BackgroundReceiver operating characteristic (ROC) curves are useful tools to evaluate classifiers in biomedical and bioinformatics applications. However, conclusions are often reached through inconsistent use or insufficient statistical analysis. To support researchers in their ROC curves analysis we developed pROC, a package for R and S+ that contains a set of tools displaying, analyzing, smoothing and comparing ROC curves in a user-friendly, object-oriented and flexible interface.ResultsWith data previously imported into the R or S+ environment, the pROC package builds ROC curves and includes functions for computing confidence intervals, statistical tests for comparing total or partial area under the curve or the operating points of different classifiers, and methods for smoothing ROC curves. Intermediary and final results are visualised in user-friendly interfaces. A case study based on published clinical and biomarker data shows how to perform a typical ROC analysis with pROC.ConclusionspROC is a package for R and S+ specifically dedicated to ROC analysis. It proposes multiple statistical tests to compare ROC curves, and in particular partial areas under the curve, allowing proper ROC interpretation. pROC is available in two versions: in the R programming language or with a graphical user interface in the S+ statistical software. It is accessible at http://expasy.org/tools/pROC/ under the GNU General Public License. It is also distributed through the CRAN and CSAN public repositories, facilitating its installation.

A new 6-plex isobaric mass tagging technology is presented, and proof of principle studies are carried out using standard protein mixtures and human cerebrospinal fluid (CSF) samples. The Tandem Mass Tags (TMT) comprise a set of structurally identical tags which label peptides on free amino-terminus and epsilon-amino functions of lysine residues. During MS/MS fragmentation, quantification information is obtained through the losses of the reporter ions. After evaluation of the relative quantification with the 6-plex version of the TMT on a model protein mixture at various concentrations, the quantification of proteins in CSF samples was performed using shotgun methods. Human postmortem (PM) CSF was taken as a model of massive brain injury and comparison was carried out with antemortem (AM) CSF. After immunoaffinity depletion, triplicates of AM and PM CSF pooled samples were reduced, alkylated, digested by trypsin, and labeled, respectively, with the six isobaric variants of the TMT (with reporter ions from m/z = 126.1 to 131.1 Th). The samples were pooled and fractionated by SCX chromatography. After RP-LC separation, peptides were identified and quantified by MS/MS analysis with MALDI TOF/TOF and ESI-Q-TOF. The concentration of 78 identified proteins was shown to be clearly increased in PM CSF samples compared to AM. Some of these proteins, like GFAP, protein S100B, and PARK7, have been previously described as brain damage biomarkers, supporting the PM CSF as a valid model of brain insult. ELISA for these proteins confirmed their elevated concentration in PM CSF. This work demonstrates the validity and robustness of the tandem mass tag (TMT) approach for quantitative MS-based proteomics.

Righini M. Cardiac biomarkers for risk stratification in non-massive pulmonary embolism: a multicenter prospective study. J Thromb Haemost 2009; 7: 391-8.Summary. Background: Troponins (cTnI and cTnT), Nterminal pro-Brain Natriuretic Peptide (NT-proBNP), myoglobin, heart-type fatty acid-binding protein (H-FABP) and fibrin D-Dimer are emergent candidates for risk stratification in pulmonary embolism (PE). Objective: To compare the respective prognostic values of biomarker with non-massive PE to predict an adverse outcome at 3 months. Patients/Methods: One hundred and forty-six consecutive patients with nonmassive PE were included in this multicenter prospective study. The combined outcome consisted of intensive care monitoring on admission, death or hospitalization attributable to either a PE-related complication [defined by PE/deep vein thrombosis (DVT) relapse or major bleeding under anticoagulation] or to dyspnoea with or without chest pain during follow-up. Results: The outcome was met in 12% of patients. In univariate analysis, a NT-proBNP level above 300 pg/ml was the strongest predictor of unfavorable outcome with an odds ratio (OR) of 15.8 [95% confidence interval (CI): 2.05-122). ORs for the other variables were: 8.0 for D-dimer >2000 ng/ml (95% CI: 1.1-64), 4.7 for H-FABP >6ng/ml (95% CI:1.5-14.8), 3.5 for cTnI >0.09 ng/ml (95% CI:1.2-9.7), 3.4 for myoglobin >70 ng/ml (95% CI:0.9-12.2). Receiver operating curve (ROC) analysis indicated that NT-proBNP was the best predictor [area under the curve (AUC) 0.84; 95%CI: 0.76-0.92; P < 0.0001] with a negative predictive value of 100% (95% CI: 91-100) at 300 pg/ ml. At that cut-off, the true negative rate for NT-proBNP was 40%. In multivariate analysis, NT-proBNP was the only significant independent predictors. Conclusions: NT-proBNP appears to be a good risk stratification marker in identifying low-risk patients with non-massive PE who could be treated in an outpatient setting.

