Future research directions in chronic obstructive pulmonary disease

Elastin-derived peptides favor type 2 innate lymphoid cells in chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is a condition characterized by chronic airway inflammation and obstruction, primarily caused by tobacco smoking. Although the involvement of immune cells in COPD pathogenesis is well established, the contribution of innate lymphoid cells (ILCs) remains poorly understood. ILCs are a type of innate immune cells that participate in tissue remodeling processes, but their specific role in COPD has not been fully elucidated. During COPD, the breakdown of pulmonary elastin generates elastin peptides that elicit biological activities on immune cells. This study aimed to investigate the presence of ILC in patients with COPD and examine the impact of elastin peptides on their functionality. Our findings revealed an elevated proportion of ILC2 in the peripheral blood of patients with COPD, and a general activation of ILC as indicated by an increase in their cytokine secretion capacity. Notably, our study demonstrated that serum from patients with COPD promotes ILC2 phenotype, likely due to the elevated concentration of IL-5, a cytokine known to favor ILC2 activation. Furthermore, we uncovered that this increase in IL-5 secretion is partially attributed to its secretion by macrophages upon stimulation by elastin peptides, suggesting an indirect role of elastin peptides on ILC in COPD. These findings shed light on the involvement of ILC in COPD and provide insights into the potential interplay between elastin breakdown, immune cells, and disease progression. Further understanding of the mechanisms underlying ILC activation and their interaction with elastin peptides could contribute to the development of novel therapeutic strategies for COPD management.NEW & NOTEWORTHY Elastin-derived peptides, generated following alveolar degradation during emphysema in patients with COPD, are able to influence the response of type 2 innate lymphoid cells. We show that the orientation of innate lymphoid cells in patients with COPD is shifted toward a type 2 profile and that elastin peptides are indirectly participating in that shift through their influence of macrophages, which in turn impact innate lymphoid cells.

Machine learning associated with respiratory oscillometry: a computer-aided diagnosis system for the detection of respiratory abnormalities in systemic sclerosis

INTRODUCTION

The use of machine learning (ML) methods would improve the diagnosis of respiratory changes in systemic sclerosis (SSc). This paper evaluates the performance of several ML algorithms associated with the respiratory oscillometry analysis to aid in the diagnostic of respiratory changes in SSc. We also find out the best configuration for this task.

METHODS

Oscillometric and spirometric exams were performed in 82 individuals, including controls (n = 30) and patients with systemic sclerosis with normal (n = 22) and abnormal (n = 30) spirometry. Multiple instance classifiers and different supervised machine learning techniques were investigated, including k-Nearest Neighbors (KNN), Random Forests (RF), AdaBoost with decision trees (ADAB), and Extreme Gradient Boosting (XGB).

RESULTS AND DISCUSSION

The first experiment of this study showed that the best oscillometric parameter (BOP) was dynamic compliance, which provided moderate accuracy (AUC = 0.77) in the scenario control group versus patients with sclerosis and normal spirometry (CGvsPSNS). In the scenario control group versus patients with sclerosis and altered spirometry (CGvsPSAS), the BOP obtained high accuracy (AUC = 0.94). In the second experiment, the ML techniques were used. In CGvsPSNS, KNN achieved the best result (AUC = 0.90), significantly improving the accuracy in comparison with the BOP (p < 0.01), while in CGvsPSAS, RF obtained the best results (AUC = 0.97), also significantly improving the diagnostic accuracy (p < 0.05). In the third, fourth, fifth, and sixth experiments, different feature selection techniques allowed us to spot the best oscillometric parameters. They resulted in a small increase in diagnostic accuracy in CGvsPSNS (respectively, 0.87, 0.86, 0.82, and 0.84), while in the CGvsPSAS, the best classifier's performance remained the same (AUC = 0.97).

CONCLUSIONS

Oscillometric principles combined with machine learning algorithms provide a new method for diagnosing respiratory changes in patients with systemic sclerosis. The present study's findings provide evidence that this combination may help in the early diagnosis of respiratory changes in these patients.

Oscillation Mechanics, Integer and Fractional Respiratory Modeling in COPD: Effect of Obstruction Severity

Purpose

This research examines the emerging role of respiratory oscillometry associated with integer (InOr) and fractional order (FrOr) respiratory models in the context of groups of patients with increasing severity. The contributions to our understanding of the respiratory abnormalities along the course of increasing COPD severity and the diagnostic use of this method were also evaluated.

Patients and Methods

Forty-five individuals with no history of smoking or pulmonary diseases (control group) and 141 individuals with diagnoses of COPD were studied, being classified into 45 mild, 42 moderate, 36 severe and 18 very severe cases.

Results

This study has shown initially that the course of increasing COPD severity was adequately described by the model parameters. This resulted in significant and consistent correlations among these parameters and spirometric indexes. Additionally, this evaluation enhanced our understanding of the respiratory abnormalities in different COPD stages. The diagnostic accuracy analyses provided evidence that hysteresivity, obtained from FrOr modeling, allowed a highly accurate identification in patients with mild changes [area under the receiver operator characteristic curve (AUC)= 0.902]. Similar analyses in groups of moderate and severe patients showed that peripheral resistance, derived from InOr modeling, provided the most accurate parameter (AUC=0.898 and 0.998, respectively), while in very severe patients, traditional, InOr and FrOr parameters were able to reach high diagnostic accuracy (AUC>0.9).

Conclusion

InOr and FrOr modeling improved our knowledge of the respiratory abnormalities along the course of increasing COPD severity. In addition, the present study provides evidence that these models may contribute in the diagnosis of COPD. Respiratory oscillometry exams require only tidal breathing and are easy to perform. Taken together, these practical considerations and the results of the present study suggest that respiratory oscillometry associated with InOr and FrOr models may help to improve lung function tests in COPD.

Differential diagnosis of asthma and restrictive respiratory diseases by combining forced oscillation measurements, machine learning and neuro-fuzzy classifiers

To design machine learning classifiers to facilitate the clinical use and increase the accuracy of the forced oscillation technique (FOT) in the differential diagnosis of patients with asthma and restrictive respiratory diseases. FOT and spirometric exams were performed in 97 individuals, including controls (n = 20), asthmatic patients (n = 38), and restrictive (n = 39) patients. The first experiment of this study showed that the best FOT parameter was the resonance frequency, providing moderate accuracy (AUC = 0.87). In the second experiment, a neuro-fuzzy classifier and different supervised machine learning techniques were investigated, including k-nearest neighbors, random forests, AdaBoost with decision trees, and support vector machines with a radial basis kernel. All classifiers achieved high accuracy (AUC ≥ 0.9) in the differentiation between patient groups. In the third and fourth experiments, the use of different feature selection techniques allowed us to achieve high accuracy with only three FOT parameters. In addition, the neuro-fuzzy classifier also provided rules to explain the classification. Neuro-fuzzy and machine learning classifiers can aid in the differential diagnosis of patients with asthma and restrictive respiratory diseases. They can assist clinicians as a support system providing accurate diagnostic options.

