1 ratio was to exclude blood vessels that had  51  been sectioned obliquely (blood vessel wall would not be representative of the actual dimensions). To quantify the particle burden in these blood vessels, a macro (computer program) was written for Image Pro Plus to automate the process of determining the Vv of PM in the blood vessel wall. Firstly, the inner lumen and the outside of the adventitia of all blood vessels were manually traced and the areas bounded by the tracings were saved as an area of interest (Aol). For this program, each pixel of the image was considered a point. The program uses these areas to calculate the area of the lumen (Al) and subtract it from the area bounded by the adventitia (A5) (Figure 13). The resultant area, which represents the blood vessel wall, would then be the analyzed using a colour segmentation file that would differentiate the black colour from the pink/red/blue tissue via a colour threshold determined prior to running the macro. Colour segmentation has been used successfully in other publications from this lab. 207 Figure 13 Steps in the program for the automated blood vessel analysis. A) Inner lumen traced. B) Inner lumen area quantified (in pixels). C) Al D) Perimeter of adventitia traced. E) Black pigment quantified (in pixels) within the perimeter of the adventitia. F) A5  ..  A  52  PM burden in lymphoidfollicles: Another structure of interest was the lymphoid follicles. As with the blood vessels, the follicles were rare, so it was prudent to also use a zigzag search to bias the selection toward lymphoid follicles. These images, unlike the blood vessels, were taken at an objective magnification of lOx (total  =  lOOx) because the  majority of follicles are larger than what a 20x objective field of view can capture. The macro written for the PM burden in blood vessels was re-written to remove the step of including and subtracting the Al area. This would allow the program to determine just the area of the follicle and also the area of the PM inside the follicle.  4.3.4  Statistical Analysis  With the final data from the PM burden in all tissues, blood vessels, and lymphoid follicles, statistical analysis was done to determine if parts of the hypothesis were supported by the data. Correlations: A scatter diagram helped to determine the relationship between 2 variables. Each dot in such a diagram represents, for example, the PM burden in the blood vessel and FEy 1 pair for one case. The strength of the correlation depends on the linear association (correlation coefficient). The closer the association is to 1, the strong the linear association, be it positive (slope up), or negative (slope down). This correlation coefficient is labeled r. For this study, a p-value of less than 0.05 was considered significant.  53  Tukey-Kramer: To compare the PM burden in the tissues between non-smoking and COPD severity groups, I used the Tukey-Kramer method to determine if there were significant differences between the 5 groups. The Tukey-Kramer method is a single-step, multi-comparison procedure used to compare the means of all treatments with the all other treatments and applied to all pairwise comparisons simultaneously, while having unequal sample sizes. The process is similar to a student’s t-test, but corrects for multiple comparisons being made. For this study, a p-value of less than 0.05 was considered significant. Kruskal- Wallis one-way-analysis-of.variance-by-ranks test: This is a non-parametric test to look at the differences of 3 or more independent groups that do not necessarily have to have a normal distribution. The actual data is replaced by rankings, and in this way the calculations are simplified. Student T-test: This test will analyze the means of two, normally distributed means of a population to determine if they are statistically different. Software: All data was compiled initially in Microsoft Excel, and then transferred over to iMP 5.1 Statistical Discovery Software (JMP, Cary, NC) to run all the statistical tests. IMP would output both the correlation coefficents and p values. To create the graphs, the graphing program Sigmaplot 10 (Systat Software Inc., San Jose, CA) was used.  54  4.4  Gene Expression  4.4.1  Concepts and Rationale  The definition of gene expression is when information of the gene is translated into functional gene products: typically mRNA and proteins. Often, the amount of gene expression (under or over-expression) can result in major physiological changes. Therefore, it makes sense to look at the gene expression in disease states, such as, COPD, in order to gain an understanding as to which genes may be associated with an increase in severity. /FVC, 1 1 or FEV Besides looking at the PM burden in the lung as it relates to FEV it is also important to see if this burden is correlated with gene expression known to be associated with both the type of inflammation in lung tissues of patients with COPD as well as the severity of COPD. Because of the chronic nature of the inflammatory response in airways and lung parenchyma in COPD, we selected to look at genes involved in chronic inflammation and the repair process. We specifically looked at these genes (see table 4) in lung parenchyma (that include the smaller blood vessels) and linked and relate it to PM burden in the lungs. Also, for blood vessels only, wall thickness was analyzed against gene expression. All patients (except for the non-smokers) in the current study were part of the patient groups where mRNA gene expression was determined by 208 They completed the members of our lab, specifically John Gosselink and colleagues. bench work for this portion of the material and methods section. The following is a brief description of the basic methodology used in that unpublished manuscript, using the same sample tissue used for this study.  