{"markup":"\u003C?xml version=\u00221.0\u0022 encoding=\u0022UTF-8\u0022 ?\u003E\n    \u003Chtml version=\u0022HTML+RDFa+MathML 1.1\u0022\n    xmlns:content=\u0022http:\/\/purl.org\/rss\/1.0\/modules\/content\/\u0022\n    xmlns:dc=\u0022http:\/\/purl.org\/dc\/terms\/\u0022\n    xmlns:foaf=\u0022http:\/\/xmlns.com\/foaf\/0.1\/\u0022\n    xmlns:og=\u0022http:\/\/ogp.me\/ns#\u0022\n    xmlns:rdfs=\u0022http:\/\/www.w3.org\/2000\/01\/rdf-schema#\u0022\n    xmlns:sioc=\u0022http:\/\/rdfs.org\/sioc\/ns#\u0022\n    xmlns:sioct=\u0022http:\/\/rdfs.org\/sioc\/types#\u0022\n    xmlns:skos=\u0022http:\/\/www.w3.org\/2004\/02\/skos\/core#\u0022\n    xmlns:xsd=\u0022http:\/\/www.w3.org\/2001\/XMLSchema#\u0022\n    xmlns:mml=\u0022http:\/\/www.w3.org\/1998\/Math\/MathML\u0022\u003E\n  \u003Chead\u003E\u003Cscript type=\u0022text\/javascript\u0022 src=\u0022http:\/\/d282kpwvnogo5m.cloudfront.net\/sites\/default\/files\/js\/js_itu2PgFdrjV-docKmLK8Jn5oXe_05RgvQh73eOhI_mE.js\u0022\u003E\u003C\/script\u003E\n\u003Cscript type=\u0022text\/javascript\u0022 src=\u0022http:\/\/mdc.sagepub.com\/sites\/all\/modules\/highwire\/highwire\/plugins\/highwire_markup_process\/js\/highwire_at_symbol.js?nzny02\u0022\u003E\u003C\/script\u003E\n\u003Cscript type=\u0022text\/javascript\u0022 src=\u0022http:\/\/mdc.sagepub.com\/sites\/all\/modules\/highwire\/highwire\/plugins\/highwire_markup_process\/js\/highwire_article_reference_popup.js?nzny02\u0022\u003E\u003C\/script\u003E\n\u003Cscript type=\u0022text\/javascript\u0022 src=\u0022http:\/\/d282kpwvnogo5m.cloudfront.net\/sites\/default\/files\/js\/js_I8yX6RYPZb7AtMcDUA3QKDZqVkvEn35ED11_1i7vVpc.js\u0022\u003E\u003C\/script\u003E\n\u003Cscript type=\u0022text\/javascript\u0022\u003E\n\u003C!--\/\/--\u003E\u003C![CDATA[\/\/\u003E\u003C!--\n(function(i,s,o,g,r,a,m){i[\u0022GoogleAnalyticsObject\u0022]=r;i[r]=i[r]||function(){(i[r].q=i[r].q||[]).push(arguments)},i[r].l=1*new Date();a=s.createElement(o),m=s.getElementsByTagName(o)[0];a.async=1;a.src=g;m.parentNode.insertBefore(a,m)})(window,document,\u0022script\u0022,\u0022\/\/www.google-analytics.com\/analytics.js\u0022,\u0022ga\u0022);ga(\u0022create\u0022, \u0022UA-15605596-27\u0022, {\u0022cookieDomain\u0022:\u0022auto\u0022});ga(\u0022set\u0022, \u0022page\u0022, location.pathname + location.search + location.hash);ga(\u0022send\u0022, \u0022pageview\u0022);ga(\u0027create\u0027, \u0027UA-189672-26\u0027, \u0027auto\u0027, {\u0027name\u0027: \u0027hwTracker\u0027});\r\nga(\u0027hwTracker.send\u0027, \u0027pageview\u0027);\n\/\/--\u003E\u003C!]]\u003E\n\u003C\/script\u003E\n\u003Cscript type=\u0022text\/javascript\u0022\u003E\n\u003C!--\/\/--\u003E\u003C![CDATA[\/\/\u003E\u003C!--\njQuery.extend(Drupal.settings, {\u0022basePath\u0022:\u0022\\\/\u0022,\u0022pathPrefix\u0022:\u0022\u0022,\u0022highwire\u0022:{\u0022markup\u0022:[{\u0022requested\u0022:\u0022full-text\u0022,\u0022variant\u0022:\u0022full-text\u0022,\u0022view\u0022:\u0022full\u0022,\u0022pisa\u0022:\u0022spmdc;13\\\/4\\\/28\u0022},{\u0022requested\u0022:\u0022long\u0022,\u0022variant\u0022:\u0022full-text\u0022,\u0022view\u0022:\u0022full\u0022,\u0022pisa\u0022:\u0022spmdc;13\\\/4\\\/28\u0022}],\u0022ac\u0022:{\u0022spmdc;13\\\/4\\\/28\u0022:{\u0022access\u0022:{\u0022reprint\u0022:true,\u0022full\u0022:true},\u0022pisa_id\u0022:\u0022spmdc;13\\\/4\\\/28\u0022,\u0022atom_uri\u0022:\u0022\u0022,\u0022jcode\u0022:\u0022spmdc\u0022}}},\u0022googleanalytics\u0022:{\u0022trackOutbound\u0022:1,\u0022trackMailto\u0022:1,\u0022trackDownload\u0022:1,\u0022trackDownloadExtensions\u0022:\u00227z|aac|arc|arj|asf|asx|avi|bin|csv|doc(x|m)?