Animal Models Reflecting Chronic Obstructive Pulmonary Disease and Related Respiratory Disorders: Translating Pre-Clinical Data into Clinical Relevance

Chronic obstructive pulmonary disease (COPD) affects the lives of an ever-growing number of people worldwide. The lack of understanding surrounding the pathophysiology of the disease and its progression has led to COPD becoming the third leading cause of death worldwide. COPD is incurable, with current treatments only addressing associated symptoms and sometimes slowing its progression, thus highlighting the need to develop novel treatments. However, this has been limited by the lack of experimental standardization within the respiratory disease research area. A lack of coherent animal models that accurately represent all aspects of COPD clinical presentation makes the translation of promising in vitrodata to human clinical trials exceptionally challenging. Here, we review current knowledge within the COPD research field, with a focus on current COPD animal models. Moreover, we include a set of advantages and disadvantages for the selection of pre-clinical models for the identification of novel COPD treatments.

High-accuracy detection of airway obstruction in asthma using machine learning algorithms and forced oscillation measurements

BACKGROUND AND OBJECTIVES

The main pathologic feature of asthma is episodic airway obstruction. This is usually detected by spirometry and body plethysmography. These tests, however, require a high degree of collaboration and maximal effort on the part of the patient. There is agreement in the literature that there is a demand of research into new technologies to improve non-invasive testing of lung function. The purpose of this study was to develop automatic classifiers to simplify the clinical use and to increase the accuracy of the forced oscillation technique (FOT) in the diagnosis of airway obstruction in patients with asthma.

METHODS

The data consisted of FOT parameters obtained from 75 volunteers (39 with obstruction and 36 without). Different supervised machine learning (ML) techniques were investigated, including k-nearest neighbors (KNN), random forest (RF), AdaBoost with decision trees (ADAB) and feature-based dissimilarity space classifier (FDSC).

RESULTS

The first part of this study showed that the best FOT parameter was the resonance frequency (AUC = 0.81), which indicates moderate accuracy (0.70-0.90). In the second part of this study, the use of the cited ML techniques was investigated. All the classifiers improved the diagnostic accuracy. Notably, ADAB and KNN were very close to achieving high accuracy (AUC = 0.88 and 0.89, respectively). Experiments including the cross products of the FOT parameters showed that all the classifiers improved the diagnosis accuracy and KNN was able to reach a higher accuracy range (AUC = 0.91).

CONCLUSIONS

Machine learning classifiers can help in the diagnosis of airway obstruction in asthma patients, and they can assist clinicians in airway obstruction identification.

Early Diagnosis of Respiratory Abnormalities in Asbestos-Exposed Workers by the Forced Oscillation Technique

BACKGROUND

The current reference test for the detection of respiratory abnormalities in asbestos-exposed workers is spirometry. However, spirometry has several shortcomings that greatly affect the efficacy of current asbestos control programs. The forced oscillation technique (FOT) represents the current state-of-the-art technique in the assessment of lung function. This method provides a detailed analysis of respiratory resistance and reactance at different oscillatory frequencies during tidal breathing. Here, we evaluate the FOT as an alternative method to standard spirometry for the early detection and quantification of respiratory abnormalities in asbestos-exposed workers.

METHODOLOGY/PRINCIPAL FINDINGS

Seventy-two subjects were analyzed. The control group was composed of 33 subjects with a normal spirometric exam who had no history of smoking or pulmonary disease. Thirty-nine subjects exposed to asbestos were also studied, including 32 volunteers in radiological category 0/0 and 7 volunteers with radiological categories of 0/1 or 1/1. FOT data were interpreted using classical parameters as well as integer (InOr) and fractional-order (FrOr) modeling. The diagnostic accuracy was evaluated by investigating the area under the receiver operating characteristic curve (AUC). Exposed workers presented increased obstruction (resistance p<0.001) and a reduced compliance (p<0.001), with a predominance of obstructive changes. The FOT parameter changes were correlated with the standard pulmonary function analysis methods (R = -0.52, p<0.001). Early respiratory abnormalities were identified with a high diagnostic accuracy (AUC = 0.987) using parameters obtained from the FrOr modeling. This accuracy was significantly better than those obtained with classical (p<0.001) and InOr (p<0.001) model parameters.

CONCLUSIONS

The FOT improved our knowledge about the biomechanical abnormalities in workers exposed to asbestos. Additionally, a high diagnostic accuracy in the diagnosis of early respiratory abnormalities in asbestos-exposed workers was obtained. This makes the FOT particularly useful as a screening tool in the context of asbestos control and elimination. Moreover, it can facilitate epidemiological research and the longitudinal follow-up of asbestos exposure and asbestos-related diseases.

Machine learning algorithms and forced oscillation measurements to categorise the airway obstruction severity in chronic obstructive pulmonary disease

The purpose of this study was to develop automatic classifiers to simplify the clinical use and increase the accuracy of the forced oscillation technique (FOT) in the categorisation of airway obstruction level in patients with chronic obstructive pulmonary disease (COPD). The data consisted of FOT parameters obtained from 168 volunteers (42 healthy and 126 COPD subjects with four different levels of obstruction). The first part of this study showed that FOT parameters do not provide adequate accuracy in identifying COPD subjects in the first levels of obstruction, as well as in discriminating between close levels of obstruction. In the second part of this study, different supervised machine learning (ML) techniques were investigated, including k-nearest neighbour (KNN), random forest (RF) and support vector machines with linear (SVML) and radial basis function kernels (SVMR). These algorithms were applied only in situations where high categorisation accuracy [area under the Receiver Operating Characteristic curve (AUC)≥0.9] was not achieved with the FOT parameter alone. It was observed that KNN and RF classifiers improved categorisation accuracy. Notably, in four of the six cases studied, an AUC≥0.9 was achieved. Even in situations where an AUC≥0.9 was not achieved, there was a significant improvement in categorisation performance (AUC≥0.83). In conclusion, machine learning classifiers can help in the categorisation of COPD airway obstruction. They can assist clinicians in tracking disease progression, evaluating the risk of future disease exacerbations and guiding therapy.

Accumulation of metals in GOLD4 COPD lungs is associated with decreased CFTR levels

BACKGROUND

The Cystic Fibrosis Transmembrane conductance Regulator (CFTR) is a chloride channel that primarily resides in airway epithelial cells. Decreased CFTR expression and/or function lead to impaired airway surface liquid (ASL) volume homeostasis, resulting in accumulation of mucus, reduced clearance of bacteria, and chronic infection and inflammation.

METHODS

Expression of CFTR and the cigarette smoke metal content were assessed in lung samples of controls and COPD patients with established GOLD stage 4. CFTR protein and mRNA were quantified by immunohistochemistry and quantitative RT-PCR, respectively. Metals present in lung samples were quantified by ICP-AES. The effect of cigarette smoke on down-regulation of CFTR expression and function was assessed using primary human airway epithelial cells. The role of leading metal(s) found in lung samples of GOLD 4 COPD patients involved in the alteration of CFTR was confirmed by exposing human bronchial epithelial cells 16HBE14o- to metal-depleted cigarette smoke extracts.

RESULTS

We found that CFTR expression is reduced in the lungs of GOLD 4 COPD patients, especially in bronchial epithelial cells. Assessment of metals present in lung samples revealed that cadmium and manganese were significantly higher in GOLD 4 COPD patients when compared to control smokers (GOLD 0). Primary human airway epithelial cells exposed to cigarette smoke resulted in decreased expression of CFTR protein and reduced airway surface liquid height. 16HBE14o-cells exposed to cigarette smoke also exhibited reduced levels of CFTR protein and mRNA. Removal and/or addition of metals to cigarette smoke extracts before exposure established their role in decrease of CFTR in airway epithelial cells.