55  4.4.2  RNA Isolation and Assessment  In the Gosselink et al. study, 208 differential gene expression in the airways and the parenchyma (which included the blood vessels) was investigated. Since most of the data generated for this thesis came from the burden of PM in the parenchyma and blood vessels, the PM and morphometric data were correlated with the corresponding patient’s gene expression data from the parenchyma. To separate the two distinct compartments, 208 used laser capture micro dissection (LCM) to remove the airway from Gosselink et al. the surrounding parenchyma and stored before RNA isolation. The start of most molecular biology experiments requires high quality, intact RNA. The isolation technique used was an RNeasy Mini kit (Qiagen, Mississauga, Ontario), which allows for the quick purification and a consistent yield of RNA from the given tissue. Using an Agilent 2100 Bioanalyzer (Agilent Technologies, Palo Alto, CA), the isolate was assessed for quality based on internal standards. 4.4.3  Amplified cDNA Before the RNA can be used in quantitative (q) polymerase chain reaction (PCR)  assays, it must be first converted to DNA. Because of the small amounts (100 ng) of RNA that were derived from the parenchyma and airways, it was necessary to convert the RNA into eDNA, and then amplify it. The kit used for this process was the Clontech Super SMART eDNA Amplification Kit (Clontech, Mountain View, CA), which is  56  209 useful for generating eDNA from very small amounts. Gosselink and colleagues confirmed that the amplified eDNA maintains the relative expression levels of the original RNA. 4.4.4  Quantitative Polymerase Chain Reaction  PCR is a technique that amplifies DNA into quantities that can be used later for molecular analysis. The benefit of doing qPCR is to amplify and quantify target sequence of DNA. The Taqman probe has a quenching dye attached to its 3’ end and a reporter dye on its 5’ end. In the intact Taqman probe, the quenching dye reduces the fluorescence of the reporter dye. However, during the amplification process, the Taq polymerase encounters the Taqman probe that is bound to the DNA being amplified and removes the 5’ fluorescently tagged nucleotide from the probe, distancing the remainder of the probe and continues amplification. This process separates the quencher from the reporter, so the reporter is free to release its energy in the form of light. The more amplification that takes place, the more reporter dye is release and more light is emitted and quantified by computer. The Taqman qPCR assay (Applied Biosystems, Foster City, CA) was used to profile the expression 46 genes chosen from the wound-healing literature (Table 4). 4.4.5  Gelatin Zymography  Gelatin zymography is a technique used to monitor enzymatic activity. It is based on sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE), but it includes a substrate, in this case, gelatin, copolymerized with the gel. The zymogram is stained a dark colour, so when the enzyme digests its substrate, the area looks clear. Of 57  the 6 patients with high and 5 patients with low MMP2 mRNA expression, in the Gosselink et al. study, 208 MMP2 activity had been measured using 10% zymogram gels with 0.1% gelatin (Biorad, Hercules, CA). The activity was quantified by densitometry of the digested bands with a Chemigenius Bioimaging System (Syngene, Cambridge, UK). 4.4.6  Statistical Analysis Gene expression from the lung parenchyma was correlated with the PM burden in  various compartments of the lung using a scatter diagram and subsequent linear association described in Section 4.2.4. Table 4 List of wound-healing genes in COPD Gene Symbol ADAM33 BCL2 COL1A1 COL3A1 CTGF EGF EGFR EGR1 F2R FGF2 FGFR FGG FN 1 GMCSF HBEGF ICAM1 IL-i B IL-4 IL-6 IL-8 IL-i 3 ITGA1  Gene Name ADAM metallopeptidase domain 33 BCL-2 collagen 1 alpha 1 collagen 3 alpha 3 connective tissue growth factor epidermal growth factor epidermal growth factor receptor early growth response 1 coagulation factor II (thrombin) receptor fibroblast growth factor 2 fibroblast growth factor receptor fibrinogen gamma chain fibronectin 1 granulocyte macrophage colony stimulating factor heparin binding epithelial growth factor intercellular adhesion molecule interleukin 1 beta interleukin 4 interleukin 6 interleukin 8 interleukin 13 integrin alpha 1 58  Gene Symbol MMP1 MMP2 MMP3 MMP8 MMP9 MMP 10 MMP 12 MMP 13 MUC5AC PDGFA PDGFRA PDGFRB PLAU PLAUR PTGS2 SERPINE2 TGFB 1 TGFB2 TGFB3 THBS1 TIMP1 TIMP2 TNF VEGF  Gene Name matrix metalloproteinase 1 matrix metalloproteinase 2 matrix metalloproteinase 3 matrix metalloproteinase 8 matrix metalloproteinase 9 matrix metalloproteinase 10 matrix metalloproteinase 12 matrix metalloproteinase 13 mucin 5 subtypes A and C platelet derived growth factor alpha platelet derived growth factor receptor alpha platelet derived growth factor receptor beta plasminogen activator urokinase plasminogen activator urokinase receptor prostaglandin-endoperoxide synthase serpin peptidase inhibitor, dade B, mem 2 transforming growth factor beta 1 transforming growth factor beta 2 transforming growth factor beta 3 thrombospondin 1 TIMP metalloproteinase inhibitor 1 TIMP metalloproteinase inhibitor 2 tumor necrosis factor vascular endothelial growth factor  4.5  Raman Microspectroscopy  4.5.1  Concepts  Raman spectroscopy is a technique based on the principles of the inelastic scattering of light, typically from a laser source. When photons strike the surface of the given element, they are absorbed and reflected back at a frequency different from that of the original light source. This difference in energy is the basis of the Raman effect. The Raman effect only makes up 0.00 1% incident photons, whereas the Rayleigh scattering (light emitted back at the same frequency) makes up the other 99.999%. Raman 59  spectroscopy is typically used in chemistry to look at specific vibrational energy of chemical bonds in molecules.  45.2  Rationale  Although the black pigment in the stained tissue is easily visualized microscopically, the composition of the particles retained in the lung tissues is unclear. This PM could be from cigarette smoke particles or other inhaled air pollution sources. Furthermore, even if one knows the composition of the original PM, post-retention biochemical changes in the tissues could have occurred. We have selected to use this technique in this pilot experiment over other techniques (ie. gas chromatography-mass spectroscopy (GC-MS)) for a number of reasons. Firstly, the technique had been used to 210 and had been shown to be useful describe PM in a study by Batonneau and colleagues in that regard. Secondly, it permitted the study of the particle in situ: all other techniques would require some form of tissue manipulation/extraction of the PM that could change their chemical composition. A further benefit of this technique would be that it could be done on the unfixed frozen tissue we used in our study. Finally, it had never been done before with tissue for the purposes of describing the chemical composition of the PM in tissue and may prove to be a novel way to describe the composition of PM. However, the downsides of this technique would be the fact that not all elements, such as some heavy metals, have a Raman spectrum, and would therefore not appear in the spectra. Time and instruction on the Raman instrument system was generously donated by the Chemistry Department in the Michael Smith Laboratories at the University of British Columbia.  