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            "title": "Integrated barcode chips for rapid, multiplexed analysis of proteins in microliter quantities of blood",
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                    "firstName": "Rong",
                    "lastName": "Fan"
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                    "lastName": "Vermesh"
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                    "firstName": "Brian K. H.",
                    "lastName": "Yen"
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                    "lastName": "Qin"
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                    "firstName": "Habib",
                    "lastName": "Ahmad"
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                    "creatorType": "author",
                    "firstName": "Gabriel A.",
                    "lastName": "Kwong"
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                    "firstName": "Chao-Chao",
                    "lastName": "Liu"
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                    "firstName": "Juliane",
                    "lastName": "Gould"
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                    "firstName": "Leroy",
                    "lastName": "Hood"
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                    "creatorType": "author",
                    "firstName": "James R.",
                    "lastName": "Heath"
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            "publicationTitle": "Nat Biotech",
            "publisher": "",
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            "date": "2008",
            "volume": "26",
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            "title": "Reproducibility and Correlations of Multiplex Cytokine Levels in Asymptomatic Persons",
            "creators": [
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                    "creatorType": "author",
                    "firstName": "Hui-Lee",
                    "lastName": "Wong"
                },
                {
                    "creatorType": "author",
                    "firstName": "Ruth M.",
                    "lastName": "Pfeiffer"
                },
                {
                    "creatorType": "author",
                    "firstName": "Thomas R.",
                    "lastName": "Fears"
                },
                {
                    "creatorType": "author",
                    "firstName": "Roel",
                    "lastName": "Vermeulen"
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                {
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                    "firstName": "Shaoquan",
                    "lastName": "Ji"
                },
                {
                    "creatorType": "author",
                    "firstName": "Charles S.",
                    "lastName": "Rabkin"
                }
            ],
            "abstractNote": "Rationale: Cytokines are humoral regulatory molecules that act together in immunologic pathways underlying pathogenesis. Grossly elevated blood levels characterize certain diseases; variations within physiologic ranges could also have significance. We therefore evaluated the performance characteristics of a multiplex cytokine immunoassay.Methods: We used a fluorescent bead-based (Luminex) immunoassay kit to simultaneously measure interleukin (IL) 1β, IL2, IL4, IL5, IL6, IL7, IL8, IL10, IL12p70, IL13, IFNγ, granulocyte colony-stimulating factor, and tumor necrosis factor-α. We tested identical aliquots of serum from 38 asymptomatic individuals on three different days and matched sets of serum, heparinized plasma, and acid citrate dextrose plasma from an additional 38 healthy donors expected to have low cytokine concentrations. We applied multiple imputation to calculate unbiased reproducibility estimates for measurements below the limits of detection. Correlations among the cytokines were assessed by Spearman rank order coefficients and principal components analyses.Results: Of the 13 cytokines, 3 were undetectable (IL1β, IL2, IL5) in more than half of the serum samples. Coefficients of variation for replicate serum measurements ranged from 18% to 44%, with intraclass correlation coefficients ranging from 55% to 98%. Only IL4, IL6, and IL8 had statistically significant correlations (Spearman ρ, 0.42-0.94) between serum and acid citrate dextrose or heparin plasma levels.Conclusions: Interindividual differences outweigh substantial laboratory variation for these assays, yielding high intraclass correlation coefficients despite unimpressive coefficients of variation. Plasma measurements generally are not reflective of serum levels and hence are not interchangeable. With their small volume, low cost per test, and multiplex capacity, Luminex-based cytokine assays have potential utility for epidemiologic studies. (Cancer Epidemiol Biomarkers Prev 2008;17(12):3450–6)",
            "publicationTitle": "Cancer Epidemiology Biomarkers & Prevention",
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            "date": "December 01 , 2008",
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                    "tag": "bead assay"
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                    "tag": "cytokines"
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            "title": "Quantifying E. coli Proteome and Transcriptome with Single-Molecule Sensitivity in Single Cells",
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                    "creatorType": "author",
                    "firstName": "Yuichi",
                    "lastName": "Taniguchi"
                },
                {
                    "creatorType": "author",
                    "firstName": "Paul J.",
                    "lastName": "Choi"
