Comparison of Bisulfite Pyrosequencing and Methylation-Specific qPCR for Methylation Assessment

Different methodological approaches are available to assess DNA methylation biomarkers. In this study, we evaluated two sodium bisulfite conversion-dependent methods, namely pyrosequencing and methylation-specific qPCR (MS-qPCR), with the aim of measuring the closeness of agreement of methylation values between these two methods and its effect when setting a cut-off. Methylation of tumor suppressor gene p16/INK4A was evaluated in 80 lung cancer patients from which cytological lymph node samples were obtained. Cluster analyses were used to establish methylated and unmethylated groups for each method. Agreement and concordance between pyrosequencing and MS-qPCR was evaluated with Pearson's correlation, Bland-Altman, Cohen's kappa index and ROC curve analyses. Based on these analyses, cut-offs were derived for MS-qPCR. An acceptable correlation (Pearson's R2 = 0.738) was found between pyrosequencing (PYRmean) and MS-qPCR (NMP; normalized methylation percentage), providing similar clinical results when categorizing data as binary using cluster analysis. Compared to pyrosequencing, MS-qPCR tended to underestimate methylation for values between 0 and 15%, while for methylation >30% overestimation was observed. The estimated cut-off for MS-qPCR data based on cluster analysis, kappa-index agreement and ROC curve analysis were much lower than that derived from pyrosequencing. In conclusion, our results indicate that independently of the approach used for estimating the cut-off, the methylation percentage obtained through MS-qPCR is lower than that calculated for pyrosequencing. These differences in data and therefore in the cut-off should be examined when using methylation biomarkers in the clinical practice

Classes of behavior of small-world networks

Small-world networks are the focus of recent interest because they appear to circumvent many of the limitations of either random networks or regular lattices as frameworks for the study of interaction networks of complex systems. Here, we report an empirical study of the statistical properties of a variety of diverse real-world networks. We present evidence of the occurrence of three classes of small-world networks: (a) scale-free networks, characterized by a vertex connectivity distribution that decays as a power law; (b) broad-scale networks, characterized by a connectivity distribution that has a power-law regime followed by a sharp cut-off; (c) single-scale networks, characterized by a connectivity distribution with a fast decaying tail. Moreover, we note for the classes of broad-scale and single-scale networks that there are constraints limiting the addition of new links. Our results suggest that the nature of such constraints may be the controlling factor for the emergence of different classes of networks

Network analysis identifies weak and strong links in a metapopulation system

The identification of key populations shaping the structure and connectivity of metapopulation systems is a major challenge in population ecology. The use of molecular markers in the theoretical framework of population genetics has allowed great advances in this field, but the prime question of quantifying the role of each population in the system remains unresolved. Furthermore, the use and interpretation of classical methods are still bounded by the need for a priori information and underlying assumptions that are seldom respected in natural systems. Network theory was applied to map the genetic structure in a metapopulation system by using microsatellite data from populations of a threatened seagrass, Posidonia oceanica, across its whole geographical range. The network approach, free from a priori assumptions and from the usual underlying hypotheses required for the interpretation of classical analyses, allows both the straightforward characterization of hierarchical population structure and the detection of populations acting as hubs critical for relaying gene flow or sustaining the metapopulation system. This development opens perspectives in ecology and evolution in general, particularly in areas such as conservation biology and epidemiology, where targeting specific populations is crucial

Value of Serum NEUROG1 Methylation for the Detection of Advanced Adenomas and Colorectal Cancer