60  4.5.3  Equipment and Software  For the purposes of this experiment, a Renishaw Ramanscope System 1000 (Renishaw) combined with an infinity-corrected Lecia DMLB microscope (Leica Microsystems, Richmond Hill, Ontario, Canada) was used. The laser in the Ramanscope system was an RL785 diode laser (Renishaw). For the purposes of the study, the 50x10.75 numerical aperture (NA) was used to focus the laser on the PM in the tissue and collect the inelastic scattering of light. The microscope was also equipped with a motorized and programmable stage (ProScan Series, Prior Scientific Inc., MA), which can move in any direction of the XYZ plane. A digital video camera is also attached to the microscope to allow real-time sample positioning via the connected computer monitor.  Typically, a Raman system consists of 4 parts: the laser, sample illumination and light collection optics, a wavelength selector, and a detector. In this system, the laser is directed through a beam expander that allows the beam to obtain uniform excitation. The excitation beam and the Raman scattered radiation are both directed to the holographic notch filter (HNF). The HNF lets the excitation beam reflect towards the sample via the microscope and allows Raman scattered radiation (coming back from the sample) to pass through to the detector. The HNF also rejects the Rayleigh scattering. The radiation travels to the grating spectrometer where it is dispersed and picked up by a thermoelectrically cooled AIMO CCDO2-06 CCD array detector (e2v technologies, Essex, UK). The signals detected by the CCD camera are sent to the Renishaw Windows-based Raman Environment (WiRE, version 1.3.30, Renishaw) and Graphic 61  Relational Array Management System software (Grams/32, version 4.14, Level II, Galactic Industries Corporation, Salem, NH).  4.5.4  Microscope Protocol  Lung sections 10 um thick of 2 cases were cut from frozen tissue in the same manner explained in Tissue Preparation section. The only difference was after the sections were cut, they were adhered to aluminum foil wrapped around plain glass slides (Figure 14). The reason for this was that silica (glass) has a strong Raman spectrum that would overpower most other elements, whereas the aluminum has virtually no spectra.  Figure 14 Tissue samples sectioned and melted onto aluminum foil wrapped around uncoated glass slide for Raman microspectroscopy use.  62  After allowing to air dry, the tissue (without coverslip) would be placed in the stage holder and the stage calibrated to point the laser directly at the black pigment in the tissue (Figure 15). Figure 15 Images captured from light microscope of the Raman system. A) The lighter colour is tissue, whereas the deep black pigment was the object of interest. B) The crosshairs would indicate the exact point where the laser would strike the tissue. II  1•  II  II  a  in  7*  II  —  ‘S  -.  A  One of the parameters of the microscope that can be controlled is laser power. We hypothesized that the main constituent of this black pigment was carbon, so under these conditions, it was possible to burn the carbon and the surrounding tissue. However, the laser power needed to be strong enough to provide a signal. Another factor to control is the exposure of the sample to the laser. For the best “exposure,” we found that a detector time of 30 seconds and a laser power of 25% seemed to give the best results. By results, the strongest peaks with the least amount of background noise. The microscope was set to a 50x objective lens. The program outputs data in wavelength number vs. arbitrary units of intensity (AUI).  63  Measurements were taken where the black pigment could be found within the tissue. Because of a lack of staining and processing, it is difficult to say exactly which compartment the black pigment was located. While adjusting the laser power, a new area of black pigment would have to be chosen because of that area might burn (characteristic of carbon). These measurements were taken on two different samples (cases) with black pigment visible to the naked eye.  64  5  Chapter Five: Results  5.1  Total Lung Burden  5.1.1  Observations  By observation alone, PM can be found in virtually all compartments of the lung. These compartments include: the parenchyma, airways, blood vessels, alveolar macrophages, and lymphoid follicles (Figure 16).  65  Figure 16 PM (black pigment) can be found in (A) the parenchyma, (B) alveolar macrophages, (C) airway wall, (D) blood vessel wall, and (E) lymphoid follicles. Jh  ‘.  44ff  %  c  I  .;•_  q  1’k2 f  ‘  r  4’  ‘S 4%  B  Sfl -  C  D 4  a  b  -  E  j  .  66  5.1.2  Comparison to Clinical and Histological Data  All compartments of the lung included (alveolar wall, airways, blood vessels, alveolar macrophages, lymphoid follicles), were grouped together for each case to get a total burden of PM. Non-smokers were compared with patients with those with COPD, and there was a significant difference (Student’s T-test, p< 0.0002) between them (Figure 17L). Patients who were smokers who had normal lung function were compared to those smokers with abnormal lung function, and there was also a significant difference (Student’s T-test, p<O.Ol) between these groups (Figure 17R). Figure 17: PM burden in non-smokers with normal lung function and those with COPD (L) and the PM burden in smokers with normal lung function (GOLD 0) and those with abnormal lung function (GOLD 1-4) (R)  —  0.025  —  CO 0  0002 0.020  CO  ‘I-  0.025 0.020  *p<0.0l  ann4e  C  C.  :  10.010  10.010  C  0.005 0.005 00000 Nor’mal  0.000  -V  Normal PFT  —  Abnormal PFT  Student t-tesf  Student t-test  When compared to each other, it appeared as if the non-smoking control had the smallest Vv of PM in all lung tissue (Figure 18). The trend of increasing Vv of PM seemed to increase up to GOLD 2, and then decrease in the GOLD 3 and 4 group. However, the only groups that were significantly different from each other were the non smoking control group and the GOLD 2 group (Tukey-Kramer, p<O.O5). 67  Figure 18 Vv of PM in all lung tissues across non-smoking controls and groups of increasing COPD severity. Non-smoking controls and GOLD 2 groups were significantly different (p<O.O5).  0.030  0025  0.020  0  0.015  4-  0 >  >  0.010  0.005  0.000 Non-smoking  Smoking  GOLD I  GOLD 2  GOLD 3+4  COPD Severity  If the GOLD 3 and 4 group was removed and the Kruskall-Wallis ANOVA is applied, then there is a significant difference  (p<O.0005) between the remaining groups  (Figure 19).  68  Figure 19 Burden of PM with increasing levels of COPD severity  •  0.03.  C)  z  *p<0 0005  (0 (0  0.02. z 0.01. 0  0.00•  I  ::::::::::.::::::::::::::::  Smokers  GOLD I  I  I  Non-smker  GOLD 2  One way ANOVA (Kruskall.WaIIis test)  The Vv of PM in each of the cases was also plotted against the clinical and 2 value of 0.13 and a /FVC had an r 1 historical data (Table 5). The Vv of PM against FEV  negative slope (-0.0002) (p  =  0.02) (Figure 20A). The Vv of PM against pack years had  2 value of 0.15 and a positive slope (0.0002) (p an r  <  0.01) (Figure 20F).  Table 5 Correlation of PM burden in all compartments of the lung with clinical and histological values 2 r  Slope  p-value  FEV1/FVC  0.13  -0.0002  0.02  FEV1  0.05  -0.0001  0.053  0.0004  0.000004  0.89  Airway thickness  0.02  0.00005  0.25  Age  0.02  0.0002  0.17  Pack Years  0.15  0.0002  Clinical/Histological Parameters  Lm  <  0.01  69  1 C) vs. Lm D) vs. /FVC B) vs. FEV 1 Figure 20 Vv of PM in all tissue A) vs. FEV airway wall thickness E) vs. age F) vs. pack years  >  0.1 0.09 0.08 0.07 0.06 0.05 0.04  >  •  0.03  0.1009 0.08 0,07 0.06’ 0.05 0.04 0.03  •  •  •  •  —0.01  —0.01  0’ —0.01’ 150  .  .  0,1• 0.09 0.08 > 0.07 0.06 0.C5 a 0.040.03°0.02-  • ..  •  .  I  B  A  0.1• 0.09 0.08 > 0.07 0.06’ 0.05 0.04 a 0.03 0 02’ 0.01’  I  10 20 30 40 50 60 70 80 90 1001101: FEV1  20 30 40 50 60 70 80 90100110120130140 FEV1iFVC  . •  • .  0-  •  200  250  300  I  I  I  350  400  450  Lrn  > -  .  200  250  D  C 0.1 0.09 0.080.070.060.05’  .  150 100 AWThicness  50  500  .  •  >  0.10,090.080.070.060.05* .*...  40  45  50  55  60 Age  65  70  75  80  E  -20  0  20  40  60 80 100 120 140 160 Pack Ye8IS  F  70  5.1.3  Comparison to mRNA Expression  The only gene where expression in the parenchyma weakly correlated with the particle burden in all compartments of lung was fibrinogen gamma chain (FGG), which is 2 value of 0.22 essentially a marker for fibrinogen production. This correlation had an r  and a positive slope (0.001) (p <0.01) (Figure 21).  Figure  21 Vv of PM  in all  tissue vs. expression  of FGG in the parenchyma  0.1 0.090.080.070.060.050.04-  °-  .  o2s751bi.515 FOG  5.2  Alveolar Wall  5.2.1  Comparison to  Clinical and  Histological  Data  Separating the alveolar wall from the total lung burden, the results indicate larger difference between COPD severity groups (Figure 22). The non-smoking control and smoking control groups were significantly different (Tukey-Kramer, p<O.05) from GOLD 2, but not significantly different when compared to GOLD 1 and 3/4.  71  Figure 22 Vv of PM in the alveolar wall across the non-smoking group and the COPD severity groups 0.025  * *  0.020  I  0.015  0.010  0.005  0.000 Non-smoking  Smoking  GOLD 1  GOLD 2  GOLD 3+4  COPD Severity The Vv of PM in the alveolar wall in each of the cases was also plotted against 2 /FVC had an r 1 the clinical and historical data (Table 6). The Vv of PM against FEV  value of 0.16 and a negative slope (-0.0002) (p  =  0.001) (Figure 23A). The Vv of PM  2 value of 0.13 and a positive slope (0.0001) (p <0.01) (Figure against pack years had an r  23F).  72  Table 6 Correlation of the PM burden in the alveolar wall with clinical and histological values 2 r  Slope  p-value  FEV1/FVC  0.16  -0.0002  0.001  FEV1  0.05  -0.0001  0.07  0.0004  0.000004  0.95  0.06  0.00007  0.10  0.0001  0.0002  0.39  0.13  0.0001  <0.01  Clinical/Histological Parameters  Em Airway thickness Age Pack Years  73  1 C) vs. Lm D) IFVC B) vs. FEV 1 Figure 23 Vv of PM in the alveolar wall vs. A) FEV vs. airway wall thickness E) vs. age F) vs. pack years. AlvWall Alveolar wall =  008-  008  007-  0.07 0.06  0.06>  >  005-  0.05-  0.04-  0.04’  :  0.030  0.02-  0.03  ...  0.02’  . —-__  °  —0.01— I I 20 30 40 50 60 70 80 90 100110120130140 FEV1JFVC  —J01. 10 20 30 40  A  I  50 60 70 80 90 100 110 12 FEV1  B  0.08  uvo-  0.07-  0.07  0.06-  0.06  >  > oos-  0.05  004-  0.04’ 0.03  0.03-  0.02’  0.02-  -001-  150  .  .  .  .:  200  300  250  350  I  I  400  450  -001  i  -rrm--’r-  200  150 100 AW Thclrness  50  50  Lm  5  D  C 0080.07  0.07-  006’  0.06>  0.05-  >  0.03-  0.03-  .  .  0.02-  :  .  .  45  50  55  60 Age  .  0.01  I  I  65  70  75  .  0.02-  G.0: —43.01— 40  0.05’ 0.04-  004-  :.  .  -20  80  E  • :._—  _——:.  I  I  0  20  I  40  I  60 80 100 120 140 160 Pacl< Years  F  74  In addition, the PM Vv in all lung tissue was compared to the PM Vv in alveolar wall, and had a strong positive correlation (slope  .71,  p<O.Ol) with an r2 value of 0.74  (Figure 24).  Figure 24 Vv of PM in all lung tissue vs. Vv of PM in the alveolar wall  u 0.08  —0.01•  I  -0.01 0  I  I  I  I  I  I  I  .01 .02 .03 .04 .05 .06 .07 .08 .09  .1  PM1O Tissue Vv  5.2.2  Comparison to mRNA Expression As with the PM burden in all tissue, the only gene that weakly correlated with the  particle burden in all compartments of lung was fibrinogen gamma chain essentially a marker for fibrinogen. This correlation had an positive slope  (0.001) (p  <  0.01)  (Figure  2 r  (FGG),  which is  value of 0.19 and a  25).  