|dot(x|m)?|exe|flv|gif|gz|gzip|hqx|jar|jpe?g|js|mp(2|3|4|e?g)|mov(ie)?|msi|msp|pdf|phps|png|ppt(x|m)?|pot(x|m)?|pps(x|m)?|ppam|sld(x|m)?|thmx|qtm?|ra(m|r)?|sea|sit|tar|tgz|torrent|txt|wav|wma|wmv|wpd|xls(x|m|b)?|xlt(x|m)|xlam|xml|z|zip\u0022,\u0022trackUrlFragments\u0022:1},\u0022ajaxPageState\u0022:{\u0022js\u0022:{\u0022sites\\\/all\\\/libraries\\\/cluetip\\\/jquery.cluetip.js\u0022:1,\u0022sites\\\/all\\\/libraries\\\/cluetip\\\/lib\\\/jquery.hoverIntent.js\u0022:1,\u0022sites\\\/all\\\/libraries\\\/cluetip\\\/lib\\\/jquery.bgiframe.min.js\u0022:1,\u0022sites\\\/all\\\/modules\\\/highwire\\\/highwire\\\/plugins\\\/highwire_markup_process\\\/js\\\/highwire_at_symbol.js\u0022:1,\u0022sites\\\/all\\\/modules\\\/highwire\\\/highwire\\\/plugins\\\/highwire_markup_process\\\/js\\\/highwire_article_reference_popup.js\u0022:1,\u0022sites\\\/all\\\/modules\\\/contrib\\\/google_analytics\\\/googleanalytics.js\u0022:1,\u00220\u0022:1}}});\n\/\/--\u003E\u003C!]]\u003E\n\u003C\/script\u003E\n\u003Clink type=\u0022text\/css\u0022 rel=\u0022stylesheet\u0022 href=\u0022\/\/d282kpwvnogo5m.cloudfront.net\/sites\/default\/files\/cdn\/css\/http\/css_Xg7z6oCTVgud_Q0huYz9x9iiD5H_2YPSJ5z2ZViSWdY.css\u0022 media=\u0022all\u0022 \/\u003E\n\u003Clink rel=\u0027stylesheet\u0027 type=\u0027text\/css\u0027 href=\u0027\/sites\/all\/modules\/contrib\/panels\/plugins\/layouts\/onecol\/onecol.css\u0027 \/\u003E\u003C\/head\u003E\u003Cbody\u003E\u003Cdiv class=\u0022panels-ajax-tab-panel panels-ajax-tab-panel-sageoa-tab-art\u0022\u003E\u003Cdiv class=\u0022panel-display panel-1col clearfix\u0022 \u003E\n  \u003Cdiv class=\u0022panel-panel panel-col\u0022\u003E\n    \u003Cdiv\u003E\u003Cdiv class=\u0022panel-pane pane-highwire-markup\u0022 \u003E\n  \n      \n  \n  \u003Cdiv class=\u0022pane-content\u0022\u003E\n    \u003Cdiv class=\u0022highwire-markup\u0022\u003E\u003Cdiv xmlns=\u0022http:\/\/www.w3.org\/1999\/xhtml\u0022 id=\u0022content-block-markup\u0022 xmlns:xhtml=\u0022http:\/\/www.w3.org\/1999\/xhtml\u0022\u003E\u003Cdiv class=\u0022article fulltext-view \u0022\u003E\u003Cspan class=\u0022highwire-journal-article-marker-start\u0022\u003E\u003C\/span\u003E\u003Cdiv class=\u0022section abstract\u0022 id=\u0022abstract-1\u0022\u003E\u003Ch2\u003ESummary\u003C\/h2\u003E\n            \u003Cp id=\u0022p-1\u0022\u003ELow-dose computed tomography (CT) is currently the best method for the early detection of lung cancer, and evidence demonstrates that screening saves lives when the technology is used properly for a high-risk population. However, lung cancer screening is not ideal, and issues include a high rate of false-positive results, complications related to diagnostic procedures, radiation-related harms, and patient anxiety. This article discusses the search for biomarkers, exhaled breath analysis, and airway gene-expression profiling, among other topics.\u003C\/p\u003E\n         \u003C\/div\u003E\u003Cul class=\u0022kwd-group\u0022\u003E\u003Cli class=\u0022kwd\u0022\u003ECancer\u003C\/li\u003E\u003Cli class=\u0022kwd\u0022\u003ESmoking Cessation\u003C\/li\u003E\u003Cli class=\u0022kwd\u0022\u003EPulmonary Genomics\u003C\/li\u003E\u003Cli class=\u0022kwd\u0022\u003ERespiratory Cancers\u003C\/li\u003E\u003Cli class=\u0022kwd\u0022\u003EOncology Genomics\u003C\/li\u003E\u003C\/ul\u003E\u003Cul class=\u0022kwd-group clinical-trial\u0022\u003E\u003Cli class=\u0022kwd\u0022\u003EOncology\u003C\/li\u003E\u003Cli class=\u0022kwd\u0022\u003EPulmonary \u0026amp; Respiratory Medicine\u003C\/li\u003E\u003C\/ul\u003E\u003Cp id=\u0022p-2\u0022\u003ELow-dose computed tomography (CT) is currently the best method for the early detection of lung cancer, and evidence demonstrates that screening saves lives when the technology is used properly for a high-risk population. However, lung cancer screening is not ideal, and issues include a high rate of false-positive results, complications related to diagnostic procedures, radiation-related harms, and patient anxiety, said Peter B. Bach, MD, MAPP, Memorial Sloan-Kettering Cancer Center, New York, New York, USA. In addition, the 20% reduction in mortality demonstrated in the National Lung Screening Trial (NLST) [NLST Research Team. \u003Cem\u003EN Engl J Med\u003C\/em\u003E 2011] has not been reached in other studies [Infante M et al. \u003Cem\u003EAm J Respir Care Med\u003C\/em\u003E 2009]. Reducing the cost and decreasing the potential harms of lung cancer screening and expediting the diagnosis of screening-detected nodules will help maximize the benefit of lung cancer. Researchers agree that better identification of people at high risk for the development of cancer is the way to achieve this goal.\u003C\/p\u003E\u003Cp id=\u0022p-3\u0022\u003EAs defined by the NLST, high risk describes a person who is aged 55 to 74 years, a heavy smoker (\u0026gt;30 pack-years), or a current or recent user (\u0026lt;15 years) of tobacco.\u003C\/p\u003E\u003Cp id=\u0022p-4\u0022\u003ECare should be taken to define others who may benefit from lung cancer screening, said Douglas Arenberg, MD, University of Michigan, Ann Arbor, Michigan, USA, emphasizing the importance of estimating risk with a risk model. Dr. Arenberg added that physicians must be able to better define risk in order to discuss it with their patients. He noted that physicians must remember that mortality\u2014not survival\u2014is valid evidence of benefit of screening.\u003C\/p\u003E\u003Cp id=\u0022p-5\u0022\u003EDr. Bach said that when communicating risk to their patients, physicians should quantify the benefits and harms, using a round denominator (such as 1000) and absolute rather than relative numbers; emphasize not smoking; and recommend useful online tools to estimate risk.\u003C\/p\u003E\u003Cp id=\u0022p-6\u0022\u003ETo help better identify patients at risk for the development of lung cancer, researchers are exploring the use of biomarkers, and several innovative approaches show promise.\u003C\/p\u003E\u003Cdiv class=\u0022section\u0022 id=\u0022sec-1\u0022\u003E\n         \u003Ch2 class=\u0022\u0022\u003ETHE SEARCH FOR BIOMARKERS\u003C\/h2\u003E\n         \u003Cp id=\u0022p-7\u0022\u003EMany biomarkers have been discovered, but none has reached clinical practice yet. Part of the problem is the long time needed for qualification and validation of candidate biomarkers, said Peter Mazzone, MD, MPH, Cleveland Clinic, Cleveland, Ohio, USA. Exhaled breath analysis, airway gene-expression profiling, and innovative technology to search for potential proteomic biomarkers are some steps toward improving the benefit of lung cancer screening.