Statistical Inference for Valued-Edge Networks: Generalized Exponential Random Graph Models

Across the sciences, the statistical analysis of networks is central to the production of knowledge on relational phenomena. Because of their ability to model the structural generation of networks, exponential random graph models are a ubiquitous means of analysis. However, they are limited by an inability to model networks with valued edges. We solve this problem by introducing a class of generalized exponential random graph models capable of modeling networks whose edges are valued, thus greatly expanding the scope of networks applied researchers can subject to statistical analysis

On Mixing in Pairwise Markov Random Fields with Application to Social Networks

International audienceWe consider pairwise Markov random fields which have a number of important applications in statistical physics, image processing and machine learning such as Ising model and labeling problem to name a couple. Our own motivation comes from the need to produce synthetic models for social networks with attributes. First, we give conditions for rapid mixing of the associated Glauber dynamics and consider interesting particular cases. Then, for pairwise Markov random fields with submodular energy functions we construct monotone perfect simulation

Hospital-level associations with 30-day patient mortality after cardiac surgery: a tutorial on the application and interpretation of marginal and multilevel logistic regression

Background: Marginal and multilevel logistic regression methods can estimate associations between hospital-level factors and patient-level 30-day mortality outcomes after cardiac surgery. However, it is not widely understood how the interpretation of hospital-level effects differs between these methods. Methods. The Australasian Society of Cardiac and Thoracic Surgeons (ASCTS) registry provided data on 32,354 patients undergoing cardiac surgery in 18 hospitals from 2001 to 2009. The logistic regression methods related 30-day mortality after surgery to hospital characteristics with concurrent adjustment for patient characteristics. Results: Hospital-level mortality rates varied from 1.0% to 4.1% of patients. Ordinary, marginal and multilevel regression methods differed with regard to point estimates and conclusions on statistical significance for hospital-level risk factors; ordinary logistic regression giving inappropriately narrow confidence intervals. The median odds ratio, MOR, from the multilevel model was 1.2 whereas ORs for most patient-level characteristics were of greater magnitude suggesting that unexplained between-hospital variation was not as relevant as patient-level characteristics for understanding mortality rates. For hospital-level characteristics in the multilevel model, 80% interval ORs, IOR-80%, supplemented the usual ORs from the logistic regression. The IOR-80% was (0.8 to 1.8) for academic affiliation and (0.6 to 1.3) for the median annual number of cardiac surgery procedures. The width of these intervals reflected the unexplained variation between hospitals in mortality rates; the inclusion of one in each interval suggested an inability to add meaningfully to explaining variation in mortality rates. Conclusions: Marginal and multilevel models take different approaches to account for correlation between patients within hospitals and they lead to different interpretations for hospital-level odds ratios. © 2012 Sanagou et al; licensee BioMed Central Ltd

On the Importance of Complaint Handling Design : A Multi-Level Analysis of the Impact in Specific Complaint Situations

Given the large investments required for high-quality complaint handling design, managers need practical guidance in understanding its actual importance for their particular company. However, while prior research emphasizes the general relevance of complaint handling design, it fails to provide a more differentiated perspective on this interesting issue. This study, which is based on an integrative multi-level framework and a dyadic dataset, addresses this important gap in research. Results indicate that the impact of a company’s complaint handling design varies significantly depending on the characteristics of the complaining customers with which the firm has to deal. Further, this paper shows that, contingent on these characteristics, a company’s complaint handling design can shape complainants’ fairness perceptions either considerably or only slightly. Overall, findings suggest that companies should apply an adaptive approach to complaint handling to avoid misallocation of attention, energy, and resources

Integration of DNA Copy Number Alterations and Transcriptional Expression Analysis in Human Gastric Cancer