75  Figure 25 Vv of PM in the alveolar wall vs. expression of FGG in the alveolar wall 0.08  O.07 O.06 0.05 O.04  FGG  5.3  Blood Vessel Burden  5.3.1  Comparison to Clinical and Histological Data The majority of PM was observed in the adventitia of the blood vessels. It is  unclear where the PM are The PM burden across the COPD severity groups showed a significant difference between the smoking control and GOLD 2 group (p=O.Ol) (Figure 26). All other groups, when compared to each other, were not statistically significant. Because the adventitial tissues are adjacent to alveolar walls, some of these PM may also reside in or maybe part of PM in alveolar walls. The PM in vessel walls may also be in lymphatic channels and be part of the lymphoid system. Further studies are needed to delineate these issues.  76  Figure 26 Vv of PM in the blood vessel walls across the non-smoking group and the COPD severity groups 3.5  3.0  2.5  2.0 1.5  1.0  0.5  0.0 Non-smoking  Smoking  GOLD 1  GOLD 2  GOLD 3+4  COPD Severity The Vv of PM in the blood vessesi in each of the cases was also plotted against /FVC had an 1 the clinical and historical data (Table 7). The Vv of PM against FEV value of 0.18 and a negative slope (-0.0002) (p  =  0.001) (Figure 27A). The Vv of PM  against pack years had an r 2 value of 0.13 and a positive slope (0.0001) (p <0.01) (Figure 27F).  77  Table 7 Correlation of the PM burden in the blood vessel wall with clinical and histological values 2 r  Slope  p-value  FEV1/FVC  0.18  -0.0002  0.001  FEV1  0.05  -0.0001  0.07  0.0004  0.000004  0.95  0.06  0.00007  0.10  0.0001  0.0002  0.39  0.13  0.0001  Clinical/Histological Parameters  Em Airway thickness Age Pack Years  <  0.01  78  Figure 27 Vv of PM in the blood vessel wall A) vs. FEV IFVC B) vs. FEy 1 1 C) vs. Lm D) vs. airway wall thickness E) vs. age F) vs. pack years  6  S  5,  S  3,  0.  I  I  I  0-  I  20 30 40 50 60 70 80 90 10011012013014 FEVI /FVC  6  6’  5.  5-  0150  200  250  350  300 Lrn  400  450  I  10 20  500  30 40  50  •I’I  I•  50 60 70 80 90 100 iiOi FE Vi  100  150  200  250  C  D  6-  6-  5.  5. 4-  3-  0 I  I: -20 Age  E  0  20  40  60 80 100 120 140 160 Pack Years  F  When the PM burden in the blood vessels was compared to the PM burden in all tissue and the parenchyma, it had an r 2 value of 0.29 and a positive slope (50.62) (p  <  79  2 value of 0.29 and a positive slope (60.05) (p <0.001) 0.00 1) (Figure 28A) and an r  (Figure 28B). Figure 28 A) Vv of PM in all lung tissue vs. Vv of PM in the blood vessel wall B) Vv of PM in parenchyma vs. Vv of PM in the blood vessel wall  -0.010  .01 .02 .03 .04 05 .06 07.08 .09 PM10 Tissue Vv  1  -0.010  01  02 03 .04 .05 PMlOPJvwaIt Vv  06  .07  B  .08  With the blood vessels traced, it was also possible to compare the wall area with 2 value of 0.12 and a positive slope (0.02) (p the PM burden, and that resulted in an r  <  0.00 1) (Figure 29).  80  Figure 29 PM area in the blood vessel vs. the wall area of the blood vessel 1.4e+5 1.2e+5 -j  1.00+6 8Oe+4  .  I -f  .  I  ..  -1 I  . • •.• • •  6.0e+4-f  II  •  4.Oe+4-f  •?‘  •  i.••  .•  I  -2.Oe-i-4 -2.Oe+5  0.0  2.Oe+5 4.Oe+5 6.Oe+5 8.Oe+5  1.Oe+6  1.2e+6  1.4e+6  1.6e+6  Wall Area (Pixels) •  Wall Area vs PM Area Plot I Regr  Wall area can also be correlated with the clinical data and histological analysis (Table 8). The wall area % against FEV 2 value of 0.07 and a positive slope 1 had an r (0.11) (p = 0.03) (Figure 30B). Table 8 Correlation of blood vessel wall thickness and clinical and histological values 2 r  Slope  p-value  FEV1/FVC  0.007  0.04  0.52  FEV1  0.07  0.11  0.03  Lm  0.01  -0.000004  0.34  Airway thickness  0.07  0.08  0.07  Age  0.001  0.04  0.80  Pack Years  0.006  0.006  0.90  ClinicaLIHistological Parameters  81  1 C) vs. Lm Figure 30 Blood vessel wall area thickness A) vs. FEV /FVC B) vs. FEy 1 D) vs. airway wall thickness E) vs. age. F) vs. pack years  80-  80  •  70-  70  20I 1 I I 20 30 40 50 60 70 80 90 100110120130140 FEV1IFVC  20  .1  I  10 20 30 40 50 60 70 80 90 100 110 120 FEV1  A  B  80-  8070-  •  0  200  250  300  70-  .  •  350  400  450  500  Lm  80-  C  • •:_  •  •  •  70  40  55  ••  —---------—-————  30 I  50  D  40  •  45  250  5Q  •.  •.  •  20-  .  >60  .  4030-  200  80 •  •  100 150 AVY Thickness  50  .  •  70-  60-  •  60 Age  65  I  I  70  75  20 80  -20  E  I  I  0  20  I  40  I  I  60 80 100 120 140 160 Pack Years  F  When the wall area % of the blood vessels was compared to the PM burden in all tissue and the parenchyma, it had an  2 r  value of 0.02 and a positive slope (123.14) (p =  82  2 value of 0.06 and a positive slope (217.98) (p 0.21) (Figure 31A) and an r  =  0.06)  (Figure 31 B), respectively. Figure 31 A) Vv of PM in all lung tissue vs. blood vessel wall area thickness B) Vv of PM in parenchyma vs. blood vessel wall area thickness  E  ———  :  5.3.2  30-  30  20— -0.01O.01.02.03.04.05.0607.08.09.1 PM1O Tissue Vv  20 0.010  01  B  .02030405.0607,08 PM1 0 .SJvwall Vv  Comparison to mRNA Expression There were no correlations with the PM burden in the blood vessels and the  mRNA expression. However, there were correlations with the blood vessel wall thickness  2 value of 0.44 and a negative slope (Table 9). The wall area % against IL-4 had an r  (-  2 value of 0.27 1.01) (p <0.01) (Figure 32A). The wall area % against PDGFRB had an r and a negative slope (-0.50) (p  <  0.01) (Figure 32C). The wall area % against TGFB1  had an r 2 value of 0.23 and a negative slope (-1.72) (p  <  0.01) (Figure 32D). The wall  2 value of 0.18 and a negative slope (-1.72) (p <0.01) area % against TNF had an r 2 value of 0.18 and a negative (Figure 32E). The wall area % against VEGF had an r slope (-0.36) (p <0.01) (Figure 32F).  83  Table 9 Correlation of mRNA expression with blood vessel wall thickness mRNA Expression  2 r  Slope  p-value  IL-4  0.44  -1.01  IL-13  0.24  -18.55  PDGFRb  0.27  -0.50  <  TGFb1  0.23  -1.72  <0.01  TNF  0.18  -1.72  <0.01  VEGF  0.18  -0.36  <  <  0.01  0.08 0.01  0.01  84  Figure 32 Blood vessel wall area thickness A) vs. IL-4 B) vs. IL-13 C) vs. PDGFRB D) vs. TGFB1 E) vs. TNF F) vs. VEGF 9a•  9080-  80  •  70-  70  1  2001I214  J012b23b340  IL-13  IL-4  j3  90  90 80-  80  •  46  b  0  56  b  20mj 70  PDGFR8  c  TGFB1  D  VEGE  F  9080-  80-  •  I..  70-:  70-i..  2001;l2O TNF  E  85  5.4  Lymphoid Follicle Burden  5.4.1  Comparison to Clinical and Histological Data In the lymphoid follicles, the PM burden had no significant difference across the  COPD severity groups (Figure 33). Non-smoking controls were not included in because they were not present in these patients and the analysis was limited to those cases that had one follicle or more. Figure 33 Vv of PM in the lymphoid follicles across COPD severity groups 7  6  .1  U)  a)  0  5  0 U-  -o 0  4  0  E>‘  -J  3  2 >  >  0— Smoking  GOLD 1  GOLD 2  GOLD 3+4  COPD Severity  Vv of PM in the lymphoid follicles can also be correlated with the clinical data and histological analysis (Table 10 and Figure 34).  