CONCLUSIONS

CFTR expression is reduced in the lungs of patients with severe COPD. This effect is associated with the accumulation of cadmium and manganese suggesting a role for these metals in the pathogenesis of COPD.

A Decade of National Heart, Lung, and Blood Institute Programs Supporting COPD Research and Education

The past decade of research in chronic obstructive pulmonary disease (COPD) has seen a new age of understanding both pathogenic mechanisms and clinical manifestations of the disease. The National Heart, Lung, and Blood Institute (NHLBI) has helped guide this progress with a series of initiatives to stimulate COPD research in various ways. These initiatives were designed to promote a precision medicine approach to treating COPD, one that takes advantage of targeting particular molecular pathways and the individual pathobiologies of the diversity of COPD patients. This review describes the strategic objectives of these initiatives, as well as some of their observed and anticipated outcomes. In addition, we address parallel steps NHLBI has taken to promote COPD awareness among the public. As we look toward the immediate future of COPD research and education, we see a time of great progress in terms of understanding and treatment. Furthermore, while this remains a debilitating and disturbingly prevalent disease, as NHLBI looks even farther ahead, we envision emerging efforts toward COPD prevention.

An improved method of early diagnosis of smoking-induced respiratory changes using machine learning algorithms

The purpose of this study was to develop an automatic classifier to increase the accuracy of the forced oscillation technique (FOT) for diagnosing early respiratory abnormalities in smoking patients. The data consisted of FOT parameters obtained from 56 volunteers, 28 healthy and 28 smokers with low tobacco consumption. Many supervised learning techniques were investigated, including logistic linear classifiers, k nearest neighbor (KNN), neural networks and support vector machines (SVM). To evaluate performance, the ROC curve of the most accurate parameter was established as baseline. To determine the best input features and classifier parameters, we used genetic algorithms and a 10-fold cross-validation using the average area under the ROC curve (AUC). In the first experiment, the original FOT parameters were used as input. We observed a significant improvement in accuracy (KNN=0.89 and SVM=0.87) compared with the baseline (0.77). The second experiment performed a feature selection on the original FOT parameters. This selection did not cause any significant improvement in accuracy, but it was useful in identifying more adequate FOT parameters. In the third experiment, we performed a feature selection on the cross products of the FOT parameters. This selection resulted in a further increase in AUC (KNN=SVM=0.91), which allows for high diagnostic accuracy. In conclusion, machine learning classifiers can help identify early smoking-induced respiratory alterations. The use of FOT cross products and the search for the best features and classifier parameters can markedly improve the performance of machine learning classifiers.

Oscillation mechanics of the respiratory system in never-smoking patients with silicosis: pathophysiological study and evaluation of diagnostic accuracy

OBJECTIVES

Silicosis is a chronic and incurable occupational disease that can progress even after the cessation of exposure. Recent studies suggest that the forced oscillation technique may help to clarify the changes in lung mechanics resulting from silicosis as well as the detection of these changes. We investigated the effects of airway obstruction in silicosis on respiratory impedance and evaluated the diagnostic efficacy of the forced oscillation technique in these patients.

METHODS

Spirometry was used to classify the airway obstruction, which resulted in four subject categories: controls (n=21), patients with a normal exam (n=12), patients with mild obstruction (n=22), and patients with moderate-to-severe obstruction (n=12). Resistive data were interpreted using the zero-intercept resistance (R0), the resistance at 4 Hz (Rrs4), and the mean resistance. We also analyzed the mean reactance (Xm) and the dynamic compliance. The total mechanical load was evaluated using the absolute value of the respiratory impedance (Z4Hz). The diagnostic potential was evaluated by investigating the area under the receiver operating characteristic curve. ClinicalTrials.gov: NCT01725971.

RESULTS

We observed significant (p<0.0002) increases in R0, Rrs4, Rm, and Z4Hz and significant reductions in Crs,dyn (p<0.0002) and Xm (p<0.0001). R0, Rrs4, Rm, and Z4Hz performed adequately in the diagnosis of mild obstruction (area under the curve>0.80) and highly accurately in the detection of moderate-to-severe obstruction (area under the curve>0.90).

CONCLUSIONS

The forced oscillation technique may contribute to the study of the pathophysiology of silicosis and may improve the treatment offered to these patients, thus representing an alternative and/or complementary tool for evaluating respiratory mechanics.

Pulmonary hypertension and vascular oxidative damage in cigarette smoke exposed eNOS(-/-) mice and human smokers

CONTEXT

Cigarette smoke is known to be associated with pulmonary hypertension in humans and in animal models. Although the etiology of pulmonary hypertension in smokers is not understood, recent work has suggested a role for inducible nitric oxide synthase (iNOS) in inducing oxidative stress.

OBJECTIVE AND METHODS

To further evaluate this question, we assessed eNOS-/- mice exposed to air or cigarette smoke for the presence of pulmonary hypertension and examined vascular remodeling and expression of nitrotyrosine, a marker of reactive nitrogen species-induced oxidative damage, using immunohistochemistry. To ascertain whether oxidants may play a role in humans, we also examined lung tissue from nonsmokers, and patients with chronic obstructive pulmonary disease (COPD) with and without pulmonary hypertension.

RESULTS

We found that eNOS(-/-) mice developed increased pulmonary arterial pressure after six months cigarette smoke exposure, and this was associated with vascular remodeling and increased vascular nitrotyrosine staining. iNOS gene expression was decreased in the pulmonary arteries of the smoke exposed animals, and no protein was detectable by immunohistochemistry. In humans, vascular nitrotyrosine staining intensity was increased in smokers with COPD compared to nonsmokers, and further increased in smokers with combined COPD and pulmonary hypertension.

CONCLUSIONS

We conclude that cigarette smoke-induced pulmonary hypertension is associated with evidence of oxidative vascular damage by reactive nitrogen species, but that iNOS does not appear to be the major contributor to such damage. Most likely the source of reactive nitrogen species is the cigarette smoke itself.

Development of a Non-Invasive Dynamic Pulmonary Function Monitor

Characterizing the complexity of airflow limitation in diagnosing and assessing disease severity in asthma, COPD, cystic fibrosis, and other respiratory diseases can help guide clinicians toward the most appropriate treatments. Current technologies allow obstructive lung disease to be measured with about 5%−10% precision. A noninvasive dynamic pulmonary function monitor (DPFM) can quantify ventilation inhomogeneities, such as those originating in partially blocked or constricted small airways, with 1% precision if inert gas concentrations can be measured accurately and precisely over three to four decades of sensitivity. We have studied the precision and linearity of a commercially available mass spectrometer, sampling the gas exhaled by a mechanical lung analog, mimicking a multibreath inert gas washout measurement. The root mean square deviation of the inert gas concentration measured for each “breath,” compared to the expected value for a purely exponential decay, is found to be about 1.1% over three decades of concentration. The corresponding overall impairment, a specific measure of ventilation inhomogeneity, is found to be about 0.2%, which indicates that were inhomogeneities observed, the corresponding impairment could be measured with 1% precision.