                },
                {
                    "creatorType": "author",
                    "firstName": "Gene-Wei",
                    "lastName": "Li"
                },
                {
                    "creatorType": "author",
                    "firstName": "Huiyi",
                    "lastName": "Chen"
                },
                {
                    "creatorType": "author",
                    "firstName": "Mohan",
                    "lastName": "Babu"
                },
                {
                    "creatorType": "author",
                    "firstName": "Jeremy",
                    "lastName": "Hearn"
                },
                {
                    "creatorType": "author",
                    "firstName": "Andrew",
                    "lastName": "Emili"
                },
                {
                    "creatorType": "author",
                    "firstName": "X. Sunney",
                    "lastName": "Xie"
                }
            ],
            "abstractNote": "",
            "publicationTitle": "Science",
            "publisher": "",
            "place": "",
            "date": "2010",
            "volume": "329",
            "issue": "",
            "section": "",
            "partNumber": "",
            "partTitle": "",
            "pages": "533-538",
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    {
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        "version": 1,
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            },
            "creatorSummary": "Todd et al.",
            "parsedDate": "2007",
            "numChildren": 0
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        "data": {
            "key": "QTCDVCGX",
            "version": 1,
            "itemType": "journalArticle",
            "title": "Ultrasensitive Flow-based Immunoassays Using Single-Molecule Counting",
            "creators": [
                {
                    "creatorType": "author",
                    "firstName": "John",
                    "lastName": "Todd"
                },
                {
                    "creatorType": "author",
                    "firstName": "Bob",
                    "lastName": "Freese"
                },
                {
                    "creatorType": "author",
                    "firstName": "Ann",
                    "lastName": "Lu"
                },
                {
                    "creatorType": "author",
                    "firstName": "Douglas",
                    "lastName": "Held"
                },
                {
                    "creatorType": "author",
                    "firstName": "Jennifer",
                    "lastName": "Morey"
                },
                {
                    "creatorType": "author",
                    "firstName": "Richard",
                    "lastName": "Livingston"
                },
                {
                    "creatorType": "author",
                    "firstName": "Philippe",
                    "lastName": "Goix"
                }
            ],
            "abstractNote": "Background: Immunoassay (IA) technology has expanded the clinical utility of protein biomarkers, but demands for increased sensitivity, dynamic reporting ranges, and small sample volumes have limited the potential clinical usefulness of many biomarkers. We assessed the performance, including limits of detection (LODs) and the dynamic reporting range, of an IA-based technology, Erenna Immunoassay System, for a series of biomarkers, including cardiac troponin I (cTnI).  Methods: Erenna IAs were used with 10 different and clinically important biomarkers to ascertain the LOD with various sample sizes (10 {micro}L to 200 {micro}L).  Results: The Erenna Immunoassay System generated LODs of 10-100 pg/L using 100 {micro}L of sample. For cTnI, the LOD was 0.2 ng/L and a 10% CV was seen between 0.78 and 1.6 ng/L.  Conclusions: The Erenna IA-based technology reproducibly measures protein biomarkers with detection limits of 10-100 pg/L, with a dynamic range of >4.5 logs in sample volumes of 50-150 {micro}L.",
            "publicationTitle": "Clin Chem",
            "publisher": "",
            "place": "",
            "date": "2007",
            "volume": "53",
            "issue": "11",
            "section": "",
            "partNumber": "",
            "partTitle": "",
            "pages": "1990-1995",
            "series": "",
            "seriesTitle": "",
            "seriesText": "",
            "journalAbbreviation": "",
            "DOI": "",
            "citationKey": "",
            "url": "http://www.clinchem.org/cgi/content/abstract/53/11/1990",
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            "PMCID": "",
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            "libraryCatalog": "",
            "callNumber": "0034",
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            "version": 1,
            "itemType": "journalArticle",
            "title": "Mass Spectrometry to Classify Non–Small-Cell Lung Cancer Patients for Clinical Outcome After Treatment With Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitors: A Multicohort Cross-Institutional Study",
            "creators": [
                {
                    "creatorType": "author",
                    "firstName": "Fumiko",
                    "lastName": "Taguchi"
                },
                {
                    "creatorType": "author",
                    "firstName": "Benjamin",
                    "lastName": "Solomon"
                },
                {
                    "creatorType": "author",
                    "firstName": "Vanesa",
                    "lastName": "Gregorc"
                },
                {
                    "creatorType": "author",
                    "firstName": "Heinrich",
                    "lastName": "Roder"
                },
                {