Background: Genomic instability with frequent DNA copy number alterations is one of the key hallmarks of carcinogenesis. The chromosomal regions with frequent DNA copy number gain and loss in human gastric cancer are still poorly defined. It remains unknown how the DNA copy number variations contributes to the changes of gene expression profiles, especially on the global level. Principal Findings: We analyzed DNA copy number alterations in 64 human gastric cancer samples and 8 gastric cancer cell lines using bacterial artificial chromosome (BAC) arrays based comparative genomic hybridization (aCGH). Statistical analysis was applied to correlate previously published gene expression data obtained from cDNA microarrays with corresponding DNA copy number variation data to identify candidate oncogenes and tumor suppressor genes. We found that gastric cancer samples showed recurrent DNA copy number variations, including gains at 5p, 8q, 20p, 20q, and losses at 4q, 9p, 18q, 21q. The most frequent regions of amplification were 20q12 (7/72), 20q12-20q13.1 (12/72), 20q13.1-20q13.2 (11/72) and 20q13.2-20q13.3 (6/72). The most frequent deleted region was 9p21 (8/72). Correlating gene expression array data with aCGH identified 321 candidate oncogenes, which were overexpressed and showed frequent DNA copy number gains; and 12 candidate tumor suppressor genes which were down-regulated and showed frequent DNA copy number losses in human gastric cancers. Three networks of significantly expressed genes in gastric cancer samples were identified by ingenuity pathway analysis. Conclusions: This study provides insight into DNA copy number variations and their contribution to altered gene expression profiles during human gastric cancer development. It provides novel candidate driver oncogenes or tumor suppressor genes for human gastric cancer, useful pathway maps for the future understanding of the molecular pathogenesis of this malignancy, and the construction of new therapeutic targets. © 2012 Fan et al.published_or_final_versio

Genomic imbalances in esophageal squamous cell carcinoma identified by molecular cytogenetic techniques

This review summarizes the chromosomal changes detected by molecular cytogenetic approaches in esophageal squamous cell carcinoma (ESCC), the ninth most common malignancy in the world. Whole genome analyses of ESCC cell lines and tumors indicated that the most frequent genomic gains occurred at 1, 2q, 3q, 5p, 6p, 7, 8q, 9q, 11q, 12p, 14q, 15q, 16, 17, 18p, 19q, 20q, 22q and X, with focal amplifications at 1q32, 2p16-22, 3q25-28, 5p13-15.3, 7p12-22, 7q21-22, 8q23-24.2, 9q34, 10q21, 11p11.2, 11q13, 13q32, 14q13-14, 14q21, 14q31-32, 15q22-26, 17p11.2, 18p11.2-11.3 and 20p11.2. Recurrent losses involved 3p, 4, 5q, 6q, 7q, 8p, 9, 10p, 12p, 13, 14p, 15p, 18, 19p, 20, 22, Xp and Y. Gains at 5p and 7q, and deletions at 4p, 9p, and 11q were significant prognostic factors for patients with ESCC. Gains at 6p and 20p, and losses at 10p and 10q were the most significant imbalances, both in primary carcinoma and in metastases, which suggested that these regions may harbor oncogenes and tumor suppressor genes. Gains at 12p and losses at 3p may be associated with poor relapse-free survival. The clinical applicability of these changes as markers for the diagnosis and prognosis of ESCC, or as molecular targets for personalized therapy should be evaluated

RNA interference-mediated c-MYC inhibition prevents cell growth and decreases sensitivity to radio- and chemotherapy in childhood medulloblastoma cells

BACKGROUND: With current treatment strategies, nearly half of all medulloblastoma (MB) patients die from progressive tumors. Accordingly, the identification of novel therapeutic strategies remains a major goal. Deregulation of c-MYC is evident in numerous human cancers. In MB, over-expression of c-MYC has been shown to cause anaplasia and correlate with unfavorable prognosis. METHODS: To study the role of c-MYC in MB biology, we down-regulated c-MYC expression by using small interfering RNA (siRNA) and investigated changes in cellular proliferation, cell cycle analysis, apoptosis, telomere maintenance, and response to ionizing radiation (IR) and chemotherapeutics in a representative panel of human MB cell lines expressing different levels of c-MYC (DAOY wild-type, DAOY transfected with the empty vector, DAOY transfected with c-MYC, D341, and D425). RESULTS: siRNA-mediated c-MYC down-regulation resulted in an inhibition of cellular proliferation and clonogenic growth, inhibition of G1-S phase cell cycle progression, and a decrease in human telomerase reverse transcriptase (hTERT) expression and telomerase activity. On the other hand, down-regulation of c-MYC reduced apoptosis and decreased the sensitivity of human MB cells to IR, cisplatin, and etoposide. This effect was more pronounced in DAOY cells expressing high levels of c-MYC when compared with DAOY wild-type or DAOY cells transfected with the empty vector. CONCLUSION: In human MB cells, in addition to its roles in growth and proliferation, c-MYC is also a potent inducer of apoptosis. Therefore, targeting c-MYC might be of therapeutic benefit when used sequentially with chemo- and radiotherapy rather than concomitantly