Machine learning algorithms and forced oscillation measurements applied to the automatic identification of chronic obstructive pulmonary disease

The purpose of this study is to develop a clinical decision support system based on machine learning (ML) algorithms to help the diagnostic of chronic obstructive pulmonary disease (COPD) using forced oscillation (FO) measurements. To this end, the performances of classification algorithms based on Linear Bayes Normal Classifier, K nearest neighbor (KNN), decision trees, artificial neural networks (ANN) and support vector machines (SVM) were compared in order to the search for the best classifier. Four feature selection methods were also used in order to identify a reduced set of the most relevant parameters. The available dataset consists of 7 possible input features (FO parameters) of 150 measurements made in 50 volunteers (COPD, n = 25; healthy, n = 25). The performance of the classifiers and reduced data sets were evaluated by the determination of sensitivity (Se), specificity (Sp) and area under the ROC curve (AUC). Among the studied classifiers, KNN, SVM and ANN classifiers were the most adequate, reaching values that allow a very accurate clinical diagnosis (Se > 87%, Sp > 94%, and AUC > 0.95). The use of the analysis of correlation as a ranking index of the FOT parameters, allowed us to simplify the analysis of the FOT parameters, while still maintaining a high degree of accuracy. In conclusion, the results of this study indicate that the proposed classifiers may contribute to easy the diagnostic of COPD by using forced oscillation measurements.

Hyperpolarized Xenon-129 gas-exchange imaging of lung microstructure: first case studies in subjects with obstructive lung disease

PURPOSE

To develop and test a method to noninvasively assess the functional lung microstructure.

MATERIALS AND METHODS

The Multiple exchange time Xenon polarization Transfer Contrast technique (MXTC) encodes xenon gas-exchange contrast at multiple delay times permitting two lung-function parameters to be derived: (i) MXTC-F, the long exchange-time depolarization value, which is proportional to the tissue to alveolar-volume ratio and (ii) MXTC-S, the square root of the xenon exchange-time constant, which characterizes thickness and composition of alveolar septa. Three healthy volunteers, one asthmatic, and two chronic obstructive pulmonary disease (COPD) (GOLD stage I and II) subjects were imaged with MXTC MRI. In a subset of subjects, hyperpolarized xenon-129 ADC MRI and CT imaging were also performed.

RESULTS

The MXTC-S parameter was found to be elevated in subjects with lung disease (P-value = 0.018). In the MXTC-F parameter map it was feasible to identify regional loss of functional tissue in a COPD patient. MXTC-F maps showed excellent regional correlation with CT and ADC (P ≥ 0.90) in one COPD subject.

CONCLUSION

The functional tissue-density parameter MXTC-F showed regional agreement with other imaging techniques. The newly developed parameter MXTC-S, which characterizes the functional thickness of alveolar septa, has potential as a novel biomarker for regional parenchymal inflammation or thickening.

Advances in proteomic techniques for biomarker discovery in COPD

Chronic obstructive pulmonary disease (COPD) is a disorder characterized by chronic inflammation of the lung with airflow obstruction and progressive deterioration of pulmonary function. The need to discover and validate biomarkers as prognostic tools of development and progression of the disease has received further support with the advent of proteomic techniques. Liquid chromatography-mass spectrometry (LC/MS) and gel electrophoresis-mass spectrometry (2-DE/MS) have been applied to investigate the proteome of a number of lung-origin samples, including sputum, bronchoalveolar lavage fluid, exhaled-breath condensate, cells and biopsies from COPD patients. In particular, 2-DE and MS are the main proteomic approaches with 2-DE presenting the major approach for quantitative proteomics. The molecules identified as potential biomarkers of COPD may represent a preliminary step for better comprehension of the mechanisms involved in the onset/progression of the disease.

Effects of carbon black nanoparticles on elastase-induced emphysematous lung injury in mice

Although adverse health effects of particulate matter with a diameter of <100 nm (nanoparticles) have been proposed, biological evidence supporting their promotion of the inflammatory lung response in vivo is limited. This study investigated the impact of pulmonary exposure to carbon black nanoparticles (CBNP) on emphysematous lung injury induced by porcine pancreatic elastase (PPE) in mice. Vehicle, two sizes (14 and 56 nm) of CBNP (50 μg/body: 4 mg/kg), PPE (0.03 U/body: 1 U/kg) or PPE + CBNP was administered intratracheally; thereafter, parameters of inflammatory lung changes were evaluated at several time-points. CBNP of 14 nm significantly induced acute lung inflammation in non-elicited subjects and aggravated PPE-elicited airway neutrophilic inflammation at an early stage (day 1), which was concomitant with the enhanced lung expression of pro-inflammatory cytokines such as interleukin-1β and chemokine such as keratinocyte-derived chemoattractant. Further, 14-nm CBNP exaggerated emphysematous lung structural changes at a delayed stage (day 14). On the other hand, 56-nm CBNP induced lung inflammation but did not influence PPE-elicited pathophysiology in the lung. Taken together, CBNP at an optimal size and dose can exacerbate PPE-induced pulmonary inflammation and emphysema. This enhancement may be mediated, at least partly, via the increased local expression of pro-inflammatory molecules.

Effects of inhaled corticosteroids in stable chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) has been described as a heterogeneous multifactorial disorder associated with an abnormal inflammatory response of the peripheral airways and with variable morphologic, physiologic and clinical phenotypes. This notion of the disease is actually poorly supported by data, and there are substantial discrepancies and a weak correlation between inflammation, structural damage, functional impairment and degree of clinical symptoms. This problem is compounded by a poor understanding of the complexity and intricacies on the inflammatory pathways in COPD. Despite the evidence for efficacy of inhaled corticosteroids (ICS) on selected clinical endpoints in COPD, we cannot assume that anti-inflammatory treatment with ICS alone or in combination with long-acting bronchodilators will necessarily improve the underlying inflammatory processes and patient relevant outcomes in COPD. Given the widespread use of inhaled corticosteroids (ICS) alone or in combination for the treatment of COPD across all severities, it is important to weigh their clinically proven benefits and shortcomings cautiously and critically. Reviewed is the current evidence-based role of ICS on inflammatory markers and patient relevant outcomes in COPD.

Extensive Analysis of Elastase-Induced Pulmonary Emphysema in Rats: ALP in the Lung, a New Biomarker for Disease Progression?

It is accepted that pulmonary exposure of rodents to porcine pancreatic elastase (ELT) induces lesions that morphologically resemble human emphysema. Nonetheless, extensive analysis of this model has rarely been conducted. The present study was designed to extensively examine the effects of ELT on lung inflammation, cell damage, emphysematous change, and cholinergic reactivity in rats. Intratracheal administration of two doses of ELT induced 1) a proinflammatory response in the lung that was characterized by significant infiltration of macrophages and an increased level of interleukin-1beta in lung homogenates, 2) lung cell damage as indicated by higher levels of total protein, lactate dehydrogenase, and alkaline phosphatase (ALP) in lung homogenates, 3) emphysema-related morphological changes including airspace enlargement and progressive destruction of alveolar wall structures, and 4) airway responsiveness to methacholine including an augmented Rn value. In addition, ELT at a high dose was more effective than that at a low dose. This is the novel study to extensively analyze ELT-induced lung emphysema, and the analysis might be applied to future investigations that evaluate new therapeutic agents or risk factors for pulmonary emphysema. In particular, ALP in lung homogenates might be a new biomarker for the disease progression/exacerbation.