\u003C\/p\u003E\n      \u003C\/div\u003E\u003Cdiv class=\u0022section\u0022 id=\u0022sec-2\u0022\u003E\n         \u003Ch2 class=\u0022\u0022\u003EEXHALED BREATH ANALYSIS\u003C\/h2\u003E\n         \u003Cp id=\u0022p-8\u0022\u003EDr. Mazzone explained that volatile organic compounds (VOCs) are present in the breath at low concentrations (low number per billion), and most VOCs represent metabolic processes in cells [Miekisch W et al. \u003Cem\u003EClin Chim Acta\u003C\/em\u003E 2004]. Research has shown that these processes differ between people with and without lung cancer. In a proof-of-principle study, colorimetric sensor array (\u003Ca id=\u0022xref-fig-1-1\u0022 class=\u0022xref-fig\u0022 href=\u0022#F1\u0022\u003EFigure 1\u003C\/a\u003E) had modest accuracy in detecting a unique chemical signature of the breath of people with lung cancer (sensitivity of 73.3% and specificity of 72.4%; p=0.01) [Mazzone PJ et al. \u003Cem\u003EThorax\u003C\/em\u003E 2007].\u003C\/p\u003E\n         \u003Cp id=\u0022p-9\u0022\u003EThese findings were confirmed in a subsequent study with 229 subjects (92 with biopsy-proven lung cancer and 137 controls; 67 subjects at risk for the development of lung cancer and 70 subjects with benign lung nodules, 4 to 20 mm in diameter). The incorporation of clinical risk factors (age, sex, smoking history, and chronic obstructive pulmonary disease) led to greater accuracy of the analysis, as did a focus on only one histology [Mazzone PJ et al. \u003Cem\u003EJ Thorac Oncol\u003C\/em\u003E 2012]. Dr. Mazzone said that the colorimetric sensor array can be developed into a clinically useful tool, but the technique is still in the early phases of qualification. He added that it is unclear whether this technique will be more accurate than currently available screening and that its greatest benefits are its ease of use and the availability of real-time results.\u003C\/p\u003E\n      \u003C\/div\u003E\u003Cdiv class=\u0022section\u0022 id=\u0022sec-3\u0022\u003E\n         \u003Ch2 class=\u0022\u0022\u003EAIRWAY GENE-EXPRESSION PROFILING\u003C\/h2\u003E\n         \u003Cp id=\u0022p-10\u0022\u003EAvrum Spira, MD, Division of Computational Biomedicine, Boston University Medical Center, Boston, Massachusetts, USA, and colleagues have developed a gene-expression profile assay to test normal epithelial cells obtained with bronchial brushing. Airway gene expression reflects the physiologic response to tobacco smoke and can serve as an early diagnostic biomarker for lung cancer [Spira A et al. \u003Cem\u003ENat Med\u003C\/em\u003E 2007]. This biomarker may help address the problem of indiscriminate nodules detected on screening and challenges in decision-making after nondiagnostic bronchoscopy; for example, helping to determine whether a biopsy should be done or it is safe to wait for repeat imaging in 3 months.\u003C\/p\u003E\n         \u003Cp id=\u0022p-11\u0022\u003EEpithelial cells in the airway become exposed to toxins from cigarette smoke, leading to genomic abnormalities. Variability in response can be measured at the gene-expression level, and differences in response are associated with individual risk for the development of lung cancer. Approximately 80% of these gene-expression changes revert to normal after a smoker quits, but 10% to 20% are irreversible changes, persisting for years, sometimes decades, after quitting [Beane J et al. \u003Cem\u003EGenome Biol\u003C\/em\u003E 2007].\u003C\/p\u003E\n         \u003Cdiv id=\u0022F1\u0022 class=\u0022fig pos-float  odd\u0022\u003E\u003Cdiv class=\u0022highwire-figure\u0022\u003E\u003Cdiv class=\u0022fig-inline-img-wrapper\u0022\u003E\u003Cdiv class=\u0022fig-inline-img\u0022\u003E\u003Ca href=\u0022http:\/\/d282kpwvnogo5m.cloudfront.net\/content\/spmdc\/13\/4\/28\/F1.large.jpg?width=800\u0026amp;height=600\u0026amp;carousel=1\u0022 title=\u0022Sensor Arrays\u0022 class=\u0022fragment-images colorbox-load\u0022 rel=\u0022gallery-fragment-images-1298635794\u0022 data-figure-caption=\u0022Sensor Arrays\u0022 data-icon-position=\u0022\u0022 data-hide-link-title=\u00220\u0022\u003E\u003Cimg class=\u0022fragment-image\u0022 alt=\u0022Figure 1.