86  Table 10 Correlation of the PM burden in the lymphoid follicles with clinical and histological values ClinicallHistological Parameters  2 r  Slope  p-value  FEV1/FVC  0.04  -0.04  0.35  FEV1  0.07  0.04  0.22  0.0006  -0.004  0.34  Airway thickness  0.02  0.02  0.07  Age  0.02  0.05  0.80  Pack Years  0.01  0.02  0.90  Lm  87  Figure 34 Vv of PM in lymphoid follicles A) vs. FEV IFVC B) vs. 1 1 FEy C) vs. Lm D) vs. airway wall thickness E) vs. age F) vs. pack years  15-  15  10  :.H.; 20 30 40 50 60 70 80 90 100110120130140 FEV1/FVC  10  A  20 30 40 50 60 70 80 90 100 110 120 FEV1  B  15-  _ 10 u_ a •  5 ..  0150  ••  .  .  —.  0  .•  I  I  200  250  350  300  400  450  50  500  100  150 AW Thickness  C  Ln,  15-  IS  10-  10  200  250  D  :-:•. 40  45  50  55  60 Age  65  70  75  80  -20  0  20  40  60 80 100 120 140 160 Pack Years  When the Vv of PM in the lymphoid follicles was compared to the blood vessel wall area and Vv of PM in the blood vessels, it had an r 2 value of 0.008 and a negative slope (-0.02) (p  2 value of 0.05 and a negative slope (-0.70) 0.67) (Figure 35A) and an r 88  (p  =  0.31) (Figure 35B), respectively. When the Vv of PM in the lymphoid follicles was  2 value of 0.002 compared to the Vv of PM in the parenchyma and in all tissue, it had an r and a negative slope (-21.55) (p negative slope (-15.15) (p  =  2 value of 0.001 and a 0.82) (Figure 35C) and ar  0.87) (Figure 35D), respectively.  =  Figure 35 Vv of PM in the lymphoid follicles vs. A) blood vessel thickness, B) Vv of PM in the blood vessel wall, C) Vv of PM in the parenchyma, and B) Vv of PM in all tissue.  ID. . Q.  s.  •  20  ID  4::  SI  I  I  4  5  I  fl  71)  1  IIC  ;i  2  %P M Mti  A  B  c 5, —  —  • I  -(I 01  0  01  02 0 04 P.q10tJ,-.i  uS  (11  (17  III 0  ujii  01  (12  I  I  (lI  04  I  (15  0i  I  07 0  .  C  D  89  5.5  Alveolar Macrophage Burden  5.5.1  Comparison to Clinical and Histological Data  In the alveolar macrophages, the PM burden in the alveolar macrophages showed a significant difference (p  =  0.0075, Tukey-Kramer) between the non-smoking and  GOLD 1 groups when compared to the GOLD 2 group (Figure 36). Figure 36 Vv of PM in alveolar macrophages across the non-smoking and COPD severity groups  0.35  0 G)  0.30  (U  -c  0 0 C) CU  0.25  0.20 (U 0 G) >  0  0.15  0.10  ‘S >  >  0.05  0.00 Non-smoking  Smoking  GOLD 1  GOLD 2  GOLD 3+4  COPD Seventy  The Vv of PM in the alveolar macrophages can also be correlated with the clinical /FVC had an 1 data and histological analysis (Table 11). The Vv of PM against FEV  90  value of 0.065 and a negative slope (-0.0002) (p  =  0.04) (Figure 37A). The Vv of PM  2 value of 0.24 and a positive slope (0.003) (p <0.01) (Figure against pack years had an r 37F). Table 11 Correlation of the PM burden in the alveolar macrophages with clinical and histological values 2 r  Slope  p-value  FEV1/FVC  0.07  -0.0002  0.04  FEV1  0.01  -0.0009  0.34  Lm  0.004  0.0002  0.63  Airway thickness  0.02  0.000 1  0.16  Age  0.04  0.003  0.10  Pack Years  0.24  0.003  Clinical/Histological Parameters  <  0.01  91  1 C) vs. IFVC B) vs. FEy 1 Figure 37 Vv of PM in alveolar macrophages A) vs. FEV Lm D) vs. airway wall thickness E) vs. age. F) vs. pack years 0.90.8  0.80.7-  0.7  0.6-  0.6  •  0.5 GA  0.4-  0.3  a 0.3  P..  0-  0  •.  I  I  I  —  I  ‘•‘‘  20 30 40 50 60 70 80 90 100110120130140 FEV1iFVC  •  •.  I  I  ••S .....  I  10 20 30 40 50 60 70 80 90 100 110 120 FEV1  A  B  0.9 0.8  0.8-  0.7  •  070.6-  0.6  •  04’ 0.3-  .  0.20.1  0.3  .  .  .  :.  —.  .  •  250  .  •  •.  .  .  •  —  .  ?..  0’  .  I  1  200  •  •  0.1  -  0—0.1150  •  0.2’  . .  350  300  400  450  500  Lm  100 150 AW Thkness  50  C  250  200  D  0.90.8 0,7  0.80.70.6-  0.6  •  I  40  45  50  55  60 Age  65  70  75  80  -20  E  0  20  40  I  I  60 80 100 120 140 160 PacII Years  F  92  5.6  Raman Spectroscopy The Raman spectra showed peaks at 1320 nm and 1590 nm, and also smaller  peaks at 2622 nm and 2638 nm (Figure 38).  Figure 38 Raman spectra of Case 1984  4000  ‘  D  3000  >, U) C .  2000  C C U)  E  D  1000  (‘3 I—  1.  —1000  I  0  500  1000  1500  2000  2500  3000  3500  4000  Raman Wavelength (nm)  93  6  Chapter Six: Discussion and Conclusion  6.1  PM Burden in the Lung  6.1.1  All Tissue  The data showed an incremental increase in PM retained in the lung tissues as COPD severity increases, except in the very severe cases (GOLD 3&4). The amount of PM retained in the lungs seems to plateau off in the severe cases (Figure 18). The bulk of this PM was retained in lung parenchyma, but PM was also retained in blood vessel walls, submucosal tissues, and lymphoid tissues as well as in airway macrophages. GOLD 2 had the highest levels of PM retained in the lung and reached up to 2% of the lung tissues. The reason why the Vv of PM retained in lung tissues decreases in GOLD 3 and 4 groups is unclear. Recent studies from our lab have shown significant lost in lung tissues with progression in COPD specifically in GOLD 3&4 cases. The lung tissues that disappear are specifically small airways and lung parenchyma. This possibly could have happened via apoptosis of lung cells with progression of the disease. It is reasonable to postulate that the tissues with high levels of PM retention are preferentially vulnerable to apoptosis and subsequently lost. With obliteration of the small airways, for example, there may be nothing left for the PM to deposit onto. These findings are novel as there are no studies to our knowledge that have used this technique to quantify the burden of PM in COPD. It is clear from the current data that PM can be deposited or translocated to virtually all compartments of the lung, including the parenchyma, blood vessels, alveolar macrophages, and lymphoid follicles. What is not clear, however, is