Instrumentation for the analysis of airflow limitation by the negative expiratory pressure technique

The aim of this work is to describe a new instrument based on the negative expiratory pressure technique able to detect expiratory flow limitation (EFL) in patients with respiratory diseases. First, we describe the design details of a virtual instrument able to apply a low pressure at the mouth during tidal expiration, simultaneously measure flow and pressure, and automatically elaborate flow-volume curves. Then, the system accuracy is evaluated investigating normal subjects and patients with chronic obstructive pulmonary disease (COPD). These experimental results revealed higher (p〈0.001) EFL in COPD patients (58.5±19.9%) than in normal volunteers (1.5±2.5%). These results are in close agreement with the physiology, confirming the high scientific and clinical potential of this system.

Forced oscillation technique in the detection of smoking-induced respiratory alterations: diagnostic accuracy and comparison with spirometry

INTRODUCTION

Detection of smoking effects is of utmost importance in the prevention of cigarette-induced chronic airway obstruction. The forced oscillation technique offers a simple and detailed approach to investigate the mechanical properties of the respiratory system. However, there have been no data concerning the use of the forced oscillation technique to evaluate respiratory mechanics in groups with different degrees of tobacco consumption.

OBJECTIVES

(1) to evaluate the ability of the forced oscillation technique to detect smoking-induced respiratory alterations, with special emphasis on early alterations; and (2) to compare the diagnostic accuracy of the forced oscillation technique and spirometric parameters.

METHODS

One hundred and seventy subjects were divided into five groups according to the number of pack-years smoked: four groups of smokers classified as < 20, 20-39, 40-59, and > 60 pack-years and a control group. The four groups of smokers were compared with the control group using receiver operating characteristic (ROC) curves.

RESULTS

The early adverse effects of smoking in the group with < 20 pack-years were adequately detected by forced oscillation technique parameters. In this group, the comparisons of the ROC curves showed significantly better diagnostic accuracy (p < 0.01) for forced oscillation technique parameters. On the other hand, in groups of 20-39, 40-59, and > 60 pack-years, the diagnostic performance of the forced oscillation technique was similar to that observed with spirometry.

CONCLUSIONS

This study revealed that forced oscillation technique parameters were able to detect early smoking-induced respiratory involvement when pathologic changes are still potentially reversible. These findings support the use of the forced oscillation technique as a versatile clinical diagnostic tool in helping with chronic obstructive lung disease prevention, diagnosis, and treatment.

Evaluating the forced oscillation technique in the detection of early smoking-induced respiratory changes

BACKGROUND

Early detection of the effects of smoking is of the utmost importance in the prevention of chronic obstructive pulmonary disease (COPD). The forced oscillation technique (FOT) is easy to perform since it requires only tidal breathing and offers a detailed approach to investigate the mechanical properties of the respiratory system. The FOT was recently suggested as an attractive alternative for diagnosing initial obstruction in COPD, which may be helpful in detecting COPD in its initial phases. Thus, the purpose of this study was twofold: (1) to evaluate the ability of FOT to detect early smoking-induced respiratory alterations; and (2) to compare the sensitivity of FOT with spirometry in a sample of low tobacco-dose subjects.

METHODS

Results from a group of 28 smokers with a tobacco consumption of 11.2 +/- 7.3 pack-years were compared with a control group formed by 28 healthy subjects using receiver operating characteristic (ROC) curves and a questionnaire as a gold standard. The early adverse effects of smoking were adequately detected by the absolute value of the respiratory impedance (Z4Hz), the intercept resistance (R0), and the respiratory system dynamic compliance (Crs, dyn). Z4Hz was the most accurate parameter (Se = 75%, Sp = 75%), followed by R0 and Crs, dyn. The performances of the FOT parameters in the detection of the early effects of smoking were higher than that of spirometry (p < 0.05).

CONCLUSION

This study shows that FOT can be used to detect early smoking-induced respiratory changes while these pathologic changes are still potentially reversible. These findings support the use of FOT as a versatile clinical diagnostic tool in aiding COPD prevention and treatment.

Challenges Associated with Estimating Minimal Clinically Important Differences in COPD—The NHLBI Perspective

Chronic Obstructive Pulmonary Disease (COPD) is a common lung disease that exemplifies the value, as well as the difficulties and challenges, of using minimal clinically important differences (MCID) in clinical research. Development and validation of better endpoints for clinical studies is critical to research progress in COPD. However, the clinical, genetic, and pharmacological heterogeneity of the COPD patient population complicates attempts to define and validate MCIDs for COPD. It is difficult to identify a single measurable outcome that reflects the many components of the COPD patient's health state. Acute exacerbations of symptoms, which COPD patients often experience, present another challenge in the development of MCIDs for this disease. Consequently, the NHLBI does not require the use of MCIDs in clinical research. This allows research on the causes, prevention and diagnosis of COPD and use of endpoints for which an MCID is not yet known. It is important for the scientific community to reach agreement on what is a meaningful MCID in therapeutic trials for COPD. Further research into the concept of the MCID and its application should enable therapeutic trials in COPD to yield knowledge that is more effectively translated into improved public health.

CIGARETTE SMOKE-INDUCED HYPERCAPNIC EMPHYSEMA IN C3H MICE IS ASSOCIATED WITH INCREASES OF MACROPHAGE METALLOELASTASE AND SUBSTANCE P IN THE LUNGS

The authors tested whether macrophage metalloelastase (MMP-12) and substance P (SP) were increased in the cigarette smoke (CS)-exposed female C3H/HeN mice with hypercapnic emphysema. The authors found that as compared to control (filtered air), 16 weeks of CS exposure significantly up-regulated mRNA and protein levels of MMP-12, the ratio of MMP-12/tissue inhibitor of matrix metalloproteinase-1, and SP/preprotachykinin-A (a precursor to SP) in the lungs. Importantly, a significant correlation was found between MMP-12 and SP, and between MMP-12/SP and the degrees of hypoxemia/hypercapnia denoted in CS-exposed mice. These data suggest a possible involvement of SP and MMP-12 in the pathogenesis of severe COPD.

N-alpha-PGP and PGP, potential biomarkers and therapeutic targets for COPD

Background

Chronic obstructive pulmonary disease (COPD) is a common respiratory disorder for which new diagnostic and therapeutic approaches are required. Hallmarks of COPD are matrix destruction and neutrophilic airway inflammation in the lung. We have previously described two tri-peptides, N-α-PGP and PGP, which are collagen fragments and neutrophil chemoattractants. In this study, we investigate if N-α-PGP and PGP are biomarkers and potential therapeutic targets for COPD.

Methods

Induced sputum samples from COPD patients, healthy controls and asthmatics were examined for levels of N-α-PGP and PGP using mass spectrometry and for the ability to generate PGP de novo from collagen. Proteases important in PGP generation in the lung were identified by the use of specific inhibitors in the PGP generation assay and by instillation of proteases into mouse lungs. Serum levels of PGP were compared between COPD patients and controls.