\u0022 src=\u0022http:\/\/d282kpwvnogo5m.cloudfront.net\/content\/spmdc\/13\/4\/28\/F1.medium.gif\u0022\/\u003E\u003C\/a\u003E\u003C\/div\u003E\u003C\/div\u003E\u003Cul class=\u0022highwire-figure-links inline\u0022\u003E\u003Cli class=\u00220 first\u0022\u003E\u003Ca href=\u0022http:\/\/d282kpwvnogo5m.cloudfront.net\/content\/spmdc\/13\/4\/28\/F1.large.jpg?download=true\u0022 class=\u0022highwire-figure-link highwire-figure-link-download\u0022 title=\u0022Download Figure 1.\u0022 data-icon-position=\u0022\u0022 data-hide-link-title=\u00220\u0022\u003EDownload figure\u003C\/a\u003E\u003C\/li\u003E\u003Cli class=\u00221\u0022\u003E\u003Ca href=\u0022http:\/\/d282kpwvnogo5m.cloudfront.net\/content\/spmdc\/13\/4\/28\/F1.large.jpg\u0022 class=\u0022highwire-figure-link highwire-figure-link-newtab\u0022 target=\u0022_blank\u0022 data-icon-position=\u0022\u0022 data-hide-link-title=\u00220\u0022\u003EOpen in new tab\u003C\/a\u003E\u003C\/li\u003E\u003Cli class=\u00222 last\u0022\u003E\u003Ca href=\u0022\/highwire\/powerpoint\/13120\u0022 class=\u0022highwire-figure-link highwire-figure-link-ppt\u0022 data-icon-position=\u0022\u0022 data-hide-link-title=\u00220\u0022\u003EDownload powerpoint\u003C\/a\u003E\u003C\/li\u003E\u003C\/ul\u003E\u003C\/div\u003E\u003Cdiv class=\u0022fig-caption attrib\u0022\u003E\u003Cspan class=\u0022fig-label\u0022\u003EFigure 1.\u003C\/span\u003E \n               \u003Cp id=\u0022p-12\u0022 class=\u0022first-child\u0022\u003ESensor Arrays\u003C\/p\u003E\n            \u003Cq class=\u0022attrib\u0022 id=\u0022attrib-1\u0022\u003ENote: Colorimetric sensor array for analysis of volatile organic compounds (VOCs) in exhaled breath. In the system, 36 spots composed of different chemically sensitive compounds are impregnated on a disposable cartridge. The colors of the spots change based on the chemicals with which they come into contact.\u003C\/q\u003E\u003Cq class=\u0022attrib\u0022 id=\u0022attrib-2\u0022\u003EReproduced from Mazzone P et al. Exhaled Breath Analysis with a Colorimetric Sensor Array for the Identification and Characterization of Lung Cancer. J Thorac Oncol 2012;7(1):137\u2013142.\u003C\/q\u003E\u003Cdiv class=\u0022sb-div caption-clear\u0022\u003E\u003C\/div\u003E\u003C\/div\u003E\u003C\/div\u003E\n         \u003Cp id=\u0022p-13\u0022\u003EA 36-gene panel was used in a clinical validation test that distinguished smokers with and without lung cancer and was validated in an independent multicenter cohort. The sensitivity was high for nodules that were \u0026lt;3 cm and for stage I or II disease, with the sensitivity of the biomarker outperforming bronchoscopy (nodule \u0026lt;3 cm: 88% vs 66%; stage I or II disease: 86% vs 40%) [Whitney DH et al. ATS 2013 (poster k43)]. When the biomarker was combined with bronchoscopy, the sensitivities increased to 96% and 93%, respectively.\u003C\/p\u003E\n         \u003Cp id=\u0022p-14\u0022\u003EThe next step is to create a less invasive test by analyzing RNA obtained from nasal mucosal brushings. The physiologic responses to smoking in the nose are similar to those seen in the bronchus, said Dr. Spira, with \u0026gt;90% of the genes in the nose changing in the same way in response to smoking as those in the bronchus [Zhang X et al. \u003Cem\u003EPhysiol Genomics\u003C\/em\u003E 2010]. Of smokers with suspect lung cancer, the test has an AUC of 0.73 in the diagnostic setting.