                    "creatorType": "author",
                    "firstName": "Robert",
                    "lastName": "Gray"
                },
                {
                    "creatorType": "author",
                    "firstName": "Kazuo",
                    "lastName": "Kasahara"
                },
                {
                    "creatorType": "author",
                    "firstName": "Makoto",
                    "lastName": "Nishio"
                },
                {
                    "creatorType": "author",
                    "firstName": "Julie",
                    "lastName": "Brahmer"
                },
                {
                    "creatorType": "author",
                    "firstName": "Anna",
                    "lastName": "Spreafico"
                },
                {
                    "creatorType": "author",
                    "firstName": "Vienna",
                    "lastName": "Ludovini"
                },
                {
                    "creatorType": "author",
                    "firstName": "Pierre P.",
                    "lastName": "Massion"
                },
                {
                    "creatorType": "author",
                    "firstName": "Rafal",
                    "lastName": "Dziadziuszko"
                },
                {
                    "creatorType": "author",
                    "firstName": "Joan",
                    "lastName": "Schiller"
                },
                {
                    "creatorType": "author",
                    "firstName": "Julia",
                    "lastName": "Grigorieva"
                },
                {
                    "creatorType": "author",
                    "firstName": "Maxim",
                    "lastName": "Tsypin"
                },
                {
                    "creatorType": "author",
                    "firstName": "Stephen W.",
                    "lastName": "Hunsucker"
                },
                {
                    "creatorType": "author",
                    "firstName": "Richard",
                    "lastName": "Caprioli"
                },
                {
                    "creatorType": "author",
                    "firstName": "Mark W.",
                    "lastName": "Duncan"
                },
                {
                    "creatorType": "author",
                    "firstName": "Fred R.",
                    "lastName": "Hirsch"
                },
                {
                    "creatorType": "author",
                    "firstName": "Paul A.",
                    "lastName": "Bunn"
                },
                {
                    "creatorType": "author",
                    "firstName": "David P.",
                    "lastName": "Carbone"
                }
            ],
            "abstractNote": "Background Some but not all patients with non–small-cell lung cancer (NSCLC) respond to treatment with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs). We developed and tested the ability of a predictive algorithm based on matrix-assisted laser desorption ionization (MALDI) mass spectrometry (MS) analysis of pretreatment serum to identify patients who are likely to benefit from treatment with EGFR TKIs.Methods Serum collected from NSCLC patients before treatment with gefitinib or erlotinib were analyzed by MALDI MS. Spectra were acquired independently at two institutions. An algorithm to predict outcomes after treatment with EGFR TKIs was developed from a training set of 139 patients from three cohorts. The algorithm was then tested in two independent validation cohorts of 67 and 96 patients who were treated with gefitinib and erlotinib, respectively, and in three control cohorts of patients who were not treated with EGFR TKIs. The clinical outcomes of survival and time to progression were analyzed.Results An algorithm based on eight distinct m/z features was developed based on outcomes after EGFR TKI therapy in training set patients. Classifications based on spectra acquired at the two institutions had a concordance of 97.1%. For both validation cohorts, the classifier identified patients who showed improved outcomes after EGFR TKI treatment. In one cohort, median survival of patients in the predicted “good” and “poor” groups was 207 and 92 days, respectively (hazard ratio [HR] of death in the good versus poor groups = 0.50, 95% confidence interval [CI] = 0.24 to 0.78). In the other cohort, median survivals were 306 versus 107 days (HR = 0.41, 95% CI = 0.17 to 0.63). The classifier did not predict outcomes in patients who did not receive EGFR TKI treatment.Conclusion This MALDI MS algorithm was not merely prognostic but could classify NSCLC patients for good or poor outcomes after treatment with EGFR TKIs. This algorithm may thus assist in the pretreatment selection of appropriate subgroups of NSCLC patients for treatment with EGFR TKIs.",
            "publicationTitle": "Journal of the National Cancer Institute",
            "publisher": "",
            "place": "",
            "date": "June 06 , 2007",
            "volume": "99",
            "issue": "11",
            "section": "",
            "partNumber": "",
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            "pages": "838 -846",
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            "seriesTitle": "",
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            "citationKey": "",
            "url": "http://jnci.oxfordjournals.org/content/99/11/838.abstract",
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            "shortTitle": "",
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            "libraryCatalog": "",
            "callNumber": "0113",
            "rights": "",
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            "tags": [
                {
                    "tag": "Personalized medicine"
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                {