Results

N-α-PGP was detected in most COPD sputum samples but in no asthmatics or controls. PGP was detected in a few controls and in all COPD sputum samples, where it correlated with levels of myeloperoxidase. COPD sputum samples had the ability to generate N-α-PGP and PGP de novo from collagen. PGP generation by COPD sputum was blocked by inhibitors of matrix metalloproteases (MMP's) 1 and 9 and prolyl endopeptidase. MMP's 1 and 9 and prolyl endopeptidase acted synergistically to generate PGP in vivo when instilled into mouse lungs. Serum levels of PGP were also significantly higher in COPD patients than in controls

Conclusion

N-α-PGP and PGP may represent novel diagnostic tests and biomarkers for COPD. Inhibition of this pathway may provide novel therapies for COPD directed at the chronic, neutrophilic, airway inflammation which underlies disease progression.

Mechanism-based inhibitors of serine proteases with high selectivity through optimization of S' subsite binding

A series of mechanism-based inhibitors designed to interact with the S' subsites of serine proteases was synthesized and their inhibitory activity toward the closely-related serine proteases human neutrophil elastase (HNE) and proteinase 3 (PR 3) was investigated. The compounds were found to be time-dependent inhibitors of HNE and were devoid of any inhibitory activity toward PR 3. The results suggest that highly selective inhibitors of serine proteases whose primary substrate specificity and active sites are similar can be identified by exploiting differences in their S' subsites. The best inhibitor (compound 16) had a k(inact)/K(I) value of 4580 M(-1)s(-1).

Free-living physical activity in COPD: assessment with accelerometer and activity checklist

To assess physical activity and disability in chronic obstructive pulmonary disease (COPD), we evaluated the use of an accelerometer and checklist to measure free-living physical activity. Seventeen males with stable COPD completed a daily activity checklist for 14 days. Ten subjects concurrently wore an Actiped accelerometer (FitSense, Southborough, Massachussetts) that records steps per day. Regression models assessed relationships between steps per day, number of daily checklist activities performed, and clinical measures of COPD status. The average steps per day ranged from 406 to 4,856. The median intrasubject coefficient of variation for steps per day was 0.52 (interquartile range [IQR] 0.41-0.58) and for number of daily checklist activities performed was 0.28 (IQR 0.22-0.32). A higher number of steps per day was associated with a greater distance walked on the 6-minute walk test and better health-related quality of life. A higher number of daily checklist activities performed was associated with a higher force expiratory volume in 1 s percent predicted and lowerbody mass index, airflow obstruction, dyspnea, exercise capacity (BODE) index. Prospectively measuring free-living physical activity in COPD using an unobtrusive accelerometer and simple activity checklist is feasible. Low intrasubject variation was found in free-living physical activity, which is significantly associated with clinical measures of COPD status.

Systemic markers of the redox balance in chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is highly prevalent and its pathogenesis is still not completely clarified. Clinically stable patients (n=21) and healthy subjects (n=24) were studied for blood markers of oxidative injury and antioxidant status. The plasma concentration of protein carbonyls was significantly increased in COPD patients, both ex-smokers (0.76 +/- 0.28 nmol mg(-1)) and smokers (0.99 +/- 020 nmol mg(-1)) versus controls (0.49 +/- 0.14 nmol mg(-1)) . The concentration of total thiols was slightly enhanced in plasma of the COPD patients (ex-smokers 492 +/- 23 micromol 1(-1) and smokers 505 +/- 36 micromol 1(-1) versus controls 450 +/- 67 micromol 1(-1); p < 0.05). The activity of the antioxidant enzyme superoxide dismutase was increased in erythrocytes (activity in U g(-1) haemoglobin; ex-smokers 4460 +/- 763 and smokers 4114+/- 1060 versus 3015 +/- 851 in controls; p > 0.01), while glutathione peroxidase activity was decreased in total blood (activity in U g(-1) haemoglobin: ex-smokers 27 +/- 9 and smokers 23 +/- 9 versus 47 +/- 25; p < 0.01). Lower levels of selenium in plasma were also found for COPD patients (concentration in mg 1(-1): ex-smokers 0.030 +/- 0.019 and smokers 0.032 +/- 0.024 versus 0.058 +/- 0.023 in controls; p < 0.01), being more evident in those with very low levels of arterial oxygen pressure. In addition, the levels of potassium and rubidium were increased in blood cells of the patient group. All these changes might reflect oxidant damage and an altered electrolytic homeostasis, and can be interpreted as markers of COPD rather than as indicators of smoking habits.

It takes two to tango: cigarette smoke partners with viruses to promote emphysema

Viruses constitute a constant and renewed threat to humans. Not only do viruses cause disease directly due to their tissue tropism and pathogenicity, but they have also been linked to autoimmunity. In their study in this issue of the JCI, Kang et al. show that exposure to cigarette smoke induces alterations in the innate immune response to viral infection and that these changes hasten alveolar destruction characteristic of emphysema in mice (see the related beginning on page 2771). This study builds on evidence that patients with chronic obstructive pulmonary disease have clinical exacerbations associated with viral or bacterial infections, which lead to worsened lung function and increased mortality. This novel paradigm may aid related genetic, biomarker, and therapeutic developments and provides important insights into the pathogenesis of emphysematous lung destruction.

Vulnerability of gastric mucosa to prednisolone in rats chronically exposed to cigarette smoke

We examined gastric mucosal vulnerability in a rat model of chronic obstructive pulmonary disease (COPD). Male Wistar rats were exposed to cigarette smoke for 12 weeks (CSE rats), and on the last 4 days of exposure, prednisolone was given to induce gastric mucosal injury. Histopathology, pulmonary function, arterial blood gases, and levels of lipid peroxides (LPO), prostaglandin E(2) (PGE(2)), hypoxia-inducible factor 1 alpha subunit (HIF-1alpha), and vascular endothelial growth factor (VEGF) in gastric mucosa were examined. We also tested the effect of rebamipide on prednisolone-induced gastric lesions. In CSE rats, although no gastric lesions were detected, LPO, PGE(2), HIF-1alpha, and VEGF levels were higher than in control rats. Prednisolone induced gastric hemorrhagic lesions more readily in CSE rats than controls, with concomitant decrease in PaO(2) and increased levels of LPO, HIF-1alpha, and VEGF. Rebamipide reversed gastric lesions without affecting any parameters examined. CSE rats were found to be a useful animal model of COPD, and COPD appeared to render the gastric mucosa vulnerable to prednisolone.

Protein expression in sputum of smokers and chronic obstructive pulmonary disease patients: a pilot study by CapLC-ESI-Q-TOF

The current report describes the use of CapLC-ESI-Q/TOF-MS for investigating the proteome profiles of hypertonic saline-induced sputum samples from 56 smokers. The severity of their lung disease ranged from normal (healthy smokers) to chronic bronchitis, chronic obstructive pulmonary disease (COPD), and COPD with emphysema. This pilot study examined the hypothesis that there were distinct differences in protein expression profiles that were related to the phenotype and cigarette smoking illness severity. A total of 203 unique proteins were identified. These may represent the most highly expressed proteins in induced sputum. Our results provide evidence that different proteins are expressed, as the disease progresses from health to more advanced stages, and support our contention that a proteomic approach would be beneficial in discovering selective molecules linked to specific COPD stages.