how long the PM  94  resides in these different compartments and the relative contributions of retained PM in each of the compartments to the documented chronic lung inflammation in 1 and There was a positive correlation between lung function data (FEy /FVC) and the total burden of PM in the lung. These associations fit the hypothesis 1 FEV by suggesting that as the particle burden increases, the lung function decreases. However, these associations were weak and suggest that PM retention in the lung tissues is just one of the potential factors that contribute to the decrease of lung function in COPD. There are potentially multiple pathways between the amount of PM deposited and retained in the lung and the eventual decline in lung function. Future studies could look at the retention of PM in specific compartments (small airways, for example) and alteration of lung function to determine if the location of PM deposition and retention is the determining factor for loss of lung function. Fibrinogen expression in the parenchyma correlated with the PM burden in the lung (Figure 21). Circulating fibrinogen in the blood has been shown to be elevated in the ’ and this 21 blood stream when subjects have been exposed to ambient air pollution 212 During moderate to increased fibrinogen has been implicated in cardiovascular deaths. severe exacerbations of COPD, fibrinogen levels in the blood have been shown to be 213 Smoking has also been shown to increase the levels of circulating elevated. . My data is the first to suggest that there is activation of fibrinogen 214 fibrinogen production in the lung tissues with an increasing PM-burden in the parenchyma of the lungs.  95  6.1.2  Alveolar Wall  The burden of PM in the alveolar wall showed a very similar trend to that of the PM burden in all compartments of the lung, which suggests that most of the PM is being deposited in the parenchyma. This phenomenon could be due to the fact that the greatest tissue volume compartment in the lung is the parenchyma. This predominant deposition of PM in the lung alveolar wall suggests that the majority of PM that is retained in the lung is of smaller size, because it is these smaller particles that have the ability the reach the alveolar spaces. Alternatively, it could also imply that the clearance of PM from the alveolar spaces is not as good as from the airways. There was a significant correlation between PM burden and lung function and pack years of cigarette smoking as already demonstrated in the total lung burden analysis suggesting cigarette smoking significantly contribute to the burden of PM retention in lung alveolar wall. The only mRNA expression data that correlated with PM-burden in the alveolar wall was also FGG, similar to the total lung burden (Figure 25).  6.1.3  Blood Vessels Particulate matter retained in blood vessel walls was predominantly found in the  adventitial layer and not in the muscle layer of vessels. The exact location of retained PM in the adventitia is unclear from the histological sections, but it is reasonable to postulate that the particles could be in lymphoid ducts in the adventitial layer seeing that the lymph ducting of the blood vessels is one of the paths of transport for particles. However,  96  further studies are needed to identify their location in vessel walls, specifically in the adventitia layer. Smokers with normal lung function (GOLD 0) have lower levels of PM in vessel walls than smokers with COPD (GOLD 2 group, Figure 26). Interestingly, the relatively large amount of PM found in the blood vessels of non-smokers was similar to smokers with normal lung function (smoking controls). This suggests environmental sources of PM exposure contribute significantly to PM retention in the lungs of normal non-smokers and potentially contribute evenly to the lung burden of PM in non-smokers and smokers alike. The PM burden in the blood vessels more strongly correlates with lung function /FVC) than total lung or alveolar wall PM burden do. Generally considered to be 1 (FEV an alternate hypothesis for systemic inflammation, the PM has, in at least one study,’ ° 8 been shown to translocate via the blood vessels into the bloodstream. There was no correlation with the PM burden found in the blood vessel wall and RNA expression in lung tissues. However, there was some correlation between mRNA expression and blood vessel wall thickness. IL-4 seems to be inversely correlated with blood vessel wall thickness. IL-4 acts by increasing the vascular permeability 215 and could promote PM deposition in blood vessel wall via this fashion. TGF-131 expression increases as the blood vessel wall thickness decreases, which may point to a potential apoptotic pathway activated by TGF-3l. The trend for other pro-inflammatory mediators, such as, PDGF3, TNF-a, and VEGF, were also to be higher when vessel walls are thinner. The reason for this inverse relationship between RNA expression of pro inflammatory mediators and thin vessel walls is unclear and needs further investigation.  97  6.1.4  Lymphoid Follicles  There seems to be no significant change in the PM burden in the lymphoid follicles between groups. This result may be due to the low number of lymphoid follicles found in the smoking and COPD cases. There were also no correlations between PM burden in the lymphoid follicles and the clinical or histological data, as well as, the mRNA expression. There also seems to be no relationship between the deposition of PM in the lymphoid follicles and the deposition elsewhere in the lung, such as the parenchyma and blood vessels.  