                    "tag": "Proteomics"
                }
            ],
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            "dateAdded": "2010-11-25T16:07:07Z",
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            "creatorSummary": "Greystoke et al.",
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            "itemType": "journalArticle",
            "title": "Optimisation of circulating biomarkers of cell death for routine clinical use",
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                    "creatorType": "author",
                    "firstName": "A.",
                    "lastName": "Greystoke"
                },
                {
                    "creatorType": "author",
                    "firstName": "J.",
                    "lastName": "Cummings"
                },
                {
                    "creatorType": "author",
                    "firstName": "T.",
                    "lastName": "Ward"
                },
                {
                    "creatorType": "author",
                    "firstName": "K.",
                    "lastName": "Simpson"
                },
                {
                    "creatorType": "author",
                    "firstName": "A.",
                    "lastName": "Renehan"
                },
                {
                    "creatorType": "author",
                    "firstName": "F.",
                    "lastName": "Butt"
                },
                {
                    "creatorType": "author",
                    "firstName": "D.",
                    "lastName": "Moore"
                },
                {
                    "creatorType": "author",
                    "firstName": "J.",
                    "lastName": "Gietema"
                },
                {
                    "creatorType": "author",
                    "firstName": "F.",
                    "lastName": "Blackhall"
                },
                {
                    "creatorType": "author",
                    "firstName": "M.",
                    "lastName": "Ranson"
                },
                {
                    "creatorType": "author",
                    "firstName": "A.",
                    "lastName": "Hughes"
                },
                {
                    "creatorType": "author",
                    "firstName": "C.",
                    "lastName": "Dive"
                }
            ],
            "abstractNote": "Background: M30™ and M65™ enzyme-linked immunosorbent assays detect circulating cytokeratin 18 fragments released during caspase-dependent or total cell death, respectively, and have potential as biomarkers in epithelial cancers. While these assays have been validated, their robustness for routine clinical use is unknown.Patients and methods: M30 and M65 were measured in matched serum and plasma samples from 31 lung cancer patients and 18 controls.Results: Time allowable between sample acquisition and processing is critical for assays in clinical use. A 4-h delay in processing at room temperature increased M30 (P < 0.0001), an effect minimised by incubation on ice. M30 and M65 in serum were resistant to processing variations including delays. Serum and plasma measurements correlated well although M30 but not M65 was lower in serum (P < 0.0005). Less variation between duplicate assays was observed in serum. Prolonged storage (−80°C) led to increased M30 (12%, 6 months; 34%, 1 year). Sample dilution in the supplied assay diluent proved non-linear, whereas dilution in donor serum or porcine plasma restored linearity up to a ratio of 1 : 6.Conclusion: We present recommendations that improve the reliability of these assays for clinical use and recommend serum as the preferred matrix with data more resistant to variations in collection.",
            "publicationTitle": "Annals of Oncology",
            "publisher": "",
            "place": "",
            "date": "May 01 , 2008",
            "volume": "19",
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            "pages": "990 -995",
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            "creatorSummary": "Rosentreter et al.",
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            "itemType": "journalArticle",
            "title": "Response of retinal ganglion cell axons to striped linear gradients of repellent guidance molecules",
            "creators": [
                {
                    "creatorType": "author",
                    "firstName": "Stephan M.",
                    "lastName": "Rosentreter"
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                {
                    "creatorType": "author",
                    "firstName": "Roger W.",
                    "lastName": "Davenport"
                },
                {
                    "creatorType": "author",
                    "firstName": "Jürgen",
                    "lastName": "Löschinger"
                },
                {
                    "creatorType": "author",
                    "firstName": "Julita",
                    "lastName": "Huf"
                },
                {
                    "creatorType": "author",
                    "firstName": "Jürgen",
                    "lastName": "Jung"
                },
                {
                    "creatorType": "author",
                    "firstName": "Friedrich",
                    "lastName": "Bonhoeffer"
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            ],