This study supports the concept that modifications of the tear proteome can reflect biological abnormalities associated with multiple sclerosis and perhaps other inflammatory conditions affecting the CNS. In addition, alpha-1 antichymotrypsin elevation in tear fluid emerges as a promising biomarker for the diagnosis of multiple sclerosis.

The intestinal epithelium is a particularly interesting tissue as (1) it is in a constant cell renewal from a stem cell pool located in the crypts which form, with the underlying fibroblasts, a stem cell niche and (2) the pluripotent stem cells give rise to four main cell types: enterocytes, mucus, endocrine, and Paneth cells. The mechanisms leading to the determination of phenotype commitment and cell-specific expressions are still poorly understood. Although transgenic mouse models are powerful tools for elucidating the molecular cascades implicated in these processes, cell culture approaches bring easy and elegant ways to study cellular behavior, cell interactions, and cell signaling pathways for example. In the present review, we will describe the major tissue culture technologies that allow differentiation of epithelial cells from undifferentiated embryonic or crypt cells. We will point to the necessity of the re-creation of a complex microenvironment that allows full differentiation process to occur. We will also summarize the characteristics and interesting properties of the cell lines established from human colorectal tumors.

Parkinson's disease (PD) pathology spreads throughout the brain following a region-specific process predominantly affecting the substantia nigra (SN) pars compacta. SN exhibits a progressive loss of dopaminergic neurons responsible for the major cardinal motor symptoms, along with the occurrence of Lewy bodies in the surviving neurons. To gain new insights into the underlying pathogenic mechanisms in PD, we studied postmortem nigral tissues dissected from pathologically confirmed PD cases (n = 5) and neurologically intact controls (n = 8). Using a high-throughput shotgun proteomic strategy, we simultaneously identified 1795 proteins with concomitant quantitative data. To date, this represents the most extensive catalog of nigral proteins. Of them, 204 proteins displayed significant expression level changes in PD patients versus controls. These were involved in novel or known pathogenic processes including mitochondrial dysfunction, oxidative stress, or cytoskeleton impairment. We further characterized four candidates that might be relevant to PD pathogenesis. We confirmed the differential expression of ferritin-L and seipin by Western blot and demonstrated the neuronal localization of gamma glutamyl hydrolase and nebulette by immunohistochemistry. Our preliminary findings suggest a role for nebulette overexpression in PD neurodegeneration, through mechanisms that may involve cytoskeleton dynamics disruption. All MS data have been deposited in the ProteomeXchange with identifier PXD000427 (http://proteomecentral.proteomexchange.org/dataset/PXD000427).

Sweat is one of the less employed biofluids for discovery of markers in spite of its increased application in medicine for detection of drugs or for diagnostic of cystic fibrosis. In this research, human sweat was used as clinical sample to develop a screening tool for lung cancer, which is the carcinogenic disease with the highest mortality rate owing to the advanced stage at which it is usually detected. In this context, a method based on the metabolite analysis of sweat to discriminate between patients with lung cancer versus smokers as control individuals is proposed. The capability of the metabolites identified in sweat to discriminate between both groups of individuals was studied and, among them, a trisaccharide phosphate presented the best independent performance in terms of the specificity/sensitivity pair (80 and 72.7%, respectively). Additionally, two panels of metabolites were configured using the PanelomiX tool as an attempt to reduce false negatives (at least 80% specificity) and false positives (at least 80% sensitivity). The first panel (80% specificity and 69% sensitivity) was composed by suberic acid, a tetrahexose, and a trihexose, while the second panel (69% specificity and 80% sensitivity) included nonanedioic acid, a trihexose, and the monoglyceride MG(22:2). Thus, the combination of the five metabolites led to a single panel providing 80% specificity and 79% sensitivity, reducing the false positive and negative rates to almost 20%. The method was validated by estimation of within-day and between-days variability of the quantitative analysis of the five metabolites

In vivo human brain extracellular fluids (ECF) of acute stroke patients were investigated to assess the changes in protein levels associated with ischemic damages. Microdialysates (MDs) from the infarct core (IC), the penumbra (P), and the unaffected contralateral (CT) brain regions of patients suffering an ischemic stroke (n = 6) were compared using a shotgun proteomic approach based on isobaric tagging and mass spectrometry. Quantitative analysis showed 53 proteins with increased amounts in the IC or P with respect to the CT samples. Glutathione S-transferase P (GSTP1), peroxiredoxin-1 (PRDX1), and protein S100-B (S100B) were further assessed with ELISA on the blood of unrelated control (n = 14) and stroke (n = 14) patients. Significant increases of 8- (p = 0.0002), 20- (p = 0.0001), and 11-fold (p = 0.0093) were found, respectively. This study highlights the value of ECF as an efficient source to further discover blood stroke markers.