Aberrant DNA methylation detected in liquid biopsies is a promising approach for colorectal cancer (CRC) detection, including premalignant advanced adenomas (AA). We evaluated the diagnostic capability of serum NEUROG1 methylation for the detection of AA and CRC. A CpG island in NEUROG1 promoter was assessed by bisulfite pyrosequencing in a case-control cohort to select optimal CpGs. Selected sites were evaluated through a nested methylation-specific qPCR custom assay in a screening cohort of 504 asymptomatic family-risk individuals. Individuals with no colorectal findings and benign pathologies showed low serum NEUROG1 methylation, similar to non-advanced adenomas. Contrarily, individuals bearing AA or CRC (advanced neoplasia-AN), exhibited increased NEUROG1 methylation. Using >1.3518% as NEUROG1 cut-off (90.60% specificity), 33.33% of AN and 32.08% of AA were identified, detecting 50% CRC cases. Nonetheless, the combination of NEUROG1 with fecal immunochemical test (FIT), together with age and gender through a multivariate logistic regression resulted in an AUC = 0.810 for AN, and 0.796 for AA, detecting all cancer cases and 35-47% AA (specificity 98-95%). The combination of NEUROG1 methylation with FIT, age and gender demonstrated a convenient performance for the detection of CRC and AA, providing a valuable tool for CRC screening programs in asymptomatic individuals

Lung emphysema and lung cancer: what do we know about it?

Emphysema and lung cancer (LC) are two diseases which share common risk factors, e.g., smoking. In recent years, many studies have sought to analyse this association. By way of illustration, we conducted a review of the scientific literature of the studies published to date, whose main designated aim was to demonstrate the relationship between emphysema and LC, and this association's influence on the histology, prognosis and molecular mechanisms responsible. We included over 40 studies (ranging from case-control and cohort studies to systematic reviews and meta-analyses), which highlight the association between emphysema and LC, independently of smoking habit. These studies also report a possible influence on histology, with adenocarcinoma being the most frequent lineage, and an association with poor prognosis, which affects both survival and post-operative complications. Oxidative stress, which generates chronic inflammatory status as well as the presence of certain polymorphisms in various genes (CYP1A1, TERT, CLPTM1L, ERK), gives rise-in the case of patients with emphysema-to alteration of cellular repair mechanisms, which in turn favours the proliferation of neoplastic epithelial cells responsible for the origin of LC

Absence of Fragmentation in Two-Dimensional Bose-Einstein Condensation

We investigate the possibility that the BEC-like phenomena recently detected on two-dimensional finite trapped systems consist of fragmented condensates. We derive and diagonalize the one-body density matrix of a two-dimensional isotropically trapped Bose gas at finite temperature. For the ideal gas, the procedure reproduces the exact harmonic-oscillator eigenfunctions and the Bose distribution. We use a new collocation-minimization method to study the interacting gas in the Hartree-Fock approximation and obtain a ground-state wavefunction and condensate fraction consistent with those obtained by other methods. The populations of the next few eigenstates increase at the expense of the ground state but continue to be negligible; this supports the conclusion that two-dimensional BEC is into a single state.Comment: 6 pages, 1 figur

Validation of Calprotectin As a Novel Biomarker For The Diagnosis of Pleural Effusion: a Multicentre Trial

Discriminating between malignant pleural effusion (MPE) and benign pleural effusion (BPE) remains difficult. Thus, novel and efficient biomarkers are required for the diagnosis of pleural effusion (PE). The aim of this study was to validate calprotectin as a diagnostic biomarker of PE in clinical settings. A total of 425 patients were recruited, and the pleural fluid samples collected had BPE in 223 cases (53.7%) or MPE in 137 patients (33%). The samples were all analysed following the same previously validated clinical laboratory protocols and methodology. Calprotectin levels ranged from 772.48 to 3,163.8 ng/mL (median: 1,939 ng/mL) in MPE, and 3,216-24,000 ng/mL in BPE (median: 9,209 ng/mL; p < 0.01), with an area under the curve of 0.848 [95% CI: 0.810-0.886]. For a cut-off value of </= 6,233.2 ng/mL, we found 96% sensitivity and 60% specificity, with a negative and positive predictive value, and negative and positive likelihood ratios of 96%, 57%, 0.06, and 2.4, respectively. Multivariate analysis showed that low calprotectin levels was a better discriminator of PE than any other variable [OR 28.76 (p < 0.0001)]. Our results confirm that calprotectin is a new and useful diagnostic biomarker in patients with PE of uncertain aetiology which has potential applications in clinical practice because it may be a good complement to cytological methods