6.1.5  Alveolar Macrophages  There seems to be no discemable trend in PM burden in the alveolar macrophages across COPD seventies. There is a significant but weak correlation with pack years, which is likely due to a rich smoking history; there is no mRNA expression data that correlates with this data. 6.2  Raman Spectroscopy  The Raman spectra showed a pair of peaks that is similar to the spectrum of graphite carbon. Carbon has a number of Raman spectra depending on the bonding of the ° found that 21 molecules (diamond only has one peak). The study by Battonneau et al. carbonaceous soot had a Raman spectrum with peaks at 1324 nm and 1582 nm, which is  98  very nearly the same peaks as found by our experiments. This finding suggests that what is left in the lung is merely the carbon core alone and any other inorganic compounds or metals may have long since been processed or dissolved. What these results also show is that this spectral analysis can be successfully used in the in situ environment. With relatively little background noise, the presence of carbon or other elements with a Raman spectrum can be visualized, without a large degree of processing to separate out the PM from the tissue. The benefit of a lack of processing keeps the PM as close to the original form before sectioning, reducing the steps that may cause a potential loss of PMassociated agglomerates. Unfortunately, there are downsides to Raman spectroscopy. Firstly, the process is not the best for working backwards. More specifically, the process is best used after mass spectroscopy to confirm the presence of certain elements. In addition, not all elements have a Raman spectra, so if some heavy metals were indeed present, this process alone would not discover them. Finally, in this process, it is difficult to say what compartment the PM is coming from, whether it is from the blood vessels, the parenchyma, or airways, because the tissue is unstained and the imaging system does not have a particularly high resolution. Future directions for this technique can be to expand the number of cases to compare the composition between COPD severity groups. Other chemical composition techniques, such as GC-MS, could be done and the results compared. In addition, results obtained after removing the tissue to separate the PM could be compared with the in situ results to see if there is any difference in composition using different techniques.  99  6.3  Conclusion The results from this study show that PM is retained in the lungs of normal non  smokers, smokers with normal lung function and COPD patients. In fact, with the exception of GOLD 3/4 patients, there is a graded increase in PM retention between these groups. It is not clear from this study how and by what mechanism the PM are deposited or retained in the lung. It seems as if PM can be found in virtually every tissue compartment of the lung; however, the majority of resides in the parenchyma. Interestingly, those that do not smoke also had significantly observable amounts of PM in their lung tissues, which suggests that PM from other sources, such as the environment, contributes to the PM burden in the lung of smokers and non-smokers. The role of PM deposition and retention in perpetuating lung inflammation and its role in the systemic inflammatory response associated with COPD remains unclear from the results of this study. Future studies would benefit from looking at the expression of genes implicated in COPD by looking at the exact location of the PM retention using Laser Capture Microdissection. Whether or not the inhibition of the clearance of PM from the lung due to COPD is the major contributing factor to an increasing PM burden in lung tissues is unclear from our data. The significant burden of PM in normal non smokers suggests that at least part of the PM retained is due to the magnitude of exposure and not due to the lung disease per Se. Our studies suggest that the PM retained in the lung does elicit an ongoing inflammatory response, but these studies need to be expanded to determine which inflammatory pathways (Figure 1 and 6) are predominantly involved Compositional analysis of retained PM suggests that carbon is the major component of the PM in lung tissues. In controlled animal and human studies, carbon  100  black has been shown to elicit both a local inflammatory response in the lung as well as a systemic inflammatory response. However we cannot exclude the possibility that the PM in the lung tissues has other deleterious components, such as, heavy metals, bacteria, viruses or organics components. Ultimately, we speculate that the PM does contribute to a low-grade lung and systemic inflammatory response in the lungs of subjects with COPD, which affects the progression of this disease.  101  References  1.  O’Donnell DE, Hernandez P, Kaplan A, et al. 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Apr 1 2003; 170(7): 3835-3842. .  114  Appendix Table 12 List of Abbreviations Abbreviation AM ATS AUI BAL BOLD CAREX COPD cDNA DNA DALYS ETS EGF ENA-78 ELF ERS ECM FGF FEV1 FVC GOLD GM-C SF GRO-a H&E HO-i HNF HIV ICAM- 1 IFN IL ILO LCM PLATINO LIF MMP mRNA mEPHX MCP- 1 NE NO  Full Title Alveolar macrophage American Thoracic Society Arbitrary units of intensity Bronchial Alveolar Lavage Burden of Obstructive Lung Disease Initiative Carcinogen Exposure Chronic Obstructive Pulmonary Disease Copy DNA Deoxyribonucleic acid Disability Adjusted Life Years Environmental tobacco smoke Epidermal growth factor Epithelial cell-derived neutrophil-activating peptide-78 Epithelial lining fluid European Respiratory Society Extracellular Matrix Fibroblast growth factor Forced Expiratory Volume in 1 second Forced Vital Capacity Global Initiative Chronic for Obstructive Lung Diseases Granulocyte-macrophage colony stimulating factor Growth-related onocogene-aipha Hematoxylin and Eosin Heme-oxygenase- 1 Holographic notch filter Human Immunodeficiency Virus Inter-cellular adhesion molecule-i Interferon Interleukin International Labour Organization Laser capture micro dissection Latin American Project for the Investigation of Obstructive Lung Disease Leukemia inhibatory factor Matrix Metalloproteinase Messenger RNA Microsomal epoxide hydrolase Monocyte chemoattractant protein-i Neutrophil Elastase Nitric oxide 115  Abbreviation NF-kB NA OR OCT PM PA}Ts PMN qPCR ROS ROFA RNA SOP 3 -D TSP TGFB1 TB TNFa 2-D VEGF Vv  Full Title Nuclear Factor kappa-light-chain-enhancer of activated B-cells Numerical aperture Odds ratio Optimal cutting temperature Particulate matter Polyaromatic hydrocarbons Polymorphonuclear Leukocytes Quantitative polymerase chain reaction Reactive oxygen species Residual oil fly ash Ribonucleic acid Standard operating procedure Three-dimensional Total suspended particles Transforming Growth Factor Beta-i Tuberculosis Tumour Necrosis Factor alpha Two-dimensional Vascular endothelial growth factor Volume fraction  116  

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