Beta2-adrenoceptor polymorphisms and obstructive airway diseases: important issues of study design

1. Asthma and chronic obstructive pulmonary disease (COPD) are chronic airway diseases characterized by airflow obstruction. The beta(2)-adrenoceptor mediates bronchodilatation in response to exogenous and endogenous beta-adrenoceptor agonists. 2. Single nucleotide polymorphisms in the beta(2)-adrenoceptor gene (ADRB2) cause amino acid changes (e.g. Arg16Gly, Gln27Glu) that potentially alter receptor function. Recently, a large cohort study found no association between asthma susceptibility and beta(2)-adrenoceptor polymorphisms. In contrast, asthma phenotypes, such as asthma severity and bronchial hyperresponsiveness, have been associated with beta(2)-adrenoceptor polymorphisms. Of importance to asthma management, coding region polymorphisms may alter the response to short-acting and long-acting beta-adrenoceptor agonists, which are commonly prescribed asthma treatments. 3. Optimizing study design would enhance the robustness of genetic association studies of ADRB2 polymorphisms in airway diseases. Characteristics of high-quality studies include suitable study design and subject selection, optimal study of polymorphisms and haplotypes, disease outcomes of relevance, adequate sample size, adjustment for confounding factors, supportive functional data and appropriate analysis, interpretation and replication. Enhancing these study design factors will provide high-quality evidence regarding the biological and clinical importance of beta(2)-adrenoceptor pharmacogenomics in asthma and COPD.

Activity monitoring and energy expenditure in COPD patients: a validation study

There is increasing interest in the objective measurement of physical activity in chronic obstructive pulmonary disease (COPD) patients due to the close relationship between physical activity level, health, disability and mortality. We aimed to (a) determine the validity and reproducibility of an activity monitor that integrates accelerometry with multiple physiologic sensors in the determination of energy expenditure in COPD subjects and (b) to document the independent contribution of the additional physiologic sensors to accelerometry measures in improving true energy expenditure determination. Eight subjects (4 male, FEV(1) 56.4 +/- 14.1%, RV 145.0 +/- 75.7%) performed 2 separate 6-minute walk and 2 incremental shuttle walk exercise tests. Energy expenditure was calculated during each exercise test using the physiologic activity monitor and compared to a validated exhaled breath metabolic system. Test-retest reproducibility of physiologic activity monitor during the walking tests was comparable to an exhaled breath metabolic system. Physiologic sensor data significantly improved the explained variance in energy expenditure determination (r(2)=0.88) compared to accelerometry data alone (r(2)=0.68). This physiologic activity monitor provides a valid and reproducible estimate of energy expenditure during slow to moderate paced walking in a laboratory setting and represents an objective method to assess activity in COPD subjects.

Religious service attendance and decline in pulmonary function in a high-functioning elderly cohort

BACKGROUND

Pulmonary function is an important indicator of respiratory and overall health, yet little is known about the psychosocial factors that predict pulmonary function itself. At the same time, religious activity is emerging as a potential health promoting factor, especially among the elderly. Whether there is a connection between religious activity and pulmonary function is unknown.

PURPOSE

In this study, we sought to examine the association between religious attendance and rate of decline in pulmonary function.

METHODS

The sample consisted of 1,174 healthy elderly persons enrolled in the MacArthur Study of Successful Aging who were followed for an average of 4.6 years. Information on frequency of religious service attendance and peak expiratory flow rate (PEFR) was collected over 3 waves. A linear mixed model with repeated measures was used to compare rate of decline in PEFR between those who attended religious services regularly and those who did not.

RESULTS

Regular religious service attendance was associated with a slower pulmonary function decline among men (by 3.71 L/min per year, p = .02) and women (by 3.27 L/min per year, p = .02), compared to those who never attend services. The findings could not be explained by differences in smoking or physical activity.

CONCLUSIONS

Overall findings support the hypothesis that religious activity may play a protective role in maintaining pulmonary health among the elderly.

Quantitative Thin-Section CT Analysis of the Enlargement and Coalescence of Low-Attenuation Clusters in Patients with Emphysema

BACKGROUND

The analysis of the number and size of low-attenuation clusters has been adopted as quantitative computed tomography (CT) analysis of emphysema; however, a detailed examination has not been made on the relation between the number of various cluster sizes and the extent of emphysema.

OBJECTIVE

The aim of this study was to evaluate the relationship between the size and number of clusters on CT scans in patients with emphysema.

METHODS

This retrospective study included 31 emphysema patients. The number (LAN) and mean size (LAS) of clusters below -950 HU, and relative low-attenuation area below -950 HU (RA950) were calculated using an image-processing program. The size of clusters was divided into 3 categories, and the number in each size category was obtained as follows: small (sLAN 0.4-8 mm(2)), medium (mLAN 8.4-40 mm(2)), and large (lLAN >40 mm(2)). The relationships between the RA950 and sLAN, mLAN, or lLAN were evaluated. Patients were divided according to the extent of RA950 (>25% = severe emphysema, <25% = mild emphysema), and the relations between RA950 and LAN, and between RA950 and sLAN, mLAN, or lLAN were evaluated.

RESULTS

The sLAN decreased as RA950 increased (r = -0.477), whereas mLAN and lLAN increased (r = 0.421, and r = 0.819). In severe emphysema, sLAN and mLAN decreased as RA950 increased (r = -0.722, and r = -0.698). In mild emphysema, mLAN and lLAN increased as RA950 increased (r = 0.732, and r = 0.972).

CONCLUSIONS

The degree of the coalescence of the clusters depends on the size of clusters and the extent of emphysema. Quantitative CT analyses of clusters are helpful to elucidate the pathophysiology and progressive nature of emphysema.

Morphological Progression of Emphysema on Thin-section CT

OBJECTIVES

To evaluate morphological changes in the number and size of low-attenuation clusters on computed tomography (CT) in patients with emphysema.

MATERIALS AND METHODS

In 27 patients who had follow-up CT scans for 6 months or greater, initial 27 scans and follow-up 39 scans were analyzed. The number per slice (LAN/s) and mean size (LAS) of low-attenuation clusters less than -950 HU, and total low-attenuation area below -950 HU per slice (LAA-950/s) were calculated.

RESULTS

LAS and LAA-950/s were significantly increased over time. No significant correlation was found between LAN/s and follow-up period. LAS increased in 37 of 39 (95%) follow-up scans, whereas LAN/s decreased in 17 of 39 (44%) follow-up scans.

CONCLUSIONS

On the morphological progression of emphysema, the mean size of low-attenuation clusters was significantly increased during the follow-up period, whereas no significant correlation was found between the number of low-attenuation clusters and follow-up period.