            "abstractNote": "Abstract 10.1002/(SICI)1097-4695(199812)37:4<541::AID-NEU4>3.3.CO;2-C Although molecular gradients have long been postulated to play a role in the development of topographic projections in the nervous system, relatively little is known about how axons evaluate gradients. Do growth cones respond to concentration or to slope? Do they react suddenly or gradually? Is there adaptation? In the developing retinotectal system, temporal retinal ganglion cell axons have previously been shown to avoid repellent cell-surface activities distributed in gradients across the optic tectum. We confronted temporal retinal axons with precisely formed striped linear gradients of repellent tectal membranes and of two candidate repellent molecules, ephrin-A2 and -A5. Axons entered gradient stripes independently of their slope and extended unhindered in the uphill direction until they suddenly avoided an apparent threshold concentration of repellent material that was independent of slope. This critical concentration was similar in both linear and nonlinear gradients, and hence independent of gradient shape. When gradients of identical slope were formed on different basal levels of repellent material, axons grew uphill for a fixed increment of concentration, possibly measured from the lowest point of the gradient, rather than up to a fixed absolute concentration. The speed of growth cones was not affected by repellent unstriped gradients below the critical concentration level. Similar results were found with membranes from cell lines stably transfected with either ephrin-A5 or ephrin-A2, two previously identified growth cone repellent cell-surface proteins. These data suggest that growth cones or axons can integrate guidance information over large distances, probably by a combined memory and adaptation mechanism. © 1998 John Wiley & Sons, Inc. J Neurobiol 37: 541–562, 1998",
            "publicationTitle": "Journal of Neurobiology",
            "publisher": "",
            "place": "",
            "date": "1998",
            "volume": "37",
            "issue": "4",
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            "partNumber": "",
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            "pages": "541-562",
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            "journalAbbreviation": "J. Neurobiol.",
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            "tags": [
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                    "tag": "axon guidance"
                },
                {
                    "tag": "growth cone"
                },
                {
                    "tag": "molecular gradients"
                },
                {
                    "tag": "topographic maps, Eph-related receptor tyrosine kinases and ligands"
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            "abstractNote": "Microarray-based sandwich immunoassays can simultaneously detect dozens of proteins. However, their use in quantifying large numbers of proteins is hampered by cross-reactivity and incompatibilities caused by the immunoassays themselves. Sequential multiplex analyte capturing addresses these problems by repeatedly probing the same sample with different sets of antibody-coated, magnetic suspension bead arrays. As a miniaturized immunoassay format, suspension bead array-based assays fulfill the criteria of the ambient analyte theory, and our experiments reveal that the analyte concentrations are not significantly changed. The value of sequential multiplex analyte capturing was demonstrated by probing tumor cell line lysates for the abundance of seven different receptor tyrosine kinases and their degree of phosphorylation and by measuring the complex phosphorylation pattern of the epidermal growth factor receptor in the same sample from the same cavity.",
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            "note": "<div id=\"abstract-1\" class=\"section abstract\">\n<h2>Abstract</h2>\n<p id=\"p-1\"><strong>Background:</strong> M30™ and M65™  enzyme-linked immunosorbent assays detect circulating cytokeratin 18  fragments released during caspase-dependent                      or total cell death, respectively, and have  potential as biomarkers in epithelial cancers. While these assays have  been validated,                      their robustness for routine clinical use is  unknown.</p>\n<p id=\"p-2\"><strong>Patients and methods:</strong> M30 and M65 were measured in matched serum and plasma samples from 31 lung cancer patients and 18 controls.</p>\n<p id=\"p-3\"><strong>Results:</strong> Time allowable between sample acquisition and processing is critical for assays in clinical use. A 4-h delay in processing                      at room temperature increased M30 (<em>P</em> &lt; 0.0001), an effect minimised by incubation on ice. M30 and M65 in serum were resistant to processing variations including                      delays. Serum and plasma measurements correlated well although M30 but not M65 was lower in serum (<em>P</em> &lt; 0.0005). Less variation between duplicate assays was observed in  serum. Prolonged storage (−80°C) led to increased M30                      (12%, 6 months; 34%, 1 year). Sample dilution in  the supplied assay diluent proved non-linear, whereas dilution in donor  serum                      or porcine plasma restored linearity up to a ratio  of 1 : 6.</p>\n<p id=\"p-4\"><strong>Conclusion:</strong> We present recommendations that improve the reliability of these assays for clinical use and recommend serum as the preferred                      matrix with data more resistant to variations in collection.</p>\n<h3 class=\"kwd-header\">Key words</h3>\n<ul class=\"kwd-group\">\n<li class=\"kwd\"><span><span class=\"kwd-search\">apoptosis</span></span></li>\n<li class=\"kwd\"><span><span class=\"kwd-search\">cell death biomarkers</span></span></li>\n<li class=\"kwd\"><span><span class=\"kwd-search\">clinical utility</span></span></li>\n<li class=\"kwd\"><span><span class=\"kwd-search\">M30</span></span></li>\n<li class=\"kwd\"><span><span class=\"kwd-search\">M65</span></span></li>\n<li class=\"kwd\"><span><span class=\"kwd-search\">small-cell lung cancer</span></span></li>\n</ul>\n</div>",
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