\u003C\/p\u003E\n      \u003C\/div\u003E\u003Cdiv class=\u0022section\u0022 id=\u0022sec-4\u0022\u003E\n         \u003Ch2 class=\u0022\u0022\u003EPROTEOMIC SEARCH FOR BIOMARKERS\u003C\/h2\u003E\n         \u003Cp id=\u0022p-15\u0022\u003EBloodborne biomarkers may also be useful in helping to identify people at high risk for lung cancer, but several physiologic and technical challenges are barriers, said Alessandra Luchini, PhD, George Mason University, Manassas, Virginia, USA. For example, bloodborne biomarkers associated with precancerous stages exist in very low concentrations, are obscured by abundant resident blood proteins such as albumin, and are rapidly degraded by endogenous and exogenous enzymes. The primary technical challenge is that mass spectrometry, the tool used most commonly to identify biomarkers, lacks sensitivity when applied directly to complex mixtures. Dr. Luchini has addressed these challenges with the development of a unique technology: bait functionalized hydrogel nanoparticles, which increase the sensitivity of mass spectrometry by four orders of magnitude.\u003C\/p\u003E\n         \u003Cp id=\u0022p-16\u0022\u003EThis innovative nanotechnology was used in a study designed to discover and validate biomarkers for subclinical disease in blood samples obtained from initially healthy men up to 25 years before a lung cancer diagnosis. The biomarkers of interest were proteins found in the blood of healthy individuals in whom lung cancer subsequently developed, but not in the blood of individuals who remained cancer-free over the same follow-up period. The data set included samples from 40 people with adenocarcinoma and 40 matched controls. Dr. Luchini and coworkers determined the top-ranking proteins among smokers, former smokers, and never smokers and identified the proteins that best separated individuals with and without cancer in the three categories. Dr. Luchini noted that there was considerable overlap in the selected protein biomarkers in the smoker and former smoker categories and that the results suggest the mechanism of carcinogenesis may be different in nonsmokers. Selected proteins are now being validated in a new cohort of patients in a blinded fashion.\u003C\/p\u003E\n      \u003C\/div\u003E\u003Cul class=\u0022copyright-statement\u0022\u003E\u003Cli class=\u0022fn\u0022 id=\u0022copyright-statement-1\u0022\u003E\u00a9 2013 MD Conference Express\u00ae\u003C\/li\u003E\u003C\/ul\u003E\u003Cspan class=\u0022highwire-journal-article-marker-end\u0022\u003E\u003C\/span\u003E\u003C\/div\u003E\u003Cspan id=\u0022related-urls\u0022\u003E\u003C\/span\u003E\u003C\/div\u003E\u003Ca href=\u0022http:\/\/mdc.sagepub.com\/content\/13\/4\/28.abstract\u0022 class=\u0022hw-link hw-link-article-abstract\u0022 data-icon-position=\u0022\u0022 data-hide-link-title=\u00220\u0022\u003EView Summary\u003C\/a\u003E\u003C\/div\u003E  \u003C\/div\u003E\n\n  \n  \u003C\/div\u003E\n\u003C\/div\u003E\n  \u003C\/div\u003E\n\u003C\/div\u003E\n\u003C\/div\u003E\u003Cscript type=\u0022text\/javascript\u0022 src=\u0022http:\/\/mdc.sagepub.com\/sites\/all\/modules\/highwire\/highwire\/plugins\/highwire_markup_process\/js\/highwire_figures.js?nzny02\u0022\u003E\u003C\/script\u003E\n\u003Cscript type=\u0022text\/javascript\u0022 src=\u0022http:\/\/mdc.sagepub.com\/sites\/all\/modules\/highwire\/highwire\/plugins\/highwire_markup_process\/js\/highwire_openurl.js?nzny02\u0022\u003E\u003C\/script\u003E\n\u003C\/body\u003E\u003C\/html\u003E"}