Neurohumoral activation as a link to systemic manifestations of chronic lung disease

COPD is a major cause of death and disability worldwide. Treatment of COPD improves lung function but is unlikely to slow the steady downhill course of the disease or reduce mortality. In COPD, numerous abnormalities can be found outside the lung. These include systemic inflammation, cachexia, and skeletal muscle dysfunction. Thus, COPD has been called a systemic disease. Convincing data demonstrate that COPD causes neurohumoral activation. By precedents derived from chronic heart failure and other diseases characterized by neurohumoral activation, we propose that the negative consequences of neurohumoral activation, namely inflammation, cachexia, effects on ventilation, and skeletal muscle dysfunction, give rise to a self-perpetuating cycle that contributes to the pathogenesis of COPD, and which may involve respiratory muscle dysfunction as well as systemic inflammation. This concept may further help explain the increased cardiovascular morbidity and mortality in COPD patients. Currently, little is known about the effect of treatments directed at neurohumoral activation and COPD. As this aspect of COPD becomes better understood, new insights may direct novel therapeutic approaches.

Steroid-resistant Inflammation in a Rat Model of Chronic Obstructive Pulmonary Disease Is Associated with a Lack of Nuclear Factor-κB Pathway Activation

RATIONALE

Emphysema is one component of chronic obstructive pulmonary disease (COPD), a respiratory disease currently increasing in prevalence worldwide. The mainstay therapy adopted to treat patients with COPD is glucocorticoids; unfortunately, this treatment has limited impact on disease symptoms or underlying airway inflammation.

OBJECTIVE

There is an urgent need to develop therapies that modify both the underlying inflammation, thought to be involved in disease progression, and the structural changes in the emphysematous lung.

METHODS

We have characterized an elastase-driven model of experimental emphysema in the rat that demonstrates COPD-like airway inflammation and determined the impact of a clinically relevant glucocorticoid.

MEASUREMENTS AND MAIN RESULTS

We observed an increase in lung neutrophils, lymphomononuclear cells, mucus production, and inflammatory cytokines. Also present were increases in average air space area, which are associated with emphysema-like changes in lung function, such as increased residual volume and decreased flow; these increases in area were maintained for up to 10 weeks. In addition, we observed that elastase-induced airway neutrophilia is steroid resistant. Interestingly, the inflammation observed after elastase administration was found to be temporally associated with a lack of nuclear factor-kappaB pathway activation. This apparent nuclear factor-kappaB-independent inflammation may explain why treatment with a glucocorticoid was ineffective in this preclinical model and could suggest parallels in the steroid-resistant human disease.

CONCLUSION

We believe that this model, in addition to its suitability for testing therapies that may modify existing emphysema, could be useful in the search for new therapies to reduce the steroid-resistant airway inflammation evident in COPD.

NO2-induced airway inflammation is associated with progressive airflow limitation and development of emphysema-like lesions in C57BL/6 mice

The major features of chronic obstructive pulmonary disease (COPD) comprise a not fully reversible airflow limitation associated with an abnormal inflammatory response, increased mucus production and development of emphysema-like lesions. Animal models that closely mimic these alterations represent an important issue for the investigation of pathophysiological mechanisms. Since most animal models in this area have focused on specific aspects of the disease, we aimed to investigate whether exposure of C57BL/6 mice to nitrogen dioxide (NO2) may cause a more complex phenotype covering several of the characteristics of the human disease. Therefore, mice were exposed to NO2 for 14h each day for up to 25 days. Initial dose response experiments revealed the induction of a significant inflammatory response at a dose of 20 ppm NO2. Mice developed progressive airway inflammation together with a focal inflammation of the lung parenchyma characterized by a predominant influx of neutrophils and macrophages. In addition, goblet cell hyperplasia was detected in the central airways and increased collagen deposition was found in the lung parenchyma. NO2-exposed mice developed emphysema-like lesions as indicated by a significantly increased mean linear intercept as compared to control mice. Finally, the assessment of lung functional parameters revealed the development of progressive airway obstruction over time. In conclusion, our data provide evidence that the inflammatory response to NO2 exposure is associated with increased mucus production, development of airspace enlargement and progressive airway obstruction. Thus, NO2-exposed mice may serve as a model to investigate pathophysiological mechanisms that contribute to the development of human COPD.

Micellar electrokinetic chromatographic and capillary zone electrophoretic methods for screening urinary biomarkers of human disorders: a critical review of the state-of-the-art

Human urine plays a central role in clinical diagnostic being one of the most-frequently used body fluid for detection of biological markers. Samples from patients with different diseases display patterns of biomarkers that differ significantly from those obtained from healthy subjects. The availability of fast, reproducible, and easy-to-apply analytical techniques that would allow identification of a large number of these analytes is thus highly desiderable since they may provide detailed information about the progression of a pathological process. From among the variety of methods so far applied for the determination of urinary metabolites, capillary electrophoresis, both in the capillary zone electrophoresis (CZE) and micellar electrokinetic chromatography (MEKC) modes, represents a robust and reliable analytical tool widely used in this area. The aim of the present article is to focus the interest of the reader on recent applications of MEKC and CZE in the field of urinary biomarkers and to discuss advantages and/or limitations of each mode.

Serendipitous discovery of an unexpected rearrangement leads to two new classes of potential protease inhibitors

The pathogenesis of a range of human diseases arises from the aberrant activity of proteolytic enzymes. Agents capable of selectively modulating the activity of these enzymes are of potential therapeutic value. Thus, there is a continuing need for the design of scaffolds that can be used in the development of new classes of protease inhibitors. We describe herein the serendipitous discovery of an unexpected rearrangement that leads to the formation of two novel templates that can be used in the design of protease inhibitors.

An animal model of autoimmune emphysema

Although cigarette smoking is implicated in the pathogenesis of emphysema, the precise mechanisms of chronic progressive alveolar septal destruction are not well understood. We show, in a novel animal model, that immunocompetent, but not athymic, nude rats injected intraperitoneally with xenogeneic endothelial cells (ECs) produce antibodies against ECs and develop emphysema. Immunization with ECs also leads to alveolar septal cell apoptosis and activation of matrix metalloproteases MMP-9 and MMP-2. Anti-EC antibodies cause EC apoptosis in vitro and emphysema in passively immunized mice. Moreover, immunization also causes accumulation of CD4+ T cells in the lung. Adoptive transfer of pathogenic, spleen-derived CD4+ cells into naive immunocompetent animal also results in emphysema. This study shows for the first time that humoral- and CD4+ cell-dependent mechanisms are sufficient to trigger the development of emphysema, suggesting that alveolar septal cell destruction might result from immune mechanisms.

Potent inhibition of human leukocyte elastase by 1,2,5-thiadiazolidin-3-one 1,1 dioxide-based sulfonamide derivatives

The design, synthesis, and in vitro biochemical evaluation of a class of mechanism-based inhibitors of human leukocyte elastase (HLE) that incorporate in their structure a 1,2,5-thiadiazolidin-3-one 1,1 dioxide scaffold with appropriate recognition and reactivity elements appended to it is described. The synthesized compounds were found to be efficient, time-dependent inhibitors of HLE. The interaction of the inhibitors with HLE is postulated to lead to the formation of a highly reactive N-sulfonyl imine (a Michael acceptor) that arises from an enzyme-induced sulfonamide fragmentation cascade. Subsequent reaction ultimately leads to the formation of a relatively stable acyl enzyme. The results cited herein demonstrate convincingly the superiority of the 1,2,5-thiadiazolidin-3-one 1,1 dioxide scaffold over other scaffolds (e.g., saccharin) in the design of inhibitors of (chymo)trypsin-like serine proteases.